WSR-88D PRECIPITATION ESTIMATION FOR HYDROLOGIC APPLICATIONS DENNIS A. MILLER Enhancements to PPS Build 10 (Nov. 1998) Terrain Following Hybrid Scan Graphical Hybrid Scan Adaptable parameters appended to DPA Open Systems RPG Range Correction Mean Field Bias Correction Radar Precipitation Estimation Stage II and III Processing HDP 4 km res. Stage II WHFS/FFMPStage III WFO RFC Rain gages Stage II Processing for individual radars 4 km resolution on HRAP grid 131 x 131 array Stage II Mean field bias adjustment multisensor gage/radar merging gage only analysis Stage II processing Generally run once per hour at H+15 mins for each radar using hourly rainfall ending at H+00 min Updated every hour to incorporate late arriving gage data by (H+1:15,H+2:15 etc) Automated QC of HDP Data Removal of HRAP bin data that are consistently bad (e.g. Mountain blockage or ground clutter contamination) Removal of bin data contaminated by anomolous propagation (AP) though use of GOES IR satellite and surface temperature data Removal of outlier bin data (R > threshold) Mean Field Bias Adjustment Attempts to account for uniform errors over the entire field such as radar calibration, improper Z-R relationship Bias is a function of current and previous hours bias Memory span parameter indicates how many hours to look into the past when determining the current bias Mean Field Bias Adjustment Single Optimal Estimation Stage II Multisensor Rainfall Field Generation Stage II Stage III Mosaics Stage II multisensor rainfall estimates on to larger HRAP grid Interactive Quality Control Can be used as main input into hydrologic models through (MAPX) Stage III Mosaic In areas that where more than one radar overlaps forecaster has choice: mean value of overlapping bins maximum value of overlapping bins If multisensor field is not available for a given area, the gage only field is used Stage III interactive features Display geographic overlays Time Lapse Zoom Display and Edit Gages Add pseudo gages Delete AP Re-run Stage II and re-mosaic Important Adaptable Parameters Memory Span (1-1000) controls responsiveness of bias adjustment Indicator Cross Correlation Coefficient (0-1) controls how good radar verses gage is at indicating where it is raining Conditional Cross Correlation Coefficient (0-1) controls how good radar verses gage is at indicating amount of rainfall Case Study Site: ABRFC Study impact of varying adaptable parameters Vary ICC (0-1) Vary CCC(0-1) Compare with 24 hour co-op gages Compare forecast with observed hydrograph Raw unadjusted Radar Estimate Analysis of 24 hour co-op reports Bias Corrected Radar Multisensor WATTS RADAR ONLY WITH NO BIAS ADJUSTMENT WATTS GAGE ONLY WATTS RADAR ONLY WITH BIAS ADJUSTMENT WATTS MULTISENSOR ESTIMATE RFC-WIDE Multisensor Precipitation Estimation Mosaic of data from lowest available height Radar Climatology used to define blocked areas Optimal Estimation to fill missing areas using available gages and surrounding good radar data Satellite and Model Data to delineate clear air AP No radar data taken from above freezing level used PRISM data used to scale estimates in missing areas FCX frequency of rainfall FCX Coverage PBZ Total Rainfall Summer Months Summer Coverage PBZ Total Rainfall Winter Months Winter coverage HEIGHT OF COVERAGE RADAR COVERAGE MAP RADAR COVERAGE MAPPRECIPITATION MOSAIC BIAS ADJUSTMENT MULTISENSOR ESTIMATION FILLS MISSING AREAS HURRICANE FLOYD RAINFALL SUMMARY AND CONCLUSIONS