Transcript Hirlam Physics Developments Sander Tijm Hirlam Project leader for physics Overview      Results of this year Verification Shallow convection Turbulence and convection for mesoscale Tuning of synoptic scale model Hirlam.

Hirlam Physics Developments
Sander Tijm
Hirlam Project leader for physics
Overview
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Results of this year
Verification
Shallow convection
Turbulence and convection for mesoscale
Tuning of synoptic scale model
Hirlam physics developments
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Mesoscale
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Verification
Surface
Turbulence &
shallow convection
Deep convection?
Radiation
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Synoptic scale
EPS & boundaries
Verification
Surface (tuning)
Turbulence
Shallow convection
Deep convection
Radiation
Wave drag
Results this year
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Hirlam physics in IFS (Convection, turbulence and
radiation, Sass, Rontu and Niemela)
Moist CBR (Sass & Tijm)
MSO/SSO (Rontu)
Surface scheme (snow and forest, talk of Stefan after
this one)
Sloping surfaces radiation (Senkova)
Stable PBL (GABLS, De Bruijn, Perov & friends)
Snow on ice (Vihma)
Lake model (Kourzeneva & Tisler)
Urban characteristics (Baklanov & Mahura)
Moist CBR
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Impact on cloud water profiles
Moist CBR
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Impact on precipitation
Snow scheme
Verification
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Verification working group to check physics of
mesoscale model
Cooperation with Aladin
Focus on relatively normal weather, which is challenge
for physics
List of cases and progress of work can be found on:
http://www.knmi.nl/~tijm/Verif/Verifworkg.html
Verification of models against observations
Model intercomparison
Baseline for future model improvement
Verification
Cloud top temperatures (Zingerle)
KF-RK
REF
Obs
Entrainment/Detrainment
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Overprediction of high clouds
Too much deep convection, too little
convection of intermediate depth
Too little entrainment (lowering of updraft
temperature) and/or detrainment (stopping
updraft mass flux)
Can also be seen in shallow cumulus
Shallow convection (De Rooy)
Specific humidity profiles for ARM with LES (left) and
Hirlam 1D using =z-1 and =0.00275
Shallow convection
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Mass flux profiles for LES (left) and =z-1 +
=0.00275 (right)
Shallow convection
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Massflux profiles for LES (left) and =z-1 + new 
(right) where  depends on cloud depth and critical
fraction
Shallow convection
qt profiles for ARM with LES (left) and Hirlam SCM (right)
c
with =1/z and new  formulation
EDMF scheme (Siebesma)
•Nonlocal (Skewed) transport through strong updrafts
in clear and cloudy boundary layer by advective Mass
Flux (MF) approach
•Remaining (Gaussian) transport done by an Eddy Diffusivity
(ED) approach
ED
zinv
MF
Use LES to derive updraft model in clear boundary
layer. 0
h (km)
1
0
x(km)
5
Updraft at height z
composed
of those grid points
that contain the highest p%
of the vertical velocities:
p=1%,3%,5%:
EDMF scheme
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One scheme for boundary layer and cumulus convection
Will be developed within AROME framework, as an
option
Cooperation with ECMWF
After successful implementation in mesoscale model,
incorporate in synoptic scale model to limit boundary
effects
Surface developments
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New surface scheme (Gollvik) for synoptic scale
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Extension of surface scheme with lake model
(Kourzeneva)
Extension with improved description of snow on ice
(Vihma)
Urban impact to be included (Mahura and Baklanov)
Tuning of surface characteristics (Garcia)
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Modeled temperature, sensitivity to lake depth
(Flake model, Kourzeneva)
Tuning of syn. Hirlam
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Sytematic errors in synoptic scale Hirlam:
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too much fog
too many and intense small scale lows
too strong convection dynamics feedback (noisy pressure
pattern)
Overestimation of evaporation over sea may be an
important factor in the development of these
phenomena, together with:
Vertical diffusion in stable and neutral conditions
Deep convection parameterization
Tuning of syn. Hirlam
Small scale developments
Summary
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Many developments for turbulence, shallow and deep
convection, surface modelling.
Shift of main effort towards the mesoscale physics
Synoptic scale remains important, for mesoscale
boundaries and SREF
Synoptic physics as close as possible to mesoscale
physics, to reduce boundary effects