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2007

90 record(s)
 
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  • Model system ALADIN, 18km horizontal resolution, 37 levels in vertical, LOPEZ microphysics etc. Ensemble system with 16 members. 2 runs per day at 00, 12 UTC, Initial perturbation: Downscaling of ECMWF Singular vector perturbation Lateral boundary perturbation: Coupling with the ECMWF EPS system Domain of products: Latitude: 38.53---54.98, 0.15 deg grid space, 110 grids; Longitude: 2.55---31.8, 0.15 deg. grid space, 196 grids Every 3 hours, from 0 to 48 hours forecast. Grid description: quadratic grid, it is the Lambert Projection DDOM: xfirst: 2.55 yfirst: 42.95 xsize: 105.0 ysize: 49.0 xinc: 0.15 yinc: 0.15 xnpole: 0.0 ynpole: 0.0

  • - preoperational model (planned to become operational in 2008) - configuration: Runge Kutta time integration scheme (dt=20sek); multi layer soil module; no parameterized deep convection; 60 levels; prognostic TKE, rain, snow and graupel - model runs are started at 00UTC 03UTC 09UTC 12UTc and 18UTC. Forecast range is 24h, except 09 and 18 run ranging upt to 30h. To complete the timeseries, dummy text files have been generated for 06UTC, 15UTC, 21UTC. Missing time steps are filled with dummy text files as well. Note: From 12th of July 2007 on, +24h forecasts are produced for 06, 15 and 21 UTC as well. Grid description: CDOM: xfirst: -2.76 yfirst: -0.02 xsize: 174.0 ysize: 141.0 xinc: 0.02 yinc: 0.02 xnpole: -170.0 ynpole: 43.0 DDOM: xfirst: -5.5 yfirst: -3.8 xsize: 500.0 ysize: 330.0 xinc: 0.02 yinc: 0.02 xnpole: -170.0 ynpole: 43.0

  • The forecasting chain is based on the 00 UTC, GFS forecasts at 0.5 degree resolution. The chain comprises the hydrostatic model BOLAM, which is driven directly by the global model, and the non-hydrostatic model MOLOCH (horizontal resolution 0.02 degrees), which is nested in cascade using a 1-way nesting procedure. BOLAM run starts at 00 UTC, MOLOCH is nested at 09 UTC. MOLOCH domain is smaller than official DPHASE domain. A 39-h MOLOCH forecast is provided daily. Only a sub-set of TIGGE list is provided (see DS). More information available here: http://www.isac.cnr.it/~dinamica/ Grid description: lat-lon Arakawa C grid. Rotated equidistant grid. DDOM: xfirst: -2.69 yfirst: -1.84 xsize: 340.0 ysize: 290.0 xinc: 0.02 yinc: 0.02 xnpole: -171.0 ynpole: 44.7

  • Non hydrostatic model Moloch, developed at ISAC CNR and operational at ARPAL CFMI-PC. Initial and boundary conditions provided by the model chain based on bolam and initialized with the 00 UTC ECMWF run. Grid description: DDOM: xfirst: -1.99 yfirst: -1.93 xsize: 200.0 ysize: 194.0 xinc: 0.02 yinc: 0.02 xnpole: -171.0 ynpole: 45.0

  • The Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data (HOAPS) set is a completely satellite based climatology of precipitation, evaporation and freshwater budget (evaporation minus precipitation) as well as related turbulent heat fluxes and atmospheric state variables over the global ice free oceans. All variables are derived from SSM/I passive microwave radiometers, except for the SST, which is taken from AVHRR measurements. The data set includes multi-satellite averages, inter-sensor calibration, and an efficient sea ice detection procedure. Changes in this version are a prolonged time series, now containing data from 1987 to 2005, a new neural network based precipitation algorithm, and inclusion of the RSMAS/NODC Pathfinder Version 5 SST fields. Additionally a new 85 GHz synthesis procedure has been implemented for the time period to compensate for the missing channel information on DMSP F08, see accuracy report. Apart from monthly and pentad (5-day) means on a global 0.5 deg. x 0.5 deg. grid, twice daily multi-satellite composite data on a global 1 x 1 grid are available.

