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Vincent N. Sakwa RSMC, Nairobi
KMD Consortium for Small-Scale Modeling (COSMO) Strengths and Weaknesses Vincent N. Sakwa RSMC, Nairobi
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Overview KMD Runs a 7km COSMO over Eastern Africa
Links Trends at global NWP centers Trends in regional NWP General Model information and configuration Show this for those interested Strengths Weaknesses
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Trends at global NWP centers
In 2012 the resolution of global NWP models will be around 16 km (ECMWF), 20km (DWD, JMA), 25 km (KMA, UKMO) and 30 km (CMC). In 2020 the resolution of most global NWP models will be around 10km and the number of layers will be around 100 or more Global NWP centers will use sophisticated, ensemble-based data assimilation systems to derive the initial state of the atmosphere.
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Trends in regional NWP Regional high resolution data assimilation at grid spacing <10km with short data cut-off times using local data not available to global centres. Convection permitting/resolving models at grid spacing of 2 to 4km without the parameterization of deep convection (e.g. COSMO-DE at DWD). Data assimilation for convection permitting/resolving models using radar data (e.g. latent heat nudging in COSMO-DE) Short range regional ensemble prediction systems (SREPS) at grid spacing < 10 km, e.g COSMO-SREPS.
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General KMD COSMO COSMO MODEL RUN SUMMARY Single Domain ~7km
434x251 grid points 60 vertical levels Model top 50 hPa Forecast length 72 hours but can do 120 hours Output frequency is 1 hours Lateral boundaries updated every 3h (GME)
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Model Physics -two stream radiation scheme (Ritter and Geleyn, 1992) including long- and shortwave fluxes in the atmosphere and at the surface; full cloud - radiation feedback; diagnostic derivation of partial cloud cover (rel. hum. and convection) Grid-scale precipitation scheme including parameterized cloud microphysics (Doms and Schättler, 1997) Two different mass flux convection schemes (Tiedtke, 1989 or Bechtold, 2001) differentiating between deep, shallow and mid-level convection Subgrid-scale orography (SSO) scheme (Lott and Miller, 1997) Level-2 scheme of vertical diffusion in the atmosphere, similarity theory (Louis, 1979) at the surface Seven-layer soil model including snow and interception storage
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COSMO Dynamics Dynamics : Non-Hydrostatic, fully compressible, advection form. Reference state: hydrostatic, stationary (v=0) Prognostic variables: ‘Cartesian’ wind components u, v, w (spherical base vectors) pressure perturbation p’, Temperature T’ humidity var. q Coordinate systems: rotated geographical coordinates generalized terrain-following height coordinate user-defined vertical stretching
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KMD COSMO Strengths High resolution model run relative to global model
Allows higher horizontal resolution (<7km grid spacing), esp. in mountainous terrain. Non-hydrostatic model Theoretically improves forecasts of convection. Convection resolving (<3 km) possible which is necessary to simulate deep convection explicitly But resolution ~7km requires convective parameterization scheme.(Kain-Fritsch CPS) Alternate solution to GME Allows to assess uncertainty based on differences Sophisticated cloud microphysics scheme including the advection of hydrometeors (rain, snow, graupel) Much better scalability on massively parallel computer systems.
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Strengths Uses GME for both COSMO is of finer resolution than the GME
Lateral boundary conditions and boundary conditions COSMO is of finer resolution than the GME And has different physics Thus provides alternate solution Areas of difference provide information about uncertainty May improve convective forecasts and thus QPF Represents the atmosp in 3 Dimension
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KMD COSMO Weaknesses Local Area Model Availability
Relies on 6-hour LBC’s from Global model Uses Global model to initiate forecast Availability Run twice daily off GFS 0000/1200 UTC cycle Forecasts to 72 hours in length takes considerable time to become available Still mesoscale not in the realm of storm scale (=<3km) Deep convection still a challenge Topography issues (surface representation)
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General Links http://www.meteo.go.ke/nwp/cosmo/index.html
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