Climate Audit

Bill F

Why would they suggest that having no difference in trend between calm and windy nights is evidence of a lack of UHI? All that proves is that the difference in UHI between windy and calm conditions is smaller than the difference between a UHI affected station and a rural station. Measuring the difference in trend between calm and windy days simply measures the magnitude of the wind’s impact to the total UHI affect.

sonicfrog

Hey, no wonder I can’t find the thing – they keep moving it on me!!!

jae

What is the x-axis in the figure?

Nathan Schmidt

The x-axis in the figure from Oke et al. 1991 is “Sky View Factor” of the city’s central area. There’s a link in the post to the original paper, saved as a pdf.

Mark T.

Hehe, I’m not sure you could ever get an accurate reading of windy vs. calm here in CO. Maybe you could get a “40 mph windy” vs. “20 mph windy” comparison. In the summer, once it gets up into the 90 degree range, the wind does nothing to cool us off: it turns the area into a convection oven. I bet I drink 16 glasses of water a day in July, else I suffer from perpetually chapped lips. 🙂

Mark

Steve Milesworthy

I don’t think it is clear from the article that the Parker paper explicitly states that the UHI effect does exist.

Essentially it is saying that comparing trends of calm and windy nights suggests that the increase in the UHI effect is not significant over 50 years.

Analysis of transects of a range of cities in a range of conditions will help to qualify the data, but won’t show anything about the historical changes in urban-ness that would influence the trend in temperatures.

nanny_govt_sucks

It’s hard to argue with observations of UHI’s:

http://www.warwickhughes.com/climate/uhi2.htm

Anthony Watts

From the conclusions of Parkers paper:

“The robustness of the analysis to the criterion for “calm” implies that the estimated
overall trends are insensitive to boundary layer structure and small-scale advection, and to siting, instrumentation, and observing practices that increasingly influence temperatures as winds become lighter.” and “In view of the error estimates (Tables 1 and 2) and
the different periods of analysis, the results are compatible with the IPCC TAR conclusion that urban warming is responsible for an uncertainty of 0.06°C in the global warming in the twentieth century.”

I have one question: Did Mr. Parket actually visit any of the weather stations to see what influences (UHI or otherwise) may be affecting the wind and temperature gathering and hence the data, or is this another armchair data wrangling study?

Given what I’ve seen in the past month in weather station surveys, and looking at the surveys done by others such as Pielke, Taylor, and Niyogi et al, and given the fact that the temperature data used in the study appears to be highly proxyed and filtered, I have no choice but to call conclusions on this paper dubious at best.

I an regularly “gobsmacked” at the poor quality of the surface data collection instrumentation and the microsite bias examples that seem to be coming in daily, yet researchers such a Parker treat the data as if it were faultless, and quote figures such as “uncertainty of 0.06°C” when the figure is below the noise level of the instrumentation.

As far as I can tell the only supportable conclusion that can be drawn from this paper is that windy days spread around a portion of the UHI effect via mass transfer.

John Norris

It sounds suspect when you have to sell a simple concept like AGW with tree rings from bristle cone pines. Same goes for showing a simple concept like UHI has minimal effects by complicating it with analysis of temps on windy verses calm days.

A number of responsibly placed and monitored thermometers, around several responsibly selected urban and rural environments, set up for climate monitoring rather than weather reporting, and two years worth of responsible data collection and you would have a relatively perfect answer to the UHI question. Am I missing something?

But the Hadley Centre has to get this funded instead. It’s not like UHI is a brand new concept this year and they haven’t had time to get it together. If these folks are actually interested in getting the real answer they should perform simple tests with 2 years of good data rather than complicated tests with 50 years of questionable data.

Joe Ellebracht

Re #15
Mr. King, thanks for the formal statement, although I am not sure Parker would agree with it 100%. I understood your statement much better than I did Parker’s explication.

Since the formal statement and the Parker paper did not track cloudiness trends, I think they are both subject to criticism as cloudiness is admitted to be an important issue. Parker tried to capture some cloudiness data, but discarded it as imperfect and also not useful, as I read his paper. Certainly there must be data on cloudiness trends Parker could have quoted to say it didn’t matter or did matter.

I also take exception to the assumption that trends in near surface temperature inversion effects are trendless. Not that I have any data to the contrary of course, but on the theory that hotter air over time might cause the rural ground-air temperature difference to increase at T-min times and thus cause a greater inversion effect over time. I also think that increasing urbanization would affect this factor, as urban surfaces would get hotter than the air temperature during the day and would not be as likely to cool at night to a temperature below the air temperature because they started out hotter at sundown and they have more thermal mass.

Steve McIntyre

Looking at Parker again, his article is even worse than I portrayed it initially. Oke talks about UHI as an urban-rural differential. Parker doesn’t ever mention urban-rural differentials, he talks about Tmin.

Now Tmin typically occurs around dawn. Parker says that the greatest UHI impact is on Tmin attributing this to Johnson et al 1991 – thus around dawn. Parker:

The main impact of any urban warming is expected to be on Tmin on calm nights (Johnson et al. 1991).

As Eli Rabett/Josh Halpern likes to say, RTFR. Jphnson et al say nothing of the sort. Nowhere do they connect UHI specifically to Tmin. Actually, they say something completely opposite. They say that the greatest UHI is just after sunset, when everything is still warm:

So Parker’s supposed authority for his “proxy” argument gives no support whatever for this particular urban myth. And I suspect that none of the stadiums of IPCC AR4 reviewers objected.

Steve McIntyre

#23. Good point. I posted up a couple of graphics from this article last year here but hadn’t started to analyze the temperature data at that time.

Willis Eschenbach

Steve, first, thanks to Dr. Parker for his prompt provision of the data.

Second, I think that the difficulty in the study (in addition to the inversion issue above) is that the wind data has suffered at least four generalizations:

1) It is not data per se, but the result of the NCEP/NCAR reanalysis (read “computer model output”) results.

2) It is gridded, rather than specific to the station.

3) The stations can be a ways from the center of the gridcell. The average distance from the gridcell center is 90 km, with the maximum distance 180 km.

4) The winds are only given for four times during the day – 0, 6, 12, and 18 GMT. These may not correspond with the times of the local minima/maxima.

He does not say how he has dealt with problem number 4. Did he take the nearest value, or interpolate between the values, or what?

If he takes the nearest value, there’s another problem. Suppose the local minimum temperature occurs at say 0200 GMT. He uses the 0000 value. But as the year progresses, the minimum temperature occurs earlier and earlier in the day, until it is at 0400 Zulu. So at some point, he’s switching between the wind before the minimum to the wind after the minimum.

And interpolating the temperatures has its own problems. Winds are generally calmer during the night, but at dawn, there is a “dawn breeze” because of the temperature difference between the lighted and unlighted portions of the globe. Depending on the latitude, however, this “dawn breeze” can either oppose or intensify the average wind. In the tropics and north of about 60N, it opposes the wind on average, so the wind often drops at dawn. This, of course, affects the timing of the minimum temperature. In either case, the wind starts to build rapidly from that point, typically peaking between 12:00 and 2:00 (local time) and slowly dying after that. And of course, all of this changes with the seasons.

The most troublesome of these generalizations to me is the use of the gridded values. I live in a valley between two high mountains on the Big Island in Hawaii. When the trade winds blow, here in the valley they shriek … but 20 miles away, it can be just light breezes. Wind is not like temperature, where the anomalies can be related over a fairly large distance. It is very site-specific, which is why such trouble is taken with things like the siting of windmills.

Because of these problems, I see no reason to believe that a global average, using wind data that is this coarse and non site-specific, will reveal much of anything.

w.

Joe Ellebracht

Well, the image did not work, here is the link

Anthony Watts

RE23,

I was in contact with Dr. Christy a couple of months back, and he was kind enough to provide me with a copy of his paper, which I’ve posted on http://www.surfacestation.org for CA readers here:

Click to access 2006_ChristyNRG_CA.pdf

A good comparison between a Valley Trend and a Sierra Nevada Trend are these two stations.

Fresno: http://data.giss.nasa.gov/cgi-bin/gistemp/gistemp_station.py?id=425723890000&data_set=1&num_neighbors=1

Electra: http://data.giss.nasa.gov/cgi-bin/gistemp/gistemp_station.py?id=425723890000&data_set=1&num_neighbors=1

Jos L.

Dear all, also have a look at:

Kenneth M. Hinkel and Frederick E. Nelson, Anthropogenic heat island at Barrow, Alaska, during winter: 2001’€”2005, Journal of Geophysical Research, VOL. 112, D06118, doi:10.1029/2006JD007837, 2007.

Abstract

The village of Barrow (71°N latitude) is the largest native community in the Arctic, with a population of approximately 4500 people. Situated on the coast of the Arctic Ocean in northernmost Alaska, the area is entirely underlain by permafrost. Although most supplies must be imported, Barrow relies on local natural gas fields to meet all energy requirements for building heat and electrical power generation. This energy eventually dissipates into the atmosphere, and can be detected as a pronounced urban heat island (UHI) in winter. Since 2001, a 150 km2 area in and around Barrow has been monitored using ‘ˆ¼70 data loggers recording air temperature at hourly intervals. The mean daily temperature of the urban and rural areas is calculated using a representative sample of core sites, and the UHI magnitude (MUHI) is calculated as the difference in the group averages. The MUHI is most pronounced in winter months (December’€”March), with temperatures in the urban area averaging 2°C warmer than in the surrounding tundra and occasionally exceeding 6°C. The MUHI is maximized under cold and calm conditions, and decreases with wind speed and warmer temperatures. It is strongly and directly correlated to natural gas utilization on a monthly basis. Integrated over the home heating season, there is an 8% reduction in freezing degree days in the village. It is unlikely that anthropogenic heat contributes to the forward shift in the snow meltout date that has been observed near Barrow over the past 60 years.

Harold Pierce Jr

Steve: Check e-mail for “Lighthouses as Unbiased Global Thermometers. This is a copy of my report that I sent Roy Spencer and John Christy who recommended yesterday that I send it to you. The title of the report is, Lighthouses: Thermometers for Accurate and Unbiased Measurement of Air Temperature at the Sea-Land Interface.

I live in BC and there are about 80 lighthouses, some with records that go back before 1900. Here are conditions: sample interval, March 16-26; only min temp used; and years that have approx the same El Nino and La Nina index were selected. Here are results for the Quatsino LIghthouse that I just finished about ten min. ago. El Nino years: 1900, 276.4 +/- 2.5 deg K, En index=1.8; 1998, 277.3 +/- 1.7 deg K EN index=3.3. La Nina Years: 1899, 273.3 +/- 1.0 deg K, LN index= -.05,
1999, 275.5 +/- 1.8 deg K LN index= -0.8. A they say, the data speak for themselves and they say the temperature at the spring equinox has remained unchanded for a century ie, no detectable global warming.

Note the difference between the means for the El Nino and La Nina years at 1900 and century later. Clearly this method will let us determine once and for allif any significant global warming has taken place. The answer is on the lighthouse walls and is NO!. End of story It’s game over. Al Gore I want a refund on the stupid video!

Steve Milesworthy

Steve McIntyre writes:

One of the main IPCC creeds is that the urban heat island effect has a negligible impact on large-scale averages such as CRU or GISS. The obvious way of proving this would seem to be taking measurements on an urban transect and showing that there is no urban heat island.

No! The study here is looking at temperature trends due to increasing urbanisation. More transects do not help. Parker explicitly states that he doesn’t dispute that UHI exists.

Steve has picked up on the fact that the Johnson citation says nothing about Tmin being affected by UHI. This means we have two possibilities:

1. Tmin is affected by UHI and Parker is right despite the fact that the evidence is not fully there.
2. Tmin is not affected by UHI – Parker is wrong. But then so is UHI. Therefore the warming trends are correct.

You can’t have it both ways.

Douglas Hoyt

Last message:
Replace trisect with transect.

MarkW

Another problem with Parker is that he just looks at wind speed, not wind direction.
Unless the distribution of heat is completely uniform, and the temperature sensor is in the exact center of that distribution, then the direction from which the wind is blowing will have an affect on the temperature at the sensor.

For example, if the sensor is near the western edge of your town. A wind from the west will cause more cooling than a wind from the east, as the wind from the east blows over a greater portion of the town before it reaches the sensor.

A wind from the north or south will have a different temperature affect.

As someone else has pointed out, whether the wind is caused by a cold front or a warm front will also affect how the wind affects the readings of the temperature probe.

There are so many variables not accounted for by this study, I just don’t see how anyone can take it seriously.

Steve Milesworthy

#37 Douglas
I was a bit confused by the use of r’ as it refers to a difference in in trend of Tmax rather than r which is a reduction in UHI.

Dropping all the (j,n) for clarity what if we write:

Trend Ac = Trend Tcmax + Trend UHI
Trend Aw = Trend Twmax + r Trend UHI

ie. calm days warm by the trend in calm-day temperatures plus the change in UHI. The trend of temperatures is allowed to be different on calm and windy days as you suggest. So your equation is rewritten:

Trend Ac – Trend Aw = (1-r) Trend UHI + Trend Tcmax – Trend Twmax

Where Tcmax is the calm-day max temps and Twmax the windy-day max temps.

Parker’s results say that the left-hand side is zero:

(1-r) Trend UHI + Trend Tcmax – Trend Twmax = 0
Trend Twmax – Trend Tcmax = (1-r) Trend UHI

So if Trend UHI is positive it has to be balanced by differences in the trends for Tmax on windy vs calm days if the UHI influence disappeared.
It implies that for stations unaffected by UHI, windy days should be getting warmer faster than calm days. Is there observational evidence for this, and does it sound likely?

Michael Jankowski

Re#22, purely anecdotal, but I agree with Johnson on the max UHI effect being observable a few hours after sunset. I spend a lot of time roaming my property and going to-and-fro the house to the fringes, and that’s exactly when I can notice the temperature gradient changing as I move towards or away from my brick home. I’ve never noticed this around dawn – any difference the temperature several hundred feet from the house is imperceptible to me (granted, I’m not a digital thermometer) from that adjacent to the house. I’m sure my brick home isn’t characteristically representative of everything that is a part of the UHI, but my personal experiences leads me to believe Johnson’s statement makes more sense. And I’m not sure how Parker can use Johnson’s statement to justify his own.

Douglas Hoyt

Let’s put it this way. Consider a rural location in 1900. Today it is on the outskirts of a town and comparing the site to still rural nearby sites, it is a degree warmer. One can then deduce that the UHI effect has had a 0.1 C/decade trend at that location over a century. Yet according to Parker’s analysis, this site has experienced virtually no net UHI warming.

The hypothetical site I described above is observed to occur in many places all over the world. It should be obvious that UHIs are contributing to the observed global warming. It can be better quantified with some direct field work.

As I pointed out above, Parker’s indirect approach is too simple and his equations are incomplete. That is why he fails to detect what has already been measured directly by many people.

Steve Milesworthy

#46 Douglas
Which site are you referring to?

#47 Hans
Can you post the temperature stats again please? Was de Bilt one of the Parker sites? Can the Parker analysis be repeated for de Bilt?

MarkW

Over in the ISO-2000 thread, Steve Milesworthy writes that the temperature record shows no evidence of urbanization.

And he complains that other people only see what they want to see.
(Steve requested that the discussion be brought to this thread.)

Ken Fritsch

Re: #12

I don’t think it is clear from the article that the Parker paper explicitly states that the UHI effect does exist.

Essentially it is saying that comparing trends of calm and windy nights suggests that the increase in the UHI effect is not significant over 50 years.

If an absolute UHI effect of a larger magnitude than now assumed (from Parker etc.) were demonstrated, it would, even without showing how much it changed over the last 50 years, indicate that the measurement of long term temperature trends might be better made by excluding urban areas and for that matter push up data users’ antenna for those environments of “rural” stations that might cause similar UHI effects.

I think Parker’s papers tend to minimize the temperature measurement uncertainties whereas the antithesis would allow for more uncertainties that might put more emphasis on the satellite and SST measurements and better insuring the accuracies and precisions of those methods.

MarkW

Steve you’re the one who claims that the temperature record does not show urbanization.
I can’t find ANY evidence to support such a claim, unless you are willing to use the highly adjusted temperature data created by the Team, using secret data and secret methods.

I guess your one of those guys who believes that nuance requires one to not see anything that doesn’t fit into the agenda you are trying to push.

MarkW

If I design a study that leaves out most of the relevant factors, I could create a “novel and interesting” paper that proves anything I want.

That’s what’s been done here.

Ken Fritsch

Re: #55

I’m not some sort of Team acolyte who has utmost faith in the temperature record. On the other hand Steve McIntyre’s partial and somewhat misleading introduction to this paper gives me good grounds for questioning the opposing team.

Not sure what you have in mind specifically about Steve M’s handling of the Parker paper, but from your sensitivity you obviously can appreciate the questioning here of the indirect Parker approach that has somehow become authoritative in the world of climate science and apparently without the amount of scrutinizing it would appear to deserve.

Parker’s indirect approach reminds me of a paper on the effects of the minimum wage level on employment by Card and Krueger that used the indirect data derived from generalized interviews with minimum wage managers to show that increasing the minimum wage actually increased employment. That paper has, of course, become the authoritative document used by those advocating increased minimum wage levels even though it has faced a goodly amount of criticism.

Warwick Hughes

I looked at Parker’s paper on this subject in Nature 2004.
His stations are from GCOS not CRU or GHCN.
I put some comments in Coolwire.
Scroll down one up from end of page.
I have just added the comments on huge heat transfers by winds.

Roger A. Pielke Sr

We have published several papers that are concerned with the Parker 2006 conclusions:

Pielke Sr., R.A., and T. Matsui, 2005: Should light wind and windy nights have the same temperature trends at individual levels even if the boundary layer averaged heat content change is the same? Geophys. Res. Letts., 32, No. 21, L21813, 10.1029/2005GL024407.

Pielke Sr., R.A., C. Davey, D. Niyogi, S. Fall, J. Steinweg-Woods, K. Hubbard, X. Lin, M. Cai, Y.-K. Lim, H. Li, J. Nielsen-Gammon, K. Gallo, R. Hale, R. Mahmood, R.T. McNider, and P. Blanken, 2007:Unresolved issues with the assessment of multi-decadal global land surface temperature trends. J. Geophys. Res. in press. http://climatesci.colorado.edu/publications/pdf/R-321.pdf

We also summarize the conclusions of our 2005 GRL paper on Climate Science [http://climatesci.colorado.edu/2006/01/23/why-there-is-a-warm-bias-in-the-existing-analyses-of-the-global-average-surface-temperature/] as follows:

“Readers of this weblog know that there have been comments on the warm bias that we have identified, as reported in Matsui and Pielke, GRL, 2005, with respect to the global analysis of surface temperature trends. This is an important issue as this climate metric is used as an icon to communicate the concept of global warming to policymakers. The abstract of the Parker 2004 Nature paper , for example, stated that the

“Controversy has persisted over the influence of urban warming on reported large-scale surface-air temperature trends. Urban heat islands occur mainly at night and are reduced in windy conditions. Here we show that, globally, temperatures over land have risen as much on windy nights as on calm nights, indicating that the observed overall warming is not a consequence of urban development.”

Parker 2004 has been used as evidence to argue that the global surface temperature trends are robust (e.g. CCSP, 2006). In the Matsui and Pielke paper, we show, however, that trends of surface air temperature should not be expected to have the same values for the different sets of days used in the Parker paper. Based on well understood concepts of boundary level meteorology, because Parker found similar trends, there necessarily must be some error in Parker’s analysis. For those unfamiliar with boundary layer meteorology, the reason for this is that minimum temperatures on calm nights should in fact show a larger warming trend than on windy nights (explained below), and not the identical trends reported by Parker. We were motivated to look at this subject because of the obvious inconsistency in the Parker results, and what we found has much broader implications for the long-term surface temperature record.

Studies of the lower levels of the atmosphere (lowest tens of meters) show that it cools at night when winds do not move warm air into the area. This cooling occurs as heat is lost to space. For this reason, minimum daily temperatures typically occur near sunrise, due to cooling overnight. The nighttime cooling varies with height. With light winds, the cooling is greater near the surface and less aloft, while with stronger winds, which are associated with greater mixing of the air above a particular location, the cooling rate is more uniform with height. Light and strong winds can be documented at a particular location from observed wind data.

