A shout out for Bob Tisdale’s blog here. Bob cross-posts at Anthony’s from time to time. At his own blog, he’s done a number of excellent analyses of SST data sets.
On many occasions, I’ve observed that critical analysis of the temperature record has spent a disproportionate amount of attention on land data sets relative to SST. While the issues there are not necessarily resolved, they are well-known. Over the past few years, many readers, including myself, have built up some familiarity with the alphabet soup of land data. Many of us, like connoisseurs of fine wine, can distinguish between GHCN, CRU, NOAA, GISS and the various vintages of USHCN.
However, speaking for myself, I’m a bit at sea, so to speak, in my connoisseurship of SST data. The differences between SST data sets was recently discussed at Anthony’s and, curiously enough, it also plays a role in Santer et al 2008, which made a curious switch in SST versions from prior articles – a switch that has thus far gone unnoticed and which affects results. I’ll return to this on another occasion.
After Anthony raised a question of a recent divergence between GISS and NOAA/NCDC temperatures, Bob T, pitched in with a careful explanation of differences between the SST data sets used in the different major global indices. Following are quotes from Bob T. In following the nomenclature for data sets, keep in mind that NOAA originates a few different SST versions, with GISS using one version and NOAA (for its own temperature index) using another.
GISS has used the NCDC OI.v2 SST anomaly data since December 1981, and before that they had used the Hadley Centre’s HADSST data. GISS then splices the two datasets together….
NOAA describes the Optimum Interpolation (OI.v2) SST anomaly data (used by GISS) as, “The optimum interpolation (OI) sea surface temperature (SST) analysis is produced weekly on a one-degree grid. The analysis uses in situ and satellite SST’s plus SST’s simulated by sea-ice cover.” The in situ data is from buoy and ship measurements. The full description of the OI.v2 data is here: http://www.cdc.noaa.gov/data/gridded/data.noaa.oisst.v2.html
The OI.vs SST anomaly is attributed by Bob T to Smith and Reynolds 2002.
NCDC has their own SST anomaly dataset for their global surface temperature product, and they calculate anomalies against the base years of 1901 to 2000.
The NCDC identifies the “Global Ocean Temperature” dataset as SR05 in its Global Surface Temperature Anomalies webpage:
Linked to the webpage is a paper by Smith et al (2005) “New surface temperature analyses for climate monitoring” GEOPHYSICAL RESEARCH LETTERS, VOL. 32, L14712, doi:10.1029/2005GL023402, 2005.
On page 2, Smith et al describe the SR05 data as, “The SR05 SST is based on the International Comprehensive Ocean Atmosphere Data Set (ICOADS [Woodruff et al., 1998]). It uses different, though similar, historical bias adjustments to account for the change from bucket measurements to engine intake SSTs [Smith and Reynolds, 2002]. In addition, SR05 is based on in situ data.”
It appears, from that quote and the rest of the paper, the SR05 SST dataset does NOT use satellite data. This is consistent with NCDC’s other long-term SST datasets. They also abstain from satellite data.
I have found no source of SR05 SST anomaly data, other than the Global, Northern Hemisphere, and Southern Hemisphere “Ocean Temperature” datasets linked to the Global Surface Temperature webpage.
ERSST v2 and ERSST v3
Bob T observes that NOAA/NCDC also supports ERSSTv2 (now discontinued) and ERSST v3 SST data sets and in the linked posts, compares these data sets to the other ones. Bob also mentions two vontages of ERSST v3, one of which seems to have disappeared (though Bob mentions that he had saved some of the disappeared data.)
In addition to the SR05 SST data, the NCDC also has two other long-term SST datasets called Extended Reconstructed SST (ERSST) data. The ERSST.v2 (Version 2) data was introduced in 2004 with the Smith and Reynolds (2004) paper Improved Extended Reconstruction of SST (1854-1997), Journal of Climate, 17, 2466-2477. Many of my early Smith and Reynolds SST Posts used ERSST.v2 data through the NOAA NOMADS system. Unfortunately, ERSST.v2 data is no longer available through that NOAA system, so the latest ERSST.v2 global SST anomaly data from NOMADS I have on file runs through October 2008.
The ERSST.v2 data was updated with ERSST.v3 data. In my opinion, it provides the most detailed analysis of high latitude SST in the Southern Hemisphere (the Southern Ocean). The ERSST.v3 data was introduced last year with the Smith et al (2008) paper: Improvements to NOAA’s Historical Merged Land-Ocean Surface Temperature Analysis (1880-2006), Journal of Climate,21, 2283-2296. The NCDC updated it with their ERSST.v3b version later in 2008, but more on that later. A limited number of datasets (based on latitude) for the ERSST.v3b data are available from NCDC (though it is available on a user-selected coordinate basis through the KNMI Climate Explorer website, as is ERSST.v2 data).
From Bob’s comments, I get the impression that ERSST v3 is not used in the three major GLB temperature reports (CRU, GISS, NOAA) and will seek confirmation of this.
I haven’t checked Bob’s posts for HadCRU yet, but I presume that they use HadSST – a newish HadISST version is now in circulation, which I glanced at recently but haven’t studied.
I was going to do this in another post, but I’ll mention the point here to perhaps motivate readers to ponder the difference between these data sets.
In the CCSP report that prompted Douglass et al 2007 (and thus Santer et al 2008), the surface observations used as comparanda were CRU, NOAA and GISS. These data sets were also used in Douglass et al.
However, in an hitherto unnoticed swap, Santer et al 2008 used ERSST v2, then hot off the press ERSST v3 and HadISSTv2 as surface comparanda. Santer purported to justify the substitution as follows:
The three SST datasets are more appropriate to analyse in order to determine whether observed lower tropospheric temperature changes follow a moist adiabatic lapse rate (Wentz and Schabel, 2000).
However, the ERSST versions also have a noticeably lower trend than GISS or NOAA (the two “hottest” series). The lower trends in the surface data reduced the mismatch between surface and observations, contributing to Santer’s claim that :
There is no longer a serious and fundamental discrepancy between modelled and observed trends in tropical lapse rates, despite DCPS07’s incorrect claim to the contrary. Progress has been achieved by the development of new T_SST , T_L+O, and T2LT datasets, …
Here the “new T_SST” data set appears to be the ERSST data – which seems to have had a somewhat complicated recent history. It looks like earlier ERSST versions used satellite data in their construction, while the most recent version has got rid of the “satellite bias” by discontinuing use of the satellite data.
Whatever the merits of the ERSST data, it’s hard to see that the comparison of satellite data to ERSST, interesting as it may be, is particularly relevant to the issue of whether there is a statistically significant difference between satellites and the “big” indices (GISS, CRU, NOAA) if it isn’t actually used in the “big” indices.
Again, I provide a caveat that my own personal handling of these SST data sets is very limited and I thus have limited connoiseurship of them at this time.