WSN05 6 Sep 2005 Toulouse, France Efficient Assimilation of Radar Data at High Resolution for Short-Range Numerical Weather Prediction Keith Brewster,

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Presentation transcript:

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

WSN05 6 Sep 2005 Toulouse, France 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 Remapping to  x = 2 km

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

WSN05 6 Sep 2005 Toulouse, France 3DVAR Applied to Fort Worth Tornadic Storm Fort Worth, Texas area tornadoes of 28 Mar km ARPS Forecast 23 UTC-06 UTC nested 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 1.5 h Forecast Wind & Cloud Assim 00:30 UTC Radar Reflectivity

WSN05 6 Sep 2005 Toulouse, France 1.5 h Forecast Cloud Only Assim 1.5 h Forecast Wind Only Assim

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

WSN05 6 Sep 2005 Toulouse, France 1.5 h Forecast Surface Vorticity Cloud Only Assim 1.5 h Forecast Surface Vorticity Wind Only Assim

WSN05 6 Sep 2005 Toulouse, France 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 1-hour Forecast (1-hr Accum Precip)17-May :00 Radar Precip Obs WRF IC: Eta Interp WRF IC: ADAS w/Radar

WSN05 6 Sep 2005 Toulouse, France 6-hr forecast (1-hr Accum Precip)17-May :00 Radar WRF IC: Eta Interp WRF IC: ADAS w/Radar Radar Precip Obs

WSN05 6 Sep 2005 Toulouse, France 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 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 periods in collaboration with SPC/NSSL Smaller-domain real-time system run daily

WSN05 6 Sep 2005 Toulouse, France 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