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Proceedings Paper

Impact of EnVar hybrid assimilation using EnKF ensembles
Author(s): V. S. Prasad; C. J. Johny; Jagdeep Singh Sodhi; E. N. Rajagopal
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Paper 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.

Paper Details

Date Published: 3 May 2016
PDF: 10 pages
Proc. SPIE 9882, Remote Sensing and Modeling of the Atmosphere, Oceans, and Interactions VI, 98820J (3 May 2016); doi: 10.1117/12.2222771
Show Author Affiliations
V. S. Prasad, National Ctr. for Medium Range Weather Forecasting (India)
C. J. Johny, National Ctr. for Medium Range Weather Forecasting (India)
Jagdeep Singh Sodhi, Andhra Univ. (India)
E. N. Rajagopal, National Ctr. for Medium Range Weather Forecasting (India)


Published in SPIE Proceedings Vol. 9882:
Remote Sensing and Modeling of the Atmosphere, Oceans, and Interactions VI
Tiruvalam N. Krishnamurti; Madhavan Nair Rajeevan, Editor(s)

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