Menne et al (J Clim 2009) reported that there were 62 station deletions and 59 station additions from the most recent roster (which itself had been modified from the original USHCN in the mid-1980s. Menne et al:
Since the 1996 release (Easterling et al. 1996), numerous station closures and relocations again necessitated a revision of the network. As a result, HCN version 2 contains 1218 stations, 208 of which are composites; relative to the 1996 release, there have been 62 station deletions and 59 additions.
I’ve provided a list of deleted and added stations below. I looked up one of the stations (the last one on the list, WY Pathfinder Dam, surfacestations.org. It was surveyed in June 2008, at which time it still existed. It doesn’t look bad as compared to the Tucson parking lot (which is still used.)
What is the basis for deleting one station and adding another? Dunno. They say that it’s due to “numerous station closures and relocations”, but there seem to be examples where this is untrue.
Figure 1. Pathfinder Dam WY.
Here’s a list of the 61 deleted sites (by state):
[1] “AZ DOUGLAS” “AZ MESA” “AR OZARK” “CO DURANGO”
[5] “GA BLAKELY” “ID CALDWELL” “ID CHALLIS” “ID COEUR D’ALENE AP”
[9] “IL GRIGGSVILLE” “KS ESKRIDGE 1SE” “KS PHILLIPSBURG 1SSE” “KY MIDDLESBORO”
[13] “KY OWENSBORO 3W” “ME ORONO” “ME RIPOGENUS DAM” “MD BALTIMORE WSO CITY”
[17] “MD COLLEGE PARK” “MD PATUXENT RIVER” “MA CHESTNUT HILL” “MA CLINTON”
[21] “MA FRAMINGHAM” “MN HALLOCK” “MN POKEGAMA DAM” “MN WINNIBIGOSHISH DAM”
[25] “MT CROW AGENCY” “MT HAUGAN (DEBORGIA) 3E” “MT POPLAR” “NE HALSEY 2W”
[29] “NH BETHLEHEM” “NJ TUCKERTON” “NY BAINBRIDGE 2E” “NY BATH”
[33] “NY CHASM FALLS” “NY PENN YAN 8W” “NY PLATTSBURGH AFB” “NY SCARSDALE”
[37] “NY UTICA” “NC BANNER ELK” “ND MAYVILLE” “OH NAPOLEON”
[41] “OK HUGO” “OR BLY 3NW” “PA FREELAND” “PA HARRISBURG CAPITAL CITY”
[45] “UT BEAVER” “UT ELBERTA” “UT HIAWATHA” “UT LOA”
[49] “UT RIVERDALE” “VT NORTHFIELD 3SSE” “WA COLFAX 1NW” “WA COLVILLE 5NE”
[53] “WA GOLDENDALE” “WA GRAPEVIEW 3SW” “WA PUYALLUP EXPERIMENT STN 2W” “WV GARY”
[57] “WV PICKENS 4SSE” “WV WILLIAMSON” “WI HATFIELD HYDRO PLANT” “WY BORDER 3N”
[61] “WY BUFFALO BILL DAM” “WY PATHFINDER DAM”
Here are the 58 added sites:
[1] “AZ CHANDLER HEIGHTS” “AZ PEARCE SUNSITES” “AR OZARK 2” “GA CAMILLA 3SE”
[5] “ID BERN” “ID COEUR D’ALENE” “ID MAY 2 SSE” “ID NAMPA SUGAR FACTORY”
[9] “IL PERRY 6 NW” “KS COUNCIL GROVE LAKE” “KS SMITH CENTER” “KY BARBOURVILLE”
[13] “KY HENDERSON 7 SSW” “ME BRASSUA DAM” “ME CORINNA” “MD BELTSVILLE”
[17] “MD BALTIMORE DOWNTOWN” “MA READING” “MA WALPOLE 2” “MA WEST MEDWAY”
[21] “MN RGYLE 4 E” “MN GRAND RAPIDS FORESTRY LAB” “MN MARCELL 5 NE” “MT HYSHAM 25 SSE”
[25] “MT SAINT REGIS 1 NE” “MT VIDA” “NE STAPLETON” “NH BETHLEHEM 2”
[29] “NJ TOMS RIVER” “NM ULCE” “NY ADDISON” “NY DEPOSIT”
[33] “NY DOBBS FERRY ARDSLEY” “NY MALONE” “NY UTICA ONEIDA COUNTY AIRPORT” “NC TRANSOU”
[37] “ND CASSELTON AGRONOMY FARM” “OH DEFIANCE” “PA LEBANON 2 W” “PA PLEASANT MOUNT 1 W”
[41] “TX PARIS” “UT FARMINGTON 3 NW” “UT MARYSVALE” “UT NEPHI”
[45] “UT SALINA 24 E” “UT SCOFIELD-SKYLAND MINE” “VT OUTH HERO” “VT SOUTH LINCOLN”
[49] “WA COLVILLE” “WA CUSHMAN POWERHOUSE 2” “WA GOLDENDALE” “WA McMILLIN RESERVIOR”
[53] “WA SAINT JOHN” “WV PICKENS 2 N” “WV PINEVILLE” “WV WILLIAMSON”
[57] “WI NEILLSVILLE 3SW” “WY BATES CREEK NO 2” “WY CODY”
Reference:
Menne et al, 2009. The United States Historical Climatology Network Monthly Temperature Data – Version 2. J Climate. http://ams.allenpress.com/perlserv/?request=get-abstract&doi=10.1175%2F2008BAMS2613.1
Climate Audit 
20 Comments
If it was me I would start with Anthony Watts’ Surface stations analysis and drop the stations with lowest quality ranking. Not sure what rational empirical criteria they used but it will be interesting to see how the changes affect the temperature trends. Call me cynical but I predict the changes will produce an increase.
