Meso-NH model. 40 users laboratories

Transcription

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

2 Space and time scales Méso-NH

3 Different meteorological models Global Climate Model (GCM) ( x > 100 km) : ARPEGE Climat NWP at synoptic scale : ECMWF, ARPEGE ( x=20-25km on France) NWP at meso-α scale : ALADIN ( x=10km) NWP at meso-β scale : AROME (2008) ( x=2.5km) Research model for synoptic to meso-γ scale : Méso-NH ( x=50km to 10m). Other meso-scale models : MM5, WRF, RAMS, LM, UM

4 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 (High resolution capability, Grid Nesting) 3. To better understand the physics (e.g. cloud processes), to characterize local effects : meso-scale to large eddy simulations 4. To carry out impact studies and use the model as a laboratory 5. To develop observation simulators : satellite, radar, lidar, scintillometer, to validate the model and to develop new data assimilation 6. To develop new couplings (e.g. Electricity, Hydrology ) and applications (astronomy ). Most recent applications : Fire propagation, Pollen dispersion, aircraft contrails, acoustic : A tool

5 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. Meso-NH-Chemistry 7. Climatology 8. Diagnostics

6 Meso-NH characteristics 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.

7 Activité scientifique Centaine d utilisateurs, en majorité INSU Thématiques variées : convection, nuages, chimie, aérosols, couche limite, surface, applications, assimilation 15 programmes (AMMA, CAPITOUL CARBOEUROPE, COPS, ESCOMPTE, EUCAARI, IHOP, MAP, QUANTIFY, TROCCINOX, HYMEX, ) 136 articles et 41 thèses Articles et thèses jusqu en sept 2009 (article séminal Lafore et al. publié en 1998)

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

9 Domaine 10-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 Domaine 2.5-km ~ km

10 M C e as nt sif ra l As many other Western Mediterranean regions, Southern France is prone to devastating flash-floods during the fall season Number of days with daily rain > 200 mm for the period [ ] on the South-East s e p l A 2002 Pyréné es 1 severe episode (+500 mm/24 h)

11 Impact of the convective system on the triggering and the localization CTRL = With cooling associated to evaporation of precipitation NOC = Without cooling Gard 02 Cumulated precipitation during 4 hours 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

12 Sensibilité à la résolution (cas du MCS 20/10/0 Observations Simulations Méso-NH 2500 m) 20AR06 (2,5 km) réflectivité radar à 16 UTC AR06G (2,5 km + 500m) (dbz) Fort impact de la très haute résolution. Description plus fine des reliefs et meilleure réprésentation du MCS du 20/10 d ingrédients à l échelle convective.

13 Phase mature du MCS du 20/10/08 17 UTC θe et vent dans la coupe 25 m/s Axe de coupe (K)

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

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

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

17 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.

18 Vertical cross-sections at x=4km W-E S-N K K θ E = θ.e Lq C PT m/s m/s Horizontal wind Barbary et al.

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

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

21 ZS (m) 3 km Etoile Massif VAL (Lidar) o Comparison with transportable wind lidar (TWL) 300 OBS (Radar) Marseille veyre 200 Puget CNRS Massif (Radar ) 26 June 2001, 1400 UTC Altitude (km) 2.5 D C 1.0 B A 0.5 VDOL 0 2 Distance (km) 4 Lemonsu et al., 2005a -4-2 TWL D 6 m s-1 Model C B City center VDOL 60 A 2 Distance (km) 4 City center 6

22 The Large Eddy Simulations with Meso-NH : Large eddys are resolved : TKEresolved >> TKE Subgrid Objectives : - To improve parametrizations - To better understand the physics (process studies)

23 METHODOLOGY to improve PARAMETRIZATIONS To correctly represent subgrids effects (turbulent eddies, Shallow clouds (Cu,Sc) a good parameterization is needed LES Single Column Model (SCM) GCM/NWP LES SCM/1D GCM/ NWP

24 LES FIRE (Sc) WANGARA Turb. Conv. sèche 1D

25 Water vapor variability in convective BL : presence of dry tongues - Couvreux et al. (2005) Lidar observations at 12h g/kg 9.0 rv qv LES P3 aircraft KA aircraft.. max (pdf) _ min (pdf) LES simulation LES Simulations at 0.5zi g/kg S(qv)<0 x= y= 100m, z<50m, t=7h

26 Impact of the pollution on the stratocumulus diurnal cycle = Aerosol indirect effect 700m 0.7g/kg rc(g/kg) Simulation LES 50m Nuage non pollué x= y= 50m, z=10m Τ=36h 0TU 6 LWP (g/m²) Polluted : non precipitating Evaporation of precipitation Cooling Limits the stratification at cloud base and the decoupling Pristine : precipitating Sandu, I., 2007 No precipitation No Cooling Maximum solar warming decoupling

27 AN OBSERVED LLJ DURING THE SABLES98 CAMPAIGN Objective: study the mixing processes across the maximum of the wind of an observed Low-Level Jet (LLJ) using LES Duero river basin 100m tower x = 6 m, y = 4 m, z = 2m (0 <z<100 m) and stretched above ( z = 5 m at about 400 m) Night: September 1998 M.A. Jiménez Universitat de les Illes Balears

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

29 SURFACE COUPLING : Examples of surface impact

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

31 Couplage végétation Atmospheric CO2 modelling : May Boundary layer heterogeneity Zi = 1600m Forest : high sensible heat flux Zi = 900m Agricultural area : low sensible heat flux Sarrat et al.(2007a)

