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

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)

http://www.aero.obs-mip.fr/mesonh

http://www.meteo.fr/

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.

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• 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


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)


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

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• 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

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• 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

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• 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

Documents

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