  • ALADIN is the operational model at Meteo-France. The horizontal resolution is 9.5km, the time step : 415s with a Semi-lagrangian scheme. There are 46 vertical levels with 15 levels below 3000m. The domain of the integration is : (-11.84W, 33.14E) (25N,56.95N) Physical parameterization: - the micro-physics scheme use 4 prognostic variables: liquid and ice cloud water, rain and snow. - the convection scheme is based on Bougeault (1985) with a donwdraft parameterization. - the operational ECMWF radiation code which is called every 60 minutes. - the burbulence is based on Louis's function with an interactive mixing length. ALADIN is coupled with ARPEGE every 3 hours and has its own assimilation system based on 3DVAR. The post-processing in GRIB files is done on a regular LAT-LON Grid with a 0.1 deg resolution on the DPHASE domain. ALADIN-FRANCE daily performs 54h forecasts starting at 0TU, 6TU, 12TU, 18TU (only the 0UTC forecast until 30h is sent) Grid description: DDOM: xfirst: 2.0 yfirst: 43.0 xsize: 161.0 ysize: 71.0 xinc: 0.1 yinc: 0.1 xnpole: 0.0 ynpole: 0.0

  • 72h forecast with MM5 V3.7, nested run using - mm5_60 run as input - 15km x 15km resolution - 77 x 73 Grids - Noah land-surface scheme - MRF PBL - Grell cumulus scheme - Graupel (Reisner2) explicit moisture scheme - Cloud for atmospheric radiation Grid description: DDOM: xfirst: 2.800095 yfirst: 42.172424 xsize: 76.0 ysize: 72.0 xinc: 0.02 yinc: 0.14 xnpole: 0.0 ynpole: 0.0

  • COSMO-SREPS (csreps) is a high-resolution ensemble system for the short-range (up to three days). The system consists of 16 integrations of the non-hydrostatic limited-area model COSMO. The model is run at about 10 km of horizontal resolution, with 40 levels in the vertical. The ensemble is generated by taking into account different sources of forecast errors, in order to describe the uncertainty affecting the scales of interest in the high-resolution weather forecast at the considered time range. Initial and boundary conditions perturbations are provided by some members of the Multi-Analysis Multi-Boundary SREPS system of INM: the 10-km COSMO runs of COSMO-SREPS are driven by the four lower resolution (25 km) COSMO runs provided by INM, nested on four different global models (IFS, GME, NCEP, UM) which use independent analyses. Each of the four 25-km COSMO run provides initial and boundary conditions (3-hourly) to four 10-km COSMO runs, which are differentiated by applying different model perturbations. Four parameters of the schemes used for the parameterisation of the sub-grid processes are randomly changed, within their range of variability, in the ensemble members. Grid description: DDOM: xfirst: -6.02 yfirst: -7.0 xsize: 135.0 ysize: 83.0 xinc: 0.09 yinc: 0.09 xnpole: 190.0 ynpole: 40.0

  • - operational model of MeteoSwiss - configuration: Leap frog time integration; Tiedtke convection scheme with moisture convergence closure; two layer soil module (likely to be changed during DOP); prognostic TKE, qr and qs; no graupel scheme - forecast range 72h starting at 00UTC and 12UTC. Missing time steps are filled with dummy text files. Grid description: DDOM: xfirst: -6.1875 yfirst: -14.625 xsize: 201.0 ysize: 121.0 xinc:0.0625 yinc: 0.0625 xnpole: -170.0 ynpole: 32.5

  • This dataset contains reconstructions of land use and land cover from AD 800 to 1992 in global coverage at 30 minute resolution. After AD 1700, the data is based on Ramankutty and Foley (1999), Foley et al. (2003) and Klein Goldewijk (2001); for earlier times, land use is estimated with a country-based method that uses national population data (McEvedy and Jones, 1978) as a proxy for agricultural activity. For each year, a map is provided that contains 14 fields. Each field holds the fraction the respective vegetation type covers in the total grid cell (0-1). The vegetation types comprise three human land use types (crop, C3 pasture and C4 pasture) and 11 natural vegetation types (based on the potential vegetation map of Ramankutty and Foley, 1999). For the time period prior to AD 1700 two additional land cover scenarios are provided (scenmin and scenmax). They quantify the uncertainties associated with this approach, through technological progress in agriculture and uncertainties in population estimates. The additional datasets combine the known uncertainties in a way to give the most extreme range for possible estimates of land use area for each year before 1700. The datasets thus do not represent consistent time series of plausible alternative scenarios, but indicate, for each year, a maximum range outside which estimates of land use area are unrealistic. See citations and references for details. Vegetation types: 1 Tropical evergreen forest 2 Tropical deciduous forest 3 Temperate evergreen broadleaf forest 4 Temperate/boreal deciduous broadleaf forest 5 Temperate/boreal evergreen conifers 6 Temperate/boreal deciduous conifers 7 Raingreen shrubs 8 Summergreen shrubs 9 C3 natural grasses 10 C4 natural grasses 11 Tundra 12 Crop 13 C3 pasture 14 C4 pasture