Further Comment On The Surface Temperature Data Used In The CRU, GISS And NCDC Analyses

In my post

An Erroneous Statement Made By Phil Jones To The Media On The Independence Of The Global Surface Temperature Trend Analyses Of CRU, GISS And NCDC

I discussed that Phil Jones implied that the GISS and NCDC surface temperature data sets confirmed the robutness of the magnitude of the multi-decadal global average surface temperature trend, even if his CRU data was excluded, since GISS and NCDC provide  independent assessments.

To present this issue further, I have reproduced below my question in 2005 on this issue and the CCSP response from

Compilation of Comments on the Public Review Draft of CCSP Synthesis and Assessment Product 1.1: “Temperature trends in the lower atmosphere – steps for understanding and reconciling differences”

Question [by Roger A. Pielke Sr]:What is the overlap in the raw data that utilized by the three groups?

The best estimate that I am aware of has a 90-95% overlap. The analyses from the three groups are hardly independent assessments, and this should not be hidden in the report.  The overlap is particularly important for the grid points analyzed in the analyses where only 1 or 2 observational data points exist. We have documented for the tropical land areas, for example (20N to 20S) about 70% of the grid points have had zero or less than one observation site! Thus to compute an average surface temperature trend over land in the tropics, which is the area where the report narrowly focuses, almost all of the raw data used on the three analyses is from the same source. Thus to present a Figure to purportedly illustrate uncertainty in the surface temperature trends is misleading.

Response from  CCSP: It is true that there are substantial, though not complete, overlaps between the data sources used in the three global surface temperature analyses. But the unimportance of this problem is shown by the abovementioned observation that the trends show strong coherence between adjacent grid boxes, even in the tropics (Figure 3.6d). Thus if the three global surface temperature analyses were to be deliberately based on different, well distributed sets of one third of the grid boxes, their global trends would still be in good agreement. Moreover it was shown by Jones et al. (1997) that on the annual global space scale there are only about 60 degrees of spatial freedom in surface temperature anomalies.

We note also that the three global surface temperature analyses are based on different methods, corroborating the validity of the analyses. The MSU groups use identical input data and yet yield estimates that differ by the same magnitude as they searched for signal. Why the surface record is being systematically identified as being a problem because of raw data overlap when this applies to all datasets is somewhat of a mystery. The analysis in this report implies that structural uncertainty is greater aloft than at the surface. It is not an altogether surprising result. The surface record is based upon instruments which remain in-situ, are generally calibrated and maintained on a regular basis, and observing practices are relatively constant. Monitoring of the upper-air is achieved either by “fire and forget” single-use radiosondes or by satellites which have at most a lifetime of several years. It is much easier to change practices and introduce significant non-climatic influences in these latter records which very likely explains the larger spread in these estimates than those at the surface.

The response is incorrect. It is written, for example, that

“It is true that there are substantial, though not complete, overlaps between the data sources used in the three global surface temperature analyses. But the unimportance of this problem is shown by the abovementioned observation that the trends show strong coherence between adjacent grid boxes, even in the tropics (Figure 3.6d). “

There are often only one data site per grid cell in the tropics, and elsewhere, so there is no way to correlate between sites within the grid cell. Second, the 90-95% data overlap that I mentioned was not questioned. Indeed, this is what is written in one of the e-mails from Phil Jones [Source: http://chiefio.wordpress.com/].

Comment by Prof. Phil Jones
http://www.cru.uea.ac.uk/cru/people/pjones/, Director, Climatic
Research Unit (CRU), and Professor, School of Environmental Sciences,
University of East Anglia, Norwich, UK:
“No one, it seems, cares to read what we put up http://www.cru.uea.ac.uk/cru/data/temperature/ on the CRU web page. These people just make up motives for what we might or might not have done. Almost all the data we have in the CRU archive is exactly the same as in the Global Historical Climatology Network (GHCN) archive used by the NOAA National Climatic Data Center [see here http://www.ncdc.noaa.gov/oa/climate/ghcn-monthly/index.php and here http://www.ncdc.noaa.gov/oa/climate/research/ghcn/ghcngrid.html ]……”

Another erroneous answer in the CCSP response is

“The surface record is based upon instruments which remain in-situ, are generally calibrated and maintained on a regular basis, and observing practices are relatively constant.”

Really! The invaluable photographic assessment of the USHCN sites has clearly documented that the observing sites are generally quite poor; see

Watts, A. 2009: Is the U.S. Surface Temperature Record Reliable? 28 pages, March 2009 The Heartland Institute.

The responses in the CCSP report clearly show the casual dismissal of the substantive issues with respect to all three of the global average surface temperature trends that are being used by policymakers to quantify global warming. The three data analyses are not indepenent assessments, and, based on our research (e.g. see) have a signficant warm bias.