PRESS RELEASE – U.S. Temperature trends show a spurious doubling due to NOAA station siting problems and post measurement adjustments.
Chico, CA July 29th, 2012 – 12 PM PDT – FOR IMMEDIATE RELEASE
A comparison and summary of trends is shown from the paper. Acceptably placed thermometers away from common urban influences read much cooler nationwide:
A reanalysis of U.S. surface station temperatures has been performed using the recently WMO-approved Siting Classification System devised by METEO-France’s Michel Leroy. The new siting classification more accurately characterizes the quality of the location in terms of monitoring long-term spatially representative surface temperature trends. The new analysis demonstrates that reported 1979-2008 U.S. temperature trends are spuriously doubled, with 92% of that over-estimation resulting from erroneous NOAA adjustments of well-sited stations upward. The paper is the first to use the updated siting system which addresses USHCN siting issues and data adjustments.
The new improved assessment, for the years 1979 to 2008, yields a trend of +0.155C per decade from the high quality sites, a +0.248 C per decade trend for poorly sited locations, and a trend of +0.309 C per decade after NOAA adjusts the data. This issue of station siting quality is expected to be an issue with respect to the monitoring of land surface temperature throughout the Global Historical Climate Network and in the BEST network.
Today, a new paper has been released that is the culmination of knowledge gleaned from five years of work by Anthony Watts and the many volunteers and contributors to the SurfaceStations project started in 2007.
This pre-publication draft paper, titled An area and distance weighted analysis of the impacts of station exposure on the U.S. Historical Climatology Network temperatures and temperature trends, is co-authored by Anthony Watts of California, Evan Jones of New York, Stephen McIntyre of Toronto, Canada, and Dr. John R. Christy from the Department of Atmospheric Science, University of Alabama, Huntsville, is to be submitted for publication.
The pre-release of this paper follows the practice embraced by Dr. Richard Muller, of the Berkeley Earth Surface Temperature project in a June 2011 interview with Scientific American’s Michael Lemonick in “Science Talk”, said:
I know that is prior to acceptance, but in the tradition that I grew up in (under Nobel Laureate Luis Alvarez) we always widely distributed “preprints” of papers prior to their publication or even submission. That guaranteed a much wider peer review than we obtained from mere referees.
The USHCN is one of the main metrics used to gauge the temperature changes in the United States. The first wide scale effort to address siting issues, Watts, (2009), a collated photographic survey, showed that approximately 90% of USHCN stations were compromised by encroachment of urbanity in the form of heat sinks and sources, such as concrete, asphalt, air conditioning system heat exchangers, roadways, airport tarmac, and other issues. This finding was backed up by an August 2011 U.S. General Accounting Office investigation and report titled: Climate Monitoring: NOAA Can Improve Management of the U.S. Historical Climatology Network
All three papers examining the station siting issue, using early data gathered by the SurfaceStations project, Menne et al (2010), authored by Dr. Matt Menne of NCDC, Fall et al, 2011, authored by Dr. Souleymane Fall of Tuskeegee University and co-authored by Anthony Watts, and Muller et al 2012, authored by Dr. Richard Muller of the University of California, Berkeley and founder of the Berkeley Earth Surface Temperature Project (BEST) were inconclusive in finding effects on temperature trends used to gauge the temperature change in the United States over the last century.
Lead author of the paper, Anthony Watts, commented:
“I fully accept the previous findings of these papers, including that of the Muller et al 2012 paper. These investigators found exactly what would be expected given the siting metadata they had. However, the Leroy 1999 site rating method employed to create the early metadata, and employed in the Fall et al 2011 paper I co-authored was incomplete, and didn’t properly quantify the effects.
The new rating method employed finds that station siting does indeed have a significant effect on temperature trends.”
Watts et al 2012 has employed a new methodology for station siting, pioneered by Michel Leroy of METEOFrance in 2010, in the paper Leroy 2010, and endorsed by the World Meteorological Organization (WMO) Commission for Instruments and Methods of Observation (CIMO-XV, 2010) Fifteenth session, in September 2010 as a WMO-ISO standard, making it suitable for reevaluating previous studies on the issue of station siting.
Previous papers all used a distance only rating system from Leroy 1999, to gauge the impact of heat sinks and sources near thermometers. Leroy 2010 shows that method to be effective for siting new stations, such as was done by NCDC adopting Leroy 1999 methods with their Climate Reference Network (CRN) in 2002 but ineffective at retroactive siting evaluation.
