Effect of subjective choices on the objective analysis of sea surface temperature data in the tropical Atlantic and Pacific oceans

Many subjective choices are required to perform an objective interpolation (OI) analysis of environmental variables. Herein, we consider the effects on the statistical analysis of sea surface temperature (SST) using (1) a structure function or covariance analysis, (2) different analytical expressions to represent the statistics of the raw data, and (3) different historical SST data sets. The historical data sets are the well-sampled Comprehensive Ocean-Atmospheric Data Set (COADS) and the poorly sampled historical expendable bathythermograph (XBT) data set. Results from these analyses are used to generate error maps for a poorly-sampled, two month XBT array and a proposed well-sampled profiling float array. For the relatively data-rich GOADS analysis, decorrelation scales are the same using either the structure function or covariance analyses. Results differ for the data-poor XBT analysis. Representative decorrelation scales in the Pacific (Atlantic) are about 11-14 (6-10) degrees in the zonal direction and 4-7 (3-6) degrees in the meridional direction. As GOADS SST data are less precise than XBT SST data, error and signal variances are greater for the former. The choice of analytical fit to the raw data (needed to generate error maps) has a dramatic effect on-the resulting uncertainty fields. Gaussian fits, because of their parabolic shape near the origin, result in smaller errors than exponential fits for the same observing array. Finally, the proposed float array can achieve the accuracies needed to resolve satisfactory upper layer heat content changes over larger areas than the present XBT network. (C) 2000 Ifremer/CNRS/IRD/Editions scientifiques et medicales Elsevier SAS.