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Meso-NH model 30 users laboratories A research model, jointly developped by Meteo-France and Laboratoire d’Aérologie.

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Presentation on theme: "Meso-NH model 30 users laboratories A research model, jointly developped by Meteo-France and Laboratoire d’Aérologie."— Presentation transcript:

1 Meso-NH model 30 users laboratories http://www.aero.obs-mip.fr/mesonh A research model, jointly developped by Meteo-France and Laboratoire d’Aérologie (CNRS/UPS)

2 Examples of Applications of Meso-NH General description of Meso-NH, Grid nestingGeneral description of Meso-NH, Grid nesting Clouds representation (explicit) : convective events, Sc, Fog, cyclonesClouds representation (explicit) : convective events, Sc, Fog, cyclones DiagnosticsDiagnostics Coupling with the surface Coupling with the surface Coupling with other models (hydrology, dispersion) Coupling with other models (hydrology, dispersion) ClimatologyClimatology The physics of Meso-NH in AROMEThe physics of Meso-NH in AROME Ways of improvements of Meso-NH Ways of improvements of Meso-NH

3 General description of Meso-NH Anelastic equations with the pseudo-incompressible system of Durran Vertical coordinate following the terrain : (Gal Chen and Sommerville, 1975) Temporal discretization : Purely explicit leap-frog scheme Advection scheme : 2nd order and 4th order eulerian schemes Spatial discretization : Arakawa C grid Grid nesting : One-way/Two-way Initial fields and LBC (radiative open) from ECMWF/ARPEGE/ALADIN. Turbulence : 1.5 order closure Cuxart-Bougeault-Redelsperger (2000) Convection : Kain-Fritsch (1993) revised by Bechtold et al. (2001) Microphysical scheme : Bulk schemes at 1-moment or 2-moments. Up to 7 prognostic species: vapor (r v ), cloud (r c ), rain (r r ), pristine ice (r i ), snow (r s ), graupel (r g ), hail (r h ) Radiation : ECMWF package Chemical on-line scheme : Gazeous and aerosols (Presentation C.Mari, Thursday) Externalized surface model (Presentation P.Le Moigne, this afternoon) DYNAMICS PHYSICS

4 Types of simulations A broad range of resolution from synoptic scales (  x~10km) to meso-scale (  x~1km) to Large Eddy Simulation (  x~10m) Real cases (from ECMWF, ARPEGE, ALADIN analyses or forecasts)Real cases (from ECMWF, ARPEGE, ALADIN analyses or forecasts) Ideal cases  unrealistic casesIdeal 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

5 Grid nesting technics At every time step : The Coarse Model (CM) gives the lateral boundary conditions to Fine Model (FM) by interpolation One-way : the FM doesn’t influence the CM Two-way : CM fields are relaxed to the average of FM fields (all variables except TKE) A single constraint : an integer ratio between the resolutions and the time steps Same vertical grids.

6 Vaison-la-Romaine : 22 september 1992 3 nested grids : 40/10/2.5km Instantaneous precipitations 2.5km One-wayTwo-way Stein et al., 2000

7 Cumulated precipitations for 9h (Obs=300mm in 6h) One-wayTwo-way Stein et al., 2000 2.5 km 10km Vaison-la-Romaine : 22 september 1992

8 Examples of Applications of Meso-NH General description of Meso-NH, Grid nestingGeneral description of Meso-NH, Grid nesting Clouds representation (explicit) : convective events, Sc, Fog, cyclones, electricityClouds representation (explicit) : convective events, Sc, Fog, cyclones, electricity DiagnosticsDiagnostics Coupling with the surface Coupling with the surface Coupling with other models (hydrology, dispersion) Coupling with other models (hydrology, dispersion) ClimatologyClimatology The physics of Meso-NH in AROMEThe physics of Meso-NH in AROME Ways of improvements of Meso-NH Ways of improvements of Meso-NH

9 0°C Autoconversion 0°C Riming Aggregation Collection Deposition Freezing Nucleation Sedimentation Ice crystals Snowflakes Graupel Hail Cloud droplets Raindrops Mixed phase cloud representation with a bulk scheme

10 MESO-NH Explicit microphysical scheme :

11 Lafore Moncrieff 89 Stratiform Density Current Convective H D A tropical squall line (P.Jabouille) : Idealized simulation according to a real case (COPT81) U W 

12 Cloud dropletsRain drops Pristine iceGraupel Snow Jabouille. Caniaux et al., 1994

13 (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

14 Snow Graupel Hail Cloud Rain Ice IOP2a IOP2a ( Strong convection) - Deep system (unblocked unstable case, low Fr) - Large amount of hail and graupel Mean vertical distribution of hydrometeors IOP8 ( Stratiform event) - Shallow system (blocked case, high Fr) - Large amount of snow IOP8 Snow Lascaux et Richard, 2005 Orographic precipitation 3D (MAP) Budgets  Predominant microphysical processes

15 Impact de la convection sur la stationnarité d’un système Ctrl Noc 4h-accumulated rainfall 18-22 UTC on 8 Sept. 2002 Noc = without evaparative cooling Ctrl = with evaporative cooling Cev. ‘95 Gard ‘02 Aude ‘99 1D-  budget over the MCS (convective + stratiform). Nuissier et Ducrocq, 2006 Strong convective events on SE of FRANCE How can mycrophysics modify the dynamics ?

