meso-nh model 40 users laboratories a research model, jointly developped by meteo-france and...
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Meso-NH model
40 users laboratories
http://www.aero.obs-mip.fr/mesonh
A research model, jointly developped by Meteo-France and Laboratoire d’Aérologie (CNRS/UPS)
PlanPlan
• IntroductionIntroduction• Clouds : Clouds : MCS, Cyclones, Cu, Sc, FogMCS, Cyclones, Cu, Sc, Fog
• Dynamics of Boundary layers : Dynamics of Boundary layers : Stable, Stable,
ConvectiveConvective • Chemistry, Dusts, ElectricityChemistry, Dusts, Electricity• Coupling : Coupling : C02, Hydrology, DispersionC02, Hydrology, Dispersion
• Applications : Applications : Duct mapping, climatologyDuct mapping, climatology
• AROMEAROME
Types of simulationsTypes of simulations
A broad range of resolution from synoptic scales A broad range of resolution from synoptic scales ((x~10km), meso-scale (x~10km), meso-scale (x~1km) to Large Eddy x~1km) to Large Eddy Simulation (Simulation (x~10m) x~10m)
• Real cases (from ECMWF, ARPEGE, ALADIN Real cases (from ECMWF, ARPEGE, ALADIN analyses or forecasts)analyses or forecasts)
• Ideal cases Ideal cases unrealistic cases unrealistic cases- Academic cases (validation of the - Academic cases (validation of the
dynamics)dynamics)- Basic studies (Diurnal cycle …) : Cloud - Basic studies (Diurnal cycle …) : Cloud
Resolving Model (CRM)Resolving Model (CRM)- To reproduce an observed reality (via - To reproduce an observed reality (via
forcings)forcings)(intercomparison : GCSS, EUROCS …)(intercomparison : GCSS, EUROCS …)
Simulations 3D, 2D, 1DSimulations 3D, 2D, 1D
Lafore Moncrieff 89
Stratiform
Density Current
Convective
HD
A tropical squall line (P.Jabouille) : Idealized
simulation according to a real case (COPT81)
U
W
Cloud droplets Rain drops
Pristine iceGraupel
Snow
Jabouille. Caniaux et al., 1994
(Keil et Cardinali, 2003)32km : 150x1508km : 145x1452km : 150x150over 51 levels
IOP8 (F<1)
IOP2a(F>1)
8 km
2 km
Monte Lema
S Pol
Ronsard
ECMWF32 km
3 Dopplerradars ( )
Orographic precipitation 3D (MAP)Orographic precipitation 3D (MAP)
How can dynamics modify the microphysics ?
Lascaux et Richard, 2005
SnowGraupel
Hail
Cloud Rain
IceIOP2a
IOP2a ( Strong convection)- Deep system (unblocked unstable case, high Fr)- 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)Orographic precipitation 3D (MAP)
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 Nuissier et Ducrocq, 2006
Strong convective events on SE of FRANCEStrong convective events on SE of FRANCE
How can mycrophysics modify the dynamics ?
Cev. ‘95
Gard ‘02
Aude ‘99
1D- budget over the MCS (convective + stratiform).
max : 135 mm
max : 25 mm
m mm
Quasi-stationnary MCS 13-14 Oct. 1995
Cumulated precipitation 01 UTC to 06 UTC the 14th Oct. 1995
MESO-NH, x=10km
max: 31 mm
MESO-NH, x=2.5kmOBSERVATIONS
(Ducrocq et al, 2002)
Initial conditions: ARPEGE analysis at 18UTC
mMESO-NH, x=2.5km
Initialisation Ducrocq et al
(2000)’s
max : 99 mm
Impact de la pollution sur le cycle diurne du stratocumulus
0.7g/kg700mrc(g/kg)
Simulation LES 50mNuage non pollué
Sandu, I., 2007
0TU 6 12 18 24 30 36
Impact d’une atmosphère polluée sur le cycle diurne = Effet indirect des aérosols
L’évaporation liée à la bruine empêche la stratification à la base du nuage et le découplage
LWP (g/m²)
FOG – 1D simulation – Temporal evolution on 18h from 18TU
rc rc
rc
Without cloud droplet sedimentation
With cloud droplet sedimentation
With cloud droplet sedimentation but a coarser vertical resolution
Rémi, S., 2006
Simulation of cyclone : case of Dina7800 km, x=36km
1944 km , x=12km
720 km , x=4km
3600 km
Automatic method of Initialization : Filtering/Bogussing
Barbary et al.
