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Keith Brewster, Ming Hu, Ming Xue and Jidong Gao Center for Analysis and Prediction of Storms

Efficient Assimilation of Radar Data at High Resolution for Short-Range Numerical Weather Prediction. Keith Brewster, Ming Hu, Ming Xue and Jidong Gao Center for Analysis and Prediction of Storms University of Oklahoma USA. Radar Analysis & Assimilation Research Topics in CAPS.

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Keith Brewster, Ming Hu, Ming Xue and Jidong Gao Center for Analysis and Prediction of Storms

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  1. Efficient Assimilation of Radar Data at High Resolution for Short-Range Numerical Weather Prediction Keith Brewster, Ming Hu, Ming Xue and Jidong Gao Center for Analysis and Prediction of Storms University of Oklahoma USA WSN05 6 Sep 2005 Toulouse, France

  2. Radar Analysis & Assimilation Research Topics in CAPS • Single-Doppler Velocity Retrieval (SDVR) • Bratseth-type Successive Correction Analysis (ADAS) • 3DVAR at Storm Scale • Cloud & hydrometeor analysis with latent heating adjustment • Phase/Position error correction methods • Ensemble-Kalman Filter at Storm Scale WSN05 6 Sep 2005 Toulouse, France

  3. Radar Analysis & Assimilation Research Topics in CAPS • Single-Doppler Velocity Retrieval (SDVR) • Bratseth-type Successive Correction Analysis (ADAS) • 3DVAR at Storm Scale • Cloud & hydrometeor analysis withlatent heating adjustment • Phase/Position error correction methods • Ensemble-Kalman Filter at Storm Scale WSN05 6 Sep 2005 Toulouse, France

  4. CAPS 3DVAR Radar Assimilation Flow Chart Radar 1 Radar 2 Radar 3 External Model Interpolator Radar QC &Remapper Radar 4 Radar N Aircraft Rawinsondes Multi-scale 3DVAR AIRS Soundings Mesonets WindProfilers METAR Cloud Analysis& Latent Heat Adjustment Sat IR SatelliteRemapper Sat Vis ARPS NWP Model WRF NWP Model ARPS-to-WRF WSN05 6 Sep 2005 Toulouse, France

  5. Radar Quality Control & Remapping • Quality Control • AP & Clutter detection • Doppler radial velocity unfolding • Remapping • Matches data spacing to model resolution • Eases reflectivity mosaicking • Can be viewed as a form of “superobbing” • Local least-squares interpolation/smoothing Quadratic in horizontal, Linear in vertical WSN05 6 Sep 2005 Toulouse, France

  6. Remapping to Dx = 2 km WSN05 6 Sep 2005 Toulouse, France

  7. CAPS 3DVAR System • General form • Rewritten in incremental form • Error correlation implemented by means of a recursive filter. • Can be applied in multi-grid fashion • Dynamic constraint: weak constraint: anelastic mass continuity WSN05 6 Sep 2005 Toulouse, France

  8. Radar Ingest- Reflectivity • Cloud analysis system • Remapped Satellite Images (Vis and IR) • Surface observations of cloud bases • Reflectivity converted to hydrometeorsRain, hail, dry snow, wet snow • Cloud water quantity and latent heating estimated using a lifted-parcel with entrainment WSN05 6 Sep 2005 Toulouse, France

  9. 3DVAR Applied to Fort Worth Tornadic Storm • Fort Worth, Texas area tornadoes of 28 Mar 2000 • 3-km ARPS Forecast 23 UTC-06 UTCnested in 9-km forecast 18 UTC – 06 UTC • Six 10-min analysis cycles (1 hour) using NEXRAD data 22 UTC-23 UTC. • Experiments: • Wind and Cloud Assimilated • Wind Alone • Cloud Alone Ming Hu et al. papers submitted to MWR WSN05 6 Sep 2005 Toulouse, France

  10. 00:30 UTCRadar Reflectivity 1.5 h ForecastWind & Cloud Assim WSN05 6 Sep 2005 Toulouse, France

  11. 1.5 h ForecastCloud Only Assim 1.5 h ForecastWind Only Assim WSN05 6 Sep 2005 Toulouse, France

  12. 00:30 UTC Radar Reflectivity 1.5 h Forecast Surface Vorticity Wind & Cloud Assim WSN05 6 Sep 2005 Toulouse, France

  13. 1.5 h Forecast Surface VorticityCloud Only Assim 1.5 h Forecast Surface Vorticity Wind Only Assim WSN05 6 Sep 2005 Toulouse, France

  14. Fort Worth Case Summary • Similar situation observed for second tornado about 15 min later. • Good forecast results for this case primarily due to cloud & diabatic portion of analysis. • Winds provide improvement to forecasted vorticity. • Applicable to on-going convection; other case studies show utility of radial wind assimilation in convection-initiation forecast situations. WSN05 6 Sep 2005 Toulouse, France

  15. 1-hour Forecast (1-hr Accum Precip)17-May-2004 01:00 WRFIC: Eta Interp WRFIC: ADAS w/Radar Radar Precip Obs WSN05 6 Sep 2005 Toulouse, France

  16. 2004 Real-time Use Summary • Spin-up at 4-km is largely eliminated using radar and satellite data. • Good results even with a static analysis-initialization. WSN05 6 Sep 2005 Toulouse, France

  17. Sample of Ongoing & Future Work with These Tools • Testing different lengths of assimilation cycle and total assimilation window length • Will also test using 3DVAR output in Incremental Analysis Updating • More real-time high-resolution test periodsin collaboration with SPC/NSSL • Smaller-domain real-time system run dailyhttp://www.caps.ou.edu/wx WSN05 6 Sep 2005 Toulouse, France

  18. Credits • CAPS Research Scientists • Ming Xue, Jidong Gao, Dan Weber, Kelvin Droegemeier • CAPS Model and Real Time System Support • Kevin Thomas and Yunheng Wang • CAPS Students • Ming Hu, Dan Dawson • WSN05 Conference Travel Support OU School of Meteorology WeatherNews Chair funds WSN05 6 Sep 2005 Toulouse, France

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