This study uses the high-resolution infrared radiation AVHRR (Advanced Very High Resolution Radiometer)-only and microwave radiation AMSR (Advanced Microwave Scanning Radiometer)+AVHRR sea surface temperature (SST) datasets to analyze
and compare non-Gaussian statistics and extreme events for SSTs. Since the primary difference between the two datasets is the lack of AVHRR data in regions of cloud cover, higher correlations between the datasets are expected in areas of low percent daily-averaged total cloud cover. These are regions where both sensors usually are capable of detecting SSTs and do not rely on the process of optimum interpolation to fill missing data. Probability density functions, skewness, kurtosis, autocorrelation time scale, and standard errors are used to reveal non-Gaussianity (i.e., statistically extreme events) in the datasets, while the correlation coefficient between the datasets is used to explore extreme events beyond a certain threshold. Non-Gaussianity is present in both SST datasets, and the highest correlations of extreme events between the datasets were within positive anomalies above a certain threshold for regions of
low percent daily-averaged total cloud cover.
