中国海及邻近海域卫星观测资料同化试验

Experiments on Assimilating of Satellite Data in the China Seas and Adjacent Seas

利用1个基于POMgcs海洋模式和多重网格三维变分同化方法建立的中国海及邻近海域海面高与三维温盐流数值预报模型,通过一系列数值试验,研究了同化卫星测高和卫星遥感海面温度观测资料对该模型预报能力的影响。试验结果表明,同化卫星测高资料可明显改善海面高度与三维温度和盐度的分析预报效果,使1 200 m以上的温度预报误差减小0.16℃,并能有效提高对海洋中尺度现象的预报能力;同化卫星遥感海面温度对100 m以上的温度和盐度的预报效果有所改善,可使海面温度的预报误差减小10%。

A three-dimensional ocean forecast system based on Princeton Ocean Model and 3DVar assimilation scheme is hired, with satellite altimeter data, sea surface temperature （SST） data as well as temperature and salinity profiles data being assimilated into it. Utilizing this forecast system, series experiments are conducted to evaluate the impact of assimilating altimeter and SST data on the forecast result. The differences in the forecasted temperature, salinity and sea surface height of the experiments have been examined. As a result of assimilating altimeter data, the average error of the forecasted temperature in the top 1200m reduced 0. 16℃. Besides, the forecasted oceanic field became more reasonable, and the forecasting ability of mid-scale events is enhanced significantly. Specially, assimilating satellite SST data is helpful to improve the accuracy of forecasted temperature in the top 100m. By assimilating SST data, error of the forecasted SST is reduced by 10%.