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ICON Physics: General Overview

Learn about the importance of parametrization in atmospheric physics and the different space-time scales involved in the ICON model. Explore the various parametrization schemes used to account for sub-grid processes and the role of turbulence in diffusive transport. Discover the contributions of radiation, cloud microphysics, and other processes in ICON physics.

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ICON Physics: General Overview

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

  2. 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)

  3. 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 100 hours 1 hour 0.01 hour data: 1957

  4. courtesy to Anton Beljaars Space and time scales

  5. Parametrized processes courtesy to Anton Beljaars

  6. Basic equations mom. equ.’s continuity

  7. Averaging (overbar) is over grid box, i.e. sub-grid turbulent motion is averaged out. Property of averaging operator: Reynolds decomposition Substitute, apply averaging operator, Boussinesq approximation (density in buoyancy terms only) and hydrostatic approximation (vertical acceleration << buoyancy).

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

  9. 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

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

  11. Physics in ICON

  12. ICON dynamics-physics cycling Tendencies Dynamics dtime Tracer Advection dtime * iadv_rcf Fast Physics Satur. Adjustment Convection dt_conv Land/Lake/Sea-Ice Cloud Cover dt_conv Turbulent Diffusion Microphysics Radiation dt_rad Satur. Adjustment Non-Orographic Gravity Wave Drag dt_gwd Slow Physics Sub-Grid-ScaleOrographic Drag dt_sso Output „dt_output“

  13. T-tendencies due to solar radiation scheme [K/day] Jan. 2012

  14. T-tendencies due to terrestrial radiation scheme [K/day] Jan. 2012

  15. T-tendencies due to turbulencescheme [K/day] Jan. 2012

  16. T-tendencies due to convection scheme [K/day] Jan. 2012

  17. T-tendencies due to SSO+GWD schemes [K/day] Jan. 2012

  18. T-tendencies due to microphysics / sat.adj. scheme [K/day] microphysics saturation adjustment Jan. 2012 Jan. 2012

  19. 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

  20. 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 (HeRZ and HD(CP)2) • potential for climate

  21. DUALM concept: multiple updrafts with flexible area partitioning

  22. preVOCA: VOCALS at Oct 2006 – Low Cloud

  23. Daniel Klocke‘s Jülich 100m ICON LES run: qc+qi

  24. GCSS process: GEWEX Cloud System Study (1994-2010) Randall et al, 2003

  25. extra slides

  26. Maike Ahlgrimm: CALIPSO trade cumulus Tiedtke DUALM

  27. 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

  28. JSBACH in ICON Schnur, 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.

  29. 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

  30. non-orographic gravity wave tuning 3.75, default launch amplitude x10-3Pa U bias IFS analysis URAP observation July 1992 (Kristina Fröhlich)

  31. non-orographic gravity wave drag tuning launch amplitude x10-3Pa 1.0 2.0 U bias 3.0 2.5

  32. 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.

  33. 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 00UTC is shown. This night-time near-surface cooling is a signal of a larger diurnal cycle resulting from a smaller ground heat flux..

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