2.6    A Rapidly Relocatable High-Resolution WRF System for Military-  Defense, Aviation and Wind Energy

Deng, Aijun, David Stauffer, Brian Gaudet and Glenn Hunter, Penn State University, USA

To support time-sensitive, high-resolution modeling applications such as emergency response and aviation, Penn State has developed a rapidly-relocatable high-resolution forecast/nowcast system based on WRF.  Penn State has been using the system for many applications, all of which use the WRF multiscale FDDA capabilities developed and implemented by Penn State.  These applications include 1) the Defense Threat Reduction Agency (DTRA) relocatable on-demand forecast system (ROFS), currently used at DTRA to support the various applications related to hazard prediction and assessment; 2) the NEXGEN airport forecast system (NGAFS) that is initialized hourly using either the Rapid Update Cycle (RUC) or the Rapid Refresh (RR) with partial cycling of land surface fields, recently developed under NOAA sponsorship to improve high-resolution forecasts for airports, and also has potential to be used for wind energy forecasts; 3)  a WRF realtime forecast system that predicts the 4-D wind fields that was used to support the flight operation of the Penn State team that won first prize at the 2011 Green Flight Challenge competition; and 4) a time-lagged WRF-Chem realtime forecast/monitoring system used to support the CO2 monitoring study during the World Economic Forum Annual Meeting 2012 over Davos, Switzerland.

Some modeling results from these applications will be presented, with special focus on the results of the NGAFS that was evaluated with the historic snowstorm that occurred in 29 October 2011.  In this case a major snowstorm over the New York City area terminals disrupted air traffic, and the timing of the transition from rain to snow turned out to be a difficult problem that was not well predicted.  Short-term dynamical forecasts using NGAFS were created using nested domains with 9-km, 3-km and 1-km grid spacings over the New York City area terminals.  The system was configured to run a 3-h pre-forecast data assimilation followed by a 6-12 h forecast every hour, The WRF cold-start initial conditions and lateral boundary conditions were provided by the 13-km operational RUC data.   It was found that NGAFS was able to reasonably predict the timing of the transition from rain to snow over the airports, and the sensitivity experiments indicated that the assimilation of Meteorological Assimilation Data and Ingest System (MADIS) surface and Aircraft Communications Addressing and Reporting System (ACARS) data was particularly beneficial.