667 High Resolution Observing System Experiments in the Dallas Fort Worth Testbed with 3DVAR Analyses and WRF Forecasts

Tuesday, 24 January 2017
4E (Washington State Convention Center )
Andrew P. Osborne, University of Oklahoma, Norman, OK; and F. H. Carr and K. A. Brewster

The urban weather testbed in the Dallas Fort Worth (DFW) metropolitan area is a multi-faceted project including collaborations from local governments, universities, and private companies.  A 2009 National Research Council (NRC) paper recommended an integrated “network of networks” approach to improve the capabilities of the U.S. mesoscale observing system.  The report suggested that testbeds should be established to show the benefits of this type of collaborative observing network approach.  This work focuses on the impact of non-conventional observation types on high-resolution model analyses and forecasts in one such testbed in the Dallas Fort Worth area. 

     The Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) has established a network of eight X-band radars in the DFW testbed to provide enhanced radar coverage, especially in the lowest levels of the atmosphere. A major part of this research evaluates the impact of assimilating this CASA radar data via several observing system experiments. Data denial experiments are run for a tornadic supercell case on December 26, 2015, with the Advanced Regional Prediction System (ARPS) three-dimensional variational (3DVAR) data assimilation system with cloud and hydrometeor analysis used to produce cycled analyses and the Advanced Research Version of the Weather Research and Forecasting (WRF) model used to perform the simulations. Besides the CASA radar network, the impact of radial velocity and reflectivity data from other radars in the area such as the Terminal Doppler Weather Radars (TDWRs) and Weather Surveillance Radar-1988 Doppler radars (WSR-88Ds) are examined along with several non-conventional surface station types including Citizen Weather Observing Program (CWOP), AWS Weatherbug, and Understory Weather data.  Impact is examined via qualitative analysis of storm location, timing, and structure as well as quantitative verification of vortex placement and the accuracy of different forecasted fields, including quantitative precipitation forecast (QPF) values and surface weather variables.

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