Evaluation of the Princeton Ocean model using South China Sea monsoon experiment (SCSMEX) data

The Princeton Ocean Model (POM) has been implemented in the South China Sea for hindcast of circulation and thermohaline structure. A two-step techniq ue is used to initialize POM with temperature, salinity, and velocity for 1 April 1998 and integrate it from 1 April 1998 with synoptic surface forcin g for 3 months with and without data assimilation. Hydrographic and current data acquired from the South China Sea Monsoon Experiment (SCSMEX) from Ap ril through June 1998 are used to verify, and to assimilate into, POM. The mean SCSMEX data (Apr-Jun 1998) are about 0.5 degreesC warmer than the mean climatological data above the 50-m depth, and slightly cooler than the mea n climatological data below the 50-m depth, and are fresher than the climat ological data at all depths and with the maximum bias (0.2-0.25 ppt) at 75- m depth. POM without data assimilation has the capability to predict the circulation pattern and the temperature field reasonably well, but has no capability t o predict the salinity field. The model errors have Gaussian-type distribut ion for temperature hindcast, and non-Gaussian distribution for salinity hi ndcast with six to eight times more frequencies of occurrence on the negati ve side than on the positive side. Data assimilation enhances the model cap ability for ocean hindcast, if even only conductivity-temperature-depth (CT D) data are assimilated. When the model is reinitialized using the assimila ted data at the end of a month (30 Apr; 31 May 1998) and the model is run f or a month without data assimilation (hindcast capability test), the model errors for both temperature and salinity hindcast are greatly reduced, and they have Gaussian-type distributions for both temperature and salinity hin dcast. Hence, POM gains capability in salinity hindcast when CTD data are a ssimilated.