ICON Physics: General Overview Martin Köhler and ICON team ICON physics
Dec 19, 2015
ICON Physics: General Overview
Martin Köhler and ICON team
ICON physics
• The standard Reynolds decomposition and averaging, leads to co-variances that need “closure” or “parametrization”.
• Radiation absorbed, scattered and emitted by molecules, aerosols and cloud droplets plays an important role in the atmosphere and needs parametrization.
• Cloud microphysical processes need “parametrization”.
• Parametrization schemes express the effect of sub-grid processes on resolved variables.• Model variables are U,V,T,q, (l,i,r,s,a)
What is parametrization and why is it needed
1 hour100 hours 0.01 hour
microscaleturbulence
• Diffusive transport in the atmosphere is dominated by turbulence.• Time scale of turbulence varies from seconds to half hour.• Length scale varies from mm for dissipative eddies to 100 m for transporting eddies.• The largest eddies are the most efficient ones for transport.
spectral gap
diurnal cycle
cyclones
data: 1957
Space and Time Scales
courtesy to Anton Beljaars
Space and time scales
Parametrized processes
courtesy to Anton Beljaars
dt
d
z
w
y
v
x
u
gwz
p
z
ww
y
wv
x
wu
t
w
vy
pfu
z
vw
y
vv
x
vu
t
v
ux
pfv
z
uw
y
uv
x
uu
t
u
1
1
1
1
2
2
2
Basic equations
mom.equ.’s
continuity
Reynolds decomposition
'.,'
',' ,'
pPp
wWwvVvuUu
o
Substitute, apply averaging operator, Boussinesq approximation (density in buoyancy terms only) and hydrostatic approximation (vertical acceleration << buoyancy).
Averaging (overbar) is over grid box,i.e. sub-grid turbulent motion is averaged out.
UUuUu 'Property of averaging operator:
1 ' '
1 ' '
o
o
U U U U P u wU V W fV
t x y z x z
V V V V P v wU V W fU
t x y z y z
Reynolds equations
Boundary layer approximation(horizontal scales >> vertical scales), e.g. :
High Reynolds number approximation (molecular diffusion << turbulent transports), e.g.:
z
wu
x
uu
''''
z
wuU
''2
Reynolds Stress
Shear production Turbulenttransport
Buoyancy
Mean flow TKE advection
Turbulent Kinetic Energy equation
2 2 2' 1/ 2( ' ' ' )E u v w local TKE:
Derive equation for E by combining equations of total velocity components and mean velocity components:
Dissipation
Storage
)'''(2/1 222 wvuE mean TKE:
Pressure correlation
' ' ' ' ' ' ' ' ' '
o
E E E EU V W
t x y z
U V g p wE w u w v w w
z z z z
Simple closures
Mass-flux method:
z
UKwu
''
K-diffusion method:
2
2
' 'u w UK K U
z z z z
Uuuz
UuMwu
upup
up
)(''
analogy tomolecular diffusion
mass flux (needs M closure)
entraining plume model
Process Authors Scheme Origin
Radiation
Mlawer et al. (1997)Barker et al. (2002)
RRTM (later with McICA & McSI) ECHAM6/IFS
Ritter and Geleyn (1992) δ two-stream GME/COSMO
Non-orographicgravity wave drag
Scinocca (2003)Orr, Bechtold et al. (2010)
wave dissipation at critical level IFS
Sub-grid scaleorographic drag
Lott and Miller (1997) blocking, GWD IFS
Cloud coverDoms and Schättler (2004) sub-grid diagnostic GME/COSMO
Köhler et al. (new development) diagnostic (later prognostic) PDF ICON
MicrophysicsDoms and Schättler (2004)
Seiffert (2010)prognostic: water vapor, cloud water, cloud ice, rain and snow
GME/COSMO
ConvectionBechthold et al. (2008) mass-flux shallow and deep IFS
Plant, Craig (2008) stochastic based on Kain-Fritsch LMU, Munich
Turbulent transfer
Raschendorfer (2001) prognostic TKE COSMO
Mironov, Mayuskava (new) prognostic TKE and scalar var. ECHAM6
Neggers, Köhler, Beljaars (2010) EDMF-DUALM IFS
Land
Heise and Schrodin (2002), Helmert, Mironov (2008, lake)
tiled TERRA + FLAKE + multi-layer snow
GME/COSMO
Raddatz, Knorr, Schnur JSBACH ECHAM6
Physics in ICON
ICON dynamics-physics cycling
Slow PhysicsSlow Physics
Non-Orographic Gravity Wave
Drag
Non-Orographic Gravity Wave
Drag
Sub-Grid-Scale Orographic DragSub-Grid-Scale
Orographic Drag
Land/Lake/Sea-Ice
Land/Lake/Sea-Ice
dtime
dt_gwd
dt_sso
dt_conv
dt_rad
dtime * iadv_rcf
dt_conv
Fast PhysicsFast Physics
OutputOutput
Tracer AdvectionTracer Advection
DynamicsDynamics
Turbulent DiffusionTurbulent Diffusion
MicrophysicsMicrophysics
Satur. Adjustment
Satur. Adjustment
Satur. Adjustment
Satur. Adjustment
RadiationRadiation
Cloud CoverCloud Cover
ConvectionConvection
„dt_output“
Tendencies
T-tendencies due to solar radiation scheme
[K/day]
Jan. 2012
T-tendencies due to terrestrial radiation scheme
[K/day]
Jan. 2012
T-tendencies due to turbulence scheme
Jan. 2012
[K/day]
T-tendencies due to convection scheme
[K/day]
Jan. 2012
T-tendencies due to SSO+GWD schemes
[K/day]
Jan. 2012
T-tendencies due to microphysics / sat.adj. scheme
[K/day]
Jan. 2012
microphysics saturation adjustment
Jan. 2012
JSBACH Land Surface ModelSchnur, Knurr, Raddatz, MPI Hamburg
JSBACH is the land surface parametrization within the ECHAM physics in the MPI Earth System Model.
