This paper is, as intended, a work in progress as a compilation of what’s current and important relative to the data sets used for formulating and implementing unprecedented policy decisions seeking a radical transformation of our society and institutions.

It was necessitated by the extraordinary revelations in the recently released CRU emails, including the admissions of Ian “Harry” Harris, the CRU programmer. He lamented about “[The] hopeless state of their (CRU) database. No uniform data integrity, it’s just a catalogue of issues that continue to grow as they’re found” and “Aarrggghhh! There truly is no end in sight. This whole project is SUCH A MESS. No wonder I needed therapy!!”

CRU’s Phil Jones, candidly confessed in a BBC interview that “his surface temperature data are in such disarray they probably cannot be verified or replicated.”

This reflects on both NOAA and NASA in the United States. Phil Jones also admits that “Almost all the data we have in the CRU archive is exactly the same as in the GHCN archive used by the NOAA National Climatic Data Center” and that NASA’s GISS uses the GHCN, applying its own adjustments, as it explains: “The current analysis uses surface air temperatures measurements from the following datasets: the unadjusted data of the Global Historical Climatology Network (Peterson and Vose, 1997 and 1998), United States Historical Climatology Network (USHCN) data, and SCAR (Scientific Committee on Antarctic Research) data from Antarctic stations.”

The first version of this paper inspired and motivated others toward a more in depth look into the data and methodology - a positive and welcome development long overdue. It is now essential that there be carried out an independent review of NOAA data methods and quality control procedures, such as is in process within CRU. This and any future versions of this paper include additional findings, corrections and enhancements based on feedback and constructive discussion.

Much attention and comment has focused on the station dropout issue. The loss of stations in the USA and worldwide is a real issue that NOAA does not dispute. NOAA claims that by focusing on temperature anomalies instead of actual temperatures the problem is resolved. In places with a reasonable density of stations, a random station dropout would likely not affect anomalies but where the data is already sparse or where the dropout was biased towards a certain character station, biases can be real and even significant. Further study is needed. Examples are provided.

This does not mitigate the fact that missing data (40% of GHCN is missing at least one month of data), poor station siting (90% of the over 1000 US climate stations out of 1221 network) and urbanization all contaminate data toward a warming bias. Over a dozen recent peer reviewed papers (including one by Dr. Phil Jones) have shown this to be the case. Dr. Jones showed a urban data contamination of 1C per century for China. The update to this paper provides more details and additional case studies attesting to a biased outcome.

In the words of two scientists frequently mentioned in the paper, we need:

“...independent groups doing new and independent global temperature analyses - not international committees of Nobel laureates passing down opinions on tablets of stone.” (Roy Spencer)

and

“...an inclusive assessment of the surface temperature record of CRU, GISS and NCDC. We need to focus on the science issues. This necessarily should involve all research investigators who are working on this topic, with formal assessments chaired and paneled by mutually agreed to climate scientists who do not have a vested interest in the outcome of the evaluations.” (Roger Pielke Sr.)

See paper here.