Observing System Experiments for Evaluating the Impact of Satellite Sea Surface Salinity on Seasonal Predictions from the GMAO S2S System

Hackert, E ; Kovach, R ; Marshak, J ; Borovikov, A ; Chang, Y ; Molod, A ; Vernieres, G

关键词: SEA SURFACE SALINITY;    OCEAN SURFACE;    FORECASTING;    EL NINO;    SOUTHERN OSCILLATION;    KELVIN WAVES;    DATA ASSIMILATION;    CLIMATE MODELS;    NASA PROGRAMS;   

RP-ID  :  OceanObs’19 OTN-CVC-09,GSFC-E-DAA-TN73218

美国|英语

来源: NASA Technical Reports Server

【 摘 要 】

We assess the impact of satellite sea surface salinity (SSS) observations on dynamical ENSO (El Nino-Southern Oscillation) forecasts. Assimilation of SSS improves the mixed layer depth (MLD) and modulates the Kelvin waves associated with ENSO. In column 2, the initialization differences between experiments that assimilate SSS minus those withholding SSS assimilation are presented. Column 3 shows examples of forecasts generated for the different phases of ENSO assimilating the different satellite SSS. In general, for all phases of ENSO, SSS assimilation improves forecasts. The far right column compares ensemble means for assimilation of individual and combined SMOS, Aquarius, SMAP (Soil Moisture and Ocean Salinity, NASA Aquarius, Soil Moisture Active Passive) SSS forecasts. Finally, the latest forecasts are presented comparing assimilation versus no- assimilation of satellite SSS for single forecasts over the last year.