The rate of heat loss to space is dependent on several factors, including cloudiness and the local atmospheric concentrations of carbon dioxide and of water vapor. Under cloudy conditions, the cooling is much less. Similarly, an atmosphere with higher concentrations of the greenhouse gases, CO2 and H2O, also reduces the cooling at night. Consequently, if there is a long-term trend in greenhouse gas concentrations or cloudiness it will introduce a bias in the observational record of minimum temperatures that will necessarily result in a bias in the long-term surface temperature record.

Because of changes to the atmosphere over the past century, there are several reasons why we should expect the nighttime cooling in the lower atmosphere to have been reduced. One reason for this is that carbon dioxide concentrations have increased, such that the local effect of greenhouse gas concentrations on temperature measurements is larger. Also, an increase of cloudiness has been reported which has the effect of reducing nighttime cooling. An increase in water vapor content in the lower atmosphere would also reduce the cooling rate at night.

Our paper shows that in such circumstances where nighttime cooling is reduced systematically over time, i.e., under trends of greater atmospheric greenhouse gases or an increase in cloudiness, the resulting effect will be to increase minimum temperatures from what they would have been absent the reduced nighttime cooling. This increase in minimum temperatures is greater on nights with light winds than nights with strong winds, due to the mixing of air, and can be on the order of 1 degree C in the lowest 10m above the ground. Minimum daily temperatures are of course important because they are used as input to calculate the daily temperatures that comprise the long-term surface temperature record.

When there is a long-term trend of a reduction in nighttime cooling, then when temperature data are collected, the combination of all of the minimum temperatures on light and strong wind nights will result in an overstatement of warming trends by tenths of a degree. (Note that this assumes that the overall reduction of nighttime cooling such as due to more cloudiness over time and/or increases in the atmospheric concentration of carbon dioxide and/or water vapor is on the order of 1 watt per meter squared. Based on the IPCC, 2001 findings, this is a reasonable estimate of the change over the recent decades in the atmospheric radiative forcing).

What this means is that because (a) the land surface temperature record does in fact combine temperature measurements of light wind and windy nights and (b) there has been a reduction in nighttime cooling, the long-term temperature record may be contaminated by a warm bias that accentuates the observed trend of warmer temperatures. Such a bias would be of similar or larger magnitude to those biases recently discussed in the context of global satellite measurements of temperature. The reduction in nighttime cooling that leads to this bias may indeed be the result of human interference in the climate system (i.e., local effects of increasing greenhouse gases or human effects on cloud cover), but through a causal mechanism different than that typically assumed.

This effect results from a systemic microclimate effect in temperature data which are present in the global temperature record, but are unaccounted for in current analyses. This raises the possibility that those GCMs that appear to accurately represent global average temperature trends over recent decades may be obtaining results that look right when compared to data, but for the wrong physical reasons. If so, this would call into question their ability to accurately predict the future evolution of the climate system.

The broader implications of Matsui and Pielke (2005), which will be well understood by anyone with an understanding of the physics of the lower atmosphere, should cause consternation among anyone who uses the global temperature trend record for scientific or policy purposes. As we have emphasized here (as have others, such as Hansen, Levitus, Barnett, Willis) a more meaningful metric than global average temperature to assess global warming is ocean heat content.”

The Parker 2006 is clearly inconsistent with our knowledge of both urban effects, and of stable nocturnal boundary layers.

Willis Eschenbach

Steve Milesworthy, you say:

Steve McIntyre writes:

One of the main IPCC creeds is that the urban heat island effect has a negligible impact on large-scale averages such as CRU or GISS. The obvious way of proving this would seem to be taking measurements on an urban transect and showing that there is no urban heat island.

No! The study here is looking at temperature trends due to increasing urbanisation. More transects do not help. Parker explicitly states that he doesn’t dispute that UHI exists.

Steve has picked up on the fact that the Johnson citation says nothing about Tmin being affected by UHI. This means we have two possibilities:

1. Tmin is affected by UHI and Parker is right despite the fact that the evidence is not fully there.
2. Tmin is not affected by UHI – Parker is wrong. But then so is UHI. Therefore the warming trends are correct.

You can’t have it both ways.

So am I correct that you think that UHI exists, and that Parker doesn’t deny that, but you and Parker think that despite the population doubling since 1960, the effect of the UHI is unchanged? Am I interpreting this correctly?

Thanks,

w.

Willis Eschenbach

Well, the quoting got messed up. The previous post should say

Steve Milesworthy, you say:

Steve McIntyre writes:

“One of the main IPCC creeds is that the urban heat island effect has a negligible impact on large-scale averages such as CRU or GISS. The obvious way of proving this would seem to be taking measurements on an urban transect and showing that there is no urban heat island.”

No! The study here is looking at temperature trends due to increasing urbanisation. More transects do not help. Parker explicitly states that he doesn’t dispute that UHI exists.

Steve has picked up on the fact that the Johnson citation says nothing about Tmin being affected by UHI. This means we have two possibilities:

1. Tmin is affected by UHI and Parker is right despite the fact that the evidence is not fully there.
2. Tmin is not affected by UHI – Parker is wrong. But then so is UHI. Therefore the warming trends are correct.

You can’t have it both ways.

So am I correct that you think that UHI exists, and that Parker doesn’t deny that, but you and Parker think that despite the population doubling since 1960, the effect of the UHI is unchanged? Am I interpreting this correctly?

Thanks,

w.

Joe Ellebracht

re #67
My read was that the effects might be strongest in the lowest few meters of the atmosphere, where we happen to take the temperature measurements at the land-based stations. This would exaggerate our perception of what was going on, and maybe mislead us humans on what policies to follow. just my 2 cents.

re urbanization, here are some statistics and projections. My success rate with graphics is zero so far, so this might look strange. The graphic is from http://ww2.unhabitat.org/istanbul+5/booklet4.pdf and the one image that I think is enlightening is here: http://www.esnips.com/doc/7644eaba-b8e9-4a61-888b-3028e530cc0f/urban-population-over-time-(gif)

Here I will try to show it:

Joe Ellebracht

Well, maybe I can get the urbanization image to come up now:

Neal J. King

Continuing from #71:

Various concerns raised about Parker’s perhaps mistaken interpretation of Johnson’s paper in my opinion miss the point that these remarks were mostly contextualization, and do not affect the main thrust of Parker’s argument; which I think is presented more straightforwardly in #15. (Of course, I would, wouldn’t I?)

This constitutes a reply to:
Steve McIntyre: Original posting (remainder)
Jason L.: #7
Michael Jankowski: #44

Neal J. King

Continuing from #73:

There is the interesting suggestion from Steve McIntyre that the higher trend in the windy-day signal implies a mixing-in of warmer air (due to suburban heating up) that over-powers the UHI (for example, from a relatively static airport) and thus suppresses the growing UHI.

It seems to me that this is the sort of question that is too difficult to answer by looking at aggregate data, because it could apply to very specific situations somewhat differently: It would be more fruitful to ask Parker to address the question directly using his site-specific data.

This constitutes a response to:

Steve McIntyre: #39
Steve Milesworthy: #43 (in part)
Joe Ellebracht: #25

Neal J. King

Continuing from #75:

Anthony Watts (#16) and Willis Eschenbach (#26) have expressed concern at all the proxying required to do get the temperature and the wind speed onto the same time-space point.

Obviously, it would be better if one didn’t have to do this. However, there are two reasons for thinking that this does not wipe out the usefulness of that approach:

– Spatially and temporally, there will be a degree of autocorrelation of behavior of wind and temperature. So even if the match is “off” a certain amount, it is reasonable to expect a degree of correlation.

– As this correlation weakens, I think the first-order effect would be the reduction of the Ac-Aw and Bc-Bw signals, because of misclassification of calm and windy days. But these signals have both survived: they are definitely well above 0, the value one would expect if the assignment into windy and calm were random. Since the signals have survived, I think it is also reasonable to expect that the trends in these signals have also survived. And the Parker hypothesis turns on this trend.

Neal J. King

Continued from #77:

Douglas Hoyt (#37) pointed out that there could be a correlation between degree of windiness and temperature. He tries to take this into account by modifying my Eqn. (6) (from #15) from:

Eqn.(6)
A(j,n) = Tmax(j,n) + r UHI*(j,n)

to Eqn. (6′)
A(j,n) = r’ Tmax(j,n) + r UHI*(j,n)

However, I agree with Steve Milesworthy (#42) that this is not the correct approach.

The point is that Tmax(j,n) is the actual “real” temperature of an ideal weather-station that was not being afflicted by asphalt highways, burning cans of rubbish, etc. It happens not to be available (or we would be using it!), but that is the intent. If on the other hand the day is windy, and by natural correlation that turns out to imply a cooler day, that lower temperature would be the starting point for both the actual measured temperature Aw(j,n) and the ideal temperature Tmax(j,n): There is no reducing factor. If it’s colder, it’s colder.

So how would the correlation between windiness and cooler temperature be reflected in the signals and the trends? I would expect that it would increase the Ac-Aw, by reducing the temperature on windy days (Aw); and reduce the magnitude of the Bc-Bw signal on windy nights (Bw)(because Bc is generally less than Bw, due to the near-surface temperature inversion).

If there is no trend over time in the windiness/temperature correlation, it won’t make any difference to the relationship of the UHI* trend to the calm-windy signal trend. I don’t, however, see an immediate way of disentangling it from the NSTI of Eqn.(8) / #15.

Neal J. King

By the way, I have not mentioned Steve Milesworthy very much in the above, because I nearly always agree with what he has said.

Neal J. King

#63: steven mosher:

In addition to what I pointed out in #69, I add:

c) In most cases, there appears to be no trend in the (calm-day) – (windy-day) signal.

a), b) & c) combined imply that the urban-heat-island effect is NOT increasing on a global basis, and therefore CANNOT serve as the “real” cause giving rise to the impression of global warming as an artefact.

So you can conclude that:

– global warming is real; or
– it’s an illusion – but it’s an illusion not caused by an increase in UHI effects

bernie

#81 Steve
A neat and clear explanation. The explanation also makes a great case for carefully ascertaining both UHI and microclimate effects associated with changes at a location and of locations (not to mention various appropriate and inappropriate corrections). It also points to the fact that the measured effects are still small and can be produced by these non-global artifacts. At a minumum the research should be in place to eliminate them.

bernie

I suspect that there are few airports in urban areas where the weather station has not experienced micro-climate changes. Wouldn’t these have to be controlled for?

Roger A. Pielke Sr.

RE#67 by Neal J. King

We show that the sampling of temperature trends at 2m overstates any boundary layer reduction in nocturnal cooling at night, regardless of the cause. I hope this clarifies.

Dave Dardinger

Well, I’m enjoying the debate in this thread. While Neal and SteveM-worthy are clearly on the warmer side, they’re holding their own and making good points, though they’ve not convinced me yet. But I do suspect that Neal, at least, is not an amateur on the subject. Either I don’t recognize the name or he’s here incognito. Which is fine with me, but until I’ve had a chance to look closely at his post 15 I’m sticking to the sideline.

TAC

I finally got around to doing a back-of-envelope calculation on the direct UHI impact — what we know “for sure” about the impact of urbanization — for the 6000-acre suburban-U.S. community into which I and 75000 other people have moved during the past 45 years. I was a bit surprised by the result: The average power-per-unit-area introduced by urbanization would be 75000[people]*1390[watts/person]/(6000[acres]*4046[m2/acre]) = 4.3[watts/m2]. By coincidence (??), four watts per square meter is the AGW-hypothesized increase in net radiative forcing one gets by doubling atmospheric CO2.

Clearly this BoE analysis is greatly oversimplified. Among other things, it ignores: heating due to changes in albedo; “waste” heat (which may be several times greater than power consumption); convection and advection; etc., etc. Actually solving the problem “correctly” — using first principles — would be hard because of boundary conditions and parameter estimation (too many coefficients for me to be comfortable, anyway).

Normally one could settle this quickly by looking at the data — exactly what Christy (#23) has attempted to do — but that only works if the data were collected with sufficient care. Not so sure we can say that…

In conclusion, it is hard to feel confident about any particular explanation for “observed warming” when serious questions remain about whether it might be no more than an artifact of changes in sampling protocols and UHI.

Am I missing something here?

😉

Hans Erren

Parker:

The main impact of any urban warming is expected to be on Tmin on calm nights (Johnson et al. 1991).

As Tmin is usually observed at dawn, that is also the time of day when UHI is smallest. I would expect UHI to have it’s biggest influence just after sunset.

Peter Hartley

Not many have commented on Pielke’s comment #62. As I understand it, he is arguing that, if the greenhouse theory is correct, “minimum temperatures on calm nights should in fact show a larger warming trend than on windy nights” and thus the finding of identical trends contradicts the greenhouse theory. While this does not address the UHI issue as such, it is a significant point that other readers of the Parker paper seem to have missed.

The other significant point Pielke makes is that “minimum daily temperatures typically occur near sunrise, due to cooling overnight.” This point has also been discussed at some length by Jonathan Lowe. Jonathan has shown that, for all the locations in Australia that he has looked at, while the minimum temperatures have shown an upward trend, temperatures at 3am, for example, have not shown any significant trend. Jonathan notes that the minimum temperatures occur shortly after sunrise before the heating from the sun begins to raise temperatures again. He also looks at trends of temperatures measured each day at other times of the day. What he finds is that the trend is larger when the effect of the sun is also likely to be stronger. Jonathan concludes that the trend in temperatures measured at different times of each day is evidence of increased solar heating in recent decades rather than greenhouse warming.

Neither of these arguments address the issue of whether UHI is affecting measured minimum temperatures, but they may in fact be more important points to make about measured trends in minimum temperatures than the one Parker is trying to make.

Cliff Huston

Re:93,97

LOL – Not only the same story, but applied to the same guy.
Willis Eschenbach:

A further oddity. The HadCRUT2 error analysis says:

Blending a sea-surface temperature (SST) dataset with land air temperature makes an implicit assumption that SST anomalies are a good surrogate for marine air temperature anomalies. It has been shown, for example by [Parker et al., 1994], that this is the case, and that marine SST measurements provide more useful data and smaller sampling errors than marine air temperature measurements would.

This jump of logic reminds me of the old story about a man standing under a street lamp looking on the ground. His friend says “What are you looking for?”.

“My keys”, he replies. “Oh, did you lose them here?”, the friend asks. “No, I lost them over there in the bushes … but the light is much better here.”

Their justification for using SST in place of air temperature is that there is “more useful data and smaller sampling errors”?!?? As a long-time sailor and commercial fisherman, I can assure you that sea and air temperatures are often quite different. This is particularly the case in areas where a change in SST causes the formation of fog, since much of the sea temperature change is taken up, not by a corresponding air temperature change, but by the condensation of water.

I see that the last twelve years have done nothing to improve Parker’s sense of logic.
Cliff

Anthony Watts

RE95, it seems to me that somebody needs to create a 3D near surface temperature station model to test various microsite effects. Seems like a perfect task to do on a Silicon Graphics Box. Wind, boundary layer, structures, trees, bushes, asphalt, heat sources, etc could all be applied over a time series that has changing insolation based on the solar illumination pattern for a given lat/lon.

Has anybody done this? While I own an SGI O2 I don’t have the time at the moment as I’m full up managing two projects.

steven mosher

re 100.

Anthony, And O2? How cool.

Anyways, you guys thought I was kidding when I said we should scale down a GCM to microsite
sizes. When I read the “canyon, boundary layer, multipath” stuff in Johnsen. I got the same
Idea. ( past life long ago and far away)

Our paths have probably crossed in the past.

Steve McIntyre

#102. For micro-site modeling, take a look at this post http://www.climateaudit.org/?p=508

steven mosher

RE 104.

I’m painfully aware ( past life) of the scale issues. You can’t outcompute molecules.

But, The lure of the AWG gravy train… A small busines contract…MicroSiteAnalysis inc.

On the other hand, if one cannot take the watts from the sun and compute TMAX
at the sensor for relativly Idealized site with any reliability…. then how
can one reliably scale up from this level?

Neal J. King

#81, #84: Steve McIntyre

You proposed to explain Parker’s null result in seeking a trend in calm-day vs. windy-day signals by assuming a windy-day mixing of non-local (Suburban) air with the local (Airport) air. I am going to try to formalize this proposal, using the same terminology already developed in #15. I will have to (extend it slightly.

The indices (j,n) are defined as in #15, but I will suppress them for the time being:

A = maximum temperature measurement, at Airport
B = minimum temperature measurement, at Airport
UHI*-a = slowly varying seasonal value of the UHI, at Airport
UHI*-s = slowly varying seasonal value of the UHI, in Suburbia
Tmax-a = “true” maximum temperature, at Airport
Tmax-s = “true” maximum temperature, in Suburbia

I am going to focus on the maximum-temperature measurements, A.

For calm days, there is no Airport/Suburban mixing, so Eqn.(5) from #15 is unchanged:
A = Tmax-a + UHI*-a

For windy days, I have to weight the two equations corresponding to Eqn.(6) for the two locations by weighting factors, k and (1-k). Thus, for windy days:

A = k(Tmax-a + r UHI*-a) + (1-k)(Tmax-s + t UHI*-s)

[Here, r is as before the windy-day reduction factor for UHI. t is similar, but reflects the fact that the temperature of the air transported from Suburbia to the Airport will be higher due to UHI – but the effect could be diluted. So I introduce a parameter “t” to avoid forcing them to be the same, which could lead to unphysical results.]

Ac and Aw are defined as the interpolated extensions of the calm-day and windy-day values as before, and are defined for all days:

Ac = Tmax-a + UHI*-a
Aw = k(Tmax-a + r UHI*-a) + (1-k)(Tmax-s + t UHI*-s)

Therefore,

Ac – Aw = (1-k)Tmax-a + (1-rk)UHI*-a – (1-k)Tmax-s – t(1-k) UHI*-s
= (1-k)(Tmax-a – Tmax-s) + (1-rk)UHI*-a – t(1-k)UHI*-s

Now, according to Parker’s reasoning:
TREND(Ac-Aw) = (1-r) TREND(UHI*)

So when he gets 0 in 277 out of 290 sites on the LHS, he determines that there is no trend in the UHI*’s for those 277 sites.

But according to Steve McIntyre’s proposal, we would have:

TREND(Ac-Aw) = (1-k)TREND(Tmax-a – Tmax-s) + (1-rk)TREND(UHI*-a)
– t(1-k)TREND(UHI*-s)

In the 277 cases of immediate interest, the LHS = 0.

Under the assumption of (more-or-less) uniform GW, the TREND(Tmax-a – Tmax-s) should also be 0; and under the assumption that GW is not happening, it is also 0, so we’re covered either way if we assume it’s 0. So let’s.

That means we have the equation:
0 = (1-rk)TREND(UHI*-a) – t(1-k)TREND(UHI*-s)

We can solve this for k:

k = (TREND(UHI*-a) – t(TREND(UHI*-s)))/(r(TREND(UHI*-a)) – t(TREND(UHI*-s)))

So that’s great, there is a value of the windy-day mixing ratio that would ensure:
a) Compliance to Parker’s finding that Ac-Aw has no trend; and
b) Still allow the UHI* trends to be non-zero. As Steve McIntyre pointed out, it must be that r(TREND(UHI*-a)) > t(TREND(UHI*-s)), so that there is is some warming over time from the suburban increase in UHI; and
c) There can still be the observed UHI, provided
(1-rk)UHI*-a > t(1-k)UHI*-s

But there are two pieces of bad news:
(1) This works at only one value for k:
k = (TREND(UHI*-a) – t(TREND(UHI*-s)))/(r(TREND(UHI*-a)) – t(TREND(UHI*-s)))

So in order for this to be an explanation of the null-measurement of the increase in UHI over 50 years, the wind behavior has to choose the right value of the mixing parameter for the whole period. Quite a coincidence!

2) I said I was going to suppress the indices. But now I bring one back: i, the site number. In the equation above, all of those trends, and even the value of r and t, depend upon the site. That means that the right value of k really needs to be written as k(i). And the real meaning of that is that the miracle of (1) has to be repeated 277 times, independently.

What this says to me is that Steve McIntyre’s proposal to explain away Parker’s null result for the UHI increase is not plausible.

Neal J. King

Responding to:
#85, #89: steven mosher

#93, #98: Cliff Huston

#101: John Norris

These comments suggest that Parker’s study is flawed by a choice of sites that lacked the causes for UHI, and thus lacked UHI.

