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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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slide1

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
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 caps1
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

caps 3dvar radar assimilation flow chart
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

radar quality control remapping
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 d x 2 km
Remapping to Dx = 2 km

WSN05 6 Sep 2005

Toulouse, France

caps 3dvar system
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
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

3dvar applied to fort worth tornadic storm
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

00 30 utc radar reflectivity
00:30 UTCRadar Reflectivity

1.5 h ForecastWind & Cloud Assim

WSN05 6 Sep 2005

Toulouse, France

1 5 h forecast cloud only assim
1.5 h ForecastCloud Only Assim

1.5 h ForecastWind Only Assim

WSN05 6 Sep 2005

Toulouse, France

00 30 utc radar reflectivity1
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 VorticityCloud Only Assim

1.5 h Forecast Surface Vorticity

Wind Only Assim

WSN05 6 Sep 2005

Toulouse, France

fort worth case summary
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

slide15
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

2004 real time use summary
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
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

credits
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