Weight interpolation for efficient data assimilation with the Local Ensemble Transform Kalman Filter

NCUIR > College of Earth Sciences > Department of Atmospheric Sciences and Graduate Institute of Atmospheric Physics > journal & Dissertation > Item 987654321/27338

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/27338

Title:	Weight interpolation for efficient data assimilation with the Local Ensemble Transform Kalman Filter
Authors:	Yang,SC;Kalnay,E;Hunt,B;Bowler,NE
Contributors:	大氣物理研究所
Keywords:	ATMOSPHERIC DATA ASSIMILATION;QUASI-GEOSTROPHIC MODEL;IMPLEMENTATION;SYSTEM
Date:	2009
Issue Date:	2010-06-29 18:36:29 (UTC+8)
Publisher:	中央大學
Abstract:	We have investigated a method to substantially reduce the analysis computations within the Local Ensemble Transform Kalman Filter (LETKF) framework. Instead of computing the LETKF analysis at every model grid point. we compute the analysis on a coarser grid and interpolate onto a high-resolution grid by interpolating the analysis weights of the ensemble forecast members derived from the LETKF. Because the weights vary on larger scales than the analysis increments. there is little degradation in the quality of the weight-interpolated analyses compared to the analyses derived with the high-resolution grid. The weight-interpolated analyses are more accurate than the ones derived by interpolating the analysis increments. Additional benefit from the weight-interpolation method includes improving the analysis accuracy in the data-void regions, where the standard LEKTF with the high-resolution grid gives no analysis corrections due to a lack of available observations. Copyright (C) Royal Meteorological Society and Crown Copyright, 2008
Relation:	QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY
Appears in Collections:	[Department of Atmospheric Sciences and Graduate Institute of Atmospheric Physics ] journal & Dissertation

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