There exists a need in the oceanography community to be able to produce climatologies of remote or poorly sampled shallow water areas through remote sensing techniques. Our goal was to construct a three-dimensional thermal structure of the Yellow Sea based primarily upon sea surface temperature data. The ability to do this successfully could lead the way to applying these techniques elsewhere using remotely sensed SST. The shallow water and dynamic conditions of the Yellow Sea made it an ideal study area. The large MOODS observational data set for the area provided us with 15,000 observations from 1929 to 1991. For the winter months we used regression techniques on the predominantly well-mixed, vertically isothermal profiles with excellent results. For the summer we applied a Feature Model which extracted physically significant depths and gradients from the observations. These modeled data were statistically compared with mixed results indicating little link between SST and mixed-layer depth but good correlation between SST and thermocline gradient. We believe interannual variability and significant sampling errors in our data contributed to our mixed results. Overall, we feel our approach is robust and has potential for further applications providing data quality issues are addressed.

Approved for public release; distribution is unlimited.

http://archive.org/details/yellowsearmalstr1094542981

U.S. Navy (USN) author