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Meso-NH model 40 users laboratories A research model, jointly developped by Meteo-France and Laboratoire d’Aérologie (CNRS/UPS)

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Presentation on theme: "Meso-NH model 40 users laboratories A research model, jointly developped by Meteo-France and Laboratoire d’Aérologie (CNRS/UPS)"— Presentation transcript:

1 Meso-NH model 40 users laboratories A research model, jointly developped by Meteo-France and Laboratoire d’Aérologie (CNRS/UPS)

2 Plan 1.General presentation of the model 2.Meso-scale simulations. 3.Large-Eddy simulations 4.Surface coupling 5.New couplings : Electricity, Hydrology, Dispersion 6.Climatology 7.Diagnostics

3 Space and time scales Méso-NH

4 The different meteorological model at Météo-France  Global Climate Model (GCM) (  x > 100 km) : ARPEGE Climat  NWP at synoptic scale : ARPEGE (  x=20-25km on France)  NWP at meso-  scale : ALADIN (  x=10km)  NWP at meso-  scale : AROME (2008) (  x=2.5km)  Research model for synoptic to meso-  scale : Méso-NH (  x=50km to 10m).

5 Why do we need a high resolution research model like Meso-NH ? 1.To improve parameterizations for Large Scale models : fine resolution simulations allow to resolve the main coherent patterns and inform on fine scale variability. 2.To help the evaluation and the improvement of NWP models like AROME 3.To better understand the physics (e.g. cloud processes), to characterize local effects 4.To carry out impact studies and use the model as a laboratory 5.To develop new couplings (e.g. Electricity, Hydrology …) A broad variety of developments and applications

6 A broad range of resolution from synoptic scales (Dx~10km), meso-scale (Dx~1km) to Large Eddy Simulation (Dx~10m) Real cases (from ECMWF, ARPEGE, ALADIN analyses or forecasts) Ideal cases  unrealistic cases - Academic cases (validation of the dynamics) - Basic studies (Diurnal cycle …) : Cloud Resolving Model (CRM) - To reproduce an observed reality (via forcings) (intercomparison : GCSS, EUROCS …) Simulations 3D, 2D, 1D From a simple to a sophisticated physics An accurate but quite expensive dynamics A set of diagnostics (budgets, profilers, trajectories …) Parallelized and vectorized A broad range of hardware system for the research community : FUJITSU, NEC, CRAY, IBM, cluster of PC  No operational objective. Meso-NH characteristics

7 The meso-scale simulations with Meso-NH : 1km<  x<10km Examples : - Flashfood event - Hail in orographic event - Cyclone - Sea breeze

8 Domaine 10-km ~ km Domaine 2.5-km Typical configuration for a real test study  A father model at 10km resolution with the deep convection scheme, the subgrid condensation scheme, the ICE3 microphysics and the 1D turbulence scheme  A son model at 2.5km resolution without deep convection scheme but with the shallow convection scheme, the ICE3 microphysics and the 1D turbulence scheme

9 Number of days with daily rain > 200 mm for the period [ ] on the South- East Massif Central Alpes Pyrénées 1 severe episode (+500 mm/24 h) 2002 As many other Western Mediterranean regions, Southern France is prone to devastating flash-floods during the fall season

10 Impact of the convective system on the triggering and the localization CTRL = With cooling associated to evaporation of precipitation NOC = Without cooling Cumulated precipitation during 4 hours Gard ‘02 CTRL = With Massif Central NOR = Without Massif Central Nuissier et Ducrocq, 2006 Cooling induced by evaporation of rain and orography forcing are 2 major factors inducing quasi-stationary convective systems

11 (Keil et Cardinali, 2003) 32km : 150x150 8km : 145x145 2km : 150x150 over 51 levels IOP8 (F<1) IOP2a (F>1) 8 km 2 km Monte Lema S Pol Ronsard ECMWF  32 km 3 Doppler radars ( ) Orographic precipitation 3D (MAP) How can dynamics modify the microphysics ? Lascaux et Richard, 2005