Vertical cross-sections at x=4km
K
m/s
K
m/s
TC
Lq
EPe.
Horizontal wind
S-N W-E
Barbary et al.
PlanPlan
• IntroductionIntroduction• Clouds : Clouds : MCS, Cyclones, Cu, Sc, FogMCS, Cyclones, Cu, Sc, Fog
• Dynamics of Boundary layers : Dynamics of Boundary layers : Stable, Stable,
ConvectiveConvective • Chemistry, Dusts, ElectricityChemistry, Dusts, Electricity• Coupling : Coupling : C02, Hydrology, DispersionC02, Hydrology, Dispersion
• Applications : Applications : Duct mapping, climatologyDuct mapping, climatology
• AROMEAROME
Couche limite stable : application à l’île de Majorque
2
1
Motivation : Comment les flux nocturnes s’organisent en l’absence de gradient synoptique fort ?
Cuxart et al.
x=1kmz=3m dans les 200 premiers m
4TU
SE
N
50 km
**55 k
m
NE
Forte stratification des vents à l’aéroport
Direction du vent Force du vent
Influence des effets locaux : la brise de mer
Urban network
Model
Lemonsu et al., 2005a
Température de l’air 26 June 2001, 1400 UTC
26 Juin 2001 : Marseille sous l’influence d’écoulements locaux, induisant des mécanismes complexes au dessus de la ville
Influence des effets locaux : la brise de mer
VAL
OBS
CNRSPuget Massif
Marseilleveyre
City centre
z = 400 m AGL
VAL
OBS
CNRS
m s-1
Puget Massif
Marseilleveyre
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
6 m s-1420-2-4-6
26 June 2001, 1400 UTC
B
C
D
A
TWL
B
C
D
A
Model
VDOLCity
center0 2 4 6 0 2 4 6Distance (km) Distance (km)
VDOLCity
center
0.5
1.0
1.5
2.0
2.5
Alt
itude (
km
)500
400
300
200
100
50
ZS (m)
Marseilleveyre
190o
Puget MassifCNRS
(Radar)
3 km
VAL (Lidar)
OBS (Radar)
Etoile Massif
Comparison with transportable wind lidar (TWL)
Lemonsu et al., 2005a
Couche limite convective : variabilité de la vapeur d’eau
Vols avions P3 Vols avions KA
Histogramme de w à Z=0.4zi
. . . . max_ _ min
Histogramme de à Z=0.4zi
Histogramme de rv à Z=0.4zi
Enveloppe max.Enveloppe min.