Leroy 2010 adds one simple but effective physical metric; surface area of the heat sinks/sources within the thermometer viewshed to quantify the total heat dissipation effect.
Using the new Leroy 2010 classification system on the older siting metadata used by Fall et al. (2011), Menne et al. (2010), and Muller et al. (2012), yields dramatically different results.
Using Leroy 2010 methods, the Watts et al 2012 paper, which studies several aspects of USHCN siting issues and data adjustments, concludes that:
These factors, combined with station siting issues, have led to a spurious doubling of U.S. mean temperature trends in the 30 year data period covered by the study from 1979 – 2008.
Other findings include, but are not limited to:
· Statistically significant differences between compliant and non-compliant stations exist, as well as urban and rural stations.
· Poorly sited station trends are adjusted sharply upward, and well sited stations are adjusted upward to match the already-adjusted poor stations.
· Well sited rural stations show a warming nearly three times greater after NOAA adjustment is applied.
· Urban sites warm more rapidly than semi-urban sites, which in turn warm more rapidly than rural sites.
· The raw data Tmean trend for well sited stations is 0.15°C per decade lower than adjusted Tmean trend for poorly sited stations.
· Airport USHCN stations show a significant differences in trends than other USHCN stations, and due to equipment issues and other problems, may not be representative stations for monitoring climate.
###
We will continue to investigate other issues related to bias and adjustments such as TOBs in future studies.
FILES:
This press release in PDF form: Watts_et_al 2012_PRESS RELEASE (PDF)
The paper in draft form: Watts-et-al_2012_discussion_paper_webrelease (PDF)
The Figures for the paper: Watts et al 2012 Figures and Tables (PDF)
A PowerPoint presentation of findings with many additional figures is available online:
Overview -Watts et al Station Siting 8-3-12 (PPT) UPDATED
Methodology – Graphs Presentation (.PPT)
Some additional files may be added as needed.
Contact:
Anthony Watts at: http://wattsupwiththat.com/about-wuwt/contact-2/
References:
GAO-11-800 August 31, 2011, Climate Monitoring: NOAA Can Improve Management of the U.S. Historical Climatology Network Highlights Page (PDF) Full Report (PDF, 47 pages) Accessible Text Recommendations (HTML)
Fall, S., Watts, A., Nielsen‐Gammon, J. Jones, E. Niyogi, D. Christy, J. and Pielke, R.A. Sr., 2011, Analysis of the impacts of station exposure on the U.S. Historical Climatology Network temperatures and temperature trends, Journal of Geophysical Research, 116, D14120, doi:10.1029/2010JD015146, 2011
Leroy, M., 1999: Classification d’un site. Note Technique no. 35. Direction des Systèmes d’Observation, Météo-France, 12 pp.
Leroy, M., 2010: Siting Classification for Surface Observing Stations on Land, Climate, and Upper-air Observations JMA/WMO Workshop on Quality Management in Surface, Tokyo, Japan 27-30 July 2010 http://www.jma.go.jp/jma/en/Activities/qmws_2010/CountryReport/CS202_Leroy.pdf
Menne, M. J., C. N. Williams Jr., and M. A. Palecki, 2010: On the reliability of the U.S. surface temperature record, J. Geophys. Res., 115, D11108, doi:10.1029/2009JD013094
Muller, R.A., Curry, J., Groom, D. Jacobsen, R.,Perlmutter, S. Rohde, R. Rosenfeld, A., Wickham, C., Wurtele, J., 2012: Earth Atmospheric Land Surface Temperature and Station Quality in the United States. http://berkeleyearth.org/pdf/berkeley-earth-station-quality.pdf
Watts, A., 2009: Is the U.S. surface temperature record reliable? Published online at: http://wattsupwiththat.files.wordpress.com/2009/05/surfacestationsreport_spring09.pdf
World Meteorological Organization Commission for Instruments and Methods of Observation, Fifteenth session, (CIMO-XV, 2010) WMO publication Number 1064, available online at: http://www.wmo.int/pages/prog/www/CIMO/CIMO15-WMO1064/1064_en.pdf
Notes:
1. The SurfaceStations project was a crowd sourcing project started in June 2007, done entirely with citizen volunteers (over 650), created in response to the realization that very little physical site survey metadata exists for the entire United States Historical Climatological Network (USHCN) and Global Historical Climatological Network (GHCN) surface station records worldwide. This realization came about from a discussion of a paper and some new information that occurred on Dr. Roger Pielke Sr. Research Group Weblog. In particular, a thread regarding the paper: 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.
