Transcript Diapositive 1

The mesoscale meteorological models
Meso-NH and AROME
C.Lac (CNRM/GMME)
For the Meso-NH community and the AROME team
Nocturnal ozone in the
residual layer over
Marseille
85ppb
Marseille
« Astronomy meets Meteorology », 15-18 September
Parc Naturel Verdon
Outlook
1. Introduction : General consideration on meteorological
predictions
2. Overview of meso-scale models
3. Meso-NH : From meso-scales to Large Eddy Simulations.
4. The new operational meso-scale model AROME
Space and time scales
On the importance of the resolution
• Prognostic variables of the model are mean variables on the grid box
Processes that need to be parametrized
What kind of models ?
2
2
-2 km
(LES)
Mesoscale models
All these kinds of models need different level of parametrization
- Climate models and Global weather prediction : All the physics parametrized
- Mesoscale models : Convection (deep) resolved.
- Large Eddy Simulation. The most energetic eddies in turbulence are resolved, but it
still needs to parameterize small-scale turbulence, radiation, microphysics.
Mesoscale models
Models
MM5
PSU/NCAR
RAMS
1990’s
Meso-NH
WRF
MF/LA
NCAR/MMM
LM
UM
UKMO
COSMO
2000’s
AROME
MF
Min.
Resolution
LES
LES
LES
LES
LES
1km
2.5km Up
to 1km
Spectral/ grid
point
Grid
Grid
Grid
Grid
Grid
Spectral
Spectral
Advection
scheme
Euler.
Euler.
Euler.
Euler.
Euler.
SL
SL
Temporal
scheme
Explicit LF
Explicit LF
Explicit LF
Explicit
Split
Explicit
Split
SI
SI
Time step
For 2.5km
8s
(Dt=3Dx )
For 2.5km
8s
(Dt=3Dx )
For 2.5km
6-8s
For 2.5km
15s
For 2.5km
15s
For 2.5km
60s
For 2.5km
60s
Nesting
2 way
2 way
2 way
2 way
2 way
1 way
1 way
Turbulence
scheme
1.5 closure
1D or 3D
1.5 closure
1D or 3D
1.5 closure
1D or 3D
2.5 closure
1D or 3D
2.5 closure
1D or 3D
1.5 closure
1D
1.5 closure
1D
Microphysics
Up to 6
species
Up to 6
species
Up to 6
species
Up to 6
species
Up to 6
species
Up to 6
species
Up to 6
species
Data
assimilation
Meso-NH model
A research model, jointly developped by Meteo-France and Laboratoire
d’Aérologie (CNRS/UPS)
40 users laboratories
http://mesonh.aero.obs-mip.fr/mesonh/
1. Recent improvements in the dynamics
2. Focus on the turbulence . Importance of the
surface coupling.
2D test case of orographic trapped waves
t = 3500 s
Horizontal wind
Previous advection
schemes
t = 5000 s
Horizontal wind
Vertical velocity
New advection schemes
Turbulent Kinetic Energy
A typical situation
for optical
turbulence
T.Maric
Cloud
Diurnal cycle of boundary layer height
Buoyancy effects
General principles of the turbulence scheme
Closure :

with
w' '   K
z
>0 in convective
<0 in stable
K  c L E , L=Mixing length
Further details in E.Masciadri’s presentation
CONVECTIVE BOUNDARY LAYER with LES
Water vapor variability - Couvreux et al. (2005)
Lidar observations
at 12h
5.0
5.0
5.5
5.5
6.0
6.0
6.5
6.5
7.0
7.0
7.5
7.5
8.0
8.0
8.5
8.5
9.0
9.0
9.5
9.5
10.
10.
LES simulation
LES Simulations
g/kg
g/kg
rv ’
qv’
LES
5.0
5.0
5.5
5.5
6.0
6.0
6.5
6.5
7.0
7.0
7.5
7.5
8.0
8.0
8.5
8.5
9.0
9.0
9.5
9.5
10.
10.
P3 aircraft
KA aircraft
. . max (pdf)
_ min (pdf)
at 0.5zi
S(qv)<0
Dx=Dy= 100m, Dz<50m, Dt=7h
STABLE BOUNDARY LAYER
Difficulty to simulate due to local circulations (drainage flows),
intermittent effects (gravity waves), low level jets (LLJ).
LES simulation of 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
Dx = 6 m, Dy = 4 m, Dz = 2m
(0 <z<100 m) and stretched
above (Dz = 5 m at about 400 m)
Duero river basin
100m tower  Night: 20-21 September 1998
M.A. Jiménez
Universitat de les Illes Balears
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
STABLE BOUNDARY LAYER : Comparison MesoNH/MM5 at meso-scale
Dx = 1km, Dzmin = 3m, 86 lev.
4H
23H
Obs.
23H
4H
A strongly stable night
MM5
Meso-NH
U
T
MNH
MM5
Bias
O.82
1.37
Rmse
0.75
1.15
Bias
1.69
0.31
Rmse
2.03
1.41
Bravo et al., 2008
23H
4H
23H
4H
On the importance of the surface coupling
for the turbulence
The SURFEX (SURface Externalized) land surface
scheme
see P.Le Moigne’s presentation
Atmospheric CO2 modelling : May – 27 2005 Boundary layer heterogeneity
Zi = 1600m
Forest : high
sensible heat
flux
Zi = 900m
Agricultural area :
low sensible heat
flux
Sarrat et al.(2007a)
A recent improvement in SURFEX: the CANOPY
scheme (Masson, 2008)
• 1D Surface Boundary Layer scheme, with 6 added levels between
the first atmospheric level and the surface
• An added term for U, q, q, TKE
• T2m becomes pronostic
AROME
(Applications of Research to Operations at
MesoscalE)
Almost-current operational meso-scale system
(2.5km) with data assimilation (P.Brousseau’s talk)
-Dynamics : from ALADIN-NH
- Physics : from Meso-NH
Objectives of AROME
- Expected to improve heavy precipitation forecasts with strong emphasis on Mediterranean
flash-floods
- Prediction of local events (fog, breeze, urban effects, orographic)
-Applications : chemistry, hydrology, fog, ocean, roads …
- A complex data assimilation system (further details in P.Brousseau’s presentation)
ALADIN Dx=10km
Vertical levels = 40,
Time step=60s
Forecast range = 36h
(1800s on 64 processors)
AROME Dx=2,5km
Diurnal convection (2)
Obs radar
Cloudiness
Total cloudiness
AROME 12 h
vs Sat Vis
25
Model performance : low-level scores
 objective scores of AROME-France using French automatic surface obs
network (hourly data every ~30km)
10m windspeed
MSL pressure
Rmse Aladin
Rmse Aladin
Rmse Arome
Bias Arome
forecast range (h)
Bias Aladin
2m Temperature
Rmse Aladin
Rmse Arome
Bias Arome
2nd AROME training course,
forecast range (h)
Lisbon,
March
2008
Bias
Aladin
Rmse Arome
Bias Arome
forecast range (h)
Bias Alad
Scores over France on 3 months
Nov07-Jan08 (Arome in pink)
Conclusion
Meso-NH
1. A well-known research model with a broad range of resolution.
Largely validated by the community. Large variety of applications for
the Boundary layer.
2. Used for Optical Turbulence (Masciadri et al.) : CN²=f (TKE, dq/dz)
AROME
1. Will be operational next month
2. Includes Meso-NH physics, a mesoscale data assimilation. Competitive
computational time.
3. Perspective for Optical Turbulence : climatology, prediction…
Thank you for your attention