Global Sea Surface Temperature Analyses: Multiple Problems and Their Implications for Climate Analysis, Modeling and Reanalysis (Hurrell and Trenberth, 1999)

Global Sea Surface Temperature Analyses: Multiple Problems and Their Implications for Climate Analysis, Modeling and Reanalysis

James W. Hurrell and Kevin E. Trenberth

Bull. Amer. Met. Soc., February 1999

Abstract

A comprehensive comparison is made among four sea surface temperature (SST) data sets: the optimum interpolation and the empirical orthogonal function reconstructed SST analyses from the National Centers for Environmental Prediction (NCEP), the Global Sea-Ice and SST Data Set (GISST) from the United Kingdom Meteorological Office, and the optimal smoothing SST analyses from the Lamont Doherty Earth Observatory (LDEO). Significant differences exist between the GISST and NCEP 1961-90 SST climatologies, especially in the marginal sea-ice zones and in regions of important small-scale features, such as the Gulf Stream, which are better resolved by the NCEP product. Significant differences also exist in the SST anomalies that relate strongly to the number of in situ observations available. In recent years, correlations between monthly anomalies are less than 0.75 south of about 100N and are lower still over the southern oceans and parts of the tropical Pacific where root mean square differences exceed 0.60C.

While adequate for many purposes, the SST data sets all contain problems of one sort or another. Noise is evident in the GISST data and realistic temporal persistence of SST anomalies after 1982 is lacking. Trends in recent years are rather different between the GISST and NCEP SSTs, and this can be partially traced to an increasing cold bias in the latter arising from incompletely-corrected satellite data. Large discrepancies exist between long-term trends in the LDEO and GISST data sets, with the former underestimating warming trends as a result of false assumptions of stationarity of statistics. The likely sources of the problems are identified and discussed, and many can be addressed in future reprocessing of SST, which is strongly recommended.

Ensembles of integrations with an atmospheric general circulation model (AGCM) are used with three of the SST data sets as lower boundary conditions to show that the differences among them imply physically important differences in the global atmospheric circulation. A case study shows that analyzed SST differences in the tropical Pacific can be as large as for a moderate El Niqo. Such large discrepancies induce local rainfall anomalies as large as 8 mm/day and are associated with global teleconnections that influence temperatures and precipitation around the world. Results also show the limitations to using AGCMs when forced by specified SSTs. It does matter, therefore, which SST analysis is used for AGCM simulations, as boundary conditions for atmospheric reanalyses, for identifying climate signals and for monitoring climate.

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Hongjun Zhang: zhangho@ucar.edu