Saturday, 29 October 2005: 8:45 AM
Alvarado ABCD (Hotel Albuquerque at Old Town)
Feng Ding, RS Information System and NOAA/NWS, Silver Spring, MD; and D. H. Kitzmiller, D. Riley, K. Shrestha, F. Moreda, and D. J. Seo
Presentation PDF
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The Range Correction Algorithm (RCA) and its companion, the Convective Stratiform Separation Algorithm (CSSA), have been developed by the Office of Hydrologic Development (OHD), NOAA's National Weather Service (NWS). The algorithms mitigate range-dependent biases in radar precipitation estimates due to nonuniform vertical profiles of reflectivity, i.e., reduce overestimates from bright band effects and underestimates from overshooting at far ranges. The results from the field evaluation of RCA/CSSA, which was conducted by the OHD during the period of March-June 2004 using real-time data from multiple radar sites, have shown that the application of RCA and CSSA significantly improved rainfall estimates, in terms of agreement with rain gauge observations. The RCA will be a desirable estimation component even after the deployment of dual-polarization upgrades to the WSR 88D network. While dual-polarization algorithms can differentiate between snowflakes and raindrops, information on the reflectivity profile is still crucial to estimation of surface rainfall when the lowest radar beam detects only snow above the melting level.
This study investigates the effect of RCA/CSSA on hydrological modeling. The NWS Hydrology Laboratory Research Modeling System (HL-RMS) was applied to several river basins within the umbrella of the WSR 88D unit in State College, Pennsylvania. Radar precipitation input with and without range correction will be input to HL-RMS in order to simulate streamflow during the period October 2002 January 2003, a wet period with some major storm events. Initial results indicate that range correction improves the representation of spatial rainfall patterns within the radar umbrella. In terms of storm-total rainfall over several hours, range correction improved the correlation between radar and rain gauge estimates from 0.55 to 0.66 (30% reduction of variance improved to 44%). The HL-RMS simulation results, such as total river discharge over all basins, peak discharges, and timing of storm peaks, will be presented.
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