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

33 Couplage ville : Simulation Brouillard lors de la campagne Paris-Fog (Tardif, 2008) Eau liquide 1er niveau (00 TU) 9 km 2.25 km 560 m 33

34 Couplage océan Full-physics atmospheric model Méso-NH : 4km ECUME surface flux parameterization 1D ocean model with 1.5 TKE closure scheme: horizontal resolution of 4 km 20 vertical levels (5m-resolution in the OML) coupled every 600 s with Méso-NH Lebeaupin et al Bathymetry ETOPO 20 Mode Initial Oceanic State Forced Realistic SST (Mercator) Coupled Realistic Ocean (Mercator) Samson, 2009

35 Original applications : - Electricity - Pollutant dispersion - Pollen dispersion (INRA Bordeaux) - Fire propagation (Univ.Corte)

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

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

38 Industrial accidental release : AZF COLOMIERS 70 10%=97µ g/m3 60 8:45 50 Max_obs=60µ g/m3 30km, x=500m Couche de mélange : flux de SE Couche résiduelle : flux de S Max=10% de concentration initiale 30km, x=500m 23:30 22:45 22:00 21:15 20:30 19:45 19:00 18:15 17:30 16:45 16:00 15:15 14:30 13:45 13:00 12:15 11:30 10:45 9:15 10:00 8:30 7:45 7:00 6:15 5:30 4:45 4:00 3:15 2:30 1:45 1:00 0:15 0 The heaviest particles have settled : strong dry deposition on Blagnac

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

40 Impact des OGM : dispersion et viabilité du pollen (INRA Bordeaux) Viabilité du pollen de maïs diminue à T élevée et REHU faible 4 variables : - Concentrations en pollen vivant et mort -Teneurs en eau du pollen vivant et mort Concentration Evaporatio n du pollen sousestimée Viabilité Concentration en pollen le 12 juillet 2003

41 Coupling with a fire propagation model (Univ.Corte) Vent 1er niveau MNH FIRE Flux de chaleur sensible et latent, Ts Domaine 3200m*1200m*1600m Résolution 40m*40m*40m

42 Coupling with a fire propagation model (Univ.Corte)

45 Contrails : Traînées de condensation à l arrière des avions Sarrat, C, R.Paugam, D.Cariolle, CERFACS Conditions dynamiques : Dans le sillage de l avion, le jet issu des moteurs interagit avec les vortex contrarotatifs générés par les ailes de l avion Humidité relative de l atmosphère importante : sursaturation par rapport à la glace : humidité relative supérieure à 130% Conditions microphysiques : Condensation sur les noyaux de condensation (présents dans l atmosphère ou issus des moteurs) de la vapeur d eau émise par les moteurs de l avion OBJECTIFS : Estimer le temps de dissipation dans la troposphère libre, ainsi que l étalement horizontal et vertical du nuage Estimer l'impact radiatif du nuage formé durant la phase de dissipation (impact contrail vs impact CO2) Mettre en place la chimie de l'ozone et de ses précurseurs pour estimer l'impact de l'aviation sur la chimie de la troposphère et des différents types de carburants (pouvoir oxydant, gaz à effet de serre plus efficaces en altitude

46 Contexte des études Contrails 1. REGIME DE JET et VORTEX 47 m t =0 s 3. REGIME DE DISSIPATION t=2s t = 100 s 1. Régime de Jet t = 1000 s 2. Régime de Vortex 3. Régime de Dissipation 2. REGIME DE VORTEX ou TOURBILLON 4. Régime de Diffusion 4. REGIME DE DIFFUSION extension horizontale : ~ 1 km ~ qq heures ~ 1 km

47 Meso-NH-Chemistry

48 M ge EC OCA -sc M G ale W E, : F,... Meso-NH-Chem: Modelling of atmospheric chemistry from local (dx=1 km) to synoptic scale (dx=50 km)

49 9km OZONE le 25 Juin km 9 UTC <30ppb 85ppb Marseille 15 UTC >90ppb >90ppb Cousin et Tulet, 2004 Parc Naturel Verdon Marseille Parc Naturel Verdon

50 Meso-NH-Chem / Modularity of the code Sensitivity test: impact of biogenic emissions Solmon et al, 2004

51 Meso-NH-Chem / Coupling of dyn/μφ/chem processes NOx production by lightning Barth et al, 2005

52 Dust parametrization in MesoNH/SURFEX (Grini et al, 2006, Tulet et al, 2005) ative i d a R ct i mp a Solar radiation

53 Dust emission and transport associated with Saharan cyclones: The February 2007 case. D.Bou Karam et al. MSG-SEVIRI Purple Dust White Clouds Deep convection in the northern part of the cyclone. Dust in the southern part. Meso-NH Vertically integrated dust mass (g/m²) x = 25km

54 Climatologie. Régionalisation climatique

55 Wind climatology over the North Alps Measurements Roses Méso-NH Aladin 953dates ans

56 OBS HYERES ALADIN 76% MESO-NH 80%

57 Diagnostics

58

59 Chaboureau and Pinty (2005) : Use of radiative transfer RTTOV to MSG x=30 km Amélioration des enclumes (cirrus) sur le seuil d auto-conversion ri* = min(2.10 5, (T ) 3.5 )

60 Simulation de réflectivités radar 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.)