However, these comments miss the fact that in virtually all sites, Parker did find a UHI. What he did not find (except in 13 out of 290 cases) was any sign that the UHI was increasing over a 50-year period.

I haven’t followed the discussion in the past concerning the water buckets. I do see a common theme, however: An interest in trying to find a way to make use of the data that have already been collected over long periods of time. We are never going to be able to reproduce those measurements: There’s no time-machine. So whatever the difficulties, it makes sense to see what can be found out from these data.

Neal J. King

Responding to:
#95: steven mosher

There are two effects to consider:
– the UHI: This is indeed reduced on windy nights, because the air gets mixed up.

– the Near-Surface Temperature Inversion: This is due to the fact that the ground cools at night due to IR radiation up towards the sky (only a small fraction of which is going to be trapped in the 2 or 3 meters it takes to pass the weather station), whereas the air will lose heat far more slowly. The result is that the ground becomes cooler than the body of air immediately above it, and this creates a temperature gradient that is in the opposite sense as that created by the UHI. However, just as with the UHI, it is weakened by the wind.

Using my terminology from #15, this shows up in the Bc-Bw signal, but not the daytime Ac-Aw signal: there is no NSTI in the daytime.

Joe Ellebracht

Re 108:

TREND(Ac-Aw) = (1-k)TREND(Tmax-a – Tmax-s) + (1-rk)TREND(UHI*-a)
– t(1-k)TREND(UHI*-s)

In the 277 cases of immediate interest, the LHS = 0.

No, I think it was not in 277 individual cases. Even in some geographically aggregated cases he found what he considered to be statistically significant values for TREND(Ac-Aw). Unless I misunderstand your point or the paper.

Neal J. King

Acknowledging:
#68, Joe Ellebracht

#88: Roger A. Pielke, Sr.

#96: Peter Hartley

I haven’t had a chance yet to study the papers listed in #62. It may be a few days. But I don’t think they’re irrelevant…

steven mosher

Thanks Neil,

I will comment more in detail later ( my brain is down another path now)

I’m having problems with Parkers title and your comment.

As I take the claim now, it is that UHI exists. Parker measured UHI.
But UHI hasnt increased in the past 50 years?

And Prior UHI was due to? And those conditions have remained stable?
Shown where in the paper?

So if UHI hasnt increased in the past 50 years, then UHI cannot be do to population
growth in the areas of the 290 stations.

And if UHI hasnt increased in the past 50 years, then we have not seen local
increases of C02 in urban areas. or if we have, those increases have no impact.

And if UHI hasnt increased in the past 50 years, then we have not seen increased
wind sheltering in these areas.

So, I’ll simply agree with Parker. UHI exists. but hasnt increased. WHY does it exist.
Cant be population or poulation density. those have increased. Cant be “urban greenhouse”
cause urban levels of GWG have icreased. Cant be buildings, cause that has increased.

So, if UHI exists, and If, as you say, Parker shows this. Then cough up the cause!

OK, I will reread his article. You have been most patient and understanding
while folks try to follow the logic ( thats not a criticism I have the same
problems with SteveM and RogerP, I’m just slow )

For grins I picked 3 sites we have good evidence for.

One in the middle of a feild. One a couple miles away in a small town.
The last 25 miles away located in a parking lot.

I looked at TMin from 1983 to 2006 on a daily basis.

Feild versus small town. Small town was about .3C hotter. TRENDS in TMIN
walked together down the time series like two lovers.

Then I look at the Feild versus The growing urban area. 20 miles away. Tmin delta was higher
( well UHI and microsite?? )
But the trend was increasing? hmm

So, there is an anecdote. Means nothing. If I got paid to do this stuff

I’d go at the problem that way.

Paired geographic sites. One demonstraby UHI impaired. One demonstrably unimpaired.

Look at Tmin trends for each. DeltaTmin kinda estimates UHI. deltaTmin trend
measures UHI growth.

The Problem? finding ‘paired’ sites. takes work.

In any case Kudos to you. You’ve answered everyone civily. I’ll chew on your ankle.
and if I say anything stupid just ignore it, or not.

Cheers

Neal J. King

#87: Keith Jackson

It is conceivable that the land-based measurements are too high.

However, unless there is a clear explanation of what is going on and how to apply a correction, there’s nothing more that can be done beyond acknowledging the discrepancy.

As you may recall, they had that discrepancy in radiosonde measurements of the lower troposphere for a decade, until someone finally copped to an algebra mistake in a data-processing procedure.

Neal J. King

#114, #115: Joe Ellebracht:

You are right, I over-interpreted: What he found was zero trend, when averaged world-wide.

That is problematic if you want to explain the increase in global average temperature as due to UHI only, but it doesn’t require perfect cancellation everywhere.

However, it still requires that the value of the k(i)’s each be such as to provide something so that the UHI trends can be averaged to 0 globally: Still a kind of “conspiracy of nature”. Whatever it is that we are trying to explain cannot be as complicated as this.

Joe Ellebracht

”
Re use of airports.
If the lowest temperature of the day is measured just after sunrise, and the highest temperature is measured in the afternoon, then both temperatures are measured during active operating times for commercial airports. Might I suggest that there is air mixing from the planes even on “calm” days. Also, this anthropogenic mixing, to the extent it is a factor, is an increasing factor over time, due to increased air traffic. Sorry for the small size of the graphic, but 2000 air passenger traffic is at the very least 30 times 1950 traffic, with impacts ranging from relocation of airports, much more frequent takeoffs and landings, much bigger planes and jet engines. This increased mixing over time would over time cause the calm days to more closely match the windy days.

If the data is from airports, local wind data is collected, and was in 1950. Probably the more recent years would be computerized and could be compared with gridded data used by Parker to verify that there is a positive correlaton between the two (local and gridded) as he assumes..

Neal J. King

#118: steven mosher:

As Joe Ellebracht pointed out, I had over-simplified the conclusion: not every UHI was static, but the global average was. This makes it difficult to attribute the increase in global average temperature to an increase in the UHIs around the world.

The commonest explanation for it I’ve heard is from use of energy, for example, for heating. However, I can imagine that a city can grow without necessarily becoming more dense. Maybe you get a 1-degree heat island that grows from one mile in radius to 10 miles in radius. Will the weather station at the center pick that up? No.

Your field/town/city examples illustrates the point:
– You are able to directly measure the town’s UHI (which holds static at 0.3 degrees) by comparison with the measurements in the fields.
– Likewise the city’s UHI, which is growing.
– What Parker’s study says is, “You can measure the UHI in the town and in the city without using the measurements in the field. Just look at the Ac-Aw signals in the town and in the city: that already tells you the UHI.”

Cheers…

Neal J. King

#90: David Dardinger

Thanks for the compliment, but I’m definitely an amateur with respect to climate science. However, I have a pretty decent background in theoretical physics, and have done a lot of reading recently: some articles and some textbooks.

So, I make no special claim to expertise or authority, but I do try to do my reasoning “on the page”: What you see is what you get, except that I might toss in references to sources that can legitimately considered authorities, if I can’t avoid it.

To understand what I’m trying to do, you would look at #15 and #108, with an additional point at #122: I’d been so focused on the methodology that I wasn’t paying that much attention to Parker’s results!

I will have to read carefully (and slowly) through Pielke’s papers on the boundary-layer issue. That will take some time…

Steve McIntyre

Parker does not provide a proper statistical analysis of all the stations. We don’t know how much variation there is between stations. It’s hard to figure out why these particular stations were chosen. It’s like too many Team publications – no selection protocols are described. Here’s a plot of the available information for the full year from Table 1 together with a line fitted to the few points. Is there anything miraculous about this fit? Obviously not. There’s nothing in this information that is inconsistent with airport suburbs urbanizing.

BTW I would also express the differential a little differently than Neal. I think that there are two sorts of effects at work -there’s a type of “Canopy UHI” denoting whether the Airport has been folded into the urban dome and just how far; and a “Microclimate HI” which denotes effects particular to the Airport.

IT just doesn’t seem surprising to me that trends at the Airport would be similar to trends at Airport_Suburbs plus or minus a little. Neal, notwithstanding your equations, Parker hasn’t shown anything anything other than that and, as Joe observed and you concede, there’s nothing miraculous here or even surprising. You do have to watch the pea under the thimble.

Steve McIntyre

However, I can imagine that a city can grow without necessarily becoming more dense. Maybe you get a 1-degree heat island that grows from one mile in radius to 10 miles in radius. Will the weather station at the center pick that up? No.

That’s a possibility, but empirically the “canopies” are bigger for bigger cities. I’ve mentioned before that maybe we’d be better off with weather stations at the center of the cities. But that’s not what Parker studied or what’s in the CRU and GISS systems (that are being updated.) You’ve got airports, which by and large, as I’ve said on many occasions, have started at urban edges and, in many cases have been folded into the urban canopy over the past 50 years or are incipient. How severe a problem is this? The only way you can tell is by old-fashioned quality control – checking every airport. There are no short cuts to quality control and Parker hasn’t invented one.

Neal J. King

#133: typo

I meant the graph in #130, of course.

John Norris

re #133

– The problem is …

Good point. I agree, I just think we should throw the bad data away.

– There is nothing stopping someone …

Good point. I agree, I just think that researchers should spend their effort on getting better data rather than polishing bad data.

– By modern standards, the data that Parker had to work with are somewhat problematic. That doesn’t mean they are valueless …

Good point. I agree, I think we just disagree on whether there is more gold or more arsenic in the suitcase.

– And by the standards of science 100 years from now, the data we have collected on climate will seem hopelessly imprecise. Does that mean we shouldn’t bother to collect any?

I think we should collect away to the best of our abilities and let our progeny make the call. I am betting you think so too.

Chris H

Joe Ellebracht,

Time to get out the back of envelope super computer.

Let d = population density of Greater London = 4,761/km2 (2005 wikipedia “Greater London”)
Let p = world Population = 6 billion (US billions)
Let a = world land surface area = 150 million km2 (wikipedia)

Assume 100% of population live in an urban environment and that Greater London is representative.

Percentage of land that is urban
= p / d / a = 6 billion / 5000 /150 million * 100
= 60 / 5 / 15
= 4/5
= 0.8%

Filippo Turturici

To point out just a couple of things:
– oceans warming slower (or cooling slower) than lands on long-time trends is absolutely normal, because water is more difficult both to warm or to cool (I mean, we require both a bigger heat flow and more time); at the contrary, I see as a non-sense theory (made by some serrist, but don’t know who) that oceans are storing up heat, and that suddenly they will release such heat as a positive feedback: or the water warms than no heat can be considered ad “stored” (we have no phase change inside oceans, so no latent heat) or oceans begin to release heat but in the same time they have to cool (because they are losing heat); so, I don’t feel strange that in last years land temperatures for some series (NCDC and GISS) can be heating up while oceans are slightly cooling, but I feel strange that they are heating up so much to reverse global trend from slightly negative/stable to slightly positive; but, in the end, all this is not an evidence that lands’ warming is led by UHI (but, this effect, I would not exclude it from having a small part in temperature trends for some regional area, but just small); both because, as writtend, it is normal to have waters warming slower than lands, and because lands’ temperatures are often measured in a not so precise way (despite they continue to give us a global uncertainity in TT values which is barely the instrumental’s one) – but, to point out, HadCRU and MSU of last years (I mean always 2002-2006) follow much better waters’ temperatures trend;
– metropolis and larger cities temperature trends actually show an increase in UHI effect, but I think the sites are few, and the covered area is very small worldwide, so the global effect is very poor (but it still can be sensible for regional effects); but I would not run out a small warming trend for airport measurements due mainly to three things: increasing jet planes traffic, enlarging airports (then more buildings and more asphalt – if you follow motor sports, or simply live in a town/city, you will know how easy they get very warmer than air during day, and how much it can slow night-time cooling) and overall having airports nearer to cities (if not becoming an area inside the city after some decade of hurban growth, e.g. Milan-Linate);
– I found no point about UHI in towns and villages; you will tell me they are not large cities; but, in comparison with 20-40-60 years ago when they were “countryside”, many small towns and villages have become part of larger hurban areas (at least in Europe and Asia) so examining just larger cities would not be enough in my opinion to get a full view of UHI effect (still remembering that it has a small global effect: we can say many matters are due to UHI instead of GW, maybe even that a small part of measured GW is due to UHI, and that GW measurements are not so precise to make us able to make good analisyses and predictions, but not that GW is due to UHI).

Filippo Turturici

#139: rightly, this is the matter of ground stations: even without sensible UHI effect, we measure temperatures in very small and concentrated areas – where not only UHI, but also soil usage matters – but that are not representative neither of the main part of land surfaces. As written above, it is natural that lands warm (cool) faster than seas: but, I think, it would be much better for studying GW (there are many other issues for lands even without GW) to point on waters rather than on inhabited lands (with a simple condition: all waters; not saying that Arctic pack is decreasing, making silence on Antarctic pack because it instead doesn’t fit AGW theories).

steven mosher

Neil,

“The commonest explanation for it I’ve heard is from use of energy, for example, for heating. However, I can imagine that a city can grow without necessarily becoming more dense. Maybe you get a 1-degree heat island that grows from one mile in radius to 10 miles in radius. Will the weather station at the center pick that up? No.”

Consider that every site has the potential to become a hot box.

Well, Johnsen identifies several causes for the hot box.

1 Canyon effects. the floor of the box cant see the full sky
2.Multipath: IR bounces around inside the box.

At some point in development I suppose the geomtry effects tail off.
3. Wall effects: the walls of the box ( buildings) retain heat and produde heat
You could see this max out as well.
4. Waste heat: humans living around the box creating adifferentail that heats the walls
of the box.
I think your density question apply here. probably tails off at some point.
5. The box of hot air can’t be mixed easily. this effect would tail off
6. A Urban greenhouse gas lid on the box.

At some point, once you have a perfect hot box the only thing that can really increase
the UHI further is a better lid, a lid that traps the IR more effectly.

So theoretically, I suppose, ( i realize this is a toy model ) as Urbanization
encroaches on the site ( walls get built, asphalt floor) one would see
increasing trends in UHI, and as density went up, you see increases, to a point,
Then then the only thing left that can increase are the lid effects

John Norris

Oops, Neal, not Neil

steven mosher

One last thing Neil,

My purpose in selecting sites. I knew the open feild would have no
geometry effects, no wall effects, little waste heat, no substantial shelter.
Only a GHG lid. temps ( min max mean) were flat for the last 24 years.
I also picked the feild because I knew the station there had everything
( wind, soil temps, insolation, rel humidty, precipitation,wind direction)

I picked the small nearby town close by to see Any kind of UHI differential.
my bet is the site is well situated, perhaps only seeing waste heat. I’m
not sure if Anthony has photos of the site, but I’ll check.

I picked the bigger town, 20 miles away, because it has seen rapid development
and we have pictures of the site and it is a mess. Located by buildings,
near asphalt, lots of windbreaks.

The point was to see the differential in UHI and to see the growth in UHI. Both
of which showed up in DElta temps and increasing Trends in Tmin.

I also picked the bigger city because its used by GISS as a quailty site.

One of the points of Anthony’s site survey is to document sites that have low
quality. Hopefully, the quality issues would be addressed. In fact NOAAs CRN
program seeks to establish a new high quality network of fully documented sites.
This network would provide an interest quality check on the existing network.

Finally, I guess I did the toy study to show how I think a proper study would
investigate the sites before dumping data in the hopper. Some ( over at RC)
has pointed out that you only need 60 good sites to characterize the global
temp. I’d ask the opposite question. How many bad ones do you need to contaminate
the record.

Cheers

Filippo Turturici

Steven (#148) try to ask RC folks them if 60 good sites might be enough too to rule out GW [as a global phenomenon] 😉 otherwise, it would not work…

steven mosher

RE 149 steveM,

You mentioned that Parker used NCEP gridcell wind information.

As you note this data may be uncorrelated with airport winds.
I think the problem is larger than that.

Parker used what I think is an arbitrary method to chracterize
calm versus windy. The point of the wind is to MIX. Per Johnsen
UHI exists, in part, because areas dont allow mixing because of shelter. Now,
Mixing happens in turbulant flow. The wind velocity required
for this varies with the surface.
The question is, at what Wind velocity
does the flow over this surface become turbulant and destroy the boundary layer.
I think it depends on the site or the surface.

SO the question is… Was it windy enough at the site to induced
mixing.

Let me put this yet another way. With a Hot surface and a thick boundary
layer you might not get mixing until the wind velocity reached very high
speeds. 8m/sec might be “calm”. Parker’s sense of calm is human. The surface
and boundary layer care nothing for this. The question is not what was the
wind velocity. The question is ” did mixing occur”

So, change Parkers definition of Windy/Calm. See what happens to TMIN trend lines.

Define Windy as the top 10% of wind speeds. Just for grins.

Ken Fritsch

My impatient with this thread can probably be attributed at least in part to the grumpiness of a grumpy old man, but I think we have gotten sidetracked from the important issues that Steve M raised in his introduction to this thread.

The conversation has been civil and the information presented, in some detail, would be helpful mainly to those who have not read the Parker 2006 article. The trend lines for max and min temperatures on windy and calm days at a number of selected (how?) weather stations are nearly self explanatory in regards to what the author is attempting to show:

1. The trend lines for min temperatures on windy and calm time periods for 290 stations over the time period from 1950-2000, while intersecting the y axis at significantly different points (the windy trend lines always showing higher temperatures but the amount can depend on season), both trend at a 0.20 degree C per decade rate.

2. The trend lines for max temperatures on windy and calm time periods have essentially the same slope but intersect the y axis at different values with the windy trend lines on average intersected at higher temperatures but this relationship can flip depending on season of the year and region of the globe.
3. Parker indicates that 13 stations (of 290) show significantly different min temperature windy versus calm trend lines over the fifty year period that could be interpreted as indicating a presents of an UHI effect.

These are all interesting observations by themselves and deserve in my estimation at lot more discussion and background than was given by the author. Instead we have the Johnson et al. 1991 reference, given more or less in passing by Parker, being used evidently as primary bases for using these trends line differences as a proxy for an UHI effect. What I was hoping was that the detailed account in Steve M’s lead in to this thread of the Johnson reference would direct the discussion towards what is the basis for this major assumption made by Parker. Without showing more evidence that his assumption holds his conclusion becomes rather empty.

Perhaps, the evidence lies in the 13 evidently unique stations in the study or in a closer look at differences in temperatures between calm and windy time periods, but on these issues the author is relatively muted.

Like what the hockey stick of Mann’s did for natural temperature variations versus the Modern Warming Period, one can hardly conceive a better method than Parker’s for tying up the UHI effect over the period of most interest to the AGW advocates and doing it globally. Now if he can show good evidence for using the min temperature differences for windy and calm conditions as a proxy for the UHI effect and how he selected his weather stations, he might sway some skeptical minds.

Steve McIntyre

#153. Personally I think that temperatures are warmer now than they were in the 1880s and would expect glaciers to retreat. I believe that this temperature increase exists independently of UHI effects. What I’m trying to understand right now is whether UHI effects have been entangled in temperature records and, if so, to what extent.

The “myth” being discussed here is not whether there is warming or not, but whether PArker has “demonstrated” that the temperature records are uncontaminated, as asserted by IPCC and others.

pochas

According to Neil’s eq 12 in #15h,

trend[TminC] – trend[TminW] = (1-r) * trend[UHI]

Note that under greenfield conditions UHI = 0 and trend[UHI] = 0

Now develop the greenfield into an urban environment so that UHI > 0. For some time during this development trend[UHI] must also be greater than zero. Apparently Parker did not detect an environment in this stage of growth. Perhaps airports exhibit UHI as a step change the day the concrete is placed.

MarkW

If a city is growing, but not growing in density, there will still an increase in temperature at the center of the city. For two reasons. First, any time there is wind, the wind will blow over more urban landscape before reaching the sensor.
Even when there is no wind, warmer urban air will radiate to colder rural air. The further away that cold rural air is, the less radiation will occur.

Finally, the entire scenario is extremely silly, since an urban area that did not increase in density as the population in the general area has increased, has never existed.

steven mosher

RE 153

Hi Lee. Thanks for hanging out. Now, since the start of this we have had, I’d say, Half a dozen
interpretations of what parker said. Apportion the causation for the lack of communication as you see fit.

a good number of us have asked, in honest desparation, for a parsing of parker.

