COSMO/ICON land-surface processes
and physiographic data
J. Helmert
with contributions from colleagues inFE1
GB FE 14 – 03/2017
Physics in ICON
Process
Radiation
Non-orographic
gravity wave drag
Sub-grid scale
orographic drag
Cloud cover
Microphysics
Convection
Turbulent transfer
Land
Authors
Scheme
Origin
Mlawer et al. (1997)
Barker et al. (2002)
RRTM (later with McICA & McSI)
ECHAM6/IFS
Ritter and Geleyn (1992)
δ two-stream
GME/COSMO
Scinocca (2003)
Orr, Bechtold et al. (2010)
wave dissipation at critical level
IFS
Lott and Miller (1997)
blocking, GWD
IFS
Doms and Schättler (2004)
sub-grid diagnostic
GME/COSMO
Köhler et al. (new development)
diagnostic (later prognostic) PDF
ICON
Doms and Schättler (2004)
Seiffert (2010)
prognostic: water vapor, cloud
water, cloud ice, rain and snow
GME/COSMO
Bechthold et al. (2008)
mass-flux shallow and deep
IFS
Plant, Craig (2008)
stochastic based on Kain-Fritsch
LMU, Munich
Raschendorfer (2001)
prognostic TKE
COSMO
Mironov, Machulskaya (new)
prognostic TKE and scalar var.
ECHAM6
Neggers, Köhler, Beljaars (2010)
EDMF-DUALM
IFS
Heise and Schrodin (2002),
Helmert, Mironov (2008, lake)
tiled TERRA + FLAKE
+ multi-layer snow
GME/COSMO
Raddatz, Knorr, Schnur
JSBACH
ECHAM6
Key task for parametrization
Parametrization schemes express the effect of subgrid/subscale processes
on resolved variables – solving the closure problem
Radiative transfer
Transfer of heat, moisture and momentum
Land/Sea surface characteristics courtesy to Anton Beljaars
Key task for parametrization
Parametrization schemes express the effect of subgrid/subscale processes
on resolved variables – solving the closure problem
Radiative transfer
Cloud
Physics
Transfer
Scheme
Radiation
Transfer of heat, moisture and momentum
Data
Assimilation
Land-Surface Scheme
TERRA
ExtPar
Physiographic
data
Land/Sea surface characteristics courtesy to Anton Beljaars
Parametrization schemes
Land-Surface Scheme
TERRA
Consider surface energy budget
Impact parameters: soil moisture and type, vegetation, surface roughness
and land-use class, snow coverage
Surface temperature depends on surface energy budget – determines PBL
development
Relationship between energy budget and water budget has to be
considered
courtesy to Anton Beljaars
Parametrization schemes
Land-Surface Scheme
TERRA
Surface temperature considers temperature of snow covered and snow free
surface fraction (snow tiles)
One-layer vegetation – Evapotranspiration after Dickinson (1984) –
interception reservoir
Urban areas: modified surface roughness, leaf area index, plant coverage detailed consideration possible
Transfer of heat, moisture and momentum
PBL coupling: application of the turbulence scheme at the lower model
boundary and iterative interpolation – Consideration of TILES (in ICON)
courtesy to Anton Beljaars
Parametrization schemes
Land-Surface Scheme
TERRA
Snow: One layer – prognostic variables : snow temperature, snow water
equivalent, snow density, snow albedo - Multi-layer snow model possible
Soil: 7-layer soil model + 1 climate layer - layer-depth between 1 cm and
14.58 m
Consider heat transfer and water transport including soil type dependent
computation of fractional freezing/melting of total soil water content in 6
heat, moisture
active soil layers inTransfer
the soil of
including
soil ice and momentum
Ocean: Prescribed surface temperature (analysis) - Charnock formulation
for roughness length – Sea ice model
Fresh water lakes: Lake model
courtesy to Anton Beljaars
ICON dynamics-physics cycling
Dynamics
Tracer Advection
Tendencies
dtime
dtime * iadv_rcf
Fast Physics
Satur. Adjustment
Convection
dt_conv
Turbulent Diffusion
Cloud Cover
dt_conv
Microphysics
Radiation
dt_rad
Non-Orographic
Gravity Wave Drag
dt_gwd
Land/Lake/Sea-Ice
Satur. Adjustment
Sub-Grid-Scale
Orographic Drag
Slow Physics
Output
„dt_output“
dt_sso
ICON setup for land-surface
Current experiments for new COSMO version
NAMELIST
LND_NML
LMELT
LMELT_VAR
ITYPE_HEATCOND
IDIAG_SNOWFRAC
ITYPE_EVSL
T
T
3
20
4
ITYPE_ROOT
ITYPE_INTERCEPTION
CWIMAX_ML
ITYPE_HYDBOUND
LSTOMATA
LSEAICE
2
1
5,00E-04
1
T
T
LLAKE
T
TERRA - Structure
H1 LvE1 H2 LvE2 H3 LvE3
0.00-0.01
0.01-0.03
0.03-0.09
0.09-0.27
0.27-0.81
0.81-2.43
2.43-7.29
7.29-21.87
H4 LvE4
H5 LvE5
H6 LvE6
TERRA – Energy budget
Solar radiation
Sensible heat
Latent heat
Snow
0.00-0.01
Heat release by
freezing/melting
Snow/Soil
Heat exchange
Soil heat flux
0.01-0.03
….
