Impact of EnVar hybrid assimilation using EnKF ensembles

V. S. Prasad; C. J. Johny; Jagdeep Singh Sodhi; E. N. Rajagopal

doi:10.1117/12.2222771

3 May 2016 Impact of EnVar hybrid assimilation using EnKF ensembles

V. S. Prasad, C. J. Johny, Jagdeep Singh Sodhi, E. N. Rajagopal

Proceedings Volume 9882, Remote Sensing and Modeling of the Atmosphere, Oceans, and Interactions VI; 98820J (2016) https://doi.org/10.1117/12.2222771
Event: SPIE Asia-Pacific Remote Sensing, 2016, New Delhi, India

Abstract

Performance of an EnVar hybrid data assimilation system based on 3D Var NGFS (NCMRWF Global Forecast System) of T574 configuration and Ensemble Kalman Filter is investigated. The experiment is conducted during the Indian monsoon season (June-September) 2015 and compared against operational GSI 3D Var system. Two way coupled dual resolution hybrid system with 80 member ensemble of T254L64 configuration are used and forecasts are done for 10days. In hybrid experiment 75% weight is given to ensemble covariance and 25% for static covariance. The forecast skill of experiments over different spatial domains is compared against observations and respective analysis. The hybrid experiment produced significant improvement in forecasts compared to 3D Var in all fields except lower level temperature over tropical regions. Improvement is also seen in the prediction of extreme rainfall events. The prediction of monsoon onset and track of cyclone Ashobaa with hybrid and 3D var system is discussed.

Citation Download Citation

V. S. Prasad, C. J. Johny, Jagdeep Singh Sodhi, and E. N. Rajagopal "Impact of EnVar hybrid assimilation using EnKF ensembles", Proc. SPIE 9882, Remote Sensing and Modeling of the Atmosphere, Oceans, and Interactions VI, 98820J (3 May 2016); https://doi.org/10.1117/12.2222771

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