Modèle
Lidar
8km
1500m
Descentes d’air sec
Thermiques
Couvreux, F., 2005
PlanPlan
• IntroductionIntroduction• Clouds : Clouds : MCS, Cyclones, Cu, Sc, FogMCS, Cyclones, Cu, Sc, Fog
• Dynamics of Boundary layers : Dynamics of Boundary layers : Stable, Stable,
ConvectiveConvective • Chemistry, Dusts, ElectricityChemistry, Dusts, Electricity• Coupling : Coupling : C02, Hydrology, DispersionC02, Hydrology, Dispersion
• Applications : Applications : Duct mapping, climatologyDuct mapping, climatology
• AROMEAROME
OZONE le 25 Juin 2001
9 UTC
9km 3km
<30ppb
Parc Naturel VerdonMarseille
85ppb
Marseille Parc Naturel Verdon
>90ppb15 UTC >90ppb
Cousin et Tulet, 2004
surfaceInfiltration d’eau
Réservoir profond
Réservoir superficiel
Sol Nu ou Rochers
Lessivage aérosols
Absorption/ diffusionDu rayonnement solaire
Refroidissement surface
Aérosols Désertiques – Génération – Transport - Effets
u*turbulence
Émission
Saltation
Exemples d’applications (5) – A. Grini / P. Tulet : Dusts
Exemples d’applications (5) – A. Grini / P. Tulet : Dusts
Barthe et al. [2005]
+
+
-
Explicite electrical scheme in Meso-NH
Local separation of charges
Transfert and transport of chargesMicrophysical and dynamical processes
Electric field
Lightning parameterizationBidirectional leader (determinist)
Vertical extension of the lightningChannel steps (probabiliste)
Horizontal extension of the lightning
Charge neutralization
E > Etrig
yes
no
Life cycle of electrical charges in a convective cell
Barthe et Pinty, JGR
Apparition of graupel
Electrization of the cloud
Apparition of electric fieldlightning
Triggering of convectionSimulation Méso-NH
PlanPlan
• IntroductionIntroduction• Clouds : Clouds : MCS, Cyclones, Cu, Sc, FogMCS, Cyclones, Cu, Sc, Fog
• Dynamics of Boundary layers : Dynamics of Boundary layers : Stable, Stable,
ConvectiveConvective • Chemistry, Dusts, ElectricityChemistry, Dusts, Electricity• Coupling : Coupling : C02, Hydrology, DispersionC02, Hydrology, Dispersion
• Applications : Applications : Duct mapping, climatologyDuct mapping, climatology
• AROMEAROME
Atmospheric COAtmospheric CO22 modelling : modelling :the Meso-NH modelthe Meso-NH model
Online coupling with the surface scheme ISBA-A-gs :
CO2 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 : CO2 concentrations variations from the atmosphere to the surface
ISBA-A-gs
Meteorological Model LE, H, Rn, W, Ts…
Atmospheric [CO2]
concentrations
Anthropogenic
Sea
Meso-NHMeso-NHSurfaceSurface
Lafore et al., 98
Noilhan et al. 89, 96, Calvet et al., 98
CO2 Fluxes
Atmospheric COAtmospheric CO22 modelling : May – 27 modelling : May – 27 2005 Boundary layer heterogeneity2005 Boundary layer heterogeneity
Sarrat et al., 2006
Concentration CO2 (ppm)
Atmospheric COAtmospheric CO22 modelling modellingMay – 27 2005 : comparisons May – 27 2005 : comparisons
obs/simuobs/simu
Simulated vertical cross section of CO2 Ocean - Marmande
Agricultural areaForest area
Vertical cross section of observed CO2 by aircraft
oceanocean forestforest croplandcroplandforestforest croplandcropland
Sarrat et al., 2006
Winter crops AssimilationForêt Respiration
VidourleVidourle
GardGard
CèzeCèze
ArdècheArdèche• 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
SPRAY• Lagrangian particle model•At least 10000 particles released •Advection+Turbulence+random• Applied to the 2 Meso-NH grids
PERLEPERLE (PProgramme d’EEvaluation des RRejets L Locaux d’EEffluents)
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
PlanPlan
• IntroductionIntroduction• Clouds : Clouds : MCS, Cyclones, Cu, Sc, FogMCS, Cyclones, Cu, Sc, Fog
• Dynamics of Boundary layers : Dynamics of Boundary layers : Stable, Stable,
ConvectiveConvective • Chemistry, Dusts, ElectricityChemistry, Dusts, Electricity• Coupling : Coupling : C02, Hydrology, DispersionC02, Hydrology, Dispersion
• Applications : Applications : Duct mapping, climatologyDuct mapping, climatology
• AROMEAROME
Roses Aladin 3 ansMéso-NH 95 dates Measurements
North Alps
Applications : Détermination de conduits de propagation d’ondes électromagnétiques.
Pourret, V., 2006 : PEA PREDEM
Co-indice de réfraction
N=(77.6/T).(P+4810.e/T)-6.e/T
Sommet du conduit de propagation = Altitude de l’inversion de M co-indice de réfraction
OG dans le sillage des îles au sommet du conduit
Réfraction normaleRéfraction vers le bas
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
Arome 60s
Case of Gard, initial Case of Gard, initial bogus 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