16 max : 135 mm max : 25 mm m mm Quasi-stationnary MCS 13-14 Oct. 1995 Cumulated precipitation 01 UTC to 06 UTC the 14 th Oct. 1995 MESO-NH,  x=10km max: 31 mm MESO-NH,  x=2.5kmOBSERVATIONS (Ducrocq et al, 2002) Initial conditions: ARPEGE analysis at 18UTC m MESO-NH,  x=2.5km Initialisation Ducrocq et al (2000)’s max : 99 mm

17 Stratocumulus : Capped BL When the CBL is blocked by an anticyclonic subsidence FIRE 1 case of EUROCS : Forcing terms : a LS subsidence + cooling (d  l /dt 0) under the inversion to balance the subsidence altitude (m) Cloud water mixing ratio (kg/kg) Min = 0.025 g/kg Max = 0.6 g/kg 0h12h0h12h0h LES simulation of the diurnal cycle (  x=50m) Observations of the base and the top cloud layer Sandu et al., 2006

18 rc  FOG – 1D simulation – Temporal evolution on 18h from 18TU Without cloud droplet sedimentation rr rcrr  With cloud droplet sedimentation

19 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.

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

21 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

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

23 Examples of Applications of Meso-NH General description of Meso-NH, Grid nestingGeneral description of Meso-NH, Grid nesting Clouds representation (explicit) : convective events, Sc, Fog, cyclonesClouds representation (explicit) : convective events, Sc, Fog, cyclones DiagnosticsDiagnostics Coupling with the surface Coupling with the surface Coupling with other models (hydrology, dispersion) Coupling with other models (hydrology, dispersion) ClimatologyClimatology The physics of Meso-NH in AROMEThe physics of Meso-NH in AROME Ways of improvements of Meso-NH Ways of improvements of Meso-NH

24 Diagnostics Budget (heat, momentum, microphysics species, TKE) with masksBudget (heat, momentum, microphysics species, TKE) with masks Diagnostic fields (radar fields, comparison with airborne or ground observations)Diagnostic fields (radar fields, comparison with airborne or ground observations) Lagrangian trajectories (3 added prognostic fields)Lagrangian trajectories (3 added prognostic fields) Passive tracersPassive tracers Tools for comparison to observations (Meso-NH tools : Presentation of I.Mallet, Wednesday 2 pm)Tools for comparison to observations (Meso-NH tools : Presentation of I.Mallet, Wednesday 2 pm) http://www.aero.obs-mip.fr/mesonh/doc.html/#lagrangian

25 Chaboureau and Pinty (2005) : Use of radiative transfer RTTOV to MSG  x=30 km

26 Observed reflectivity Simulated reflectivity (radar de Bollène le 8 sep. 2002 à 21 UTC, élévation=1,2°) Caumont, 2006 Radar reflectivity

27 Examples of Applications of Meso-NH General description of Meso-NH, Grid nestingGeneral description of Meso-NH, Grid nesting Clouds representation (explicit) : convective events, Sc, Fog, cyclonesClouds representation (explicit) : convective events, Sc, Fog, cyclones DiagnosticsDiagnostics Coupling with the surface Coupling with the surface Coupling with other models (hydrology, dispersion) Coupling with other models (hydrology, dispersion) ClimatologyClimatology The physics of Meso-NH in AROMEThe physics of Meso-NH in AROME Ways of improvements of Meso-NH Ways of improvements of Meso-NH

28 Lake Town Sea Nature Méso-NH AROME Arpège / Aladin SURFACE EXTERNALIZED SURFACE : Exchange of data flow at each time step between the 2 models Atmosphere forcing Sun position Radiative fluxes albedo emissivity radiative temperature fluxes : Momentum, heat, water vapor, CO2, chemistry Boundary conditions for turbulence and radiative schemes Presentation of P.Le Moigne

29 OZONE le 25 Juin 2001 9 UTC 9km 3km <30ppb Parc Naturel VerdonMarseille 85ppb MarseilleParc Naturel Verdon >90ppb 15 UTC >90ppb Cousin et Tulet, 2004