Somebody might want to comment on the attached link….if only to put the record right….so to speak.
http://krugman.blogs.nytimes.com/2009/06/27/temperature-trends/
Re: dunbrokin (#2), I don’t think anyone is denying there’s been warming, and he’s correct about the choosing of the end points giving you the graph you want. The issue here surely is that if the US and RoW are going to spend $trillions combating GW then it is best for all concerned that the data on which this action is based is the best data available. If a station was put in place fifty years ago and is now in a parking lot in downtown Ordinarysville, it is likely to be giving higher temperature readings than it was fifty years ago even if the temperature has stayed constant. I guess it’s how GISS are treating this data that’s the point at issue.
Re: dunbrokin (#2),
Look, there’s lots of evidence that temperatures have increased since the 19th century. The Krugman graphic is the GISS global, rather than GISS US which has a somewhat different appearance.
Re: Steve McIntyre (#10),
I think there’s potential that the majority of the warming is due to bad sensor networks. I read a post here from some time ago which showed the sparseness of the data back in the 1900’s – an eye opener to say the least. Combine that with the terrible siting issues, inconsistencies of measurement times and UHI, I’m not sure we can conclude the amount warming to 1C accuracy from this information. If we take the best sites in the world from the last 50 years uncorrected, that might be our best bet to know what happened.
Re: jeff Id (#11),
I agree 1000% with the need to work from the best quality data – “best” being defined in some objective way. Anthony’s CRN1-2 stations very much represent that.
The problem is the lack of equivalent information elsewhere – particularly when the US history is rather discordant from ROW temperature history.
The problem with all these data sets seems to be that they are a rancid stew of good and bad data, seemingly with negligible effort at quality control, instead using weird multivariate methods to supposedly adjust the bad data – methods that are invariably poorly explained and documented and unknown outside climate science.
Re: Steve McIntyre (#12),
Do you know if the methods are known inside climate science? Not a sarcastic question.
Re: Steve McIntyre (#12),
Steve, but it’s Science. And we’ve finally joined the age of Science-Based Policy.
Re: Steve McIntyre (#10), (1) But (?) apparently we really have no idea of how much they have increased absent natural climate forcings and
(2) is Krugman’s graph an accurate representation of the “true” global temperature?
Or check to see if there’s a correlation between station quality and whether it’s been retained or dropped. Should be pretty simple stat exercise.
Obviously, the thesis to check statistically is whether the trend in the dropped stations differs from the trends in the retained stations (and perhaps the added stations, if available).
It was my impression that in the 1988-98 period, most of the difference in land temps v. ocean or atmospheric temps resulted from dropping land stations that were not trending upward.
I’m sure Watts will encourage survey of any deleted stations which can be found. It’s an obvious bit of research which should be added to the pile… especially because so much other research was indirectly using those stations’ data.
I’d be interested to know what the trend of the dropped stations was too. Call me a cynic ;).
Roseau, MN (not on the list above) went away in 2007 when the radio station it was at moved to a new location. I was there this weekend.
Some stations move because volunteer observers who graciously allow the stations to be placed on their private property either move or retire from service. Stations at municipal facilities may change because of staffing or structural changes. Data recording and transmission only takes a few minutes per day so the program essentially benefits from the free services and good will of hundreds of people who have other things to do as their main activities. Thus the constant changing of sites in the network is inevitable.
“ID NAMPA SUGAR FACTORY” Are you kidding me? Have these new stations been added to surfacestations.org yet? I’ll go do a survey of that one as I live quite close. And can tell you right now that is not a wise choice of location based on the name. I certainly would not put a quality weather data gathering station anywhere near that place.