12 Snow Graupel Hail Cloud Rain Ice IOP2a IOP2a ( Strong convection) - Deep system (unblocked unstable case, high Fr=U/Nh) - Large amount of hail and graupel - Main process : Riming Mean vertical distribution of hydrometeors IOP8 ( Stratiform event) - Shallow system (blocked case, low Fr) -Large amount of snow - Main process : Vapor deposition on snow IOP8 Snow Lascaux et Richard, 2005 Orographic precipitation 3D (MAP)

13 Z > 60 dBz 12 km 100 km Tabary, 2002 (x) hail + graupel (o) hail ( ) rain (o) hail (x) hail + graupel ( ) rain graupel Simulation (Meso-NH) Orographic precipitation 3D (MAP) IOP2a Radar observations

14 Simulation of cyclone : case of Dina 7800 km,  x=36km 1944 km,  x=12km 720 km,  x=4km 3600 km Automatic method of Initialization : Filtering/Bogussing Barbary et al.

15 Vertical cross-sections at  x=4km K m/s K Horizontal wind S-N W-E Barbary et al.

16 Local effects : Sea breeze Δ = 250 m 250m of resolution 20km Temperature at Marseille, the 26th june 2001 at 15h Lemonsu et al 2005a

17 VAL OBS CNRS Puget Massif Marseille veyre City centre z = 400 m AGL VAL OBS CNRS m s -1 Puget Massif Marseille veyre City centre z = 50 m AGL West SSB South SSB South- East DSB Horizontal wind field 26 June 2001, 1400 UTC Lemonsu et al., 2005a Local effects : Sea breeze

18 6 m s June 2001, 1400 UTC B C D A TWL B C D A Model VDOL City center Distance (km) VDOL City center Altitude (km) ZS (m) Marseillev eyre 190 o Puget Massif CNRS (Radar) 3 km VAL (Lidar) OBS (Radar) Etoile Massif Comparison with transportable wind lidar (TWL) Lemonsu et al., 2005a

19 The Large Eddy Simulations with Meso-NH : Large eddys are resolved : TKE resolved >> TKE Subgrid Examples : - Stable BL - Convective BL - Impact of the pollution on the Stratocumulus diurnal cycle

20 AN OBSERVED LLJ DURING THE SABLES98 CAMPAIGN  Night: September m tower Duero river basin  x = 6 m,  y = 4 m,  z = 2m (0

21 Results (I): Mean profiles M.A. Jiménez Universitat de les Illes Balears The maximum of the wind and the height are well captured The LLJ height coincides with the inversion height The surface temperature obtained from the LES cools down much more than the observations

22 Lidar observations LES Simulations rv’rv’ LES simulation g/kg P3 aircraft KA aircraft.. max (pdf) _ min (pdf) LES qv’qv’ at 0.5z i Water vapor variability in convective BL : presence of dry tongues - Couvreux et al. (2005) at 12h  x=  y= 100m,  z<50m,  t=7h S(q v )<0

23 Impact of the pollution on the stratocumulus diurnal cycle = Aerosol indirect effect 0.7g/kg 700m r c (g/kg) Simulation LES 50m Nuage non pollué Sandu, I., TU  x=  y= 50m,  z=10m  =36h LWP (g/m²) Polluted : non precipitating Pristine : precipitating Evaporation of precipitation  Cooling  Limits the stratification at cloud base and the decoupling No precipitation  No Cooling  Maximum solar warming  decoupling


25 The SURFEX (SURface Externalized) land surface scheme see P.Le Moigne’s presentation

26 Sarrat et al.(2007a) Atmospheric CO 2 modelling : May – Boundary layer heterogeneity Zi = 900m Agricultural area : low sensible heat flux Zi = 1600m Forest : high sensible heat flux

27 Sarrat et al.(2007) Atmospheric CO 2 modelling : Models Intercomparison Winter crops Absorption of CO2 Forest Respiration

28 Simulation Brouillard lors de la campagne Paris-Fog (Tardif, 2008)  Eau liquide 1er niveau (00 TU) m2.25 km 9 km


30 Application : New couplings - Hydrology - Electricity - Pollutant dispersion

31  TOPMODEL (Beven and Kirkby, 1979) distributed hydrologic model with one model by basin : 9 basins ( km²)  Objectives : - Flow and rapide flood forecasts - Retroaction of the hydrology on the atmosphere - Available for AROME HYDROLOGY : Development of the coupling Meso-NH-ISBA-TOPMODEL CNRM/GMME/MICADO Crues des 5-9 septembre 2005 Débits simulés à St Martin d’Ardèche (~ 2500km 2 )

