THE USE OF SIMULATED RADAR REFLECTIVITY FIELDS IN THE DIAGNOSIS OF MESOSCALE PHENOMENA FROM HIGH-RESOLUTION WRF MODEL FORECASTS

Composite radar reflectivity (the maximum reflectivity in the grid column) and single level radar reflectivity are becoming increasingly popular as a means for displaying forecast fields from high-resolution numerical weather prediction (NWP) models. Displays of composite equivalent radar reflectivity factor (hereafter, the “Reflectivity Product”) have been produced from the output of NWP models for several years by modelers at the Center for Analysis and Prediction of Storms (CAPS), the National Center for Atmospheric Research (NCAR), and by the Local Analysis and Prediction (LAPS) group at the Forecast Systems Laboratory (FSL). This past winter, simulated radar reflectivity fields were produced over the entire CONUS domain during the Developmental Testbed Center (Bernardet et al. 2005) Winter Forecast Experiment (DWFE), and made availabl e for experimental forecasting purposes to the Natio nal Weather Service (Koch et al. 2005). The fields were produced from 5-km Weather Research and Forecast ing (WRF) model forecasts made by the NCAR Advanced Research WRF (ARW) model and the NCEP Nonhydrostatic sMesoscale Model (NMM). This past spring, model refl ectivity fields from 2-km and 4-km versions of the A RW and a 4.5-km version of the WRF-NMM forecasts wer e utilized during the Storm Prediction Center - National Severe Storms Laboratory Spring Program (SPC/NSSL Spring Program; Kain et al. 2005). It has also recently become possible to compare the Reflectivity Product, as well as 1-km AGL reflectivity fields from models to high quality, three-dimensional, national radar reflectivity mosaic products on a 1-km Cartesian grid being developed at NSSL. The Reflectivity Product offers major advantages over traditional precipitation forecast displays, including the obvious fact that radar reflectivity is easier to verify in real time by direct comparison with readily available, observed composite reflectivity products. In addition, there are subtler benefits of this product that are relevant to understanding mesoscale processes. The chief advantage of the model Reflectivity Product is that it allows one to more easily see detailed mesoscale and storm-scale structures capable of being forecast by finer resolution NWP models. Examples demonstrating this advantage for a variety of mesoscale phenomena are presented in this paper. Before any meaning can be ascribed to the Reflectivity Product for the purpose of interpreting mesoscale model forecasts, it is important to understand how it is determined. The equivalent reflectivity factor is computed from the forecast mixing ratios of grid-resolved hydrometeor species, assuming Rayleigh sc ater i ngb yph l ofk w da nxp o til sz d rb u. Dg h WFE,p erc tib ldf s ah g uof thesi mu la d rcvy WRFm od elsf rw n t, aby gc ov er ag fl tiyb w~25dBZn hsNMc omp a re dt hAW.O n,fev rc o nt iwa h gdu SpP r og am, th NMp d ucni b ly w v s fmax iu refl c t vy op d h AW sn,w i thNMv alu sm do n~50 BZ.Wexplain how these differences are mostly attributable to the differences in model physics and postprocessing. It is important to note that it is not possible to make a strict comparison between composite reflectivity computed from a model grid point and that measured by scanning radar. Since the radar resolution degrades with distance from the transmitter, scanning radars cannot detect hydrometeors in the lower atmosphere due to the earth’s curvature effect, and numerous other considerations (ground clutter, anomalous propagation, bright bands…). Thus, any attempt to make direct comparisons between the model simulated reflectivity fields and radar measurements is replete with problems.