2. Some files in the initial press release had some small typographical errors. These have been corrected. Please click on links above for new press release and figures files.
3. A work page has been established for Watts et al 2012 for the purpose of managing updates. You can view it here.
==========================================================
Note: This will be top post for a couple of days, new posts will appear below this one. Kinda burned out and have submission to make so don’t expect much new for a day or two. See post below this for a few notes on backstory. Thanks everybody! – Anthony
NOTE: 7/31/12 this thread has gotten large and unable to load for some commenters, it continues here.
So the result is just like Dr Christy’s PDAT data.
They mixed good and bad and the result was the worst. Who would say that?
“Anthony, mpaul is correct. The PR release document needs a strong headline and lede! Editors simply will glance and pitchr otherwise. (The press has become extremely lazy form my early days.) You need to put the conclusion (the ‘take-away’) in the headline and explain significance in the lede.
Bravo work and brilliant tactical approach on a highly public pre-release, making it obvious that politics are at work if rejected by the journals.”
Agreed. Punch it up Anthony. It’s too important, and you’ve worked too hard.
“Comparisons demonstrate that NOAA adjustment processes fail to adjust poorly sited stations downward to match the well sited stations, but actually adjusts the well sited stations upwards to match the poorly sited stations.”
I wish I was actually surprised.
Just one little typo in the graphs – the y axis of Figure 12 – CONUS station class comparison using gridding, with a Class 1&2 baseline – should read DELTAtemp from Class 1/2.
As mentioned above, the % of global coverage of the U.S. being relatively small, I think it fair to say that the “new” calculation of warming being closer to the IPCC global estimates doesn’t provide any validity to the IPCC. Rather, it opens the door to examine more closely the remaining global network of temperature data.
We could see a whole new picture of earth’s temperature history… and the one we should be seeing. Up, down, the same, oscillating, whatever.. we really do need to know what the truth is.
Antony, there is a mistake in the color scales: it is writen “>0.0” instead of “<0.0"
REPLY – My mistake. (And the other one on that scale.)
“After NOAA Adjustments” …. always upwards.
WELL DONE!!!!!!!!!!!!!!!!!! *CLAPPING*
So observational data beat computer generated ‘data’.
To paraphrase:
Chance of these adjustments occurring randomly are vanishingly miniscule…
So either its pure incompetence on behalf of a lot of different people over a long time or a conspiracy of a small set of people.
Will there be scalps taken?
Kudos, Anthony, et al.
(This is useful and that’s a high compliment when I have seen so much “could, maybe, might based on ifs and wishes” published that, IMO, is useless.)
I started learning about “How NOT to Measure Temperature” when I started visiting WUWT at around the time “How not To Measure Temperature #52 (or so)” was posted. I’m just a dumb ol’ engineer so I have a tendency to get a little leery when people are so sure of where we are going when we apparently didn’t know where we were and didn’t know where we’d been, temperature-wise. The hook was well set and I was easy to reel in; I have since been a regular to WUWT and have learned quite a bit about the complexity and issues (political and scientific) that make getting a handle on the Earth’s climate such a difficult task.
Nothing like working on the fundamentals first. Yay! Good stuff!
Well done Anthony! Congratulations and kudos to you and all your volunteers!
Bravo. Worth waiting for and, for me anyway, it does live up to the hype. In fact it is the confirmation of much that I could see when delving into station data, but, frustratingly, not show conclusively in analysis. The result was a sort of cognitive disconnect and I’ve just breathed a huge sigh of ‘ahhh’.
Tucker says:
July 29, 2012 at 12:20 pm
Any idea on why and how NOAA came to their adjustment methodology?
Confirmation bias, layered on confirmation bias, layered on confirmation bias.
AW – Slide 43 since is there a typo NOAA Adj Average at the top is .25 in the map .30?
Great PPT looking forward to the paper. PS I could be wrong.
This is far important than people think. its WORLDWiDE (the UHI effect). There is NO AGW period so this posting is in fact as important as WUWT said.
I’m not credentialed, but my take is he (they?) is talking about the :of record” the warmists talk about.
No way to talk about “cooling since” with out the whole record.
Finally, …
We have a paper and analysis which makes sense.
Which makes sense in terms of all the different situations we have seen with temperatures and trends and understanding that the UHI was an important factor.
Which makes sense in terms of looking at Raw unadjusted data versus how it turns out after NOAA adjusts it.
