SRNWP

Jean-Marie Bettems & Guy de Morsier, MeteoSwiss

SRNWP/EWGLAM meeting, OsloOctober 2004

Poster Session:

Numerical Weather Prediction

at MeteoSwiss

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SRNWP

Highest point: 3109m

The Alpine Model at MeteoSwiss - aLMo

Swiss implementation of COSMO model

non-hydrostatic, fully compressible

Prognostic variablespressure, 3 wind components, temperature, specific humidity, cloud water, cloud icesoon: turbulent kinetic energy,precipitation (snow, rain)

Mesh defined on the right panelhorizontal: regular, 7km mesh sizevertical: terrain following 45L,100m thickness up to 2000m,top at 25km

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SRNWPThe Alpine Model at MeteoSwiss - aLMo

Initial conditions from assimilation cycle based on nudging method

currently only in-situ observations used (synop, ship, buoy, temp, amdar)provision for GPS IWV and windprofiler

Lateral boundary conditions from IFS/ECMWF global model 3 hourly frames

In production since 20013-hourly intermittent assimilation cycle two 72h forecasts per day97% reliability (i.e. 2 problems/month)

Performance of a single 72h forecastRun on NEC SX5 at CSCS (Swiss National Supercomputing Center)28 Gflops sustained on 14 PUs (25% of peak), 60‘ elapsed time12GB main memory13GB output data

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SRNWPMotivation for higher resolutionForecast of local weather

7 km mesh

2.2 km mesh

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SRNWP

aLMo 7km, regional scale

Own assimilation cycle

2 daily 72h forecast

Planed aLMo/2 configuration (2005-7)Nested in ECMWF and aLMo/7

IFS/ECMWF, 25km, synoptic scale

4 daily updates

aLMo 2.2km, local scale

Own assimilation cycle

8 daily 18h forecast

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SRNWPPlaned aLMo/2 configuration (2005-7)Scientific developments

MeteoSwiss coordinates and participates in many scientific developments

Latent heat nudging with radar data (ETHZ, DFG)

Assimilation of GPS derived water vapor (swisstopo, ETHZ)

Snow analysis using Meteosat 8 (EUMETSAT, ETHZ)

Snow, lake temperature, vegetation analysis using NOAA satellites (Uni Bern)

Turbulence in planetary boundary layer (EPFL)

Dynamical downscaling of ECMWF EPS with the LM (COSMO, NCCR)