Initial Results of a Mesoscale Short-Range Ensemble Forecasting System over the Pacific Northwest

Abstract
Motivated by the promising results of global-scale ensemble forecasting, a number of groups have attempted mesoscale, short-range ensemble forecasting (SREF), focusing mainly over the eastern half of the United States. To evaluate the performance of mesoscale SREF over the Pacific Northwest and to test the value of using different initial analyses as a means of ensemble forecast generation, a five-member mesoscale SREF system was constructed in which the Pennsylvania State University–National Center for Atmospheric Research fifth-generation Mesoscale Model (MM5) was run with initializations and forecast boundary conditions from major operational centers. The ensemble system was evaluated over the Pacific Northwest from January to June 2000. The model verification presented in this study considers only near-surface weather variables, especially the observed 10-m wind direction. The ensemble mean forecast displays lower mean absolute wind direction errors than the component ensemble members when av... Abstract Motivated by the promising results of global-scale ensemble forecasting, a number of groups have attempted mesoscale, short-range ensemble forecasting (SREF), focusing mainly over the eastern half of the United States. To evaluate the performance of mesoscale SREF over the Pacific Northwest and to test the value of using different initial analyses as a means of ensemble forecast generation, a five-member mesoscale SREF system was constructed in which the Pennsylvania State University–National Center for Atmospheric Research fifth-generation Mesoscale Model (MM5) was run with initializations and forecast boundary conditions from major operational centers. The ensemble system was evaluated over the Pacific Northwest from January to June 2000. The model verification presented in this study considers only near-surface weather variables, especially the observed 10-m wind direction. The ensemble mean forecast displays lower mean absolute wind direction errors than the component ensemble members when av...