Radar data assimilation in the Canadian high-resolution ensemble Kalman filter system: Performance and verification with real summer cases

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Title:	Radar data assimilation in the Canadian high-resolution ensemble Kalman filter system: Performance and verification with real summer cases
Authors:	鍾高陞;Chang, Weiguang;Chung, Kao-Shen;Fillion, Luc;Baek, Seung-Jong
Contributors:	地球科學學院大氣科學學系
Keywords:	Algorithms;Assimilation;Background checks;Climatology;Convergence;Cross correlation;Data assimilation;Data collection;Experiments;High resolution;Humidity;Kalman filters;Localization;Meteorology;Precipitation;Radar;Radar data;Radar reflectivity;Reflectance;Squalls;Storms;Studies;Summer;Variables;Velocity;Weather
Date:	2014-01-01
Issue Date:	2026-04-21 13:53:26 (UTC+8)
Publisher:	American Meteorological Society;Washington: American Meteorological Society
Abstract:	摘要： An 80-member high-resolution ensemble Kalman filter (HREnKF) is implemented for assimilating radar observations with the Canadian Meteorological Center’s (CMC’s) Global Environmental Multiscale Limited-Area Model (GEM-LAM). This system covers the Montréal, Canada, region and assimilates radar data from the McGill Radar Observatory with 4-km data thinning. The GEM-LAM operates in fully nonhydrostatic mode with 58 hybrid vertical levels and 1-km horizontal grid spacing. As a first step toward full radar data assimilation, only radial velocities are directly assimilated in this study. The HREnKF is applied on three 2011 summer cases having different precipitation structures: squall-line structure, isolated small-scale structures, and widespread stratiform precipitation. The short-term (<2 h) accuracy of the HREnKF analyses and forecasts is examined. In HREnKF, the ensemble spread is sufficient to cover the estimated error from innovations and lead to filter convergence. It results in part from a realistic initiation of HREnKF data assimilation cycle by using a Canadian regional EnKF system (itself coupled to a global EnKF) working at meso- and synoptic scales. The filter convergence is confirmed by the HREnKF background fields gradually approaching to radar observations as the assimilation cycling proceeds. At each analysis step, it is clearly shown that unobserved variables are significantly modified through HREnKF cross correlation of errors from the ensemble. Radar reflectivity observations are used to verify the improvements in analyses and short-term forecasts achievable by assimilating only radial velocities. Further developments of the analysis system are discussed. 出版者： Washington: American Meteorological Society 出版日期： 2014-06-01 出處： Monthly weather review, 2014-06, Vol.142 (6), p.2118-2138 資源來源： EBSCOhost OmniFile Full Text Select 版權： Copyright American Meteorological Society Jun 2014 版權： Copyright American Meteorological Society 2014 識別號： ISSN: 0027-0644 識別號： EISSN: 1520-0493 識別號： DOI: 10.1175/MWR-D-13-00291.1 識別號： CODEN: MWREAB
Appears in Collections:	[Department of Atmospheric Sciences] journal & Dissertation

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