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Update on model developments: Meteo-France NWP models

Jean-Marcel Piriou Centre National de Recherches Météorologiques Groupe de Modélisation pour l’Assimilation et la Prévision. Update on model developments: Meteo-France NWP models. CLOUDNET Workshop / Paris 4-5 April 2005. Summary: Update on model developments

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Update on model developments: Meteo-France NWP models

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  1. Jean-Marcel Piriou Centre National de Recherches Météorologiques Groupe de Modélisation pour l’Assimilation et la Prévision Update on model developments: Meteo-France NWP models CLOUDNET Workshop / Paris 4-5 April 2005

  2. Summary: • Update on model developments • Work done: Validating models within CLOUDNET: BLH, surface fluxes • Ongoing work: comparing radar vs SYNOP cloudiness scores • Now available: Model output on the new sites • Perspectives: reading the CLOUDNET database in Toulouse

  3. Update on model developments

  4. Update on model developments • 2004-01 Sea ice masks from SSMI, relax towards NESDIS 0.5° SSTs, reduce snow evaporation rates, … • 2004-03 Use AQUA radiances in data assimilation, interactive mixing length, … • 2004-05 Cloudiness (more cirrus clouds, more cloudiness intermediate values), FMR radiation scheme (3h ARPEGE predictions, 1h assimilation) • 2004-10 Use AMSU-B data, Seawind Quickscat, …

  5. NWP GCM Climate GCM 25-70km operations Limited area ALADIN Mesoscale modelling 10km operations « Unifying » SGS physical schemes: • Radiation • Turbulence • SGS convection Cloud Resolving Model AROME Precipitating convective clouds explicitly taken into account 2.5km operations  2008 Global ARPEGE, stretched & regular grids

  6. Validating models within CLOUDNET

  7. Selection of dry or cloudy convective boundary layer Validating models within CLOUDNET: Anne Mathieu • Selection of days between April and August 2003 • Cabauw 95 days • Chilbolton 81days • SIRTA 75 days • Models : ARPEGE • IFS • Met-Office model : turbulent fluxes are not available • RACMO : results are strange – more test are needed • Comparisons between models and observations done on an hourly basis

  8. Frequency distributions of CLBH observed and diagnosed (LCL) Validating models within CLOUDNET: Anne Mathieu • Slightly better agreement than with the CLBH predicted • Essentially same flaws than the predicted CLBH.

  9. Conclusions Validating models within CLOUDNET: Anne Mathieu For selected days of cloudy convective boundary layer on the CLOUDNET stations • Boundary layer cloud base height predicted within more than 300m 40% of the hours for IFS 55% of the hours for ARPEGE. Same behavior in the different stations. ARPEGE : Under-estimation of the CLBH due to warm and humid biases at the surface • Essential condition to have a good prediction of dry and cloudy boundary layer diurnal cycle : right surface field prediction. • Soil scheme • Surface layer scheme • Precipitations (convection)

  10. Comparing radar vs SYNOP cloudiness scores

  11. Comparing radar vs SYNOP cloudiness scores • The ARPEGE (Météo-France global model) cloudiness scores against CLOUDNET radars improved, as the scores against SYNOP became less good • The validation team has made a more extensive comparison CLOUDNET radars vs SYNOP total cloudiness • How to compute a good model equivalent to the SYNOP total, low, medium and high cloudiness? • Validating cloudiness: more confident in radar/lidar validations than to SYNOP observations

  12. Model output on the new sites

  13. Model output on the new sites • Since 1st september 2002: sites Chibolton, Cabauw, Palaiseau • Since 16 March 2005: sites Lindenberg and Potenza, plus the 5 ARM sites: Darwin, Manaus, Nauru, North Slope of Alaska, Southern Great Plains (10 sites daily, cron) Work done by François Vinit.

  14. Perspectives • Reading in 2005 the CLOUDNET 10 sites database in Toulouse (François Vinit). • AROME (2.5km) model data

  15. Summary: • Update on model developments • Work done: Validating models within CLOUDNET: BLH, surface fluxes • Ongoing work: comparing radar vs SYNOP cloudiness scores • Now available: Model output on the new sites • Perspectives: reading the CLOUDNET database in Toulouse

  16. Global ARPEGE Aquaplanet mode SCM ARPEGE (EUROCS, GATE, TOGA,BOMEX, ARM, …) Global regular ARPEGE / 4DVAR-ass./ 66 km PHYSICS LAM ALADIN / coupled/ 10 km Global stretched ARPEGE / 4DVAR-ass./ 20 to 200 km

  17. Description of the large-scale cloud and precipitation scheme

  18. Cloud scheme • Developed by P. Lopez (QJRMS, 2002) • Designed for variational assimilation of cloud and RR obs • Prognostic var : Qc (cloud condensates) & Qp (precip water) • Semi-lagrangian treatment of the fall of precipitation (Lopez,2002)

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