Neil King, has done a stand up job. Personally I think we reached an interesting and fruitful
Disagreement. He made me think. Same with milesworthy and others.. I don’t mean to single
Neil out, but he has been a badger of sorts, dedicated to understanding. Kudos to him.

So, Lee, when you write:

“Parker asks whether the change in average temperature over time in areas with UHI is different than in areas outside the UHI. He does this by looking at whether windy days, with outside air mixed into the urban environment, shows a different change than calm days. Parker’s experiment directly accepts the reality of UHI, contrary to your claims in the top post – Parker is looking at comparative rates of change over time, not at whether UHI exists. This is clear and obvious – you know it, you refer to this in your comments. Your attack on Parker in the top post is deeply dishonest.”

I’m a bit confused. I
1. Where ( quote the text) does parker ask whether the change in TMEAN over time in areas with UHI is different
than areas without UHI?

2. Where does he demostrate “outside air” mixing into an urban enviroment. I’m looking at the fresno
airport ( a site used by Parker) and I’m wondering which DIRECTION of wind Parker
used to specify that the wind was from “outside” a UHI area.. . Which direction
of wind brings “OUTSIDE AIR” to urban fresno? open question. I’m looking for that in parker.
Would it be wind from the East? or southeast.. I’m searching his paper and data and I cannot
find anything about “wind from outside the UHI area” In one sense all wind is from outside
of the site ( a point), but When santa Anas blow from the desert toward the southern california
coast thats a wind from outside the UHI area. ( hot as bloody hell)

3. Where does Parker classify sites as to whether they are UHI or not? How does he do this?
I missed the site surveys. UHI is caused by more than Population . It’s related to SITING. This
is why NOAA is redoing the network. Have a look at CRN. I can make a site in the middle
of wilderness into an HOTBOX. ( have a look at lake spaulding) So where are Parkers site
surveys?
Without a site survey showing the geometry of the site and composition of the surrounding area
This UHI classification is under question.

4. He did not look at WINDY days with outside air MIXED. He looked at wind VELOCITY
at the grid level. And he looked at the correlation of wind VELOCITY at the grid with wind
velocity at the site. Simple question. If I told you that the wind was moving 600 Miles per
hour over a surface, would you say that was a MIXING event?

Johnsen talks about Turbulance decreasng UHI, I think Parker needs to condiser
that the distinction is not CALM versus WINDY, the issue is Turbulant versus Laminar/stagnant. A hot
laminar wind will not cool stuff off. More simply. wind speed says little about MIXING. So, parker measured
velocity. He did not measure mixing at the site. I would have fewer issues with Parker if his
bifuraction were Turbulant ( mixed) verfsus laminar/stagnant. (unmixed).

steven mosher

Hi Lee,

Good to see you comment back. Trust me I know the urge to shoot from the hip. So,
your apology is accepted. Anyway Let me address you point by point. I will keep
it civil, since my goal is simply to figure things out, hopefully make a contribution
maybe ask one good question.

So,

you wrote

“I was sloppy – windy conditions reduce UHI in several ways, by mixing, by moving outside air in, etc.”

Well, Windy conditions do NOT reduce UHI. TURBULANT conditions can reduce UHI. I’m just reading
Parkers source. Let me illustrate. STRONG WINDS FROM THE DESERT rush to southern california.
This is called the santa Ana winds. Its a blast furnace. Wind speed is IMMATERIAL. You get a nice blast furnace
called the desert sending its wind your way . Also, you are still being sloppy.
CALM STAGNANT AIR over the city: UHI effect.
LAMINAR flow through the city: UHI effect can be enhanced but not disrupted.
TURBULANT FLOW; ( wind in surges, eddies, chaotic flow, spkiy erratic velocity) Layer of hot air
canopy gets MIXED and heat in the boudary escapes to the sky.

All parker did was say “windy” means winds in the 3rd tercel. That is simply idiotic. The boundary
layer gives a whit about the decile or tercile of wind speed.

You go on:

“If you want to be pedantic, go ahead. It doesnt change my point.”

Well, call it what you like, I’d like a clear exposition of parker. NEIL and milesworthy have come the
closest. Personally, I have no issue with being pendantic. Badge of honor. Then again, I could just
say “wind blows the heat away” or “wind blows the light away” or “wind blows the IR radiation away”

“Parker very clearly stated in several places that he was looking at
whether UHI caused significant differences in the temperature increase over time.
He very clearly stated that UHI exists – see for example the penultimate paragraph of the Conclusions.”

I’ll have a look at that pragraph. Thanks. But King and Milesworthy already pointed out that Parker accepted UHI.
Their position is that Parker claims NO INCREASE in UHI over the last 50 years. So, My question to
Neil, explain why ,given the known causes of UHI, that ther has been no increase.

But you went further and said parker identified UHI sites. He did not.

You go on:

“When SteveM makes his clearly stated, several times, argument that Parker was disputing
the existence of UHIs (what else is SteveM saying, when he argues taht
Parker’s paper doesnt disprove the existence of UHIs) he was simply being dishonest.”

Well, actually, a bunch of folks thought the same thing. ( especially given the title)
After some time, some defenders have modified the hypothesis about what parker
claims, by saying, He doesnt deny UHI, only denies that UHI has INCREASED in the last 50 years.
Well parker also claims that urban weather stations are in PARKS. ( we havent found one like this yet
got any clues) Anyway, UHI increases, according to parker defenders stopped 50 years ago.
Why, given the known causes of UHI?

You conclude:

“I’ll also note, not for the first time,
that SteveM is making a habit of quoting partial sentences
without giving article and page numbers. Bad form – its a favorite technique of quote miners.”

here is the funy thing. When SteveM quotes something I can actually go check it out. I have the
document ( openness is good) I have a search engine. So I search for what he quotes. Then evalaute.
My sense is this. Most guys here would love to catch steveM on something. cause a good number of
of folks here get a kick out of finding mistakes. Pedants. I live for the friggin day, regardless.

The issue I have is with people who paraphrase. or the people who wave toward a source. or the people
who apply confidentality to their words.

Willis Eschenbach

Here’s an oddity that perhaps someone can help with. Parker says he’s not using the actual data.

Smoothed (Jones et al. 1999) daily climatological averages of Tmax and Tmin, for 1961’€”90 where possible (86% of stations), were created for each station, and anomalies calculated.

The citation is to:

P. Jones, E. B. Horton, C. K. Folland, M. Hulme, D. E. Parker, and T. A. Basnett, 1999: The use of indices to identify changes in climate extremes. Climatic Change, 42, 131’€”149. Kalnay, E., and M. Cai, 2003: Impact of urbanization and land-use

I cannot find a copy of this online, if someone is willing to send me a copy at willis_AT_taunovobay.com, it would be much appreciated.

More to the point, however … why is he using smoothed maxima and minima?

I see another problems with his analysis. This is that the NCEP/NCAR reports the wind at four times daily: 0, 6, 12, and 18 GMT. However, they do not report the average wind during the period, as they do with say precipitation. Instead, they report instantaneous values at those times. This increases the difficulty of determining what the wind might have been at an intermediate time.

To me, this question of the generality of using 4 x daily, gridded “winds” to compare to the local SAT is a glaring flaw in Parker’s argument. A line of thunderstorms comes through one city, mixing the air thoroughly, while another city fifty miles away is untouched … yet both of them are treated with the same “average” wind, whatever that might be.

In addition, the direction of the wind is critical. Wind blowing from the Poles is usually colder, while winds blowing from the Equator are warmer. Wind off the ocean is cooler than wind off the land. “Santa Ana” winds, or foehn winds, are hot winds … when one of them starts to blown, his assumption that wind will cool down the UHI gets blown out the window.

Wind is a local phenomenon, not a grid-scale phenomenon.

I repeat my request to those who argue that Parker accepts that there is a UHI. If so, given that

‘€¢ the global population has doubled since 1960, and

‘€¢ energy use has doubled since 1960, and

‘€¢ the urban population has increased a staggering 3.7 times since 1960,

what is the theoretical basis for Parker’s conclusion that there has been no change in the UHI?

w.

PS – I note a comment in Parker’s paper:

The analysis failed to detect the known urban warming at Fairbanks, Alaska (Magee et al. 1999), whereas the analysis using near-surface winds did so

If his method doesn’t detect the large and well-studied urban warming in Fairbanks, it is definitely a blunt instrument …

Steve Milesworthy

#166 Willis Eschenbach
Parker compares daily windy or calm data with the smoothed climatological data to calculate the anomolies.

With regard to the wind, I assume that days in which it is windy at 0 and 6, but not windy in between are few. Even so, remember this is a proxy study. I assume there isn’t a source of more complete data for the full 50 years.

I repeat my request to those who argue that Parker accepts that there is a UHI. If so, given that…

I note that a notable increase in UHI effect has been detected in China in winter, but are there studies of UHI changes in places with less extreme increases in urbanisation? Should Parker have a theory about why UHI has not increased before adequate data on increases in urbanisation and likely effects has been gathered?

pochas

Has infrared aerial photography been given a try? Or maybe we really don’t want to know.

Hans Erren

re 171:
He also claims that “no UHI trend at dawn” can be used to prove “no UHI trend at dusk”.

steven mosher

A while back in the thread in discussion with Neil King, I did a little toy study.
( see #118)
I took the Marysville site ( which anthony has photo documented) and I compared it to
two sites in Colusa ( 20-25 miles away) From the photos of Marysville, we have a good
guess that the site is a hotbox. Buildings around leading to multipath Radiation,
and waste heat. Concrete and asphalt around impairing evapotranspiration, And shelter
effects from the wind breaks close by. Did you know a tree effects the flow stream
to a level 30 times its height? Anyway, I took the marysville site because it’s a siting
disaster and its used by GISS.

One site in Colusa was of particular interest to me. It’s an agriculuture weather station
part of californias pest managment system. Located in a feild.

When compared for the past 20 years or so, I saw this. Tmin in the feild was lower than
Tmin in marysville. No suprise, UHI. When I looked at the trend in Tmin, the difference
was widening. UHI getting worse. A local example of the global phenomena that Parker denies.

basically, with a direct method, with a method where you classify the site based on actual
survey, You don’t have to look at the wind. The increase in TMIN trend, which is the signal that
Parker is looking for under calm conditions, shows up under any condition.

So, now I’m in the processes of doing another little toy study. Parker Uses Fresno airport
as a site. AND Anthony is headed to fresno to document the
Site at the airport. Checking agriculature records on the area turns up a bunch of sites
within 30 miles. And one site a handfull of miles north at the university ( you wont find
this stuff in Jones or Hansen) The university looks a bit urban ( site survey will tell)
And there are other sites in the area that are clearly Rural, but for now, I tossed
The unversity data in the hopper.

So, a quick and dirty comparison of TMIN Airport – Tmin University.
Daily data averaged for the year.

If we see a delta in Tmin, that would signal some UHI. If we see the delta GROWING over time, that
signals increasing UHI. ( parkers arguement)

For the years 1982-2006. Average Tmin (airport) – Average Tmin (univesity)
( C)

1
2
1.8
1.9
1.8
0.9
0.8
1.4
1.5
1.5
1.4
1.3
1.4
1
1.4
1.3
1.3
1.6
1.8
1.8
1.8
2
2
2.2
2.1

Have a look. tell me your thoughts.
If I get time I’ll pull data for the really rural sites
The point is that Parker resorted to a really indirect method, when a more direct method was
available

Ken Fritsch

In order to cut directly to the chase I have these questions for Steve Milesworthy and Neal J. King:

If the differences in trend lines for Tmin under windy versus calm conditions can serve as a proxy for a changing UHI effect how would this be calibrated?

If we cannot measure the UHI effect directly by some other means how would one calibrate Parker’s measurements?

Is not it the case that had Parker seen an even small but significant difference in his windy versus calm trendlines, he would have had a calibration problem in relating the trend line differences to a degree temperature UHI effect? Would not this indicate that a zero difference avoids all these issues?

Can either of you show in a post an excerpt from a reference that definitively and unequivocally spells out the basis for Parker’s assumptions for Tmin under windy versus calm conditions? And for that matter explains the differences for Tmin and Tmax that Parker sees for windy and calm conditions?

steven mosher

SteveM the worthy

You wrote:

“No, Parker’s method would be to split the dataset into windy vs calm.”

AGREED. But Parker did this bifuraction Because he thought the following.

IF a site were Urban ( UHI impaired) and If UHI is increasing over time,
Then we should see the signal in a calm/windy comparison.

I’d skin the cat another way. Classify the site. Then analysize the signal.

I understand his method. It’s a noise farm. But, you can do it without actually
looking at a site and making an assesment.

Kenneth Fritsch

Steve Milesworthy, thanks for your thoughtful replies to my questions, but you may have overlooked my most cutting to the chase question which I have repeated below. To me it is major point of Steve’s M analysis of the Parker paper and one that on reviewing the posts here I do not seen a detailed reply.

Can either of you show in a post an excerpt from a reference that definitively and unequivocally spells out the basis for Parker’s assumptions for Tmin under windy versus calm conditions? And for that matter explains the differences for Tmin and Tmax that Parker sees for windy and calm conditions?

steven mosher

What steveS Said!

Willis Eschenbach

Steve Milesworthy, you say:

I note that a notable increase in UHI effect has been detected in China in winter, but are there studies of UHI changes in places with less extreme increases in urbanisation?

which led me to look up the degree of urbanization in a few countries. Globally, since 1960 the world population has about doubled, but the urban population has gone up by 3.7 times. A couple of representative statistics:

World 3.7 times the urban population
Western Europe 1.4
US 1.8

So, while the US and Europe have not gained as much as China, the US urban population has nearly doubled.

UHI can also happen in small towns, as the example of Barrow, Alaska shows.

w.

Neal J. King

Steve McIntyre,

Thanks for making available pdf’s of the Johnson and Oke papers. However, I’m having trouble printing them: They seem to come out with the top & bottom cut off.

Is it possible you could post better-printing versions?

The papers in question are:

Johnson, G. T., T. R. Oke, T. J. Lyons, D. G. Steyn, I. D. Watson and J. A. Voogt, 1991: “Simulation of surface urban heat islands under `ideal’ conditions at night, Part 1: Theory and tests against field data,” Boundary-Layer Meteorology, 56, 275-294.

Oke, T. R., G. T. Johnson, D. G. Steyn and I. D. Watson, 1991: “Simulation of nocturnal surface urban heat islands under `ideal’ conditions: Part 2. Diagnosis of causation,” Boundary-Layer Meteorology, 56, 339-358.

Thanks.

PaulM

# 174 well done steve mosher. As steve Mc said in the original post this is obviously the right thing to do. There is no need to make a string of dubious hypotheses about wind, as done by Parker, or invent artificial equations, as done by Neal. The answer is right there in the data. Classify the sites as urban or rural (before looking at the data!) Then look at the trend in each group.
Here is another thing that is completely wrong in Parkers paper. He says UHI is most evident in summer. In fact the study by Easterling et al that he quotes seems to show much stronger UHI in winter than in summer.
There is another great misquotation here (#22). Parker: “Easterling found that UHI was little more than 0.05 degrees/century”. Easterling: “The difference in the trends is about 0.1 degrees per 100 years”. Well, I suppose it is true that 0.1 is little more than 0.05!

MarkW

Neil,

Try changing the orientation to portrait.

Cliff Huston

Neal,

I printed both papers without problems, on my Mac and on my PC (XP). I’m printing to an HP 4050N (Postscript) over ethernet from Acrobat 6.xx on both systems. Most problems I’ve seen, on other forums, printing Acrobat documents usually turns out to be a print driver problem. You might want to check to see if there is a later driver for your printer. BTW, I find it strange that your having problems printing to A4, when both papers appear to originate in A4 – I printed to US letter (8.5″ x 11″).

Cliff

Cliff Huston

Neal,

Parker printed fine here as well. The only difference I can see is that the Parker paper was originated in US letter format. If I print the A4 format papers (to US letter), without scaling, I see, as you reported, the top and bottom cut off. Have you checked the driver set-up in the control panel? Some times the Windows defaults over ride the the application print dialog. I have seen this A4/US letter mismatch reported before (on Windows, both directions) and generally it was a driver or print control panel set-up issue.

Cliff

steven mosher

RE 195..

Flow therm?

I assume its an analysis package?

I’m wondering about the money to be made in doing EIR analysis for modifications
to the cityscape. Seriously, If these nitwits have their way, I’ll be paying taxes
out of my southern nozzle at a rate which will stall the intake.

You’re a Cali guy. So you will get a kick out of this.

http://www.project2105.org

To preserve salmanoid downstream of the dam, cold water will be drawn from the
lower levels of the lake ( killing the fish in the lake) by installing a Thermal
curtain.

The local tribes object because the lake covers ancient indian burial grounds.

Steve Sadlov

Flow therm is canned software used by engineers designing various products – electronics, automotive, etc.

Vince Causey

Going back to the formal methods that Neal and others have used, I’d like to suggest one of my own, similar to Neals. First thing is I’m thinking that windy conditions are mostly associated with low pressure systems, and therfore cloudy and cooler. Therefore let
Trend[Ac] – Trend[Aw] = (1 – r)Trend[UHI] + Cw
where the new term Cw represents the cooling effect of windy weather systems. It is constant and trendless. Parker already showed that Tren[Ac] – Trend[Aw] is zero. This gives us the possibility that (1 – r) = 0 because Cw is trendless. Therefore UHI dissappears from the equation and Cw represents the difference between the 2 lines Ac and Aw. In other words Parkers results can be explained by the cooling effect of the windy weather conditions. Now, the obvious test of this claim is to do a control experiment with rural stations. If the Cw effect is correct then the same results should be obtained from the rural sites. However, if the rural sites do not show any difference between Ac and Aw, then the difference Parker has recorded is due to UHI which has no trend.
Parker has not performed this control so his conclusion is unproven.

Steve Milesworthy

Steve McIntyre, thanks for making Johnson 1991 available.

I was surprised to say the least to find that the paper reports that the models found a maximum heat island intensity “towards or at the end of the ‘night'” justifying the Parker focus on Tmin.

Neal J. King

Continued from #203:
Responding to:
#149: Steve McIntyre
#169: MrPete

a) “Unadjusted data”: Why should Parker apply an urban adjustment? He’s depending on the urban heating to give him his signal.

b) “Correlation between NCEP grid-cell reanalysis and actual windspeed”: Parker studied that issue for 26 stations. For 18 out of the 26, the correlations were in the range 0.6 – 0.8. More detail is in Appendix C.

Neal J. King

Continued from #205:
Responding to: #160: MarkW

– When there is no wind, it would seem intuitive that the temperature would be higher in the center of the urban region than at the edge. However, if the direction of heat loss is vertically upward rather than horizontally outward, the difference would quickly saturate as the city grow wider. This is the sort of thing that has to be determined by a survey, certainly geographical and possibly over time.

– When there is a wind, the temperature of the breeze will depend not only on how long a distance it has passed through a city to get to the station, but how much heat it has picked up along the way. If the wind is more than a slow drift, it might not be very much at all. This is a question of some calculations, and possibly some experiments.

– The question of whether increased population leading to increased density does not seem silly to me: i) some aspects of the UHI do not depend on population density (Johnson); ii) there is a limit to how close people like to live to each other, sometimes enforced by housing codes.

Neal J. King

Continued from #206:
Responding to:
#137: Joe Ellebracht

#138: Chris H.

#139: Willis Eschenbach

The question at which Parker’s study was addressed was the question: “Could the global warming apparent in the record of land-based temperatures be due to an increase over time in the local UHI effects?”

What this means is that the question of whether or not urban areas are representative of the world’s land area is completely separate from this question: That speaks instead to the question of whether an urban trend can be legitimately interpreted as a global trend.

But Parker is asking about the actual (as opposed to artefactual) nature of the weather-station trends themselves, not about whether they are representative.

Neal J. King

Continued from #208:
Responding to: #166: Willis Eschenbach

– “Why is Parker using smoothed maxima and minima?”
Probably it was faster and easier. He doesn’t acknowledge anyone for help in doing data analysis, so he may not have had much help. He may have figured that if the results of the study looked interesting, surely someone would be willing to do it more thoroughly later.

– It’s easier to calculate average precipitation than average wind velocity: precipitation is collected over time, but measured at discrete times. But a velocity measurement only relates to a specific time.

