Sampling Error Impacts on Climate Applications of Infrared Sea-Surface Temperature Fields

Abstract:

Long time series of accurate Sea Surface Temperatures (SSTs) are needed to resolve subtle signals that may be indicative of a changing climate. However, sampling errors primarily caused by clouds and inter-swath gaps are generated in satellite infrared SSTs. This study on quantifying such sampling errors in infrared SST fields indicates potential risks of misinterpretation in some climate applications. Physical mechanisms are proposed to interpret the sampling errors in the west pacific warm pool, tropical instability wave region, and stratocumulus deck regions. Dependency are tested to study the capability of predicting such sampling errors. Our results show that sampling errors in infrared SST fields are intrinsic and form geophysical patterns most likely resulted from SST-cloud interactions. Low- and mid- latitude sampling errors are dominated by the seasonal cycle in SSTs and thus can be determined by simulating the infrared sampling on a climatology reference, while high latitude sampling errors remain a large uncertainty due to the sparsest observations.