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  • The D-Phase MicroPEPS is a LAF-Ensemble (lagged average forecast) that is based upon 5 different high resolution models: COSMOCH2 LMK AROME CMCGEMH ISACMOL2 The individual members can be found in the respective experiments 'dphase_*' in this data base. As time lagged forecasts the initialisation times t-3h and t-6h relative to the reference time t are incorporated. In a maximum the MicroPEPS might have 9 members (COSMOCH2: 3, LMK: 3, AROME: 1, CMCGEMH: 1, ISACMOL: 1). While COSMOCH2 and LMK generate new forecasts every 3 hours the other models run less frequently. In the 6 hour MicroPEPS time window AROME, CMCGEMH and ISACMOL provide one run each. During operation the ensemble size might change due to the availability of the forecasts. The MicroPEPS uses equal weights for averaging its members. The MicroPEPS generates probability forecasts by interpreting the overlapping areas of the single forecasts as members of a local ensemble. Due to the different domains of the deterministic models the size of the ensemble depends on location. Hence the quality of the forecasted probability distributions varies over the domain. There will be four runs a day at 0, 6, 12 and 18 UTC. Grid description: CDOM: xfirst: 6.0 yfirst: 47.0 xsize: 168.0 ysize: 151.0 xinc: 0.03 yinc: 0.02 xnpole: 0.0 ynpole: 0.0 DDOM: xfirst: 2.0 yfirst: 43.0 xsize: 535.0 ysize: 351.0 xinc: 0.03 yinc: 0.02 xnpole: 0.0 ynpole: 0.0

  • INMSREPS is 20 Member Multi-Model, Multi-Boundaries on 0.25 degree horizontal resolution with 40 vertical levels running twice a dayat 00 and 12 UTC. Forecast from HH+00h upto HH+72 h (with 6hourly forecast output). The 20 members are labeled with abbreviations, which denote the combination between limited area model (LAM)(first character) and global model condition (the next two characters): LAMs: H means HRM, I means HIRLAM, M means MM5, L means Lokal Model (COSMO) and U means Unified Model. GLOBAL CONDITIONS: AV means GFS (AVN), EC means ECMWF, GM means GME, UK means UKMO. This results in the following combinations: HAV,HEC,HGM,HUK,IAV,IEC,IGM,IUK,MAV,MEC,MGM,MUK,LAV,LEC,LGM,LUK,UAV,UEC,UGM,UUK. The 20 ensemble members are interpolated to a common verification area with 0.25 degree horizontal grid resolution, there is no FIX data set for this system. Grid description: DDOM: xfirst: 2.0 yfirst: 43.0 xsize: 65.0 ysize: 29.0 xinc: 0.25 yinc: 0.25 xnpole: 0.0 ynpole: 0.0

  • dphase_prevah The hydrological model PREVAH is adopted for (ensemble) runoff forecasts for several basins in Switzerland and North Italy. Runoff nowcasting is driven by observed meteorology consisting of data from meteorological stations and operational radar precipitation data. Forecasts are computed with three deterministic NWP models and with one atmospheric ensemble predictions system (EPS). Principal investigators are the Institute for Atmospheric and Climate Sciences of the ETH (IAC_ETH) and the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL). Data providers: Observed meteorology: MeteoSwiss, WSL, IST-SUPSI Rainfall Radar: MeteoSwiss CLEPS, COSMOCH2 and COSMOCH7: MeteoSwiss MM5_15: FZK, IMK-IFU Observed discharge: Swiss Federal Office for Environment (FOEN), CONTICINO Basins: Verzasca_at_Lavertezzo, Ticino_at_Bellinzona, Maggia_at_Solduno, Tresa_at_Rocchetta, Toce_at_Candoglia, Ticino_at_Miorina, Thur_at_Andelfingen, Linth_at_Mollis Sub-Experiments: Runoff nowcasting, CLEPS, COSMOCH2 and COSMOCH7 at all basins MM5_15 and Rainradar only at Verzasca_at_Lavertezzo, Thur_at_Andelfingen, Linth_at_Mollis

  • The Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data (HOAPS) set is a completely satellite based climatology of precipitation, turbulent heat fluxes and freshwater budget (evaporation minus precipitation) as well as related athmospheric 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 dataset includes multi-satellite averages, inter-sensor calibration, and an efficient sea ice detection procedure. Changes in this version are a longer 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, making a continuous time series for all parameters for the whole time series possible. This dataset contains 1 degree twice daily globally gridded multi-satellite composite products, providing high temporal resolution. Each grid-cell contains data from only one satellite pass, there is no average from two or more satellites. Early passes are overwritten by later passes. This method provides more spatial homogeneity than averaging all available data. The fields are stored for 0-12 and 12-24 UTC. Timesteps in the data files are at 0 UTC (0-12 UTC overpasses) and 12 UTC (12-24 UTC overpasses). Each grid-cell contains the average of data from the satellite that passed this gridbox closest to 12 and 24 UTC, respectively. Other gridded data sets available are pentad (5-day) and monthly means on a global 0.5 deg. x 0.5 deg. grid. For more information see

  • COSMO-ME is the high-resolution operational implementation of COSMO Model at the National Meteorological Service of Italy. The model domain covers most of continental Europe and the entire Mediterranean Basin. The horizontal resolution is 7km (0.0625deg) with 40 vertical levels. The model is routinely run on the ECMWF super-computer once a day at 00Z with hourly output. The initial conditions are interpolated from the Italian Met. Service 3DVAR-FGAT data assimilation system. The boundary conditions (BC) are provided by IFS global model. Grid description: DDOM: xfirst: -5.875 yfirst: -14.312 xsize: 194.0 ysize: 112.0 xinc: 0.0625 yinc: 0.0625 xnpole: -170.0 ynpole: 32.5

