On the Impact of Super Resolution WSR-88D Doppler Radar Data Assimilation on High Resolution Numerical Model ForecastsSteven R. ChiswellJanuary 13, 200913 IOAS-AOLS 7B.2

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Research FocusAs the increase in computational power and availability has made higher resolution real-time model simulations possible, the need to obtain non-standard observations to both initialize numerical models and verify their output has become increasingly important. Assimilation of radar velocity and precipitation fields into high-resolution model simulations can improve precipitation forecasts with decreased "spin-up" time and improve short-term simulation of boundary layer winds with application to:Simulating the regional atmospheric transport of airborne contaminant plumes.Improving weather forecasts for response to severe weather events, wildfire management and effective utilization of resources for conducting critical outdoor work.

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Doppler Radar Assimilation NWS upgrade of existing NEXRAD Doppler radars during 2008 from 1 km x 1.0 degree to 0.25 km x 0.5 degree data resolution yields 13.5 million data points per elevation angle at 4-5 minute frequency.

0.25 km Resolution1.0 km ResolutionLegacy ResolutionSuper Resolution

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Radar Assimilation MethodRadar measurements:ReflectivityRadial Velocity

QC processanomalous propagationfalse echoesrange foldingcalculate error thresholdstransform coordinate space

Model constraints:rainfall & cloud waterdiabatic heating vertical & horizontal velocityColumbia, SC Radar Reflectivity

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Application of Radar Assimilation Case Study 0000 UTC, August 4, 2008Columbia, SC radar KCAE located 91 km NNE of SRS upgraded to super resolution July 23, 2008.Afternoon-evening thunderstorms passing through SRS at 0000 UTC August 4, 2008 model initialization time.Maximum wind gusts recorded at SRS towers- 19 mph at 4 m, 37mph at 61m.Cold pool created by thunderstorm outflow NE of SRS analyzed in 12km NAM initialization. Model runs using Weather Research and Forecasting (WRF) model with 2.5 km and 0.5 km grids with WRF-3DVAR assimilation.

SRSWRF model domain 00-06 UTCAugust 4, 2008Flow field & cloud water concentration

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August 4, 2008 0000Z Surface AnalysisWeak cold front becoming stationary CAPE values from 3250-4000 J/KgModerate vertical shear capable of producing strong wind gustsSurface temperature low 90s, dewpoint Mid 70s.

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0000 UTC, August 4, 2008

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0000 UTC, August 4, 2008

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0000 UTC, August 4, 2008NCEP operational model analysis resolves cold pool and complex wind field structure where surface observations are availableFew NWS reporting stations available in vicinity of SRSRadar data adds valuable input to model especially where other data is limited

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Standard Deviation of Reflectivity Field1.0 km0.25 km

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Model Forecast ComparisonRadarCold pool dominates in WRF base run driving convection SE.Radar assimilation provides needed information in vicinity of SRS filling observational data void.Base

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Base 00:45Radar 00:45Model Spin-up ComparisonBase 01:15Radar 01:15

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Model Verification

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HYSPLIT Plume Comparison for Hypothetical Simulation BaseRadar

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Model run comparison4 km1.33 km

0.55 km

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ConclusionsThe spin-up time for precipitation was observed to be less with radar data assimilation. The lack of standard observational data in many areas poses an important data void where radar observations can provide significant input for both model forecasts as well as verification analysis. Increased radar data resolution provides additional storm structure resolution while decreasing the root mean squared variance.Refined turbulence fields give added definition to regional transport conditions.0100Z WRF forecast with radar assimilation