A Real-Time Convection-Allowing Ensemble Prediction System Initialized by Mesoscale Ensemble Kalman Filter Analyses
A Real-Time Convection-Allowing Ensemble Prediction System Initialized by Mesoscale Ensemble Kalman Filter Analyses
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DOI:
10.1175/waf-d-15-0013.1
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发表时间:
2015-10
影响因子:
2.9
通讯作者:
C. Schwartz;G. Romine;M. Weisman;R. Sobash;Kathryn R. Fossell;Kevin W. Manning;S. Trier
中科院分区:
文献类型:
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作者:
C. Schwartz;G. Romine;M. Weisman;R. Sobash;Kathryn R. Fossell;Kevin W. Manning;S. Trier
AbstractIn May and June 2013, the National Center for Atmospheric Research produced real-time 48-h convection-allowing ensemble forecasts at 3-km horizontal grid spacing using the Weather Research and Forecasting (WRF) Model in support of the Mesoscale Predictability Experiment field program. The ensemble forecasts were initialized twice daily at 0000 and 1200 UTC from analysis members of a continuously cycling, limited-area, mesoscale (15 km) ensemble Kalman filter (EnKF) data assimilation system and evaluated with a focus on precipitation and severe weather guidance. Deterministic WRF Model forecasts initialized from GFS analyses were also examined. Subjectively, the ensemble forecasts often produced areas of intense convection over regions where severe weather was observed. Objective statistics confirmed these subjective impressions and indicated that the ensemble was skillful at predicting precipitation and severe weather events. Forecasts initialized at 1200 UTC were more skillful regarding precipita...