– Your concerns about the nature of trying to analyze a continuous quantity like wind velocity by measurements discrete in time and space are reasonable. However, these issues are inevitable in that he is trying to wrest information from data that are both limited and irreplaceable: One cannot go back over the last 50 years and do a better job. And he has addressed the question in Appendix C: the correlations of wind in time & space afford some confidence that there is a meaning to his calculations. The very fact that there is a gap between the calm- and windy-day readings indicates that there is some reality that he is reaching, even if attenuated by less than 100% correlation.

Neal J. King

Continuing from #211:
Responding to:
#165: Ken Fritsch

There are limitations imposed by journals on how much space they are willing to give an article. In addition to that, they often impose page charges. For these reasons already, it is impractical for a scientist to publish all the data upon which his conclusions are based.

However, Parker seems to have been willing to make more information available upon request.

Neal J. King

Continued from #212:
Responding to:
#176: Ken Fritsch

#177: Steve Milesworthy

I don’t know if the term “calibration” applies, but I would refer you to #15, Eqn.(12). This of course doesn’t determine the factor of (1-r).

The fact that r is not = 1 would follow from the study by Hinkel et al. of Barrow, AL. But it is more or less obvious: If the wind is blowing warm air away, the temperature will be cooler, so r

Steve McIntyre

#205, 213. We’ve discussed the etymology of the term “Hockey Team” and its shortened version Team in the past. I didn’t originate the term – it was originally used at realclimate to say that I wasn’t merely challenging Mann; I was challenging an entire Hockey Team.

Neal J. King

Continued from #215:
Responding to: #144: steve mosher

OK, I’ve finally been able to print and read (to some extent) the papers by Johnson and Oke.

Some of the source of the UHI has to do with the number of people and some of it has to do with the buildings.

Neal J. King

Continued from #219:
Responding to:
#152: steven mosher

In Section 3, Parker points out that when he tried out a change of definition of “calm” from “lightest tercile” to “lightest decile”, the global trend in Tmin did not change. To quote him, “So the overall analysis appears not to show an urban warming signal and to be robust to the criterion for calm.”

Neal J. King

Continued from #221:
Responding to:
#164, #183: steve mosher

– Personally, I would think that the proper division between “windy” and “calm” would be some specific speed. However, Parker chose to use percentiles. However, as mentioned above (somewhere), when he altered his definition from lowest-tercile to lowest-decile, there was no significant difference in the trends. So that suggests that his definition was not sufficiently bad to make any difference: windy is windy.

– It is a question as to why a growth in UHI hasn’t been more evident. I suspect that a detailed topographic study of a city over some time may be necessary to answer this question. My casual idea is that there will be some kind of saturation: the UHI doesn’t just get hotter and hotter as you get deeper into the city, but there is some kind of saturation. But that’s just an off-the-wall thought.

Neal J. King

Continuing from #223:
Responding to:
#178: steve mosher

Classifying the sites and measuring afterwards constitutes a different analysis.

They are complementary, not exclusive.

Neal J. King

Continuing from #225:
Responding to:
#129: Brooks Hurd

I’m glad that Parker was responsive to your request for more information.

It is an expected signature of GW that the diurnal variation should be decreasing.

Neal J. King

Continuing from #227:
Responding to:
#158: pochas

Parker’s study covered the period of 1950-2000.

It’s likely that, if the weather station were not present for all 50 years, he would have omitted it from the study.

If a weather station is installed at an airport, that probably means that it was installed at the time of the creation of the airport, or shortly thereafter: As someone remarked above, who care’s about the weather in the middle of the sticks? But what that means is that it’s quite possible that no one ever installed a weather station and then found out later that someone built an airport there:
Either:
– The station was installed after the airport was built; or
– It has nothing to do with airports.

Neal J. King

Continuing from #229:
Responding to:
#171: James Lane

No, not all of the UHI needs to be removed by the wind. In my Eqn.(12) in #15, the amount is (1-r)UHI. (Maybe Eqns. (9) and (10) would be more appropriate.)

The closer r is to 1, the more obvious the effect. But the graphs that Parker shows already show that r is not 0. In principle, that’s all that’s really necessary.

Neal J. King

Continuing from #231:
Responding to:
200: Vince Causey:

Your proposal depends on too many coincidences:

– First of all, you have inserted Cw, a cooling effect, in an equation about TRENDS. The only way this makes sense is if you are talking about the TREND of the cooling effect of the wind. But you have also stated that the Cw is trendless, so the TREND = 0. You should instead go back to Eqn.(8) in #15.

– Anyway, if (1-r) = 0, there would be no gap between Ac and Aw, and Bc and Bw.

– Actually, I discussed this already in #78.
I think you need to study the situation further.

krghou

Re: #229

Thanks for the reply, Neal. You have contributed well to one of the most thoughtful discussions I have seen here recently.

Anyway, it appears I wasn’t very clear in my first post. Then network I was refering to was not the stations used in the Parker study, but any one used to compute a US or North American average for instance.

As an example suppose in 1950 50% of the station used for computing a US temp average were rural, and 50% urban with constant 3C UHI effect (not increasing as per Parker). Over time fewer rural stations are available, and by 2000 only 25% are rural. Obviously the mean US temperature would increase due to the weighting of UHI effected sites (off top of head 0.75C), even if the UHI contribution at each particular site was constant.

Neal J. King

#216: Steve McIntyre

My impression remains the same, as expressed in #235: Unless you want to address only a closed group of committed initiates, there is absolutely no point – or advantage – in objectifying people who don’t agree with you as a monolithic entity incapable of straightforward logical thinking. It doesn’t make your argument any more convincing.

Steve McIntyre

Lee, please provide a quote where I said that:

SteveM’s original article here is disputing whether Parker has shown that there is no UHI.

I said of Parker’s article that he:

purports to show the absence of an [UHI] effect on large-scale averages by showing that the temperature trends on calm days is comparable to that on windy days.

I didn’t say that he was a UHI-denier; I said that he denied that UHI had a material effect on the large-scale averages (GISS, CRU), which is exactly what he claimed.

I concluded with the question:

Has Parker shown that the belief that UHI affects CRU and GISS averages is an urban myth? Or is the belief that Parker has shown the irrelevance of UHI to large-scale averages an urban myth

?

Because CRU and GISS are anomaly based, any affect on these averages would affect the trends and vice versa.

Steve McIntyre

#239. Neal, I asked this generally, but it got lost. Can you give me any citation containing measurements in any city confirming in an urbanizing situation that NCEP gridcell windy versus calm trends are a indicator for urbanization (in a known environment). Without some ground truthing, it’s just a “proxy”. So are tree rings.

In the one site that I’ve examined data (Freso in another post), there is a known urbanizing setting and windy-calm doesn’t identify it.

Steve McIntyre

Lee, you’re getting overwrought because you don’t understand the role of anomalies in the large-scale averages. You say:

He accepts UHI, explicitly – of course that will affect the average temperature of gridcells that have urban stations.

That’s not correct. IF you were averaging actual temperature measurements, this would be true, but the gridcell methods convert temperatures to anomalies. If there’s no change in UHI effect, then the any UHI is washed out in the anomaly. I repeat one more time: because CRU and GISS are anomaly based, having an impact on the large scale averages can be accomplished only through trends and vice versa. I assumed that everyone understood that, but obviously you don’t. There’s nothing incorrect in my characterization of Parker; it’s just that you don’t understand how anomaly systems relate to trends and vice versa. I might have expressed it more clearly for people that aren’t up to speed, but that’s a very different matter.

I discuss and describe UHI to introduce things. I provided a companion post Godowitch et al that discussed UHI in more detail.

Lee

I will grant, Steve, that one can make a (very) sideways argument that by using ‘average” you were referring to the anomaly trend. That usage is in line with the rest of your article, though – you are a very good writer, and I believe yo write for exactly the impact yo want – and doesnt address the transect stuff, nor the irrelevant to Parker data showing a UHI (not a trend), nor the quote mine.

Jim Johnson

Here’s a poser …

Parker acknowledges that there is a strong Tmin warming trend, windy vs calm, across europe and asia on winter nights, and that this trend is concealed in the global annual average. He understates this. The windy warming trend is strongest in europe and asia on windy winter nights, but it holds across his reported data (Table 1), for all seasons.

What I would like to know is, where on earth (literally) is the opposing cooling trend that accomplishes the concealment?

It is not in the Arctic, or Europe, or North America, or Asia. It is not in the entire Northern Hemisphere north of 20*N, nor in the Tropics north of 20*S. And it is not in Australasia. So says Parker.

That only leaves the very southern tip of Africa, the skinny part of South America, and Antarctica. WTF?

Parker asserts that UHI effects on the land surface temp record would be shown by a difference in trend between windy and calm nights. He finds such a trend up in the 95% of the planet’s landmass that hosts 99% of the worlds people.

And given that he is able to make his asserted case by zeroing out that warming trend for the global, he must have found a really strong trend in opposite direction, somewhere in the rest of the planet that has no people.

It appears to me that he has either demonstrated an effect of UHI on the temp record, or invalidated his assumptions and/or methods.

Or, all of the above.

Steve McIntyre

#246.

Parker acknowledges that there is a strong Tmin warming trend, windy vs calm, across europe and asia on winter nights, and that this trend is concealed in the global annual average. He understates this. The windy warming trend is strongest in europe and asia on windy winter nights, but it holds across his reported data (Table 1), for all seasons.
What I would like to know is, where on earth (literally) is the opposing cooling trend that accomplishes the concealment?

Good question. Here’s a barplot showing distinct regions from Table 1 (Annual), excluding NH north of 20 which is a subtotal. For 241 out of 265 stations, there is regionally a greater trend on windy days than calm days. On Parker’s unproven hypothesis that this trend is an index of urbanization increases, this would indicate a de-urbanization in most of the globe during the past 50 years.

The offset as you note is in the Tropics, but there’s something wonky here as the trends are only 0.17 versus 0.18 over 24 stations: located in Thailand, Phillipines, Malaysia, Colombia, U.S. and French colonies. There doesn’t seem to be enough weight to offset the other stations. Very strange. There are some other wonky entries in Table 1- some trends for “all day” exceed both the calm and windy trends, which is impossible. So there’s something wrong here.

Willis Eschenbach

Neal, thank your for your participation in the thread. You say:

– The benefit of Parker’s method is that it makes use of 50 years of data that have already been gathered, and which no one is ever going to be able to collect again.

Actually, he’s comparing 50 years of temperature data to 50 years of computer generated winds … but if that is valid, why not compare 50 years of computer generated winds to 50 years of computer generated temperature data?

w.

Neal J. King

Responding to:
#246: Jim Johnson
#248: Steve McIntyre

Parker’s calculations of trends are a bit opaque to me, too.

As I remarked earlier, it would actually be useful to boil down people’s questions to a small number of focused issues and ask Parker to reply. Maybe we could start a draft.

Neal J. King

Replying to:
#247: TAC

#252 should have referenced your remark as well.

“A paradox, not an explanation.” Well, clearly, some more work on this is needed!

Neal J. King

Replying to:
#245: James Lane

Actually, if you look at the graphs, it’s usually warmer on windy nights. For example, in the caption to Fig. 6: “Tmax is, as expected, lower on windy than on calm days in summer (b), but higher on windy than on calm days in winter (a), because persistent near-surface inversions are limited to calm weather.”

The reason is that on calm nights, the still air protects the temperature inversion (from the rapid cooling of the ground due to IR radiation to the sky), whereas on windy nights the inversion layer is disturbed.

Not quite as intuitive as one would expect!

Neal J. King

Replying to:
#250: Willis Eschenbach

1) The NCEP/NCAR Reanalysis project is probably much easier to work with to get comparisons over a 50-year period. Stealing a quote from the site
(http://www.cpc.ncep.noaa.gov/products/wesley/reanalysis.html#intro)
“Until recently, the meteorological community has had to use analyses that supported the real-time weather forecasting. These analyses are very inhomogeneous in time as there have been big improvements in the data assimilation systems. This played havoc with climate monitoring as these improvements were often produced changes in the apparent ‘climate’. Even fundamental quantities such as the strength of the Hadley cell has changed over the years as a result of the changes in the data assimilation systems.”

2) Parker does address this issue in Appendix C. He believes that it should not cause a global bias exceeding 10% of the observed warming signal.

Kenneth Fritsch

Neal J. King, while your attempts to clarify what Parker has explained/imparted in his paper have been admirable, if for nothing more than the shear effort of it all, I think most of us, in the end, however, including you — I think — can agree that for Parker’s paper being considered an authoritative source and on a critical question vis a vis climate policy, it leaves too many questions unanswered. I find no conspiracies here, but I am puzzled why these questions have not been settled by the climate community or at least more concerted attempts at settling it than I see being made. His “averaged” global finding is a very convenient one for the advocates of AGW, much in the same manner as Mann’s HS was.

I think he owes some answers before the more skeptical amongst us will be satisfied. I only hope his reaction to questioning is better than that Mann has shown. Without the answers from Parker, I only see digging into the available data for contradiction and confirmation as being productive ‘€” and that is where I think Steve M does a particularly good job.

Dave B

#258…Neal said:

2) Parker does address this issue in Appendix C. He believes that it should not cause a global bias exceeding 10% of the observed warming signal.

He believes it…hmmm…odd wording, isn’t it? especially for a scientist? Does parker prove it, or offer supporting evidence? or does he just hand-wave his belief? ( I don’t have appendix C, if you have it, send it along, i’d like to see for myself.

Neal J. King

#260: Ken Fritsch

Of course I think questions are fair.

However, I also think that it would be most fair if some effort were made to create a finite list of well-defined questions that would be likely to satisfy the questioners. I don’t think anyone looks forward to being hounded by an endless stream of “why”s.

If we lay out a polite but thorough list of non-redundant questions that address the study that he actually did (and are not disguised forms of “Why didn’t you do a different study?”), I can only imagine that he would be pleased to answer the questions. (Whether he would have the time or energy to re-do the analysis on different lines is another question.)

Neal J. King

#263: Steve McIntyre

I think the situation is addressed in #259: It’s not an issue of whether you have a proxy for urbanization, it’s a question as to whether the analysis was done on a sample representative of the globe.

Jim Johnson

Neal,

“I use the word “believe” because I haven’t sat down and made sure I followed it all out.”

Why would your comfort with the material affect the word you use to characterize Parker’s commitment to a proposition?

Put down the pom-poms. Read more. Talk less.

Dave Dardinger

re: #264

If we lay out a polite but thorough list of non-redundant questions that address the study that he actually did

I notice you haven’t gotten to my question in 257 yet. Now, true the question isn’t precisely about what he did, but it is about how the results can be interpreted, so I think it needs answering.

Kenneth Fritsch

Re: #264

If we lay out a polite but thorough list of non-redundant questions that address the study that he actually did (and are not disguised forms of “Why didn’t you do a different study?”), I can only imagine that he would be pleased to answer the questions. (Whether he would have the time or energy to re-do the analysis on different lines is another question.)

Obviously the straight forward requests would be to obtain sufficient information and data to repeat his analyses and to do the analyses differently, and, for my preferences, look at the data in greater detail with regards to individual sites and shorter time periods. Those are requests that really would only formalize what he should already have provided or be prepared to provide as a practicing scientist. It should require little extra effort on his part.

Other questions for Parker would and should be, in my mind, limited to asking him for the details of his (hopefully a prior) site selection process and rationale and more details on the scientic foundations of using such an indirect method as his trend comparison when one might intuitively think more direct ones are available. But those are my views and perhaps why I think a query by committee may not be particularly effective.

Jim Johnson

Neal,

– There is some question as to how the global trend of UHI averages to zero, although the trends of nearly all regions for which trends are reported are positive.

No.

There is some question as to how the global trend of ‘windy-calm’ averages to zero, given the large magnitude and areal extent of the reported positive trends vs that of the reported negative trends.

There is some other question as to whether ‘windy-calm’ trends mean anything at all with respect to UHI … and if so what that meaning is both alleged to be by (Parker 2006) and actually is, for all values (positive, zero, negative) of ‘windy-calm’ trends.

And following from those two, there is a further question as to whether or not averaging local, daily ‘windy-calm’ trends to larger scales (temporal or spatial) is a legitimate exercise at all, given the meanings assigned to such trends.

Those would be a good start. Others, such as …

There is some question as to how it is possible to assign each station day to one of two windspeed classifications that are defined by a tercile binning.

… you might want to ask later, so as to not appear to be preparing for a trial or something. 🙂

TAC

I would be interested in disaggregated results by site and by year. What Parker reported were averages, which can be misleading if outliers, multiple populations, or un-modeled processes are present. Specifically, it would help to have a list of stations with identifying metadata and (for each station and year): TminCalm, TminWindy, TmaxCalm, TmaxWindy.

Although I don’t expect to find anything earth-shattering, I think it would be interesting to check the sensitivity of the conclusions to choices of statistical approach. Parker considered simple autocorrelation, but the this sort of data also exhibits homoscedasticity, as well as spatial and long-term-temporal correlations that likely need to be addressed, too. Given the structure of variability in similar datasets, it seems likely that GLS (generalized least squares), at the least, would be appropriate.

However, that conclusion might depend on one’s purpose. For reasons that Neal has touched on (in particular, the beneficial cancellation that occurs in “crossing the river twice”), the best strategy for estimating the component of UHI in estimated global temperature trends during the last 50 years is likely not the same strategy as is needed to provide insight into the physics of UHI. It might turn out that Parker’s approach addresses the first problem while doing nothing for the second.

Neal J. King

#272, #277: Ken Fritsch

There are three reasons why I would not favor the approach you propose:

1) Introducing oneself with a “gimme all your data, and if I want your opinion I’ll beat it out of you” approach establishes a relationship that is not merely adversarial but hostile. That has the tendency to shut the door to further discussion.

2) For a scientist, being approached respectfully should not be taken as being overly deferential, if the right questions are being asked. In my experience, the best way of establishing your credibility with technical people is not by attempting to bully or one-up them, but by focusing with laser-sharp focus on the technical issues and potential weak points of the argument. That puts both of you on the same side: staring critically at the problem, not at each other. If both of you are trying to understand what is going on, you are partners, and people will go through some effort for partners, even short-term partners. But if your approach is, “I know you’re wrong, and I’m trying to find the evidence for that,” the interaction is completely different, and likely to provide far less information.

3) Scientists are generally more than willing to explain how they have come to their conclusions. But that doesn’t mean that they are ready or willing to turn over raw data:
– Depending upon the size of the group (and he doesn’t acknowledge any assistants), he may have taken shortcuts in how the data are formatted and organized. To me, that suggests that he might have to do quite a bit of work to prepare his raw data in such a way that it would be presentable to an outsider, instead of being highly confusing or even misleading. The fact that he didn’t do a 100% analysis of all the data that he had available suggests some kind of resource limitation (probably time) to me, so shortcuts are more likely. He probably did as much as he thought was necessary to answer his questions. In the same way, most people don’t prepare each tax return with the expectation of getting an IRS audit: They do a good-enough job that, if they are challenged, they can put together a reasonable picture, with some extra effort. That does not mean that they would be ready to go on a moment’s notice; and they don’t seem to look forward to these occasions of self-justification, either.
– Finally, even the collection of the raw data, much more the different stages of analysis, represent a considerable degree of intellectual effort. Science is a competitive enterprise, and scientists will prefer to milk the last drop of significance from their data before releasing it to the world: this is their livelihood.

If you take these three points into consideration, you might see two things in the questions I have asked:
– I have been polite, but I have also focused on the specific issues that, assuming that Parker’s work is valid and carefully done, are still puzzling. These are questions that should interest him as well.
– I have also asked these questions in an open-ended way, so that Parker gets a chance to explain what he was thinking about. This aspect is the weakest point of his papers: His parsimony in explaining his motivation for adopting certain strategies. (My impression is that this is a combination of responding to the journal’s space limitations, page charges, and the British style of understatement.) I suspect that many of his methodological peculiarities will be much better understood when we have an understanding of what he was trying to do, and what constraints he was operating within.
– Finally, going in politely at the beginning does not preclude screaming and yelling later, if information is not forthcoming. The reverse is not the case.

Neal J. King

#275: James Lane

According to my analysis in #15, the answer to your question lies in the factor “r”: (1-r) is the proportion of the UHI that is “blown away” by the wind.

I don’t see how this value can be measured by the data available, and it is not necessary to believe that it is constant over all sites.

I think your question boils down to the issue of more precisely how his global average is calculated.

Dave Dardinger

Neal, you’ve mentioned a couple of times that Parker would be amenable to a set of questions which doesn’t set off alarm bells.

