ICON Physics General Overview Martin Khler and ICON

ICON Physics: General Overview Martin Köhler and ICON team ICON physics

What is parametrization and why is it needed • 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)

Space and Time Scales • 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. cyclones microscale turbulence diurnal cycle spectral gap data: 1957 100 hours 1 hour 0. 01 hour

Space and time scales courtesy to Anton Beljaars

Parametrized processes courtesy to Anton Beljaars

Basic equations mom. equ. ’s continuity

Reynolds decomposition 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. Property of averaging operator:

Reynolds equations Boundary layer approximation (horizontal scales >> vertical scales), e. g. : High Reynolds number approximation (molecular diffusion << turbulent transports), e. g. : Reynolds Stress

Turbulent Kinetic Energy equation local TKE: mean TKE: Derive equation for E by combining equations of total velocity components and mean velocity components: Storage Mean flow TKE advection Pressure correlation Turbulent transport Shear production Buoyancy Dissipation

Simple closures K-diffusion method: analogy to molecular diffusion Mass-flux method: mass flux (needs M closure) entraining plume model

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 Mc. ICA & Mc. SI) ECHAM 6/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, Mayuskava (new) prognostic TKE and scalar var. ECHAM 6 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 ECHAM 6

ICON dynamics-physics cycling Dynamics Tracer Advection Tendencies 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 Sub-Grid-Scale Orographic Drag dt_sso Land/Lake/Sea-Ice Satur. Adjustment Slow Physics Output „dt_output“

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 [K/day] Jan. 2012

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] microphysics saturation adjustment Jan. 2012

JSBACH Land Surface Model Schnur, 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 Martin Köhler and ICON team Goals: § turbulence option to ICON that is scientifically and operationally appealing § reference for default TKE scheme § reserach (He. RZ and HD(CP)2) § potential for climate

DUALM concept: multiple updrafts with flexible area partitioning

pre. VOCA: VOCALS at Oct 2006 – Low Cloud

Daniel Klocke‘s Jülich 100 m 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 § z 0 calculation § exchange coefficients § call TERRA to get land fluxes § ocean cold skin, warm layer description § TOFD, drag from 5 m-5 km orography § EDMF solvers for qt/T, u/v, tracer (e. g. aerosol) § multiple diagnostics including T 2 m, gusts

JSBACH in ICON Schnur, Knurr, Raddatz, MPI Hamburg New development of unified JSBACH code that works with the ICON and ECHAM 6 (MPI-ESM 1) 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. f 90) 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 tuning launch amplitude x 10 -3 Pa 3. 75, default U bias IFS analysis URAP observation July 1992 (Kristina Fröhlich)

non-orographic gravity wave drag tuning launch amplitude x 10 -3 Pa 1. 0 2. 0 U bias 2. 5 3. 0

ICON: exponential roots 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: moisture dependent soil heat conductivity default level 2 moisture dependency level 2 default level 7 moisture dependency level 7 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 00 UTC is shown. This night-time near-surface cooling is a signal of a larger diurnal cycle resulting from a smaller ground heat flux. .