A Comparison of Satellite and In Situ–Based Sea Surface Temperature Climatologies

The purpose of this study is to present a satellite-derived sea surface temperature (SST) climatology based on Pathfinder Advanced Very High Resolution Radiometer (AVHRR) data and to evaluate it and several other climatologies for their usefulness in the determination of SST trends. The method of evaluation uses two longterm observational collections of in situ SST measurements: the 1994 World Ocean Atlas (WOA94) and the Comprehensive Ocean‐Atmosphere Data Set (COADS). Each of the SST climatologies being evaluated is subtracted from each raw SST observation in WOA94and COADS to produce several separate long-term anomaly datasets. The anomaly dataset with the smallest standard deviation is assumed to identify the climatology best able to represent the spatial and seasonal SST variability and therefore be most capable of reducing the uncertainty in SST trend determinations. The satellite SST climatology was created at a resolution of 9.28 km using both day and night satellite fields generated with the version 4 AVHRR Pathfinder algorithm and cloud-masking procedures, plus an erosion filter that provides additional cloud masking in the vicinity of cloud edges. Using the statistical comparison method, the performance of this ‘‘Pathfinder 1 erosion’’ climatology is compared with the performances of the WOA94 18 in situ climatology, the Reynolds satellite and in situ blended 1 8 analysis, version 2.2 of the blended 18 Global Sea-Ice and Sea Surface Temperature (GISST) climatology, and the in situ 58 Global Ocean Surface Temperature Atlas (GOSTA). The standard deviation of the anomalies produced using the raw WOA94 in situ observations and the reference SST climatologies indicate that the 9.28-km Pathfinder 1 erosion climatology is more representative of spatial and seasonal SST variability than the traditional in situ and blended SST climatologies. For the anomalies created from the raw COADS observations, the Pathfinder1 erosion climatology is also found to minimize variance more than the other climatologies. In both cases, the 58 GOSTAclimatology exhibits the largest anomaly standard deviations. Regional characteristics of the climatologies are also examined by binning the anomalies by climatological temperature classes and latitudinal bands. Generally, the Pathfinder 1 erosion climatology yields lower anomaly variances in the mid- and high latitudes and the Southern Hemisphere, but larger variances than the 18 climatologies in the warm, Northern Hemisphere low-latitude regions.