From the “global warming data looks better with heat-sinks and air conditioners” department.
Dr. Mark Albright, of the University of Washington writes:
Here is a great example of how NOT to measure the climate! On our way back to Tucson from Phoenix on Monday we stopped by to see the Picacho 8 SE coop site at Picacho Peak State Park. Note the white MMTS temperature monitor 1/3 of the way in from the left. The building is surrounded by the natural terrain of the Sonoran Desert, but instead the worst possible site adjacent to the paved road and SW facing brick wall was chosen in 2009 as the location to monitor temperature.
Here is a view looking Northeast:
For an aerial view in google maps:
The NCEI HOMR metadata repository tells us:
COMPATABLE EQUIPMENT MOVE 55 FEET DUE WEST. EQUIPMENT MOVED 05/06/2009. (that is when the new state park visitor center was built)
Picacho 8 SE has it all: brick building, parking lot, road, and air conditioner heat exchangers within a few feet of the MMTS sensor.
This one takes the cake, and I think it is worse than our former worst-case USHCN station (now closed) located in a parking lot in Tucson at the University of Arizona:
Picacho 8 SE is a COOP site, not part of USHCN, but it (along with others) is used as basis for the adjustments to the stations that have not been compromised. This is the crux of the problem, and why it is so important to seek out the good and unperturbed stations for their record, and discard the rest. No amount of general purpose algorithms and adjustments can fix garbage temperature data produced by stations like this, nor should we even try. This is a Class 5 station, the worst of the worst, and should be closed rather than continuing to pollute the climate dataset.
“The majority of weather stations used by NOAA to detect climate change temperature signal have been compromised by encroachment of artificial surfaces like concrete, asphalt, and heat sources like air conditioner exhausts. This study demonstrates conclusively that this issue affects temperature trend and that NOAA’s methods are not correcting for this problem, resulting in an inflated temperature trend. It suggests that the trend for U.S. temperature will need to be corrected.” He [Watts} added: “We also see evidence of this same sort of siting problem around the world at many other official weather stations, suggesting that the same upward bias on trend also manifests itself in the global temperature record”
“Our viewpoint is that trying to retain stations with dodgy records and adjusting the data is a pointless exercise. We chose simply to locate all the stations that DON”T need any adjustments and use those, therefor sidestepping that highly argumentative problem completely. Fortunately, there was enough in the USHCN, 410 out of 1218.”
1. Comprehensive and detailed evaluation of station metadata, on-site station photography, satellite and aerial imaging, street level Google Earth imagery, and curator interviews have yielded a well-distributed 410 station subset of the 1218 station USHCN network that is unperturbed by Time of Observation changes, station moves, or rating changes, and a complete or mostly complete 30-year dataset. It must be emphasized that the perturbed stations dropped from the USHCN set show significantly lower trends than those retained in the sample, both for well and poorly sited station sets.
2. Bias at the microsite level (the immediate environment of the sensor) in the unperturbed subset of USHCN stations has a significant effect on the mean temperature (Tmean) trend. Well sited stations show significantly less warming from 1979 – 2008. These differences are significant in Tmean, and most pronounced in the minimum temperature data (Tmin). (Figure 3 and Table 1)
3. Equipment bias (CRS v. MMTS stations) in the unperturbed subset of USHCN stations has a significant effect on the mean temperature (Tmean) trend when CRS stations are compared with MMTS stations. MMTS stations show significantly less warming than CRS stations from 1979 – 2008. (Table 1) These differences are significant in Tmean (even after upward adjustment for MMTS conversion) and most pronounced in the maximum temperature data (Tmax).
4. The 30-year Tmean temperature trend of unperturbed, well sited stations is significantly lower than the Tmean temperature trend of NOAA/NCDC official adjusted homogenized surface temperature record for all 1218 USHCN stations.
5. We believe the NOAA/NCDC homogenization adjustment causes well sited stations to be adjusted upwards to match the trends of poorly sited stations.
6. The data suggests that the divergence between well and poorly sited stations is gradual, not a result of spurious step change due to poor metadata.
The result speaks for itself:
Figure 4 – Comparisons of 30 year trend for compliant Class 1,2 USHCN stations to non-compliant, Class 3,4,5 USHCN stations to NOAA final adjusted V2.5 USHCN data in the Continental United States