In a recent CNN interview discussed at RC here, Joe D’Aleo said:
Those global data sets are contaminated by the fact that two-thirds of the globe’s stations dropped out in 1990. Most of them rural and they performed no urban adjustment. And, Lou, you know, and the people in your studio know that if they live in the suburbs of New York City, it’s a lot colder in rural areas than in the city. Now we have more urban effect in those numbers reflecting — that show up in that enhanced or exaggerated warming in the global data set.
Gavin Schmidt excoriated this claim as follows:
D’Aleo is misdirecting through his teeth here. … he also knows that urban heat island effects are corrected for in the surface records, and he also knows that this doesn’t effect ocean temperatures, and that the station dropping out doesn’t affect the trends at all (you can do the same analysis with only stations that remained and it makes no difference). Pure disinformation.
Later in the comments (#167), an RC reader inquired about UHI adjustments, noting the lack of discusison of this point as follows:
#167/ In all of the above posts there is no mention of the urban heat island effect, nor of the effect of rural station drop out nor of the effect the GISS data manipulation has on surface temperature. Why is that?
To which Gavin replied:
[Response: Because each of these ‘issues’ are non-issues, simply brought up to make people like you think there is something wrong. The UHI effect is real enough, but it is corrected for – and in any case cannot effect ocean temperatures, retreating glaciers or phenological changes (all of which confirm significant warming). The station drop out ‘effect’ is just fake, and if you don’t like GISS, then use another analysis – it doesn’t matter. – gavin]
Neither CRU nor NOAA have archived any source code for their calculations, so it is impossible to know for sure exactly what they do. However, I am unaware of any published documents by either of these agencies that indicate that they “correct” their temperature index for UHI effect (as Gavin claims here) and so I’m puzzled as to how Gavin expects D’Aleo to be able to “know” that they carry out such corrections. And as to GISS adjustments, as we’ve discussed here in the past (and I’ll review briefly), outside the US, they have the odd situation where “negative UHI adjustments” are as common as “positive UHI adjustments”, raising serious questions about whether the method accomplishes anything at all, as opposed to simply being a Marvelous Toy.
CRU Urban Adjustments?
The most recent exposition of CRU methodology is Brohan et al 2006, which stated in respect to UHI that they included an allowance of 0.1 deg C/century in the uncertainty, but does not describe any “correction” to the reported average temperature:
The previous analysis of urbanisation effects in the HadCRUT dataset [Folland et al., 2001] recommended a 1 sigma uncertainty which increased from 0 in 1900 to 0.05 deg C in 1990 (linearly extrapolated after 1990) [Jones et al., 1990]. … To make an urbanisation assessment for all the stations used in the HadCRUT dataset would require suitable meta-data for each station for the whole period since 1850. No such complete meta-data are available, so in this analysis the same value for urbanisation uncertainty is used as in the previous analysis [Folland et al., GRL 2001]; that is, a 1 sigma value of 0.0055 deg C/decade, starting in 1900… The same value is used over the whole land surface, and it is one-sided: recent temperatures may be too high due to urbanisation, but they will not be too low.
For greater certainty that CRU makes no “correction” for UHI in the actual temperature (only an allowance in the “uncertainty”), Folland et al (GRL 2001) stated:
We add independent uncertainties due to urbanisation, changing land-based observing practices and SST bias corrections. … The uncertainties given by RSOA due to data gaps and random errors (Figure 1a) were augmented using published estimates of global uncertainties associated with urbanization effects (e.g. Jones et al., 1990),…We assume that the global average LAT uncertainty increased from zero in 1900 to 0.1°C in 1990 (Jones et al, 1990), a value we extrapolate to 0.12°C in 2000 (Figure 1a).
Both sources clearly stated that they allow for UHI only by a slight increase in their uncertainty factor. Note that even this estimate relies on Jones et al 1990, a study which has been discussed at CA preciously. After Jones refused for years to identify the stations used in the 1990 study, FOI actions obtained this information. We discussed Jones et al 1990 in a number of posts. We observed here that Jones et al 1990 made untrue claims on the quality control for their Chinese network (the falseness of which would rise to misconduct in many fields). Jones et al 1990 described their QC procedures for Chinese stations as follows:
The stations were selected on the basis of station history; we selected those with few, if any changes in instrumentation, location or observation times.
I observed at the time that I had been able to track down third-party documentation on stations used in Jones’ China network and that it was “impossible that Jones et al could have carried out the claimed QC procedures.” Doug Keenan followed up on this with a complaint against Wang. As I recall, part of Wang’s defence was that the station histories consulted in 1990 had now been “lost”. So station histories – documents that had survived World War II, the Communist Revolution, the Great Leap Forward, carefully preserved by diligent clerks – were lost or destroyed by climate scientists under the IPCC regime. Hard to believe.
Be that as it may, Brohan et al 2006 does not say that they make any “correction” to their records for UHI, only that they make a slight increase in “uncertainty” – a completely different thing even in Gavin-World.
NOAA UHI Adjustments
The homepage for the NOAA temperature index is here. It cites Smith and Reynolds (2005) as authority. Smith and Reynolds, in turn, state that they use the identical procedure as CRU, i.e. they make an allowance in uncertainty, but do not correct the temperature index itself.