Which makes sense with our own personal experience garnered over the years looking at these issues and looking in your own backyard.
Which makes sense in terms of how far the NOAA goes to make it impossible to do this analysis without starting from the ground up – surveying all the stations on your own personal time no less.
Congratulation Anthony.
NOAA? We’re with the Humane Association, we know what you’ve been doing, and we’re here to take the pooch away.
I haven’t read the paper yet. But, though I’m not a scientist, I understand that “science” is based on accurate observation or “data”. Accurate data then leads to trying to understand it. Some, it would seem, (I’m being kind.) have taken questionable data and made it even more questionable to support an even more questionable theory that a particular political philosophy has embraced. (Was that a run-on sentence?)
Anthony “et al”, Thanks for your efforts to keep the data honest.
Assuming this holds then, at the very least, you’ve demonstrated that the results on temperature trends are sensitive to siting and that an overestimate of temperature increase is likely to have been made. The fact that this is so far restricted to the US is irrelevant since it has a wider significance. This is important.stuff (if it holds) Well done for getting the work to the stage at which you’re happy that its sufficiently solid such that it can now go out for review. .
You should be prepared that the likely response to it is (a) pretend it doesn’t exist (maybe this will work and you didn’t need to cancel the holiday). If (a) doesn’t work then argument (b) its not even peer-reviewed will be made, ignoring the fact that this doesn’t stop others talking about their work in advance of publication. Argument (b) will be joined by (c ), which is that its written by biased bloggers (with the implication that its therefore bound to be wrong). Failing all of this, argument (d) will be rolled out, which is a complicated refuting argument involving some very technical terms which sound impressive to an uncritical journalist. Peer review will also likely be a little rough….
By the way, why doesn’t BEST and the other groups use this new site classification technique ? I assume its been discussed in the literature. If so, what are stated pros and cons ?
.
FYI – minor grammar typo for/in – on lines 757 & 758
This qualitative approach, including rural-urban temperature differentials with value-neutral distance measurements, most certainly confirms AW’s site-specific Weather Station theses. The fact that Big Government “climate researchers” (sic) have so adamantly opposed such self-evident determining factors is a damning indictment of AGW Catastrophism on every level.
Next up: Might the Green Gang now admit that atmospheric/oceanic circulation patterns plus Total Solar Irradiance (TSI) rather than some negligible trace-gas “forcing” drive cyclical climatic variations– that per a looming 70-year “dead sun” Solar Minimum, Earth faces not a “runaway Greenhouse Effect” [spare us] but a renewed onset of Pleistocene Ice Time in wake of a fading Holocene Interglacial Epoch?
Alas, facts matter little to Kentti Linkola, Rajendra Pachauri, Hans Joachim Schellnberger. But after this, their Zombie Hypotheses will have to prick new dolls.
Zeke Hausfather: Any chance we can have a list of station IDs with their new classifications to play around with? Replication being important and all that
I second the motion. BEST released code and data at the time of their preprint. Will WUWT do the same?
REPLY – All will be forthcoming. Though you may have to wait until publication for every last bit. But you’ll get it all. I didn’t work so hard to see it all chucked in some dang inaccessible archive! ~ Evan
Kudos, Anthony, Evan, Steve & John:
Anthony, the SurfaceStations project shows your farsightedness. The rewards for your diligence and (and that of your volunteers) was a long time coming but your thoroughness and patience seem to be finally bearing fruit. While the initially speculated release of more climategate emails would have been more titillating, the release of new hard science is ultimately of higher worth than any politically oriented revelations. The paper would seem to be a solid first step in re-evaluation of the entire GHCN instrumental record. The temperature records before 1979 are rife with dubious TOBS and other adjustments that mostly serve to cool historical temperatures compared to the true raw data. I salute you and will toast you and your co-authors tonight at dinner.
Be careful, not to be carried away by your enthusiasm. The difference between what you say in the paper and in the powerpoint presentation:
Draft Paper:
This is true in all nine geographical areas of all five data samples. The odds of this result having occurred randomly are quite small.
PowerPoint:
This is true in all nine geographical areas of all five data samples. The odds of this result having occurred randomly are vanishingly minuscule.
is disturbing. Do don’t such things.
REPLY – Depends on your definitions. For all nine areas to be cooler fro Class 1\2 is a 1/512 shot. For all nine to be significantly cooler is more like 1 in 20,000. Then on top of that, it holds for all 5 slices of data. That’s pretty darn vanishingly minuscule. ~ Evan