32 Barthe et al. [2005] Explicite electrical scheme in Meso-NH Local separation of charges Transfert and transport of charges Microphysical and dynamical processes Electric field Lightning parameterization Bidirectional leader (determinist) Vertical extension of the lightning Channel steps (probabiliste) Horizontal extension of the lightning Charge neutralization E > E trig yes no

33 Life cycle of electrical charges in a convective cell Barthe et Pinty, JGR Apparition of graupel Electrization of the cloud Apparition of electric field lightning Triggering of convection Simulation Méso-NH

34 30km,  x=500m Industrial accidental release : AZF Couche résiduelle : flux de S Couche de mélange : flux de SE Max=10% de concentration initiale 30km,  x=500m 10%=97  g/m 3 Max_obs=60  g/m 3 The heaviest particles have settled : strong dry deposition on Blagnac

35 SPRAY Lagrangian particle model At least particles released Advection+Turbulence+random Applied to the 2 Meso-NH grids  PERLE P E R L E  PERLE (Programme d’Evaluation des Rejets Locaux d’Effluents) Dispersion Meso-NH 2 grids (Regional  x=8km, L=240km/ Local  x=2km, L=60km) 36 levels until 16km ALADIN initialization and coupling Meso-scale meteorology Modelling system for environmental emergency

36 Climatologie. Régionalisation climatique

37 Roses Aladin 3 ansMéso-NH 95 datesMeasurements Wind climatology over the North Alps


39 Climat futur : 52 cas ARPEGE Climat / OPAMED8 : modèle couplé océan- atmosphère, rés. horizontale : ~50 km Simulations ARPEGE Climat / OPAMED 8 (climat présent climat futur ) Climat présent : 51 cas méthode d’identification des cas extrêmes pour sélectionner des situations représentatives CL 1CL 4CL 1CL 4 Sélection des cas les plus proches distance de corrélation spatiale Climat futur : 10 casClimat présent : 10 cas CL 1CL 4CL 1CL 4 CYPRIM : Régionalisation climatique des pluies intenses avec le modèle Meso-NH. A.-L. Beaulant

40 Simulations avec Meso-nh  Configuration en 2 domaines emboités (2-way grid-nesting) Domaine 1 de résolution horizontale ~ 10 km Domaine 2 de résolution horizontale ~ 2.5 km (centré sur l’évènement convectif)  Les simulations débutent à 12 UTC le jour J-1 et se terminent à 06 UTC le jour suivant J+1 (42 h) ARPEGE Climat / OPAMED8 ~ km Domaine 1 : Rh ~ 10 km Domaine 2 : Rh ~ 2.5 km MESO-NH  Les conditions initiales et aux limites sont fournies par les champs du modèle ARPEGE Climat / OPAMED8 (toutes les 6 heures) Rh ~ 50 km  La convection est paramétrée pour le domaine à 10 km (paramétrisation de Kain et Fritsch) tandis qu’elle est résolue explicitement pour le domaine à 2.5 km.

41 mm mm mm mm mm mm mm mm Cumuls de pluies sur les 24 1ères heures pour les 10 cas du climat futur 16 mm mm t0 à t UTC J-1 à 12 UTC J mm

42 Diagnostics

43 Chaboureau and Pinty (2005) : Use of radiative transfer RTTOV to MSG  x=30 km Amélioration des enclumes (cirrus) sur le seuil d’auto-conversion

44 Réflectivités observées Réflectivités simulées avec Méso-NH (radar de Bollène le 8 sep à 21 UTC, élévation=1,2°) « Développement communautaire d’un opérateur-simulateur d’observation radar » (Caumont O., V. Ducrocq, G. Delrieu, M. Gosset, J. Parent du Châtelet, J.-P. Pinty, H. Andrieu, Y. Lemaître et G. Scialom, 2006 : A radar simulator for high-resolution nonhydrostatic models. J. Atmos. Oceanic Technol.) Simulation de réflectivités radar

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