Impact of the Ensemble Kalman Filter Based Coupled Data Assimilation System on Seasonal Prediction of Indian Summer Monsoon Rainfall

The sensitivity of seasonal prediction (June to September) Indian monsoon initial state from two variants coupled data assimilation (CDA) products, viz. the Climate Forecast System (CFS) Reanalysis (CFSR) and Institute Tropical Meteorology, University Maryland- Weakly Coupled Analysis (IWCA) is explored in this study. IWCA implements local ensemble transform Kalman filter, incorporates theoretically advanced features flow-dependency ensemble-based analysis compared CFSR. CFS version-2 predictions using simulate large-scale features, convection centers well, improve skills CFSR predictions. enhanced quality Ocean-Atmospheric cross-domain equilibrium reduce shocks springtime Further, sustained consistency aided variability better improved study strongly advocates adaptation CDA methods for probable seamless