Radar in aLMo

Assimilation of Radar Information in the Alpine Model of MeteoSwiss

Daniel Leuenberger and Andrea RossaMeteoSwiss

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Radar in aLMoIntroductionRadar information is gaining importance in mesoscale data assimilationLatent Heat Nudging (LHN): Assimilation method for precipitation informationTrigger model precipitation where radar detects precipitation (heating), supress it elsewhere (cooling)4DDA, yet computationally very efficientConceptionally simpleAssimilation of non-prognostic variables not straight forwardHeuristic approach of weighting observations and model

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Radar in aLMoRadar ObservationsSwiss radar network: 3 C-Band Doppler RadarsBest estimate of surface rain: preprocessed (e.g. clutter reduction, vertical profile corrections)Resolution: 2 x 2 km2, 5 min

Radar Quality Map

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Radar in aLMoReal Case StudyCase

System of severe convection over SwitzerlandTriggered around 22h30 UTC over the Massif CentralDevelopment ahead of weak cold frontModerately unstable environment as observed by the Swiss radiosonde Payerne at 00UTC (CAPE ~250 J/kg)Strong wind shear (~ 30 m/s at 6000m)

SimulationsOperational Alpine Model (aLMo) of MeteoSwiss (x=7km)Convection ParametrizationStarted 21.8.00 00 UTC from GME of DWDCTRL (no forcing)LHN during 6hLHN+ during 3h, free forecast afterwards

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Radar in aLMo

010203040506

CTRL LHN Radar

Case Study of the 21.8.2000 StormHourly Sums of Precipitation: Forcing during 6h

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Radar in aLMo

01020304

1h Free Forecast

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2h Free Forecast

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3h Free Forecast

Case Study of the 21.8.2000 StormHourly Sums of Precipitation: Forcing during 3h

CTRL LHN+ Radar

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Radar in aLMoFindings IModel is able to assimilate radar observationsGood impact in analysis, sfc winds in line with observationsSome impact in free forecast up to 03hModel loses information quickly, i.e. storm dies too earlyWhy is the model not able to maintain storm?

Environment not representative?Model resolution ?

Try to find reasons by means of idealized simulations

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Radar in aLMoIdealized SimulationsSetup

Environment from Payerne sounding of 21.8.00 00UTCFine mesh (x = 1km), no CPS, no soil model, no radiationTrigger convection with warm bubble: No storm development

wind shearPayerne profile

KW profile

Payerne sounding

KW sounding

Klemp Wilhelmson EnvironmentLarge amount of CAPE (~ 1200 J/kg)Moderate wind shearFavorable for splitting supercell storms

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Radar in aLMoOSSE SetupReference run

Convection initiated with warm bubbleModel sfc rain serves as „artificial radar observations“

LHN AnalysisSame environment as reference runNo warm bubble initiationLHN during 3h (artificial rain rates from reference run)

LHN ForecastLHN during first 30, 60 min Free run afterwards

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Radar in aLMoInsertion Frequency of Precipitation Input

LHN linearly interpolates between subsequent observationsExamine relevance of insertion frequency t to LHN Analysis

t = 10minlinear interpolation

t = 1min

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Radar in aLMoLHN Analysis (LHN during 3h)

“OBS“ t = 10min

t = 4mint = 1min

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Radar in aLMoDomain Sum of LH Nudging Increment

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Radar in aLMoLHN Forecast (t = 1min)

“OBS“

Free forecast after 30 min

Analysis (LHN during 3h)

Free forecast after 1h

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Radar in aLMoSensitivity to Horizontal Grid Spacing

Analysis (LHN during 3h)Free forecast after 1h

x = 2km

x = 5km

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Radar in aLMoFindings IILHN capable of analysing and initiating supercell stormGood temporal sampling of the observed phenomena is importantRepresentative large-/mesoscale environment importantEven a poorly resolved forcing is able to initiate and maintain storm evolution in appropriate environmentSupercell storm very stable dynamics: are findings ‚portable‘ to other situations?

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Radar in aLMoOutlookReal-case study

Reduction of grid-size to 2kmStudy impact of errors in radar dataMore cases

Idealized OSSESensitivity of vertical forcing distributionAssimilation of model 3D latent heating fieldsAssimilation of horizontal windsConsider case which is less driven by dynamics

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Radar in aLMo

Thank you for your attention !