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
18
Embed
WSN05 6 Sep 2005 Toulouse, France Efficient Assimilation of Radar Data at High Resolution for Short-Range Numerical Weather Prediction Keith Brewster,
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
WSN05 6 Sep 2005Toulouse, 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 StormsUniversity of Oklahoma USA
WSN05 6 Sep 2005Toulouse, France
Radar Analysis & Assimilation Research Topics in CAPS
• 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 2005Toulouse, France
Remapping to x = 2 km
WSN05 6 Sep 2005Toulouse, 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
xyxRyxxxBxxx coTobTb JHHJ 11
2
1
2
1)(
22
2
1DJ cc
z
w
y
v
x
uD
WSN05 6 Sep 2005Toulouse, 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 2005Toulouse, France
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 2005Toulouse, France
1.5 h ForecastWind & Cloud Assim
00:30 UTCRadar Reflectivity
WSN05 6 Sep 2005Toulouse, France
1.5 h ForecastCloud Only Assim
1.5 h ForecastWind Only Assim
WSN05 6 Sep 2005Toulouse, France
00:30 UTC Radar Reflectivity
1.5 h Forecast Surface Vorticity
Wind & Cloud Assim
WSN05 6 Sep 2005Toulouse, France
1.5 h Forecast Surface Vorticity
Cloud Only Assim
1.5 h Forecast Surface VorticityWind Only Assim
WSN05 6 Sep 2005Toulouse, 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.