Assimilation of Different SST Datasets to a Coastal Ocean Modeling System in the Yellow and East China Sea

作者：Kwon Kyungman; Choi Byoung Ju^*; Lee Sang Ho

来源：Journal of Coastal Research, 2018, 85: 1041-1045.

DOI：10.2112/SI85-209.1

• SST
• Yellow and East China Sea
• data assimilation
• ensemble Kalman filter
• OISST
• MGDSST
• OSTIA
• MWIR

Global gridded gap-free sea surface temperature (SST) datasets were quantitatively evaluated using independent in situ datasets in the Yellow and East China Sea from September 2011 to February 2012. The assimilation effect of the four different SST datasets on a regional ocean modeling system was examined. The SST from the gridded SST datasets was compared with two ocean buoy SST data and bi-monthly routine hydrographic observation data in the Yellow Sea (YS). The root-mean-square differences (RMSDs) of the OISST, MGDSST, OSTIA, and MWIR SST datasets relative to the in-situ SST were 0.64, 0.53, 0.62, and 0.91 degrees C, respectively. The RMSDs of SST were higher than 1 degrees C for all datasets in the southeastern corner of the YS. Ocean circulation was simulated with a regional ocean model, and the SST data from the four SST datasets were assimilated. Assimilation of the SST to the ocean model improved the ocean current as well as temperature distribution. The daily mean simulated temperature was compared to the observed SST and vertical profiles of the temperature at the ocean buoys and hydrographic observation stations. After the assimilation of OISST, MGDSST, OSTIA and MWIR datasets, RMSDs of the simulated SST were 0.78, 0.92, 0.66 and 0.86 degrees C, respectively, at the buoy stations. The RMSDs of the simulated subsurface temperature were 1.60, 1.67, 1.56 and 1.70 degrees C, respectively, at the hydrographic observation stations. The simulated SSTs from the model with assimilation of the OSTIA and OISST datasets had relatively smaller RMSDs.

• 出版日期2018-5