I’m afraid that that’s probably not possible at this point. I’d be astounded if he has not be alerted by one or more likely several people that he’s being debated on ClimateAudit. Sure from a public view ClimateAudit is under the radar, but for the cogniscenti I’m sure it’s watched carefully. And I think Steve or some others here have sent questions or requests already. In fact, I’m sure of it as that’s what one thread not long before this one was precisely about; to compliment him and someone else for responding promptly and favorably to data requests.

Therefore I’m sure he knows what’s going on and likely is keeping a bit of an eye on things as he surely knows of Steve from the M&M vs MM wars.

Neal J. King

#282: Dave Dardinger

It is not a question of “setting off alarm bells” or not.

It is a question of opening an open-minded discourse.

And if he is informed that the questions in question represent the boiled-down discussion of several people, I think he will give it more attention.

No tricks, nothing up my sleeve.

Kenneth Fritsch

Re: #278

Neal J. King, I believe, as DD indicated #282, Steve M has already requested the data and Parker has agreed to follow up that request. I’ll agree to disagree with how you in how we classify the appropriateness of a formal request, and, since you have agreed to present questions in a manner that at least according to your standards would not allow an excuse for less than a full reply due to potential “hurt feelings” or “aggressive asking” or whatever non-issue might be offered, I will throw the challenge to you and await the replies from Parker to your queries’€” but not for a long, long time.

Perhaps your and my experiences have been with a different variety of scientists. I always found that the truly committed scientists wanted to talk, write, explain, defend and generally show off their data and the analyses of it to the point of doing so at something less than a drop of hat and without provocation or prodding. Therefore when I hear of scientists who show hesitancies in these activities, pardon me, if I wonder.

Steven mosher

RE 285.

Neil, My gut sense looking at this stuff.

The UHI signal or the Microsite signal is there. Direct analysis of individal sites shows this.

At a global level, or with an indirect method, you’re unlikely to detect the signal with

high confidence. Eliminating Highly comprimised sites would bring the SST profile and MSU profile

Into better accord with the land record. The land record is out of sorts. Fiddle with that.

Steven mosher

re 289.

size of the effect. extent of the effect. variance.

Hans Erren

If I am a subject on a blog I go there in person. eg eli with his knmi analysis where he tries to defend the giss homogenisation.
Parker OTOH is hiding is his ivory tower, hoping that the thunderstorm will drift away.

Kenneth Fritsch

Re: #287

The point is that I don’t want to screw up the probing by making assumptions about the personality of the author.

Neal, I understand your concerns in erring on the side of caution. I look forward to your questions of Parker and his responses and thank you in advance for your efforts.

Gentlemen. If Parker is, or has read this blog he will be laughing his socks off. You are talking as children planning a plot against a parent unaware the parent is standing outside your bedroom door. I’ll ask…. no I will…. no I want to…. but you asked last time…. so?

No, Paul, it is you who is laughing his socks off. Even at my advanced age I have sufficient “child like” sensitivities to realize what people are really saying. As for Parker, it does not matter what his reactions are to these preparations. We will learn from his responses and from a lack of response on his part.

Neal J. King

#292: Hans Erren

You and Parker are different people, and may very well take a different attitude towards discussion. That’s primarily a question of personality. But I don’t think we’re primarily interested in Parker’s personality, are we?

I’m not, anyway.

Neal J. King

#294: Ken Fritsch

I’m glad you appreciate the point. As you said, we’ll learn from whatever he says, and from whatever he doesn’t say.

jae

297: You can’t “blow off” UHI. See this link.

Neal J. King

OK, folks:

Here’s my formulation of the questions.

I would be interested to hear any fine-tuning of them. (But I don’t guarantee to accept everything, either!)

I will submit them to Parker at a suitable time, depending on feedback. Pity it’s Friday already.

Here goes:

1) We have noticed that, of the 290 stations included in the analysis, the U.S. sites seem to be at airports. Are all the 290 sites at airports? Can you explain why you think that the sampling used in this study is representative for the question of estimating the impact of increasing UHI on a global-warming measure?

2) There is some question as to how the global trend of windy – calm’ averages to zero, although the magnitude and extent of the positive-trending areas would seem to exceed those of the negative-trending areas. Can you provide some insight on that?

3) Given that there can be no doubt that urbanization is going on, it is a surprise that, on a global level, there seems to be no visible growth in the UHI. Even if it is not comparable to the global-warming signal, one would expect to see something. Can you speculate as to why nothing seems to show up, at the global level?

4) What is the minimum UHI trend that could be detected, on a global basis?

5) Your study is based upon the understanding that the difference between the calm and windy day/night measurements reflects the UHI and near-surface temperature inversions. An alternative view has been suggested in our discussion: that the windy day/night measurements reflect the influence of air from a broader region, which has a lesser UHI. This is a picture in which we have an urban hotspot surrounded by a larger suburban region, both of which are undergoing an increase in UHI ‘€” but the suburban UHI is always weaker. (This is one reason why the airport question comes up earlier, in 1).) In this view, the trend in the urban UHI would be hidden by the equal trend in the suburban UHI. Can you comment on the feasibility of this interpretation?

6) You have suggested that the calm-day ‘€” windy-day signal is a proxy for degree of urbanization. If this turns out not to be the case, would that affect your broader conclusions? And if so, how?

7) As you know, Roger A. Pielke Sr. has raised an issue with regards to your study, that it does not take into account sufficiently complications concerning the near-surface temperature inversion. (This is what I was get out of it, anyway.) Would these issues be side-stepped by focusing attention on the Tmax measurements instead of the Tmin measurements?

MarkW

Parker’s claim is that if UHI doesn’t decrease when the wind blows, then there is no UHI.

If on the other hand, what is happening is that turbulence caused by wind is pulling down warmer from air aloft, then that would mask any “blow off” of UHI.

Among many other things, what Parker needed to have done was paired rural and urban sites that were close enough to be under the same wind conditions, and then compared the affects of wind on both of his stations.

There are still the problems of just declaring a day windy or not. I know it’s simpler, but sometimes you can simplify your test beyond all useability. He needed to graph the affect (cooling/warming) based on wind speed.
He needed to demonstrate that the “wind” he was charting was actually the wind that was affecting both the temperature sensor and the urban area being tested.
He needed to graph wind direction vs. affect measured.

Since none of these things were done. The study is useless.

jae

So the 4 years of study of Barrow by Hinkel & Nelson support Parker’s assumption that a wind will blow away UHI.

??? Do you mean SOME UHI??? It says:

The MUHI is maximized under cold and calm conditions, and decreases with wind speed and warmer temperatures.

It doesn’t say the UHI is blown away!

Neal J. King

#306: jae

Please read #301.

Then read #305.

jae

Parker’s claim is that if the trend of the “calm – windy” signal is not increasing with time, then the trend of UHI is also not increasing. He never claims there is no UHI: in fact, his “calm – windy” measures it to be a non-zero value.

I’m confused. If there were only 1000 people in Barrow, would there be as much UHI effect as there is for 4,500 people? It appears to me that the UHI has to increase with increasing population. Ergo, the UHI effect increases with time for most places.

John F. Pittman

#302, #307 Wouldn’t “trend of the “calm – windy” signal is not increasing with time, then the trend of UHI is also not increasing” be largely dependent on the location of the energy souces with respect to normal wind direction and the location of the station? Assume more and more energy from UHI sources, if the wind does not blow towards the unit, the signal has less chance of expierencing that energey. Conversely, if an area is growing, props to jets, 100 cars to 1000 cars, etc, and the wind blows towards the unit one expects more energy. Since one would assume about 33% of the stations would indicate UHI, counting partial energy increase from overlap and other heat effects, does this mean a.) that we should expect that global warming cooled at a rate of 33% of the estimated total UHI, or b.) that the method lacks the definition to detect a plus/minus 33% increase or decrease? based on his results.

David Smith

Re #311 Hi, Neal. You’re well-read in Parker while I’ve just begun to read the paper. I’m hoping you can help me with a basic question. I apologize in advance if this has been answered earlier.

My question is, why did Parker chose predominantly high-latitude rural stations to demonstrate a correlation between NCEP reanalysis winds and the actual station observations? It seems more appropriate to choose a variety, with a heavy weighting towards urban stations in lower latitudes.

Higher-latitude stations tend to be windier than those in lower latitudes and tend to be in regions of greater pressure differential, where the NCEP reanalysis is (in my thinking) more likely to represent true wind conditions. Middle and lower latitude locations may well show less correlation, similar to Phoenix AZ in Parker’s Appendix B.

Parker’s conclusions heavily depend on the premise that NCEP computer-generated (pressure differential derived) winds represent reality, a premise that may not be the case in regions of less pressure differential (= lower winds).

Thanks

Neal J. King

#312: John F. Pittman:

As I mentioned in #307:
“The suggestions you’re making are not unreasonable, but they are not the study that he did. They might very well be legitimate areas in which someone could look harder. But without a study that shows that there is an interesting conclusion to be drawn, no one would want to do so much work. So maybe someone (maybe even Parker) will be inspired to do the job more carefully, and see how much of the original conclusion is sustained.”

David Smith

Re #317 Thanks for the reply, Neal, it is helpful. I’m trying to get comfortable with fundamental aspects of Parker’s analysis.

Of the 26 stations chosen to demonstrate a correlation between NCEP reanalysis wind and actual wind (see Figure 1(b)), the locations are:

Alaska – 6
Northern Russia/Siberia – 12
Northern Finland – 2
Continental US – 6
Rest of world – zero

The continental US includes Phoenix AZ and possibly Houston TX, two large urban areas, with the rest being smaller places. (Note- the locations are all based on an ocular examination of Figure 1(b) and may be off.)

It’s an odd pattern for a UHI study. Surely lower-latitude, urbanized places like the UK, Europe, Australia, Japan, Singapore, South Africa, etc could have offered historical wind data as easily as 1950-2000 Siberia.

I think two fair questions would be, “What is the basis for choosing the 26 stations?” and “Can the same degree of correlation be shown for, say, urban stations in Europe, Japan and Australia?”

If the reanalysis/reality correlation is poor at most stations then Parker’s analysis is doomed. Poor correlation would likely lead to the two trends ( T,windy and T,calm) looking about the same, which is what he presented in the paper.

One meteorological reason that I wonder about a poor correlation is that I expect the effect of wind on nighttime temperature to be greater than the 1C Parker shows. Most of the stations are inland and higher latitude, where things can get quite cool at night if there is little wind to mix the air. I was surprised when I saw only a 1C wind effect.

I think your question in #317 is well-stated.

It would be interesting if he could provide plots of representative cities where actual wind data (not reanalysis data) is available, like say Chicago and Yokohama, and can show a no-difference in long-term trend in specific urban islands using real data.

(As an aside, it would also be interesting if someone skilled in graphics could plot Parker’s stations on an equidistant type global map, rather than the equilatitude projection he uses. My eyeballs tell me that he’s heavily weighted towards the high latitudes of the Northern Hemisphere, moreso than it appears at first glance at his Figure 1.)

Again, thanks for putting your time into helping this review.

TAC

Neal, thank you for taking the lead in organizing questions for Parker. I think you bring a renewed sense of civility to Climate Audit (my personal view — “auditors don’t need no stinkin’ permission” — clearly needs some refinement). Though SteveM has always exhibited tremendous courtesy toward everyone, the same cannot be said about all of us.

Anyway, I’m looking forward to reading Parker’s replies. Thanks!

🙂

Steve Milesworthy

#319 Steve McIntyre
Question 3: Johnson 1991 says on page 281

Both models achieve their maximum [heat-island] intensity towards, or at the end of, the ‘night’. Given the shape of the curves, it is not possible to estimate the time of their maxima more accurately

Tmin occurs at the end of a night, so Parker has cited correctly.

Neal J. King

#318: Dave Smith

You suggest, “If the reanalysis/reality correlation is poor at most stations then Parker’s analysis is doomed. Poor correlation would likely lead to the two trends ( T,windy and T,calm) looking about the same, which is what he presented in the paper.”

I would also point out that if the correlation were poor at most stations, not only the trends but the differences (calm – windy) would be washed out. My feeling is that a lack of correlation would hit each one (signal & trend) proportionately.

However, I will modify the text of the question to bring up the issue of how the 26 stations were selected. Watch below.

Neal J. King

#319: Steve McIntyre, remainder
#322: Steve Milesworthy
#323: Steve McIntyre

– The question about Johnson: As discussed previously, I don’t see that Parker’s reading of Johnson, whether he got it right or wrong, is a central issue. In my representation of Parker’s argument in #15, I just assumed that the wind will reduce the UHI and the NSTI effects. This seems to be very much in line with the study of Barrow. Whether it is the biggest effect of the evening or not doesn’t seem to be germane.

– As I understand Parker’s paper, his point was to demonstrate that the global GW trend had not been contaminated by a growing-UHI trend. It is actually irrelevant to his point as to whether this has anything to do with actual urban changes as such (ref. #251).

If you can convince me that these points matters, I will include them; otherwise not.

Neal J. King

#327: Oops

There is an accidental emoticon that popped in. It’ supposed to be the label for item 8.

Is there some way to turn those things off?

Richard Lewis

The measuring and recording of atmospheric temperature at locations around the world for the past century+ has been fundamentally an urban project. Temperatures weren’t (and aren’t, except by means of satellites) measured where people weren’t. So the attempt by IPCC, et al, to minimize the UHI effect is to engage in a a statistically tautalogical exercise. The global temperature record (GISS, etc.) IS the record of the UHI effect. Differences between “rural” and “urban” records are a matter of … degree, not type.

I have followed CA with fascination and admiration for several years now, and applaud the continuing audit process. Properly interpreting the screams of tortured statistics is a crucial endeavor.

David Smith

Re #324 Hi, Neal. If I look at Parker’s Figure 4 and estimate the typical difference between a calm day and a windy day I get about a 1.2C (2F) difference (0.9C at night plus 0.3C in the afternoon). I think that most meteorologists would tell us that Parker’s 1.2C calm-vs-windy difference is considerably smaller than what actually occurs. A true calm-vs-windy difference is probably several times greater than 1.2C. This indicates to me that Parker’s correlation between reanalysis wind and actual wind is suspect.

Another wrinkle is cloud cover. If, on average, windy days have more cloud cover than calm days then the delta-T mentioned above may be, in part or whole, due to that cloud cover difference. My guess is that, in mid and high latitudes, windy days indeed tend to be cloudier than calm days. I don’t know about the tropics.

So, I don’t know what we’ve got with this paper. I wish Parker had used urban sites having actual wind data, even at the price of analyzing fewer than 260 stations.

Neal J. King

#331: Steve McIntyre

I will update the write-up according:

“3) In Table 1 of Parker (2005), although for the global average, the windy trend equals the calm trend, this seems to be true in only one region (Tropics) which has only about 41 stations; whereas the windy trend exceeds the calm trend in 5 regions with about 224 stations (Arctic, Europe, Asia, North America, Australasia). (These counts are based on information you have provided separately to Steve McIntyre.) Can you provide some insight on this result?”

Steve McIntyre

#334. It would be more accurate to say that , from the list of 265 stations provided by Parker to me, I deteremined that there were 41 in the 20S-20N band defined by Parker as Tropics.

David Smith

Re #335 Neal, I explained the 1.2C poorly.

Calm days have a greater temperature range than windy days, due to differences in vertical mixing. This is true whether an UHI is involved or not. My guess is that, globally, the calm vs windy spread is perhaps 5C (though it varies considerably among locations).

If Parker is finding only a 1.2C spread, then I suspect that his “calm day” bucket and his “windy day” bucket contain many misallocated days.

Parker offers some station data in the Appendix. Suppose that Phoenix (Figure C1(b) in the appendix) is representative of the global correlation between actual wind and reanalysis wind. As an exercise, take a pencil and divide the dots into thirds along the x-axis and then the y-axis, with 1/3 of the dots being in the “calm” terce, 1/3 in the “normal” terce and 1/3 in the “windy” terce. (The pencil-drawn figure should look like a tic-tac-toe figure.)

The only dots that are properly allocated are those in the lower-left box and in the upper-right box. The other dots (those vertically aligned with the two boxes mentioned above) are misallocated.

As an alternate exercise, estimate the median windspeed in the “calm” reanalysis terce and the “windy” reanalysis terce for Phoenix and see how little difference exists.

Is Phoenix representative of global urban stations? I don’t know. I do suspect, though, that the windy, high-latitude stations Parker examined may not be representative of the globe. It’s a critically-important issue in my mind.

(Regardless, if it doesn’t rain today we’re off to photograph another Texas MMTS station (Brenham) for Anthony’s collection, so no more Parker talk. The GISS plot for Brenham is here . I think we’ll find an unadjusted 1940 station move plus nearby tree encroachment, but no barbeque pits or A/C exhausts. We shall see!)

Steve McIntyre

Here is an excellent recent article on UHI. http://climate.gsfc.nasa.gov/publications/fulltext/Jin.AMS.PrintVersion.pdf

More importantly, although a single urban region may not result in a large impact on global climate, the collective impact of all urban regions on the global climate system is as yet unknown and unstudied. Jin et al. (2004) show that zonal mean UHI has 1-3 degree warming over the Northern Hemisphere latitudes, implying that the collective UHI may be a significant contributing factor in the overall global warming signal

Jin et al (2004) actually 2006 is not mentioned in AR4.

Steve McIntyre

Sorry – http://climate.gsfc.nasa.gov/publications/fulltext/Jin_Peters-Lidard_2005.pdf

David Smith

Re #339 Thanks again, Neal, for helping people like me sort through the Parker paper. I’m beginning to read the main body of the article and perhaps I can use that to illustrate my concern. Correct me where I err.

Suppose that from 1950 to 2000 there was a 0.5C increase in T(min) due to undetected UHI growth. Using Parker’s method and assuming that the reanalysis wind accurately reflects the true wind I would expect to see Parker’s “calm” and “windy” plots diverge by 0.23C over the 50 years.

Why 0.23C? Well, per Oke (see Steve M’s reference), wind affects UHI in proportion to the inverse square root of the windspeed. An eyeball exam of the data in Parker’s appendix indicates that “windy” days are perhaps 3 times more windy than “calm” days, so using Oke’s approximation we’d expect the plots to diverge by 0.23C.

Now, detecting that 0.23C divergence depends on there being a good relationship between reanalysis windspeed and actual windspeed, such that all points are allocated properly and the spread between calm and windy is at its maximum. However, if the relationship between reanalysis windspeed and actual windspeed is poor, then there are many misallocated points and the spread lessens (dampening occurs.

My suspicion is that the dampening is greater than 50%, but let’s assume it’s 50%. That means that the divergence we’re seeking is now 0.115C, which is small and difficult to detect.

I assumed 0.1C/decade UHI growth, which is very large, and my other assumptions were generous towards detection of a divergence. If I had made assumptions more in line with the Phoenix data then the divergence I was seeking would have been considerably smaller than 0.115C indicated above.

So, to me, any dampening from lack of correlation between reanalysis and actual data is critically important, due to the small size of any underlying signal.

Neal J. King

#344: David Smith
#345: Steve McIntyre

I agree in both cases that there is a question. That’s why I have posed two relevant questions on the list:
“5) Given that there can be no doubt that urbanization is going on, it is a surprise that, on a global level, there seems to be no visible growth in the UHI. Even if it is not comparable to the global-warming signal, one would expect to see something. Can you speculate as to why nothing seems to show up, at the global level?

6) What is the minimum global UHI trend that could be detected, using these methods?”

I think these questions get to the heart of the issue. I know you would like to pin him down to specific calculations, but my perspective is that Parker knows his calculations far better than I do. Rather than try to “trick” him into revealing a some hidden bias, I would rather just ask him what he thinks is going on.

Analogy with financial auditing: My brother is a CPA who used to do auditing for one of the Big 4 auditing firms. He predicted years ago that there would be a meltdown in companies relying up on external financial auditing for their justification. Going forward, he predicts that the Sarbanes-Oxley rules will not help: by spelling out so explicitly what the auditors MUST do, these rules, in effect, specify what the auditors must do to AVOID RESPONSIBILITY for their misleading explanation. His prescription was that the auditors should make a simple statement that “the auditing report gives an accurate portrayal of the financial condition of the corporation.” Failure to conform to that would be much easier to prove than by the Sarbanes-Oxley rules.

Along the same line, I prefer to ask Parker what he thinks is going on, and why.