Physical processes: Energy and moisture balance at the surface (implicit coupling within vertical
diffusion scheme of atmosphere) 5-layer soil temperatures and hydrology Snow, glaciers Hydrologic discharge (coupling to ocean)
Bio-geochemical processes: Vegetation characteristics represented by Plant Functional Types Phenology Photosynthesis Carbon cycle Nutrient limitation (nitrogen and phosphorus cycles) Dynamic vegetation Land use change
EDMF-DUALM turbulence scheme in ICON
Goals:
turbulence option to ICON that is scientifically and operationally appealing
reference for default TKE scheme
reserach (HeRZ and HD(CP)2)
potential for climate
Martin Köhler and ICON team
DUALM concept: multiple updrafts with flexible area partitioning
N
iuiuiui
upup waw1
)(´´ A
preVOCA: VOCALS at Oct 2006 – Low Cloud
Daniel Klocke‘s Jülich 100m ICON LES run: qc+qi
GCSS process: GEWEX Cloud System Study (1994-2010)
Randall et al, 2003
extra slides
Maike Ahlgrimm: CALIPSO trade cumulus
Tiedtke DUALM
call tree EDMF
3 parcel updrafts (test, sub-cloud, cloud)
mass-flux closure
z0 calculation
exchange coefficients
call TERRA to get land fluxes
ocean cold skin, warm layer description
TOFD, drag from 5m-5km orography
EDMF solvers for qt/T, u/v, tracer (e.g. aerosol)
multiple diagnostics including T2m, gusts
JSBACH in ICONSchnur, Knurr, Raddatz, MPI Hamburg
New development of unified JSBACH code that works with the ICON and ECHAM6 (MPI-ESM1) models.
Has its own svn repository (https://svn.zmaw.de/svn/jsbach) and is pulled into the ICON code on svn checkout/update via svn:externals property
Self-contained model; ICON code itself only contains calls to JSBACH for initialization and surface updating at each time step (src/atm_phy_echam/mo_surface.f90)
Currently, only the physical processes have been implemented in the new JSBACH code; bio-geochemical process to be ported to new code in the coming months
New structures for memory and sub-surface types (tiles) that allow a more flexible handling of surface characteristics and processes: PFTs, bare soil, lakes, glaciers, wetlands, forest management, urban surfaces, etc.
ICON physics upgrades and tunings 2013 Aug-Dec
• Non-orographic gravity wave tuning • Marine surface latent heat flux in TKE scheme - rat_sea • Land surface physics
• Exponential roots• Moisture dependent heat conductivity
• Cloud cover scheme • Tiedtke/Bechtold convection parameters• Bechtold diurnal cycle upgrade • Horizontal diffusion • new TURBDIFF code
non-orographic gravity wave tuninglaunch amplitude x10-3Pa
IFS analysis
URAP observation July 1992(Kristina Fröhlich)
3.75, default
U bias
non-orographic gravity wave drag tuning
1.0
launch amplitude x10-3Pa
3.02.5
2.0
U bias
In TERRA plant roots are a sink constant to a depth dependent on vegetation type.
Now: the uptake of moisture is described exponentially as a function of depth.
The default setting soil level 1-4 are moister than the IFS soil and the levels below 5-8 are dryer after 10 days simulation in July. The new formulation exactly counter acts those IFS/ICON differences with 1-4 becoming dryer and 5-8 becoming moister. So more moisture is left lower down and more is taken out near the top of the soil.
ICON: exponential roots
ICON: moisture dependent soil heat conductivity
Moisture dependent formulation based on Johansen (1975) as described in Peters-Lidard et al (1998, JAS).
The impact is most prominent in the Sahara, which has virtually no soil moisture, because the previous constant formulation was tuned to moist soils. The cooling in the Sahara in the top most soil level and a warming in the lowest dynamic soil level after 24 hours at 00UTC is shown. This night-time near-surface cooling is a signal of a larger diurnal cycle resulting from a smaller ground heat flux..
default level 2 moisture dependency level 2
default level 7 moisture dependency level 7