Den stora tråden om global uppvärmning/växthuseffekten

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ABSTRACT
The objective of this research was to test the hypothesis that Global Average Surface Temperature (GAST) data, produced by NOAA, NASA, and HADLEY, are sufficiently credible estimates of global average temperatures such that they can be relied upon for climate modeling and policy analysis purposes. The relevance of this research is that the validity of all three of the so- called Lines of Evidence in EPA’s GHG/CO2 Endangerment Finding require GAST data to be a valid representation of reality.


In this research report, the most important surface data adjustment issues are identified and past changes in the previously reported historical data are quantified. It was found that each new version of GAST has nearly always exhibited a steeper warming linear trend over its entire history. And, it was nearly always accomplished by systematically removing the previously existing cyclical temperature pattern. This was true for all three entities providing GAST data measurement, NOAA, NASA and Hadley CRU.


As a result, this research sought to validate the current estimates of GAST using the best available relevant data. This included the best documented and understood data sets from the U.S. and elsewhere as well as global data from satellites that provide far more extensive global coverage and are not contaminated by bad siting and urbanization impacts. Satellite data integrity also benefits from having cross checks with Balloon data.


The conclusive findings of this research are that the three GAST data sets are not a valid representation of reality. In fact, the magnitude of their historical data adjustments, that removed their cyclical temperature patterns, are totally inconsistent with published and credible U.S. and other temperature data. Thus, it is impossible to conclude from the three published GAST data sets that recent years have been the warmest ever –despite current claims of record setting warming.


Finally, since GAST data set validity is a necessary condition for EPA’s GHG/CO2 Endangerment Finding, it too is invalidated by these research findings.

VII. SUMMARY & CONCLUSIONS


In this research report, the most important surface data adjustment issues are identified and past changes in the previously reported historical GAST data are quantified. While the notion that some “adjustments” to historical data might need to be made is not challenged, logically it would be expected that such historical temperature data adjustments would sometimes raise these temperatures, and sometimes lower them. This situation would mean that the impact of such adjustments on the temperature trend line slope is uncertain. However, each new version of GAST has nearly always exhibited a steeper warming linear trend over its entire
history.


That was accomplished by systematically removing the previously existing cyclical temperature pattern. This was true for all three entities providing GAST data measurement, NOAA, NASA and Hadley CRU.


As a result, this research sought to validate the current estimates of GAST using the best available relevant data. This included the best documented and understood data sets from the U.S. and elsewhere as well as global data from satellites that provide far more extensive global coverage and are not contaminated by bad siting and urbanization impacts. Satellite data integrity also benefits from having cross checks between UAH and RSS as well as with Balloon data.


The conclusive findings of this research are that the three GAST data sets are not a valid representation of reality. In fact, the magnitude of their historical data adjustments, that removed their cyclical temperature patterns, are totally inconsistent with published and credible U.S. and other temperature data. Thus, it is impossible to conclude from the three published GAST data sets that recent years have been the warmest ever –despite current claims of record setting warming.


Finally, since GAST data set validity is a necessary condition for EPA’s GHG/CO2 Endangerment Finding, it too is invalidated by these research findings.

The Undersigned Agree with the Conclusions of this Report:

Dr. Alan Carlin
Retired Senior Analyst and manager, US Environmental Protection Agency, Washington, DC.
Author, Environmentalism Gone Mad, Stairway Press, 2015.
Ph.D., Economics, Massachusetts Institute of Technology, Cambridge, MA. BS, Physics, California Institute of Technology, Pasadena, CA.

Dr. Harold H. Doiron
Retired VP-Engineering Analysis and Test Division, InDyne, Inc. Ex-NASA JSC, Aerospace Consultant
B.S. Physics, University of Louisiana - Lafayette
M.S., Ph.D., Mechanical Engineering, University of Houston

Dr. Theodore R. Eck
Ph.D., Economics, Michigan State University M.A, Economics, University of Michigan Fulbright Professor of International Economics
Former Chief Economist of Amoco Corp. and Exxon Venezuela
Advisory Board of the Gas Technology Institute and Energy Intelligence Group

Dr. Richard A. Keen
Instructor Emeritus of Atmospheric and Oceanic Sciences, University of Colorado
Ph.D., Geography/Climatology, University of Colorado
M.S., Astro-Geophysics, University of Colorado
B.A., Astronomy, Northwestern University

Dr. Anthony R. Lupo
IPCC Expert Reviewer
Professor, Atmospheric Science, University of Missouri
Ph.D., Atmospheric Science, Purdue University
M.S., Atmospheric Science, Purdue University

Dr. Thomas P. Sheahen Ph.D., Physics, M.I.T. B.S., Physics, M.I.T.

Dr. George T. Wolff
Former Chair EPA's Clean Air Scientific Advisory Committee
Ph.D., Environmental Sciences, Rutgers University
M.S., Meteorology, New York University
B.S., Chemical Engineering, New Jersey Institute of Technology

Study Findings:
These analysis results would appear to leave very, very little doubt but that EPA’s claim of a Tropical Hot Spot (THS), caused by rising atmospheric CO2 levels, simply does not exist in the real world. Also critically important, even on an all-other-things-equal basis, this analysis failed to find that the steadily rising Atmospheric CO2 Concentrations have had a statistically significant impact on any of the 13 critically important temperature time series data analyzed.