MarkW

#305,

The study shows that it will blow away UHI in arctic conditions, for a town of 4500.

Prove to me that it will also work in the S. California for a town of 25 million.

Prove to me that it will work on the plains for a town of 500,000.

You haven’t proven anything yet.

Another problem with the Parker study is that he doesn’t control for town size.
How long does it take for a 6mph wind to “blow out” the UHI, for a city that’s 100 miles across?

Neal J. King

OK, here is my proposed final text for the questions. Since some people may not have seen it over the weekend, I’ll will wait until Tuesday morning (GMT) to send them to Parker. Fine-tuning will be welcomed until then:

1) We have noticed that, of the 290 stations included in the analysis, the U.S. sites seem to be at airports. Are all the 290 sites at airports? Can you explain why you think that the sampling used in this study is representative for the question of estimating the impact of increasing UHI on a global-warming measure?

2) In Appendix C of Parker (2005), you studied the correlation between the actual station wind speeds and the NCEP-NCAR reanalysis values for 26 stations. This is important, since one would ideally have used actual wind speeds at the same time as the temperature readings for all stations and measurements. These 26 stations seem to be higher-latitude stations. Would that give rise to any selection effects?

3) In Table 1 of Parker (2005), the windy trend exceeds the calm trend in 5 regions (Arctic, Europe, Asia, North America, Australasia), and the calm trend equals the windy trend in only the Tropics region. However, the global average shows that the calm trend equals the windy trend overall. According to information on 265 stations that you have provided separately to Steve McIntyre, there would seem to be 224 stations in the first collection, and 41 in the Tropics; I suppose there should be another 25 which were not included. Can you provide some insight into how this works out?

4) In Table 1 of Parker (2005), for the North American region, the trends for “All” days exceeds those for “Windy” and for “Calm”. This seems a bit odd. Can you clarify that?

5) Given that there can be no doubt that urbanization is going on, it is a surprise that, on a global level, there seems to be no visible growth in the UHI. Even if it is not comparable to the global-warming signal, one would expect to see something. Can you speculate as to why nothing seems to show up, at the global level?

6) What is the minimum global UHI trend that could be detected, using these methods?

7) Your study is based upon the understanding that the difference between the calm and windy day/night measurements reflects the UHI and near-surface temperature inversions. An alternative view has been suggested in our discussion: that the windy day/night measurements reflect the influence of air from a broader region, which has a lesser UHI. This is a picture in which we have an urban hotspot surrounded by a larger suburban region, both of which are undergoing an increase in UHI ‘€” but the suburban UHI is always weaker. (This is one reason why the airport question comes up earlier, in 1).) In this view, the trend in the urban UHI would be hidden by the equal trend in the suburban UHI. Can you comment on the plausibilitiy of this interpretation?

8) You have suggested that the calm-day ‘€” windy-day signal is a proxy for degree of urbanization. If this turns out not to be the case, would that affect your broader conclusions? And if so, how?
9) As you know, Roger A. Pielke Sr. has raised an issue with regards to your study, that it does not take into account sufficiently complications concerning the near-surface temperature inversion. (This is what I was get out of it, anyway.) Would these issues be side-stepped by focusing attention on the Tmax measurements instead of the Tmin measurements?

PaulM

Neal, We can already answer 1 – no, the 290 sites are not all airports. Certainly his stations in UK, Iceland and Ireland are mostly non-airports.
If, as you say, all the US sites are airports but most of the europe ones are not, this would give a straightforward UHI explanation for why the trend in the US is 0.25 but for europe it is only 0.17! His trends merely show the growth in airports over the last 50 years. So I would like to know what is the trend for the airports compared with the non-airport sites?

Neal J. King

#352, #353:

The reason I asked about the 290 airports was because someone said that he thought they might be nearly all airports: from #39:

“First, all (or nearly all) the U.S. sites in the Parker network are from airports. I haven’t parsed non-US locations yet, but it’s a fair surmise that nearly all the non-US Parker sites are airports as well.”

Feel free to propose better wording, in the spirit of the question.

Steve McIntyre

Neal, the question would be – what proportion are at airports (does he have a list)? Are there any site considerations applicable to airports that could have an impact on his findings? If you’re asking him to expand his views, it would be interesting to get a reconciliation of his results to Jin’s.

Neal J. King

#356: Steve McIntyre

Here is the revised wording for question 1:
“1) We have noticed that, of the 290 stations included in the analysis, the U.S. sites seem to be at airports. Can you estimate what proportion of these sites are at airports, and do you think there are any site considerations applicable to airports that would affect your results? In general, can you explain why you think that the sampling used in this study is representative for the question of estimating the impact of increasing UHI on a global-warming measure?”

I’ve only just been able to print out 2 of Jin et al.’s papers, and haven’t had any chance to read them. Since there’s been no real chance to discuss these papers, it seems premature to toss them into the mix right now. Particularly since they don’t seem to reference Parker’s study, anyway.

(By the way, if you could get the last one I mentioned in #343, that seems more likely to contain an alternative view to Parker’s.)

MarkW

last time I checked, there were a lot more than 280 cities in the world. From the comments of others, it looks like Parker’s sample is not representative.

As to lighting candles, so what.

Are you arguing that bad data is better than no data? I would disagree completely.

Steve Sadlov

RE: #348 – Prove to me that it will work for broad regions encompassing a web with nodes consisting of proper “cities” and strands consisting of diffuse exurban zones – ala Eastern US, ala Western Europe and increasingly ala SW US coast and parts of Asia.

jae

The link given in 340 IS a very interesting study. One quote:

Oke (1976) showed
that even for a small town of 1000 residents, the typical
UHI effect is in the range of 2° to 2.5°C. This has recently
been confirmed by Torok et al. (2001), who
found that the urban’€”rural temperature differences
may scale with the logarithm of a region’s population.
Such changes on thermodynamics can modify mesoscale
circulations over urban areas (e.g., Wong and
Dirks 1978; Yan and Anthes 1988; Avissar and Pielke
1989; Chen and Dudhia 2001).

steven mosher

Neal,

his approach does ot address my concern.

he varied Calm from first terce to first decile.

two issues.

The surface doesnt care about the distrubution of velocity.

Site X: highly sheltered. Wind speeds from 1m/sec to 10 msec. Uniformly distributed.
Since the site is highly sheltered the top three terce could seem calm. the top 9 decile
could be calm.

Site Y: wide open and smooth: wind speeds from 1m/sec to 10 m/sec. Uniformly distributed.
Since the site is not sheltered the bottom terce could cause mixing.

CALM/WINDY is not a function of the distribution, its a function of the surface and you
should investigate both.

Second point, related. Changing definition of Calm is not enough.

In any case, you are a fair judge. I leave it to you to decide ifyou want to ask a question about this.
Won’t whine if you don’t.

Neal J. King

#366: steven mosher

I think Parker has addressed the question of windiness to the extent that he can, without expanding the scope of his activities by an order of magnitude:

– I agree that the significance of wind speed can depend on local conditions, but it’s a big jump from compiling available measurements to traveling around the world to measure Reynold’s numbers at 290 sites. His research budget would have to go up by a couple of orders of magnitude, just to cover the airfare.

– Given this limitation, he has done what he can do: fiddled with the definition of “calm” to see what effect it would have. Apparently, it’s not major.

We can see what kind of response we get to the other questions.

Neal J. King

#365: jae

Parker has a better excuse for not citing Jin et al. than the reverse: if you look at the dates of submission for the manuscripts, Parker likely knew nothing of Jin, but Jin should have been informed about Parker (2004).

In any case, I have a chance to look at Jin, Dickinson & Zhang (2005), “The Footprint of Urban Areas on Global Climate as Characterized by MODIS.” I note the following:

– Jin et al. measure UHI using skin-temperature rather than surface-air temperature. As they state:
“Satellite-measured skin temperatures are related to the surface air temperatures but do not necessarily have the same seasonal and diurnal variations, since they are more coupled to surface energy exchange processes and less to the overlying atmospheric column. Consequently, the UHI effects from skin temperature are shown to be pronounced at both daytime and nighttime, rather than at night as previously suggested from surface air temperature measurements.”
So the results they get don’t directly relate to Parker’s index.

– Jin et al. don’t measure trends over a long period of time. So their results aren’t in a position to contradict Parker’s.

– Finally, one point they cite even provides a possible explanation of why Parker’s results don’t show any significant UHI trend: “Oke (1976) showed that even for a small town of 1000 residents, the typical UHI effect is in the range of 2° to 2.5°C. This has recently been confirmed by Torok et al. (2001), who found that the urban’€”rural temperature differences may scale with the logarithm of a region’s population.”

If the UHI only grows as the logarithm of the population, that could go a long way to explaining why Parker doesn’t see any UHI trend.

And, to keep the eye on the ball, that is all that Parker is claiming: He is not saying that there is no UHI effect, or even no UHI trend. He is just saying that the GW signal is not being caused by a UHI trend, because that trend is not big enough.

robert mcconnell

If there are any meteorologists on this thread, I’d like to hear from them. In my experience, which covers locations on both coasts of North American, several central locations and various trips to Europe and the South Pacific, wind is not an independent variable. It is part of specific weather events. In particular, wind accompanies the advance of cold fronts, as well as thunderstorms, which are also cooling events. The immediate temperature drop that accompanies these can be 10 deC or more. The cooling effect of rainfall, as in thunderstorms, will be markedly different in urban as compared to rural environments. Parker’s whole thesis fails the test of the real world.

Neal J. King

OK, I have sent the letter. Here is the final transmitted form of the questions:

///////////////////////////////////////////////
1. We have noticed that, of the 290 stations included in the analysis, the U.S. sites seem to be at airports. Can you estimate what proportion of these sites are at airports, and do you think there are any site considerations applicable to airports that would affect your results? In general, can you explain why you think that the sampling used in this study is representative for the question of estimating the impact of increasing UHI on a global-warming measure?

2. In Appendix C of Parker (2005), you studied the correlation between the actual station wind speeds and the NCEP-NCAR reanalysis values for 26 stations. This is important, since one would ideally have used actual wind speeds at the same time as the temperature readings for all stations and measurements. These 26 stations seem to be higher-latitude stations. Would that give rise to any selection effects?

3. In Table 1 of Parker (2005), the windy trend exceeds the calm trend in 5 regions (Arctic, Europe, Asia, North America, Australasia), and the calm trend equals the windy trend in only the Tropics region. However, the global average shows that the calm trend equals the windy trend overall. According to information on 265 stations that you have provided separately to Steve McIntyre, there would seem to be 224 stations in the first collection, and 41 in the Tropics; I suppose there should be another 25 which were not included. Can you provide some insight into how this works out?

4. In Table 1 of Parker (2005), for the North American region, the trends for “All” days exceeds those for “Windy” and for “Calm”. This seems a bit odd. Can you clarify that?

5. Given that there can be no doubt that urbanization is going on, it is a surprise that, on a global level, there seems to be no visible growth in the UHI. Even if it is not comparable to the global-warming signal, one would expect to see something. Can you speculate as to why nothing seems to show up, at the global level?

6. What is the minimum global UHI trend that could be detected, using these methods?

7. Your study is based upon the understanding that the difference between the calm and windy day/night measurements reflects the UHI and near-surface temperature inversions. An alternative view has been suggested in our discussion: that the windy day/night measurements reflect the influence of air from a broader region, which has a lesser UHI. This is a picture in which we have an urban hotspot surrounded by a larger suburban region, both of which are undergoing an increase in UHI ‘€” but the suburban UHI is always weaker. (This is one reason why the airport question comes up earlier, in 1).) In this view, the trend in the urban UHI would be hidden by the equal trend in the suburban UHI. Can you comment on the plausibility of this interpretation?

8. You have suggested that the calm-day ‘€” windy-day signal is a proxy for degree of urbanization. If this turns out not to be the case, would that affect your broader conclusions? And if so, how?

9. As you know, Roger A. Pielke Sr. has raised an issue with regards to your study, that it does not take into account sufficiently complications concerning the near-surface temperature inversion. (This is what I was get out of it, anyway.) Would these issues be side-stepped by focusing attention on the Tmax measurements instead of the Tmin measurements?

///////////////////////////////////////////////

Now it’s Parker’s move.

Neal J. King

Re #374

Parker has acknowledged receipt of the list of questions.

Kenneth Fritsch

Re: #373

So since the UHI Parker gets is about 2 times too small (compared to other measurements), I would expect his measured trend difference to be 2 times too small. But since he got essentially zero, 2 x zero still = zero.

I think, Neal, you have noted, in your defense of Parker’s findings, the same simplifying results that I, on the other hand, have found to be a convenience that makes me very skeptical ‘€” at least without more detailed understanding and analyses of the Parker data.

The zero temperature trend differences averaged over the globe for the 50 years, that have been purported to be those must influenced by any potential anthropogenic influences, becomes another simplifying result that can be used to claim that the “average” UHI effect over those critical years was zero. If one were searching for a finding that would in one result allow the AGW advocates to claim that little or no adjustment for UHI is required for there temperature trends this would, no doubt, be it. With a zero trend difference one no longer needs to “calibrate” the results to relate it to a quantifiable UHI temperature effect.

Parker’s result has the same appeal to those already convinced of significant and future adverse AGW in that they can consider it as hard or at least harder evidence for their views. It has much the same appeal as the Mannian HS had a few years ago. I think through similar circumstances and reasons these two findings received something less than normal critical reviews and needed or need to be looked at with a critical if not skeptical eye.

I believe a poster who appeared neutral to favorable to Parker in this discussion suggested that Parker had done a good job of data mining in discovering these results. There is a thin line between data mining and data snooping and in my view depends much on one’s a priors going into the search. Certainly working backwards from a desired conclusion would be considered data snooping and renders the statistical significance of the result, for all practical purposes, impossible to determine.

jae

379, Steve S:

In fact, UHI is a cumulative effect of numerous “hot spots” (flux sources) simultaneously radiating IR, and conducting heat to adjacent solids, gases and liquids. The flux is what it is and no amount of wind reduces the source energy.

I think this is a very important point. A hot brick continues to radiate energy to the surroundings, no matter how much wind there is. The UHI effect is real and it is that simple, IMHO.

Neal J. King

#378: Ken Fritsch

The point you are making is what led me to include the question:

“6. What is the minimum global UHI trend that could be detected, using these methods?”

We shall see what Parker says.

jae

383: How about the link in 377?

Neal J. King

Questions to Parker, Part 0:

Actually, I got answers to our compiled questions back from Parker last week, but I was overwhelmed in other things to do, so I didn’t deal with them.

For ease of reference, I will post them separately. Here goes:

Neal J. King

Question to Parker, Part 2:

Question:
In Appendix C of Parker (2005), you studied the correlation between the actual station wind speeds and the NCEP-NCAR reanalysis values for 26 stations. This is important, since one would ideally have used actual wind speeds at the same time as the temperature readings for all stations and measurements. These 26 stations seem to be higher-latitude stations. Would that give rise to any selection effects?

Response:
The choice of 26 stations was limited by availability of data. Reanalysis winds are likely to have been equally representative at other locations owing to the availability of pressure data to control the reanalysis; one exception being in mountainous terrain.

Neal J. King

Questions to Parker, Part 4:

Question:

In Table 1 of Parker (2005), for the North American region, the trends for “All” days exceeds those for “Windy” and for “Calm”. This seems a bit odd. Can you clarify that?

Response:

“Windy” is the windiest third of days, and “calm” the least windy third. “All” includes everything, including therefore the middle third. The differences are well within the error bars cited in the table. Also, trends do not always combine in a simple linear manner when combining samples, because of nonlinearity in the least-squares process.

Neal J. King

Questions to Parker, Part 6:

Question:

What is the minimum global UHI trend that could be detected, using these methods?

Response:

From the standard errors in Table 1 of my J Climate paper, the calm-night trends and windy-night trends for the globe have 95% confidence limits (⯠2 standard deviations) of 0.05 and 0.06 deg C per decade. So the difference between calm trends and windy trends for the globe can be estimated with 95% confidence within ‘ˆš(0.052+0.062) ~ 0.078 deg C per decade. If we then assume that nearly all of any urban effect will be concentrated in the calm nights, which were defined as the calmest third of nights, then overall urbanisation trends of about 0.03 deg C per decade (a bit more than a third of 0.078 deg C per decade) in minimum temperature should be readily detectable. If more conservatively we assume that not much more than half the urban warming effect is concentrated in the calm nights with the rest in the intermediate-wind-strength nights, then urbanisation trends of about 0.05 deg C per decade in minimum temperature should be readily detectable. As urbanisation is felt in minimum temperatures much more than in maximum temperatures ‘€” which may even be reduced – an urbanisation trend of 0.025 deg C per decade in mean temperature should be detectable using the more conservative assumption. This is about 10 times smaller than the rates of global warming over land since the late 1970s reported in the IPCC 4th Assessment. The more conservative assumption allows for some stations to be affected by large heat islands which persist to some extent even in windy weather (Morris et al. (J. Applied Meteorology, 40, 169-182 (2001))); but GSN stations will almost always be in smaller settlements than Melbourne, with smaller heat islands easily reduced by any wind, or with no heat island at all. None of the US stations used in my J Climate paper is in a city with a population approaching that of Melbourne (3.8 million). [Note that Morris et al’s true heat island in windy weather is about 0.2 deg C weaker than apparent in their results, because the urban station is about 20m lower than the average of the other stations].

Neal J. King

Questions for Parker, Part 8:

Question:

You have suggested that the calm-day ‘€” windy-day signal is a proxy for degree of urbanization. If this turns out not to be the case, would that affect your broader conclusions? And if so, how?

Response:

I think it will be the case and give an example in my 2006 paper. See also my response to (7). See also A. J. Arnfield, International J. Climatology, 23, 1-26 (2003).

TAC

Neal, thanks for doing all the heavy lifting on getting answers to the questions. Please extend thanks to Parker (if he doesn’t read CA).

I plan to read the responses carefully before responding, but one thing jumps out at me: I can’t help wondering what Parker means by

Trends do not always combine in a simple linear manner when combining samples, because of nonlinearity in the least-squares process.

My memory is that he fit by restricted mle, and I don’t recall any mention of least squares. In any case, least squares is linear. Am I missing something here?

Steve Sadlov

Back to square one, what a waste of time.

TAC

#397 Neal, I haven’t worked with RMLE, and in any case I’ll have to re-read what Parker did before I can say anything intelligent. In the meantime, my guess is that Parker computed the trends based on likelihood employing contrasts (calm/windy same-site data). I have seen RMLE used for computing variances in similar circumstances involving random-effects models.

Of course you can fit either linear or non-linear models by least squares. My only point was that the non-linearity arises because of the model, not the fitting procedure, and least squares is linear in the sense that differentiation of the sum of squares wrt parameters — typically employing the chain rule — yields simultaneous linear equations whose solution is the least squares fit.

However, I doubt that’s what Parker was referring to; I was hoping you could shed some light on this.

I guess I have some work to do… 😎

Thanks again!

Neal J. King

#396, #397, TAC:

OK, I did some simple algebra & calculus, and I agree that if I have a set of N values X-i(n), which I am trying to fit to the form

X-i = (m-i)n + b-i

then:

m-i = [E(n x-i(n)) – E(n)E(x-i(n)]/[E(n^2)- (E(n))^2]

b-i = [E(x-i(n))E(n^2) – E(n)E(n x-i(n)]/[E(n^2)- (E(n))^2]

where E() means the average over the range n = 1 to N

So you would expect the slope for the sequence
Z(n) = X(n) + Y(n) to be the sum of the slopes for X and Y. Hence, you would expect averaging to work as well.

However, I guess there could be problems if the separate data sets have different numbers of data points (different N). I think he has something fairly specific in mind: He doesn’t say that slopes don’t combine linearly, he says they don’t always combine linearly.

Neal J. King

#400, #401: TAC & steven mosher:

When I google “maximum likelihood”, I get tutorial articles that seem easy to understand.

When I google “restricted maximum likelihood”, I get research papers (mostly involving raising cattle). These papers seem to assume more than I know about statistical methods.

Insight on this matter will have to come from someone other than me!

steven mosher

PS neal..

I’m of the opinion that the UHI signal would reach a threshold level, after which
it won’t matter much or will be very hard to detect. I’m just dubious that it happened back in 1950 or so.

Utterly subjective, of course.

TAC

Neal and steven (#401, #402, #404), I have not found a good reference to REML on th eweb, and am awaiting arrival of Diggle [1999] — which I hope explains everything — before commenting on Parker’s (inadequately described) REML method. We may need to ask Parker for more details.

