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.
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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.
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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.
The fundamental takeaway for me is that they have apparently used the most contaminated data (the most poorly-sited stations) to adjust the least contaminated data (the best-sited stations) to match. That is just plain wrong of them to do, the adjustment process at any given station notwithstanding. It says they have more “trust” in the contaminated data than the uncontaminated data and that reeks of confirmation bias because the contamination moves the trend in the same direction as their hypothesis.
Another question..
Was this work independently reproduced before today ? Here, I mean that there are several authors. Did the lead author ask one of the other authors (or indeed anyone else) to verify with wholly independent software the main results ?
REPLY – St. Mac vetted it. We’ll be providing my spreadsheets. ~ Evan
Well done Anthony et al. Been looking forward all weekend to this post and it’s been worth the wait. The truth will set us free (eventually!).
Anthony, if you want to generate press from this you”ll need to summarise your findings more coherently – or to put it bluntly, sensationally. I doubt you’ll get any publicity from this whatsoever unless you can reframe it in these terms:
1. Temperature rises across the USA mainland over time have been overstated by a significant factor.
2. It is therefore likely the threat of Global Warming has been overstated.
3. This raises serious questions about current CO2 modeling and the urgency to react.
Canonical !
Well done. Your work should become the standard by which others are judged. Given the coverage Muller has had recently it it good that you pushed to get it out in a timely manner. We need to be able to answer that stuff in a timely manner.
Examples: Slashdot HuffingtonPost
What logic can NOAA et al point to that makes adusting temps upward for a station near a heat sink (or exhaust) a sensible idea?
PS I’m sure that anyone who finds or points out a genuine mistake in the paper or this post won’t be refered as a “beetle larvae”. 😎
Hello again 🙂
I had to look it up and post.. Peter (and his dad) knew it all along..
http://wattsupwiththat.com/2009/12/09/picking-out-the-uhi-in-global-temperature-records-so-easy-a-6th-grader-can-do-it/
Cheers,
LoN
Hmm, Fig8 — the Rural MMTS stations, excluding airports graph would be my pick for the most uncontaminated site-grouping. The raw data shows averaged US trends during 78-to-present to be a mere .03C/decade.
Oh, but it doesn’t include the TOBS, the TOBS…./sarc
Kudos from Yorkshire, Anthony,
I’m curious about why the SE stations, for the most part, received the least amount of adjustment
I just donated $50.00 Keep up the good work.
[REPLY: Thank you vry much. -REP]
Well done so far (assuming no significant errors are found in the paper). Now the rest of the world’s stations need to be reviewed so there can be a credibility in the global record and put to bed once and for all CAGW story so far.
Congratulations everyone! I guess now Michael Mann will get a chance to peer review Stephen McIntyre’s work, but without having to wait for years to get the raw data.
To me this is the really important paragraph:
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.
The surface stations project was ‘just amateur Anthony being picky about the experts. But now the surface stations project data is being put through a World Met Office ISO standard. That will be extremely difficult to wriggle out of.
Kudos to all Anthony.
Congratulations Anthony…a job well done!
TRUTH – Its the new hate speech.
“During times of universal deceit, telling the truth becomes a revolutionary act.” George Orwell.
Spurious doubling of 30-year warming trend from well-sited surface temperature
monitoring stations, 92% of which is due to erroneous upward data adjustments by NOAA of the actual data from those well sited stations? Does this pass the “close enough for government work” test? Wonder how much has been spent by NOAA making these erroneous adjustments, how much has been spent on research employing said erroneous data, and how much has been spent on misdirected public policies influenced by said erroneous data? Taxpayers want and deserve to know!
Congrats, great stuff. Wonderful to see the meteorological standard being used to standardize the methodology. Also great to see the wide distribution of the paper before submission, should make for a more honest and thorough review process and expedite feedback from all perspectives. Poor Muller, your paper takes the wind out of his sails (GIGO).
Beyond the scope of your paper, why is the emphasis in climatology on average temps rather than total heat (why isn’t humidity factored in?). Also don’t understand how surface temps can be used to calculate global warming or cooling when the vast majority of climate heat is stored in the oceans. Last, it seems like the process of computing ocean heat content is not as open as it might be.
This was a study of US stations, not world stations, if I read correctly.
Be hard to say much about the world from that.
Pure ignorance: Do “we” have any information about the quality of the global data (I think I recall a report of a single station being used to characterize all of Siberia)?
Can a math relationship be developed for “US data:satellite data::satellite data:world data”?
Almost as ignorant: Do “we” have the raw data from which to re-work the record, or is that among the things that have been lost?
Is there anyone starting to do the same study for another country which inputs a lot of temperature data into the World’s base data? Perhaps the UK, or New Zealand…?
Figure 23 is impressive as well, tmin tmax and tmean with identical (!) trends for 1/2 sations but heavily increased tmin trends for 3/4/5 stations.
please check line 300 in the article: ‘and are do consider’. Good work!
I’m a bit puzzled; I’ve looked through the paper, but I can’t find it clearly stated whether the data you used for your analysis was the completely unadjusted data, or the data adjusted for time-of-observation (you state, of course, that you’re using the same data as in Fall et al.–but that was unadjusted, TOB adjusted, and homogenized data, with comparisons between all three, while unless I’m misreading things here the primary comparisons in this paper are between your own analysis vs. homogenized data. I can’t find it stated one way or another whether TOB data was used for your analysis or not). Would you mind clearing up this point (or, unless this is just an obvious case of my failing to read what was plunked down right in front of me, perhaps clarifying it in future edits of the paper)?
REPLY – Raw, no TOBS. ~ Evan
In line 498 should that be class 3 rather than class 2?
REPLY – Yes. ~ Evan
Congratulations on a fine bit of work.
I know very little about this, but has this rather simple minded experiment been done? Rather than using a single temperature sensor, a grid of temperature sensors are used at test sites that will encompass “contaminated” areas by heat sources and rather more remote areas. Eg: if one sensor is in a car park, what is the difference between its readings and ones 200, 500,1000 … yards away in a field?
A number of different test sites, i.e. rural and urban would be needed.
Using modern radio methods, logging can be done without cabling.
This would give direct experimental evidence of the effects that are inferred (correctly in my view) in this paper. it would also give a better experimental basis for DESIGNING a surface temperature monitoring system than we have a present (assuming that one will be needed in the era of remote sensing).