JP1.9
Deconstructing the Ensemble Transform Kalman Filter adaptive sampling methodology for tropical cyclones
Sharanya J. Majumdar, Univ. of Miami/RSMAS, Miami, FL
The Ensemble Transform Kalman Filter (ETKF) is one of the candidate methodologies that is being tested for adaptive sampling guidance in the environment of tropical cyclones in the Atlantic and Northwestern Pacific basins. To date, only the most basic guidance has been provided, and numerous outstanding issues remain. First, the ETKF is constrained by the estimation of the analysis error covariance matrix, which differs considerably from its operational counterpart. The sensitivity of the ETKF guidance to this estimation will be presented. Second, the ETKF is entirely dependent on the ensemble used. Extensions to a combined ensemble from NCEP, ECMWF and CMC, and their respective contributions to the covariance structure will be shown, together with the evolution of the dominant eigenmodes of the forecast error covariance matrix. Finally, the relative sensitivity to hypothetical observations of wind, temperature and relative humidity at different levels will be presented. Cases will be selected from the 2006 and 2007 seasons.
Joint Poster Session 1, Tropical Cyclones and Probability/Statistics Posters
Monday, 21 January 2008, 2:30 PM-4:00 PM, Exhibit Hall B
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