However, I would be surprised if pursuing REML leads to anything important. Parker’s Figure 4 makes it pretty clear that the difference between average temperatures on windy days and average temperatures on calm days is nearly constant over time, at least for his dataset. REML would have to be pretty weird in order to obscure a trend in the difference.

There is still the question of whether the Parker dataset is appropriate for detecting UHI. However, the point that Neal and others have made is that it may not matter with respect to the question at hand: If the Parker dataset is representative of the data used to compute the global temperature trends (not sure about this), and if we believe the UHI effect should be reduced or eliminated on windy days (not sure about this, either), then we can address the question of whether UHI effects have contaminated the global temperature trend signal without addressing the question of whether or not the UHI effect exists (a clever design, IMHO).

What concerns me most about Parker’s results? At this point it is Anthony Watt’s discoveries related to the network of temperature monitoring sites. Uncertainty in data complicates, to say the least, interpretation of subsequent results.

Neal J. King

#407, UC:

Well, I still didn’t get much out of that link.

Something that occurs to me, however: in #402, I assumed that all samples have the same number of data points. In my presentation, they do, because I use interpolation to fill in “windy-night” curves for days that are not windy, and the “calm-night” curves for days that are windy. I did this so we would have a well-defined set of trends to talk about.

In practice, I bet that Parker didn’t do that: He probably took trends directly from the available data points. But since different sites would have different windy and calm nights, that very likely would throw off the linearity of slopes. I’ll think about it some more.

MarkW

another thing Parker didn’t do was define why temperatures that should be dependant on UHI, actually were dependant on it and why temperatures that were not dependant on it, actually weren’t.

John F. Pittman

#411

What he didn’t find was any evidence that the temperatures that should be independent of UHI had different trends than the temperatures that should be influenced by it.

Ok, I’ll bite. If he did not find differnt trends, when UHI, by definition, is a measurable difference, then the direct implication is that he did not find UHI when he should. Or he has essentially invalidated those data as being relevant to any discussion of global warming and UHI, or at a minimum, our ability to measure is suspect.

Peter Hartley

Putting what David Smith says in #413 in a slightly different way, Parker’s method is very susceptible to an error based on his method of classifying days by wind speed. As a thought experiment, suppose he used a table of random numbers to classify days into windy and calm ones. What you would expect to find if he has a large number of days is that the trends would not be statistically different in the two groups of days. The two measures of trend slope would converge to the same number as the number of observations increased. To rule out the interpretation that he has misclassified days by windiness, he needs to show his classification is accurate as a measure of wind speed at each station on each night in the sample. I do not think he has done this to anyone’s satisfaction. I think the question of whether the daily minimum was the best measure to use for his purpose is also a very good one. Can one show that you get the same result using temperatures at 3am? Has there been any follow up analysis to check the robustness of his result in this dimension?

Steve Sadlov

Another related flaw of Parker is the seeming notion of mixing out. As if UHI was limited to some thin layer near the surface, and not, as is actually the case, constituting a much larger dome, impacting distances of hundreds of feet in the cases of hamlets, thousands of feet in the case of small towns and miles in the case of cities. So, any “mixing” due to wind is only mixing within the UHI dome! DOH!

Steve Sadlov

RE: #419 – Those winds may actually be bringing in heat from the UHI of the Bay Area!

Steve Sadlov

RE: #421 – I would imagine that most of the areas of the NH that are more populated than the Gobi or some parts of the Actic, essentially have a continuous series of interlinked UHI affected volumes over them. Is sort of a general adder term, at all locations, which varies depending on population density and the degree of surface / land use mods as well as with wind / time / seasonal and day to day variations in anthropogenic flux. Of course Parker detected only 0.06 degrees delta because he was not measuring UHI versus no UHI – he was measuring variations in UHI over time.

Steve Sadlov

RE: #423 – The only case I know of where these mild sorts of winds would have any sort of cooling effect at all would be where they are coming off of a cold ocean – and that impact would only affect the first couple of miles inland. Winds of this sorts certainly are not going to cause turbulance. At the risk of jumping to conclusions, Parker probably had an axe to grind (an AGW hype axe) when he did his study. If so another scientist working toward a goal outside the realm of science. Sadly, one of many.

Sam Urbinto

So why is variation in UHI important? The effect of UHI on the anomalies and the global temperature variation would seem important. For example, I would think the effects of say the entire urban area that Chicago and outlying urban areas have upon climate would be huge and far reaching, much greater than just the area it covers. It would seem, just on the face of it, that all the warming we see that’s actually there is due to:

1. UHI
2. Number of people
3. Amount of land with vegetation that allows the sun’s energy to reach the ground (or in other words, not a jungle or forest, but mowed grass, farmland, etc)
4. Loss of forest and jungle

Sam Urbinto

Yeah, but this wouldn’t be the first time I’ve called into question the fact that nobody seems to be able to provide either a margin of error or any proof of what’s being measured is in fact ‘exactly’ what it’s being reported as. I doubt the thermometers, even if properly sited, are accurate to better than .1 and maybe not even that. Show me the data and the adjustments is what I say.

But to think that a 20 square mile concrete area isn’t hotter than a 20 square mile forest or high grasses or patch of ocean, or even somebody’s front porch on a couple of acres, is delusional, and thinking that the effects of that concrete (or asphault or mixture) 20 square miles in size doesn’t extend a ways out and up is insane.

Wind. What is it a hurricane? Bah.

MarkW

Another point. Is Parker using the average windiness for the day, or the peak windiness. I’ve lived in cities where afternoon showers were common, and for those near the shower, it got quite windy, but only for a few minutes. The rest of the day was dead calm.

SteveSadlov

I challenge the very notion that wind can really blow away UHI. I might accept it reducing it in the case of very small developments. But for anything bigger than a small city, I don’t buy the notion that UHI can be “blown away” at all. I think Parker either innocently believes UHI to be a rather small scale development, vertically, or, cunningly has decided to portray it that way. I challenge the notion that UHI is limited to the boundary layer. I believe it can extend much higher. I also challenge the notion of distinct “islands,” against a “natural” background. I believe the effect to be far more diffuse and distributed. Especially in places like Europe and the Eastern half of North America.

SteveSadlov

RE: #433 – It would need to create vertical mixing of such an extreme magnitude, that the tubulent flow actually exceeded the extent of the “dome” of UHI. Otherwise, all you’d be doing is slightly tweaking the thermal gradient function within the overall “dome.” I will also grant that a substantial (e.g. over 15 or 20 MPH) wind, may result in elongation and shape distortion of the “dome” into more of a tear drop. But, as I’ve repeatedly noted, the flux, at / near ground, is what it is. Heat flow is what it is. Both heat flow from anthropogenic sources as well as reradiation.

SteveSadlov

Final comment, then I must depart, the equivalent wind in terms of scale, to the airflow in say, a typical contemporary high density server, would be something like 300 MPH straight line winds.

steven mosher

RE 430.

He is not using average windiness. CRUDELY, he looks at wind speed at the grid level.

Then, he BINS the wind speed into two buckets. Top third. Bottom third.

Top third is “windy”. bottom third is Calm

This is nonsense. the first site I looked at, Fresno, had wind speeds that were distributed
in a Poission fashion. High wind speed (8mph) was a rare event. Binning the TOP THIRD of the wind speed
required that one define Windy as something around 3MPH. You dont feel wind chill at that windspeed, much
less blow the UHI away.

I will give my diabolical conclusion. PARKER PROVED THIS: the wind rarely blows hard enough to get rid of UHI.

SteveSadlov

RE: #439 – Data snooping and overfitting are explicit goals of those who do these things.

James Erlandson

Existing Climate Data Sources and Their Use in Heat Island Research

Balling and Brazel (1987b) analyzed long-term temperature records from the cooperative network in Phoenix. Twelve stations were selected, all of which experienced location changes of less than a kilometer and elevation changes of less than 30 m over their period of operation … Averages of daily temperature maxima and minima for the summer months of June, July, and August were examined for trends over the period 1949-1985.

The slope of Summertime Average of Daily Maxima varied from 0.029 to 0.073 degrees K/year. The slope of Summertime Average of Daily Minima varied from -0.036 to 0.114 degrees K/year.

aurbo

As stated well back on this thread, it appears to me that Parker establishes a straw man by somehow averring that lack of significant differences in temperatures between windy and calm summer nights in urban areas shows that UHI effects are minimal.

The whole idea of UHI as a weather phenomenon has to do with the difference in temperature between urban areas and rural areas irrespective of urban winds. 50 years of experience in forecasting and observing temperatures at various locations with both urban and rural targets clearly shows that there is a marked difference in temperatures between the two. The maximum differences occur not in summer, but in winter time (longer nights) under clear skies and calm winds when such a combination of events are observed at the rural stations. Urban differences under similar conditions are much less whether or not there is wind and even more so when skies are overcast. So the critical temperature, the one displaying the largest urban/rural difference is Tmin in winter. (Add a snow-cover and you can have readings over 20° F different between the rural and urban site even when both points are in the same airmass).

The fundamental question is whether these cooler rural readings change appreciably as the site becomes urbanized and to what extent this occurs. Most of the Parker thesis is simply bafflegab.

To determine these differences it is important to survey areas where the weather stations, the urban one in particular, are not located near a geophysical boundary where surface temperatures in one direction are significantly different from those in other directions. This is especially relevant in coastal cities where ocean temperatures can be vastly different from those over the adjacent land areas. [An earlier post, #19, noted that Boston vs rural temperatures differed depending on whether there was an east (onshore) wind or a west (offshore) wind. This is simply a result of Boston’s famous sea breeze effect which any Redsox fan can attest to, and not really relevant to the Parker theses]. Useful sites to examine would be in interior areas where large bodies of water or adjacent geophysical discontinuities are not in play.

nevket240

May I put my 2 bobs worth in and ask if anyone has considered the construction of the modern city in relation to a city built 100 years ago??
The modern home is usually solid brick with a tile roof, or iron. The modern freeway is a concrete & bitumen monster, (anyone laid down on a bitumen road in summer fixing their jalopy?)
100 years ago most homes built here in OZ were timber with a shingle or iron roof. Not much heat retained there. The roads were gravel or dirt. Over the 100 years we have evolved into using more bricks, more concrete roof tiles, more bitumen and more concrete footpaths, freeway dividers etc.
is your area the same??? cheers.

John F. Pittman

#447 FYI. Iron roofs are required for many historical homes.

David Brewer

The general method in IPCC-promoted studies of temperature phenomena is:

1. Posit a given measurement as a definitive test of a non-AGW temperature phenomenon.
2. Devise a method poor enough to fail to correlate the measurement with the phenomenon.
3. Fail to find a correlation, “proving” that the non-AGW phenomenon is not present.
4. Deduce that any trend in the measurement must be due to AGW.

Parker is a good example. Point 1 is that windy nights test whether there is UHI. Point 2 drags in a variety of gross approximations and disregards confounding factors. Instead of looking at really windy nights, take wind speed in terciles so that even the top tercile has many nights with insufficient wind to affect UHI. Insert noise by using reanalysis of daily winds instead of actual wind measurements around the time temperature minima are reached. Ignore wind direction. Make a hash of the classification of stations, etc. With enough of this type of bungling, the correlation virtually disappears, and point 4 is a cakewalk.

Parker is good at this, but he is not the supreme exponent of the technique. The real geniuses are at the National Climate Data Center – Easterling, Petersen and co. Their 1997 paper in Science (Jones and Parker were among the co-authors) will probably go down in history as the worst approach ever to finding the UHI – or the best approach to not finding it. Again, an indirect measure is used – this time it was changes in daily temperature range (DTR) between urban and rural stations. Since UHI definitely reduces DTR, by warming nights more than days, you need a really bad method to fail to correlate the two.

But they managed it. Main steps as follows. First, as in Parker, avoid looking at extreme cases that would give the game away – instead, divide the stations into just two groups, which is even better than terciles for blurring the picture. Second, as UHI increases steeply up to about 30,000 population, set the bar at 50,000, leaving a pile of stations in your rural group that already have substantial UHI. Help this muddle along by using population data 30 years out of date, shifting even more urban warming into the non-urban group. Next, use a one-off measurement of population, not the change over time, as your UHI proxy. This gives you a nice apples and pears comparison – changes in DTR versus absolute UHI at a certain point in time. Lastly, just in case there might be some correlation left, botch the arithmetic so you scatter random errors through the whole calculation. Hey presto: UHI does not reduce DTR. DTR can now be cited on the first page of next IPCC Working Group 1 Report as if it were evidence of AGW! (last bullet point on numbered page 2 here: http://www.ipcc.ch/pub/spm22-01.pdf; further details from Warwick Hughes at http://www.warwickhughes.com/climate/easterling.htm).

Most other AGW-promoting studies use some variant of the general method above. The hockey stick was a bit more complicated, but not much. It set up tree rings as a measure of annual temperature. That was even more dubious than wind and temperature, what with the confounding effects of rainfall, tree disease or damage, insolation, seasonality, non-linear responses etc. So it was easy to find all noise and no trend for 1000 years. The tricky bit was to discover “innovative” statistical methods to give an uptick in the 20th century. But as they knew what they were looking for, this was not impossible – just invalid. Once they had a thousand years of noise and a spurious recent uptick, it was easy to jump to step 4, and be NOT able to think of any other explanation for the “exceptional” recent temperature rise than our old friend AGW.

Even the “fingerprint” studies of the cause of global temperature change since 1850 follow a rather similar pattern: leave out half the natural variables, make unproven assumptions about aerosols etc. and you can soon fail to find any other explanation for warming that our old pal of molecular weight 44.

In all cases, the key steps are to “invalidate” some non-AGW factor using an incompetent technique, and then finger AGW as the sole reasonable explanation of the data. It boils down to “botch and switch”.

BTW, it’s not that Parker and his mates are being dishonest. They are just people who know the right answer before they start their investigation, and who lack the rigour and technical expertise to see that their methods are scientifically invalid. Remember too that they are respected figures in bureaucracies in which received wisdom passes for truth, and where the incentive structure places less weight on scientific discovery and accuracy than on getting things published, defending the party line, and swinging next year’s budget increase. If any of us were in Parker’s shoes, we’d behave the same way – or we’d be out.

jcspe

David Brewer says:

November 4th, 2007 at 1:42 pm
The general method in IPCC-promoted studies of temperature phenomena is:

1. Posit a given measurement as a definitive test of a non-AGW temperature phenomenon.
2. Devise a method poor enough to fail to correlate the measurement with the phenomenon.
3. Fail to find a correlation, “proving” that the non-AGW phenomenon is not present.
4. Deduce that any trend in the measurement must be due to AGW.

I have never seen it explained any better. Thanks for the road map. It will definitely help me.

Larry

1. Posit a given measurement as a definitive test of a non-AGW temperature phenomenon.
2. Devise a method poor enough to fail to correlate the measurement with the phenomenon.
3. Fail to find a correlation, “proving” that the non-AGW phenomenon is not present.
4. Deduce that any trend in the measurement must be due to AGW.

I don’t think it’s that passive, at least in the case of the HS and the MWP. Mann invented the cherry-picking automaton.

Chris Harrison

Larry,

Google “Corrugated Iron” and you will see that this is a common usage for corrugated galvanised mild steel. I don’t think the term iron includes steel in modern usage so “corrugated iron” is probably an historical hang over.

Dave Dardinger

re: #456

“corrugated iron” is probably an historical hang over.

Usually I think of corrugated iron or steel (or aluminum), as being the sine wavey sort of medal. But the old roofs of houses had sections a couple or three feet wide with a crimp like ^ in the center and rounded or v crimps on the sides so that the pieces could be interlocked and (assuming they were installed correctly), would allow rain and melting snow to run off.

Geoff Sherrington

Re # 459 barryw

Can I equate your sentence

Joining a cause greater than oneself gives you a sense of both belonging and worth.

with “greed for fame”? If the greater cause gains dominance you achieve your fame, especially if you were an early adopter.

nevket240

#447
Larry.
we call it corrugated iron, some refer to it as a TIN roof. Very thin, 2-4 mm (??) thick. It used to be painted a reflective silver or galvanised, now it is coated in various colours to suit the area and taste.
I’m just thinking along the line that all are concerned with the expansion of urban areas and foilage etc. But what about the physical attributes of those expanding constructions?? Inner commercial areas are all conctrete and glass. Residential areas are what have changed the most in 100 years in terms of materials & appearance as well as size. Thers another bogeyman to consider. The small 3 room house of the 1940’s to the McMansions of today. (subprimed, of course)
regards.

steven mosher

WIND in the city. Some real time data:

From this study:

http://pages.unibas.ch/geo/mcr/Projects/BUBBLE/textpages/md_tracer.en.htm

Nasif Nahle

# 465,

Steven Mosher,

I’m not Parker, but obviously Village is colder than Cities. BTW, it seems spaghetti graphs have become fairly popular.

bender

If there is a UHI effect in the spatial domain (and no one disputes this), then it had to grow over time. Any failure to detect the time trend must indicate a faulty method, as space and time are inseparable. Seems you’ve pin-pointed the fault. (Note how Parker seems to have fooled himself, thrice, into believing his own rhetoric! Once when writing the proposal, once when writing/revising the paper, and once when replying to a CA auditor.) Now the question is: what is the true magnitude of the trend?

steven mosher

Click to access diss.pdf

Wind in the street. city. region.

Nice work.

steven mosher

NET RADIATION. for a small city and a village 4 clicks away

Weird. As I have pointed out before, the research on UHI may end up skewering Parker.

Larry

Never mind. I understand what you’re saying now.

bender

mosher,
You are aok. I saw the problem in Parker’s reasoning but was far too timid to say anything. Afraid to stir the pot too much. You not only got guts, you audited down the problem to a very specific thing. That’s tenacity. Cheers to you.

bender

Where is the missing UHI?

Buried in what is incorrectly presumed to be pure AGW.

SteveSadlov

Obviously, land surface mods also have an impact. These include changing the substrate, changing vegetation, covering the substrate, creating artificial bodies of water and building structures.

SteveSadlov

I’m also going through that paper.

kim

In the link to Climate Science at 484, Joe d’Aleo has a compelling graph of station dropout and global temps with discontinuities in 1990 of both.
=============================

Dave Dardinger

Bump

For Norbert or others who want a jump into what’s been talked about here concerning Parker and his claim that Urban warming doesn’t exist.

STBro

Just a revisit on this one. See

http://hesomagazine.com/environment/urban-heat-islands-the-other-type-of-island-in-the-japanese-archipelago/

and

Urban Heat Islands depend on several factors:

when combined, these factors are sometimes referred to as “urban morphology” … “urban morphology (the hottest zones in the city are those with the tallest and the highest density of buildings, without green spaces and with intense generation of heat from traffic, commerce and services);”

geometry: affects radiative, convective evaporative, and conductive heat transfer; urban geometries tend to selectively block or intensify winds, tend to impact the extent of greenspace, increase exposed surface area, change the sky view factor, add overall heat capacity when compared to rural areas; example – “The canyon structure that tall buildings create enhances the warming. During the day, solar energy is trapped by multiple reflections off the buildings while the infrared heat losses are reduced by absorption.”

artificial heat generation: transportation, industry, commerce, utilities, residential, waste (decomposition)

local weather: winds can affect as can cloud cover; large urban centers create their own upwelling and local microclimate …

“anti-rural factors” – lack of evaporative cooling from soil and plants, lack of plant cooling, increased thermal conductivity and capacity from artificial structures, faster water runoff and sequestration in cities

The primary problem between IPCC and actual science is population-based:

“Peterson and others support the IPCC viewpoint at towns with less than 10,000 populations are towns without the need for adjustment for urbanization. Oke (1973 and Torok et al (2001) show that even towns with populations of 1000 people have urban heating of about 2.2 C compared to the nearby rural countryside. Since the UHI increases as the logarithm of the population …”

“Doug Hoyt has noted, in 1900, world population is 1 billion and in 2000, it is 6 billion for an increase of a factor of six. If the surface measuring stations are randomly distributed and respond to this population increase … we note that UHIs occur only on land or 29% of the Earth’s surface … the net global warming would be 0.29*1.7 or 0.49 C which is close the observed warming. It is not out of the realm of possibility that most of the twentieth century warming was urban heat islands.”

Click to access URBAN%20HEAT%20ISLAND.pdf