An Analysis of Sea Surface Temperature Anomalies in the AVHRR & AMSR + AVHRR Datasets

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Sunday, 17 January 2010
Exhibit Hall B2 (GWCC)
James J. Taeger, The Florida State University, Tallahassee, FL; and P. Sura

Various studies have shown a link between sea surface temperature (SST) anomalies to extreme events in climate over the world's oceans. Particularly when tropical cyclones or mid-latitude cyclones travel over warmer anomalies, they tend to intensify in strength, just as when they travel over colder anomalies, they tend to weaken or cease to further intensify. Our research begins with calculating daily SST anomalies from the Reynolds' Advanced Very High Resolution Radiometer (AVHRR) data set from January of 1982, to December of 2008 by performing higher statistics of skewness and kurtosis. Next, we compare the AVHRR data set, which uses infrared radiation to measure SSTs, with the Reynolds' Advanced Microwave Scanning Radiometer (AMSR) + AVHRR, which uses microwave radiation to measure SSTs, and is blended with AVHRR data as well. Both data sets use in situ data from ships and buoys where SSTs cannot be measured, but the major advantage of the AMSR + AVHRR v. the AVHRR data is that it can measure SSTs through clouds, where the AVHRR cannot. We compare the two by calculating the correlation coefficient over the globe from January of 2003, to December of 2008. Our hypothesis for the two data sets is for them to have a low correlation over regions of constant cloud cover, and our results seem to verify this. We analyze the data over periods of extended seasons such as extended summer (May-October), extended winter (November-April), and the full year. As we continue research, we will concentrate on more of a local scale (such as the Gulf of Mexico and the Gulf Stream) and aim to relate higher moments of skewness and kurtosis of non-Gaussian SST anomalies, to extreme events in climate.