Abstract

In collaboration with the Army Test and Evaluation Command (ATEC), NCAR has developed a Real-Time Four Dimensional Data Assimilation and forecasting (RTFDDA) system. The RTFDDA system is built around the Penn State/NCAR Mesoscale Model version 5 (MM5) and the Weather Research and Forecasting mode... Show moreIn collaboration with the Army Test and Evaluation Command (ATEC), NCAR has developed a Real-Time Four Dimensional Data Assimilation and forecasting (RTFDDA) system. The RTFDDA system is built around the Penn State/NCAR Mesoscale Model version 5 (MM5) and the Weather Research and Forecasting model (WRF). RTFDDA is capable of continuously collecting and ingesting diverse synoptic and asynoptic weather observations from conventional and unconventional platforms, and provides accurate spun-up nowcasts and short-term forecasts. Operational RTFDDA systems have been implemented at seven ATEC test ranges in the last six years, providing rapidly updated, multi-scale weather analyses and forecasts, for the synoptic scale down to the mesogamma-scale, with the fine-mesh domain having 1 - 3 km grid increments, depending on the range. Among these modeling systems is one deployed at the Army Cold Regions Test Center, Alaska. The CRTC RTFDDA system began operation in 2002. Since then, the system has experienced many updates and enhancements which include improvements in the data-assimilation scheme and model physics parameterizations, the transition from MM5 to WRF, the inclusion of special observations from the test range, and the use of MODIS cloud-drift winds and other new data. Recently, the RTFDDA system has been expanded for generating ensemble analyses and probabilistic forecasts (E-RTFDDA). E-RTFDDA is currently available to be run "on-demand", i.e., for supporting special test events and case studies. In this paper, we'll briefly describe the RTFDDA modeling system, and the performance of the model operational forecasts for CRTC. A case study of a winter cold-air surge event over the CRTC region, from January 22 through 27, 2007, will be described to illustrate the ability of the RTFDDA and E-RTFDDA models, and also the challenges for future study. Finally, we will show that both RTFDDA and E-RTFDDA are globally relocatable, and thus can be easily adapted to support other weather-sensitive applications in different areas of Alaska. Show less