Took pics at a climate station at a North Dakota sugar factory yesterday. Stevenson screen in the middle of a big old expanse of asphalt. Tho it was in a grassy median shaded by a line of trees. Security guards at the plant read the temp evey hour.
USHCNv2 “drops” Napoleon OH, one of the stations singled out in Anthony’s study as particularly bad, lying as it does in a sea of paving at a waste water treatment plant since 2/14/2000.
In its place, USHCNv2 “adds” Defiance OH. However, the USHCNv2 station list shows that its “Defiance” is in fact a “composite” of Defiance (Coop 332098) and two other stations, Coop 335664 and 335669. However, these are simply the codes for Napoleon, before and after a small move on 5/1/62.
Since the Defiance record runs from 3/1/1893 to the present, there was no need to splice its early or later period onto another station, so it is not clear why or how Napoleon was merged with the Defiance record. The USHCNv2 station list merely names the additional stations that are part of “composite” records, but does not indicate when which station is used.
So to the extent USHCNv2 has “dropped” bad stations, it may in fact have retained them, simply by averaging them into “new” stations. This should be studied in greater detail.
In order to better understand what kinds of adjustments were made when the USHCN temperature series Version 1 (V1) went to Version 2 (V2), I looked at those stations with the largest absolute trend differences between the V1 and V2 series and also compared those large difference stations to stations with large trends but little or no difference between the V1 and V2 series.
For the first part of the analysis I limited my trend measurements to those stations with complete data for the 1920-2006 period of interest. I then looked at those stations with trend differences between V1 and V2 of greater than 0.1 and less than -0.1 degrees C per decade. I compared those stations by CRN rating as determined from the Watts team’s latest reported findings and by the USHCN population designation (urban, suburban and rural) as reported in the Watts team spreadsheets. The table below lists the results of this analysis.
The numbers are small for concluding much from the CRN ratings comparisons, but I can conjecture that the CRN 1 and CRN2 category portions show greater positive trends than does their respective population portions and that CRN5 portion shows a greater negative trend than does its population portion. The three population designation comparisons shows a very apparent bias for the largest V1 and V2 trend differences, both positive and negative, to occur with the rural stations. A somewhat surprising finding, since the rural stations are sometimes and in some ways considered a standard for adjustments to other stations.
The results from the second part of the analysis is shown below where I have presented time series for V1 and V2 at a given USHCN station for two general cases where (1) the trend differences are large and denoted by the trend lines in the graphs and (2) the trend differences between V1 and V2 are very small but the trend for both versions are relatively large. I have dispersed the graphs in such a way that the examples of the two cases can be seen on top of one and another for ease of comparison.
Nothing jumps out for me in the way of differentiating why the stations with large trend differences between V1 and V2 have a V1 appearance different than that of the V1 time series that have small differences between V1 and V2. Perhaps the readers of this post can offer some differentiating features.
My second point of confusion on this matter involves visually understanding from these examples in the graphs how those corrections might have been applied. I believe that the algorithm whereby the breakpoints are determined are available but as I recall not in a packaged form for direct application to a time series. I do not recall whether sufficient information is available to apply an algorithm for adjusting the time series given the breakpoints.
It is important to keep in mind that the breakpoints are not determined based on the stations time series but rather based on the difference time series of the station in question compared two stations at a time with correlated and nearby stations. The explanation is listed below:
Presented below are links to relevant sources of data used in this analysis.
Link to the Watts team data on CRN ratings and population designation for the USHCN stations:
http://www.surfacestations.org/USHCN_stationlist.htm
V1 (Urban USHCN) data from this link:
http://cdiac.ornl.gov/epubs/ndp/ushcn/ndp019.html#tempdata
V2 data from these links:
ftp://ftp.ncdc.noaa.gov/pub/data/ghcn/v2
ftp://ftp.ncdc.noaa.gov/pub/data/ushcn/v2/monthly
V2 adjustments explained from this link:
http://www.ncdc.noaa.gov/oa/climate/research/ushcn
Stations dropped from v1 are not necessarily closed. Example, I took pictures of LOA, UT, this summer, thinking it was still in the USHCN. I’m not sure when it was dropped, but I presume it was prior to my visit. The volunteer seemed to be unaware of what her data was being used for; seems odd to me that a matter of such interest would not be shared with the volunteers–that would be great public relations.
The replacement stations are not necessarily any better than the originals. The replacement for LOA, for example is Salina. Take a look at the picture at
and tell me a sensor on top of a multi-story building almost on top of what appear to be large air conditioning units is better than the LOA station. (You can see my pictures for Loa on the surfacestations gallery.)