Heat release by
freezing/melting
TERRA – Energy budget
Thermal processes
Evolution of the soil temperature
Evolution of the soil temperature layer 1
Surface forcing
Frozen soil
-
Soils maintain some liquid water at temperatures below freezing point
-
Freezing point depression: Curvature of water around small hydrophilic soil
particles (Davis, 2001)
-
Analogous to freezing point depression by solutes in water
- Result: Thin liquid water films surrounding soil particles at T<0°C
Frozen soil
For peat f_c and f_s of sand is used
Frozen soil
Snow
Main effects
Insulation effect: Decoupling of soil from atmosphere (30%-90% of the
snow mantle is air)
Albedo Effect: Higher albedo than any other natural surface (0.4-0.85 for
bare ground/low vegetation, 0.2-0.33 for snow in forests)
Snow melting prevents rise of surface temperature above 0°C for a long
period in spring – impact on hydrological cycle and energy budget at
surface
G. Balsamo, 2007
Snow Model
One layer – prognostic variables : snow temperature, snow water
equivalent, snow density, snow albedo
Multi-layer – Vertical profiles in snow pack; considers equations for the
snow albedo, snow temperature, density, total water content and content of
liquid water. Therefore phase transitions in the snow pack are included.
Snow aging processes
Albedo and density
High Albedo
Low Density
Low Albedo
High Density
Snow
Qrad
Tsnow
f snow
Ts
hs ρ s , SWE
Tso1
(1 − f snow )
Ts
Snow
Snow fraction
Schneebedeckungsgrad
Schneebedeckungsgrad ist lineare
Funktion des SWE
Einfluss von Wald und subskaliger
Orographie wird im
Schneebedeckungsgrad nicht
berücksichtigt
f snow
SWE
=
0.015m
f snow = f (hsnow , SSO, landuse, freshsnow)
Existenz von Schnee wird bisher bei
der Bestimmung der skalaren
Rauigkeitslänge nicht berücksichtigt
Roesch et al., 2001
Snow
Thermal processes for snow
Evolution of the snow temperature
Heatflux through the snow
Surface forcing
ICON setup for land-surface
Current experiments for new COSMO version
NAMELIST
LND_NML
LMELT
LMELT_VAR
ITYPE_HEATCOND
IDIAG_SNOWFRAC
ITYPE_EVSL
T
T
3
20
4
ITYPE_ROOT
ITYPE_INTERCEPTION
CWIMAX_ML
ITYPE_HYDBOUND
LSTOMATA
LSEAICE
2
1
5,00E-04
1
T
T
LLAKE
T
TERRA – Water budget
Transpiration
Evaporation
Snow, Rime
Snow
Rain, Dew
Interception
Surface runoff
0.00-0.01
Infiltration
0.01-0.03
Capillary
transport
Gravitational
transport
Sub-Surface runoff
….
TERRA - Structure
Hydrological processes
TERRA - Structure
Hydrological processes
Interception store
Snow store
Soil water
Soil ice
TERRA – Evapotranspiration
(Ament, 2006)
TERRA – Soil water transport
Evolution of the soil liquid water fraction
Richards equation
for the water flux
Hydraulic diffusivity and conductivity are soil type dependent
ICON setup for land-surface
Current experiments for new COSMO version
NAMELIST
LND_NML
LMELT
LMELT_VAR
ITYPE_HEATCOND
IDIAG_SNOWFRAC
ITYPE_EVSL
T
T
3
20
4
ITYPE_ROOT
ITYPE_INTERCEPTION
CWIMAX_ML
ITYPE_HYDBOUND
LSTOMATA
LSEAICE
2
1
5,00E-04
1
T
T
LLAKE
T
ExtPar
Physiographic data
B. Ritter
NWP and Climate models: e.g. ICON R02B07 13 km,
CDE 2.5 km
Physiographic
data
Orography
GLOBE: 1 km
ASTER: 0.03 km
Aerosols: 500 km
NDVI: 5 km
Soil data
DSMW: 10 km
HWSD: 1 km
Lake: 1 km
Surface albedo: 5 km
T2M climatology: 50/500 km
Land use
GLC2000 1 km
GLCC 1 km
GlobCover 0.3 km
Physiographic data on model grid
Impact of physiographic data
LE
H
H
LE
Uncertainties: Land-Sea Mask
GLCC USGS land use / land cover system
GLC2000 land use classes
Globcover 2009
(now used to derive land-sea mask)
GLOBE Orography: HSURF
Land use: LAI_MAX
Land use: Evergreen Forest
Land use: Surface Emissivity
Albedo-MODIS: ALB_DIFF CLIM
Soil-DMSW: Soil Type
COSMO/ICON land-surface processes
and physiographic data
Very efficient land-surface scheme
TERRA
Considers snow, vegetation, frozen
soil
Energy – and water budget
Valid for all Earth‘s climatic zones
Uses physiographic data from
EXTPAR
GB FE 14 – 03/2017