  • The forecasting chain is based on the 18 UTC, ECMWF forecasts at 0.25 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 18 UTC, MOLOCH is nested at 00 UTC. MOLOCH domain is smaller than official DPHASE domain. A 48-h MOLOCH forecast is provided daily. Only a sub-set of TIGGE list is provided (see DS). More information available here: Grid description: lat-lon Arakawa C grid. Rotated equidistant grid. DDOM: xfirst: -3.5 yfirst: -14.0 xsize: 330.0 ysize: 290.0 xinc: 0.021 yinc: 0.02 xnpole: -170.0 ynpole: 32.5

  • Forecast data are modelled by a 30-km parallel version of the hydrostatic BOlogna Limited Area Model (BOLAM) operational at the National Agency for Environmental Protection and Technical Services (APAT) at Rome (Italy). This version, referred as 30-km QBOLAM model, is the driving model of the 11-km QBOLAM model which is described in the dphase_qbolam11 experiment. For DPHASE project, forecast data are provided over a subdomain (refered as DDOM) of the original domain (which covers the entire Mediterranean Basin). Not all the meteorological fields selected for the experiment are provided, since some of these are not produced by the QBOLAM model. Initial and boundary conditions for a 60-h QBOLAM33 forecast are derived from the European Centre for Medium-Range Weather Forecasts analysis and forecast issued at 1200 UTC on the previous day. Grid description: Please note that the westermost longitude and the southermost latitude points refer to the sub-domain chosen for MAP DPHASE. The QBOLAM original domain covers the Mediterranean Basin. DDOM: xfirst: -10.2 yfirst: 4.2 xsize: 54.0 ysize: 40.0 xinc: 0.3 yinc: 0.3 xnpole: -167.5 ynpole: 51.5

  • This experiment contains forecasts from the LMK (COSMO-DE) high resolution model of DWD (2.8km horizontal resoultion and 50 model levels). Model runs are started every 3h at 00, 03, 06, 09, 12, 15, 18 and 21 UTC with a forecast range of +18h. LMK (COSMO-DE) is an operational forecast model of DWD. Therefore, we adapted the output of the model as close as possible to the tigge+ list, but there are some differences; see dataset summaries. For a detailed description of the LMK (COSMO-DE) model, please contact the originator of the data. All datasets for COPS in the database have an output frequency of 15 minutes. If the variables are not provided by LMK (COSMO-DE) with an output frequency of 15 minutes then the hourly output has been linearily interpolated in time. LMK (COSMO-DE) provides only a subset of the TIGGE+ variables with an output frequency of 15 minutes. These are: Total precipitation (all types) (kg/m**2) acc_st 011 002 TPT2 Precipitation: grid-scale only, rain (kg/m**2) acc_st 102 201 SURF Precipitation: grid-scale only, snow (kg/m**2) acc_st 079 002 SURF Precipitation: grid-scale only, graupel (kg/m**2) acc_st 132 201 SURF Precipitation rate: grid-scale only, rain (kg/s/m**2) inst 100 201 SURF Precipitation rate: grid-scale only, snow (kg/s/m**2) inst 100 201 SURF Precipitation rate: grid-scale only, graupel (kg/s/m**2) inst 100 201 SURF Total column water vapour (or precipitable water) (kg/m**2) inst 054 002 SURF Total column cloud water (or cloud water) (kg/m**2) inst 076 002 SURF Total column cloud ice (or cloud ice) (kg/m**2) inst 058 002 SURF W-velocity (m/s) inst 040 002 MUVW Grid descitption: CDOM: xfirst: -2.73 yfirst: -2.927 xsize: 135.0 ysize: 118.0 xinc: 0.025 yinc: 0.025 xnpole: -170.0 ynpole: 40.0 DDOM: xfirst: -5.882 yfirst: -6.685 xsize: 441.0 ysize: 279.0 xinc: 0.025 yinc: 0.025 xnpole: -170.0 ynpole: 40.0

  • The Canadian Meterological Centre (CMC) is running the Global Environmental Multiscale (GEM) model in limited-area mode for the duration of the MAP D-PHASE project (1 June - 31 November 2007). The model is run once-daily directly from operational GEM meso-global forecast data (grid spacing of 33 km). A pair of domains are used for the project with horizontal grid spacings of 15 km and 2.5 km. This outer (low resolution or driving) grid is initialized daily at 0000 UTC and covers all of Europe, out to the British Isles, the North Sea, and Nortern Africa. The timestep for this forecast is 300 sec and outputs are available hourly. No regional analysis or data assimilation cycle is undertaken during this project. All observational data will therefore be ingested only indrectly in the regional setup through the outer grid initialization and hourly boundary updates from the meso-global model. The GEM model is a semi-implicit, semi-Lagrangian, two time-level, non-hydrostatic model that runs in a wide variety of configurations. An updated version (v3.3.0) of the GEM model is being used for the MAP D-PHASE project in preparation for the Vancouver 2010 Olympic Games project. This version takes advantage of recent developments designed to enhance the quality of guidance over regions of steeply-sloping orography, including the addition of a 6-category bulk microphysics scheme and time-varying orography over the initialization period. For more information on -the GEM model dynamics: see Cote et al (1998) [Mon. Wea. Rev.]. -the model physics package: contact Recherche en Prevision Numerique for the related technical document by Mailhot. -the model's microphysics scheme: see Milbrandt and Yau (2007) [Mon. Wea. Rev.]. Grid description: DDOM: xfirst: 2.0 yfirst: 43.0 xsize: 201.0 ysize: 101.0 xinc: 0.08 yinc: 0.07 xnpole: 0.0 ynpole: 0.0

  • 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