Performance of four sea surface temperature assimilation schemes in the South China Sea

Abstract

Four existing sea surface temperature (SST) assimilation schemes are evaluated in terms of their performances in assimilating the advanced very high resolution radiometer pathfinder best SST data in the South China Sea using the Princeton Ocean Model. Schemes 1 and 2 project SST directly to subsurface according to model-based correlations between SST and subsurface temperature. The difference between these two schemes is related to the order of vertical projection and horizontal optimal interpolation (OI). In Scheme 1, the spatially non-uniform SST observations are first projected to subsurface levels, followed by horizontal OI at each level. While in Scheme 2, the remotely sensed SSTs are first optimally interpolated to all grid points at the surface, followed by projecting gridded SSTs to subsurface levels. Scheme 3 assumes that the mixed layer is well mixed and has a uniform temperature vertically. In Scheme 4, SST is propagated to subsurface levels using a linear relationship of temperature between any two neighboring depths (Scheme 4a) or between surface and subsurface (Scheme 4b), which is derived by empirical orthogonal function (EOF) technique. To verify the results of the four schemes, the authors use the hydrographic data from two cruises during the South China Sea Monsoon Experiment in April and June 1998. It was shown that all four schemes could improve the SST field by reducing about 50% of the root mean square errors (RMSEs). All but Scheme 3 can improve model thermocline structure that is too diffused otherwise, though the RMSEs increase in the thermocline, especially for Scheme 2 when the model has opposite bias between upper layers and lower layers. Scheme 3 fails in the subsurface depth by increasing the thermocline depth, especially when there is a cold model bias. Projecting SST downward by EOF technique can deepen the depth of assimilation especially in Scheme 4a. Both Schemes 4a and b can correct the bias in the mixed layer and do not change the vertical thermal structure.