30 Atmospheric CO 2 modelling : the Meso-NH model Online coupling with the surface scheme ISBA-A-gs :   CO 2 surface fluxes : - assimilation (<0) CO2 absorption by vegetation - respiration (>0) CO2 emissions from ecosyst. depends on temperature - anthropogenic emissions (>0) and ocean fluxes (<0 in our latitude)   Feedback : CO 2 concentrations variations from the atmosphere to the surface ISBA-A-g s Meteorological Model LE, H, Rn, W, Ts… Atmospheric [CO 2 ] concentrations Anthropogenic Sea Meso-NH Surface Lafore et al., 98 Noilhan et al. 89, 96, Calvet et al., 98 CO 2 Fluxes

31 Atmospheric CO 2 modelling : May – 27 2005 Boundary layer heterogeneity OCEANFOREST AREA AGRICUL. AREA Simulated vertical cross section of the mixing ratio at 14UTC Zi = 900m Zi = 1600m

32 Atmospheric CO 2 modelling May – 27 2005 : comparisons obs/simu Simulated vertical cross section of CO 2 Ocean - Marmande Agricultural area Forest area Vertical cross section of observed CO 2 by aircraftoceanforestcropland forestcropland

33 Examples of Applications of Meso-NH General description of Meso-NH, Grid nestingGeneral description of Meso-NH, Grid nesting Clouds representation (explicit) : convective events, Sc, Fog, cyclonesClouds representation (explicit) : convective events, Sc, Fog, cyclones DiagnosticsDiagnostics Coupling with the surface Coupling with the surface Coupling with other models (hydrology, dispersion) Coupling with other models (hydrology, dispersion) ClimatologyClimatology The physics of Meso-NH in AROMEThe physics of Meso-NH in AROME Ways of improvements of Meso-NH Ways of improvements of Meso-NH

34 Vidourle Gard Cèze Ardèche TOPMODEL (Beven and Kirkby, 1979) distributed hydrologic model with one model by basin : 9 basins (200-2200 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 K.Chancibault et al., CNRM/GMME/MICADO

35 SPRAY Lagrangian particle model At least 10000 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 Will be exported to AROME Modelling system for environmental emergency

36

37 Examples of Applications of Meso-NH General description of Meso-NH, Grid nestingGeneral description of Meso-NH, Grid nesting Clouds representation (explicit) : convective events, Sc, Fog, cyclonesClouds representation (explicit) : convective events, Sc, Fog, cyclones DiagnosticsDiagnostics Coupling with the surface Coupling with the surface Coupling with other models (hydrology, dispersion) Coupling with other models (hydrology, dispersion) ClimatologyClimatology The physics of Meso-NH in AROMEThe physics of Meso-NH in AROME Ways of improvements of Meso-NH Ways of improvements of Meso-NH

38 Vosges, Forêt Noire : 1.2 km Alpes du Nord 2 km Alpes du Sud 2 km Pourtour méditerranéen 3 km Auvergne 2 km Sud-Ouest 3 km Geographical area with Meso-NH wind climatology Limousin 1km Bourgogne 2 km Quiberon 1 km

39 Roses Aladin 3 ansMéso-NH 95 datesMeasurements North Alps

40 Examples of Applications of Meso-NH General description of Meso-NH, Grid nestingGeneral description of Meso-NH, Grid nesting Clouds representation (explicit) : convective events, Sc, Fog, cyclonesClouds representation (explicit) : convective events, Sc, Fog, cyclones DiagnosticsDiagnostics Coupling with the surface Coupling with the surface Coupling with other models (hydrology, dispersion) Coupling with other models (hydrology, dispersion) ClimatologyClimatology The physics of Meso-NH in AROMEThe physics of Meso-NH in AROME Ways of improvements of Meso-NH Ways of improvements of Meso-NH

41 AROME : Application of Researh to Operations at MEsoscale Future non-hydrostatic model 2.5km resolution Dynamics based on ALADIN-NH (semi-implicite, semi- lagrangian) Data assimilation ALADIN 3D-VAR Physics based on Méso-NH : microphysics ICE3, Turbulence 1D, shallow convection, externalised surface http://www.cnrm.meteo.fr/aladin/aladin2/traceMP/AROMErunMP.html

42 Arome 60s Case of Gard, initial bogus Lame d’eau 12-22 Tu radar de Nîmes > 300 mm Couplage : Aladin 3h Forecasts MésoNH 4s 304 mm 274 mm MésoNH –  t= 4s, CPU = 24h20 AROME –  t =60s, CPU = 2h30

43 Main current works of improvement for Meso-NH 1.DYNAMICS : Meso-NH computationaly too expensive (small  t) – Handicap especially for chemistry simulation (a lot of species) : eulerian advection scheme, explicit temporal scheme.  New eulerian advection scheme (PPM) 2.PHYSICS: Boundary layer clouds (Cu, Sc) at meso-scale (2km): interaction between shallow convection scheme, turbulence and cloud scheme Radiation : revised, for overlapping cloud layers Microphysics : Bulk 2 moment schemes for LES Improvement of sedimentation advection

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