Examination of situation-dependent background error covariances at the convective scale in the context of the ensemble kalman filter

NCUIR > College of Earth Sciences > Department of Atmospheric Sciences > journal & Dissertation > Item 987654321/100038

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Title:	Examination of situation-dependent background error covariances at the convective scale in the context of the ensemble kalman filter
Authors:	鍾高陞;Chung, Kao-Shen;Chang, Weiguang;Fillion, Luc;Tanguay, Monique
Contributors:	地球科學學院大氣科學學系
Keywords:	Algorithms;Climatology;Correlation;Correlation analysis;Data assimilation;Dynamical systems;Dynamics;Earth, ocean, space;Errors;Exact sciences and technology;External geophysics;Kalman filters;Localization;Meteorology;Precipitation;Radar;Radar data;Structures;Studies;Weather;Weather forecasting;Wind
Date:	2013-10-08
Issue Date:	2026-04-21 13:46:10 (UTC+8)
Publisher:	American Meteorological Society;Boston, MA: American Meteorological Society
Abstract:	摘要： A high-resolution ensemble Kalman filter (HREnKF) system at the convective scale has been developed based on the Canadian Meteorological Center's operational global ensemble Kalman filter (EnKF) system. This study focuses on the very early stage of transition from purely homogeneous isotropic background error correlations to situation-dependent correlations. It has been found that forecast error structures can develop situation-dependent features in as little as 15 min. Furthermore, the dynamic and thermodynamic variables require different periods of time to build up their own forecast error structures. Differences in these structures between regions with and without precipitation are also investigated. An examination of temperature tendencies revealed that physical processes are as important as dynamical forcing in determining the structure of convective-scale errors structures, and that once physical processes become active, these structures change rapidly before the onset of precipitation. This study is intended to be the basis for a systematic exploration in the near future of the usefulness of the HREnKF system in assimilating high-density observations such as radar data. 出版者： Boston, MA: American Meteorological Society 出版日期： 2013-10-01 出處： Monthly weather review, 2013-10, Vol.141 (10), p.3369-3387 資源來源： EBSCOhost OmniFile Full Text Select 版權： 2014 INIST-CNRS 版權： Copyright American Meteorological Society Oct 2013 版權： Copyright American Meteorological Society 2013 識別號： ISSN: 0027-0644 識別號： EISSN: 1520-0493 識別號： DOI: 10.1175/MWR-D-12-00353.1 識別號： CODEN: MWREAB
Appears in Collections:	[Department of Atmospheric Sciences] journal & Dissertation

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