For LST [land surface temperatures] , bias errors may be caused by urbanization over the twentieth century, and uncertainty due to the use of nonstandard thermometer shelters before 1950 (Jones et al. 1990; Parker 1994; Folland et al. 2001). Here we use the LST bias uncertainty estimates of Folland et al. (2001).
GISS U.S. Adjustments
Unlike CRU and NOAA, GISS makes a decent effort to adjust for UHI in the U.S. (outside the USA, its efforts are risible.) A few days ago, I showed the notable difference between the GISS (UHI-adjusted) version in the US and the NOAA unadjusted version, where the difference is much more than 0.1 deg C/century asserted by CRU/NOAA.
surfacestations.org has made a concerted effort to identify high-quality stations within the USHCN network (CRN1-2 stations) and preliminary indications are that the GISS U.S. estimate will not differ greatly from results from the “best” stations (though there will probably be a little bias.)
This does not prove that CRU and NOAA estimates are any good. Quite the contrary. It shows that the CRU and NOAA failures to make UHI adjustments along the lines of GISS are introducing a substantial bias in these records.
GISS ROW Adjustments
Last year, I reviewed GISS adjustments outside the US in a series of posts. These adjustments are pig’s breakfast. In many cases, GISS makes UHI adjustments the “wrong” way” i.e. their adjustments presume a UHI cooling effect. These goofy results are mentioned passim by Hansen as “false local adjustments”. At the end of the day, there is no evidence that Hansen’s “UHI” adjustments outside the U.S. even begin to deal with the problem. Posts were here here here here here here.
The difference between the US and ROW arises because the US has a fairly unique backbone of long relatively rural stations (the USHCN network), where, despite all the barbecues and air conditioners and parking lots, an attempt has been made at having weather stations located at non-airport non-urban locations. GISS uses nightlights information to subset this data and to choose a subset as a trend reference. There’s lots to dislike in the execution, but the intent makes sense.
Outside the US, there is no corresponding network. A lot of the stations are in cities and virtually all of the recent data (post-1990) is from airports. GISS uses hopelessly obsolete population meta-data to supposedly identify “rural” stations, but GISS “rural” is all too often small city (or even large city). Unlike the US, GISS methods don’t find sure ground and thus their adjustments end up being essentially random, mostly reflecting random site relocations and having nothing to do with UHI adjustment. They may say that they adjust for UHI, but this cannot be demonstrated in their actual adjustment, which throws up nonsensical wrong-way adjustments. Even Hansen acknowledges the wrong-way adjustments as being a problem:
it is difficult to have confidence in the use of urban records for estimating climate change…some urban stations show little or no warming, even a slight cooling relative to rural neighbors. Such results can be a real systematic effect e.g. cooling by planted vegetation or the movement of a thermometer away from the urban center or a random effect of unforced regional variability and measurement errors. Another consideration is that even rural locations may contain some anthropogenic warming.
And CRU and NOAA don’t even bother.
“urban heat island effects are corrected for in the surface records”
Contrary to Gavin’s assertion, there is no evidence that CRU or NOAA correct their records for urban heat island effects. They make a very slight allowance in their “uncertainty” for UHI relying ultimately on an estimate made in Jones et al 1990, a study which made untrue (and impossible) claims about quality control steps.
The only network where a plausible adjustment is made is the GISS US network (representing less than 2% of the world’s surface, as NASA GISS reminds us.) While GISS US results are plausible, outside the US, the GISS adjustment is a pig’s breakfast and no sane person can claim that they live up to the warranty. What makes this frustrating is that the US temperature history (GISS version) had 1934 as a record year – a result that was at variance with the other indices and other parts of the world. Is this because this is the only network/country combination with an effective UHI adjustment or because of a unique “regional” climate history in the US?
Whether or not urban heat islands have a material impact on the surface records is a different question. The difference between GISS US results and NOAA US results is strong evidence that there is a noticeable impact – one which needs to be addressed by CRU and NOAA and by GISS outside the US. In my opinion, Gavin’s own statement that “urban heat island effects are corrected for in the surface records” is, to borrow a phrase from realclimate, “disinformation”.
For the record, I think that Gavin was entitled to complain about the lack of balance or representativeness in the Lou Dobbs panel: whether D’Aleo, Lehr and Wissner-Gross are right or wrong about their points, they are completely unrepresentative of the mainstream climate community, which is surely entitled to complain on that count. My not discussing their solar views here doesn’t mean that I endorse them – Gavin Schmidt and his colleagues spend time deconstructing such analyses; solar proponents should pay attention to criticism regardless of the quarter from which it originates; given that others do such analyses, I think that my time is better spent on issues not covered elsewhere. The fact that there is a legitimate complaint against the construction of the Lou Dobbs panel doesn’t mean that Schmidt should make untrue claims about what CRU and NOAA do in their construction of surface records.
Joe D’Aleo responds to realclimate here, referring, inter alia, to some CA analyses.
Smith, T. M., and R. W. Reynolds (2005), A global merged land air and sea surface temperature reconstruction based on historical observations (1880-1997), J. Climate, 18, 2021-2036.
Folland, C. K., N. A. Rayner, S. J. Brown, T. M. Smith, S. S P. Shen, D. E. Parker, I. Macadam, P. D. Jones, R. N. Jones, N. Nichols and D. M. H. Sexton (2001), Global temperature change and its uncertainties since 1861, G.R.L, 28, 13, 2621–24, (2001GL012877).
Brohan et al 2006,…