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2007

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    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

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    The experiment CLM_C20_2_D3 contains European regional climate simulations of the years 1960-2000 on a regular geographical grid. The data are generated during post processing of the corresponding data stream 2 experiment (CLM_C20_2_D2) of regional climate model runs (CLM non hydrostatic, see http://www.clm-community.eu ). The simulations of the 20th century (1960-2000) have been forced by the second (_2_) run of the global 20th century climate (EH5-T63L31_OM-GR1.5L40_20C_2_6H) with observed anthropogenic forcing. In data stream 3 (_D3) the output variables of CLM data stream 2 and some additionally derived parameters are stored as time series on a regular grid with a horizontal spacing of 0.2 degree. The model parameters have been transformed onto the regular geographical grid by the CDO routines. Please note, that none of the variables has been corrected for topographical differences between the two grids. The model domain of data stream 3 covers the European region starting at 34.6/-10.6 (lat/lon, centre of lower left grid box) with an increment of 0.2 degree. The number of grid points is 177/238 (lat/lon). For some model variables and additionally derived parameters some statistics on daily, monthly or yearly basis are available. See also http://sga.wdc-climate.de for a list of available parameters. Please contact sga"at"dkrz.de for data request details. See http://sga.wdc-climate.de for more details on CLM simulations in the context of the BMBF funding priority "klimazwei", some useful information on handling climate model data and the data access regulations. The output format is netCDF Experiment with CLM 2.4.11 on NEC-SX6(hurrikan) raw data: hpss:/dxul/ut/k/k204095/prism/experiments/C20_2

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    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 http://www.hoaps.org/.

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    The SRNWP-PEPS consists of 21 different operational limited area models: Weather Service / Limited Area Model / Resolution [km] / Coupling Model / Forcast Period / Time Interval [h] / Main Run [UTC] Denmark HIRLAM 16 ECMWF +60h 1 0, 6, 12, 18 Finland HIRLAM 22 ECMWF +54h 1 0, 6, 12, 18 Ireland HIRLAM 16 ECMWF +48h 3 0, 6, 12, 18 Netherlands HIRLAM 22 ECMWF +48h 1 0, 6, 12, 18 Spain HIRLAM 18 ECMWF +48h 1 0, 6, 12, 18 Norway HIRLAM 22 ECMWF +30h 1 0, 12 Sweden I HIRLAM 11 ECMWF +48h 3 0, 6, 12, 18 Sweden II HIRLAM 22 ECMWF +48h 3 0, 6, 12, 18 Belgium ALADIN 15 ARPEGE +60h 1 0, 12 Austria ALADIN_A 9.6 ARPEGE +48h 1 0, 12 France ALADIN_F 11 ARPEGE +48h 3 0, 12 Croatia ALADIN_L 8.9 ARPEGE +48h 3 0, 12 Czech Rep. ALADIN_L 11 ARPEGE +48h 1 0, 12 Hungary ALADIN_L 11 ARPEGE +48h 1 0, 12 Slovakia ALADIN_L 11 ARPEGE +48h 3 0, 12 Slovenia ALADIN_L 9.5 ARPEGE +48h 3 0, 12 United Kingdom UKMO-LAM 12 UM global +48h 3 0, 6, 12, 18 Germany LME 7 GME +78h 1 0, 12 // Germany LME 7 GME +48h 1 6, 18 Switzerland aLMo 7 ECMWF +72h 1 0, 12 Italy EuroLM 7 EuroHRM +60h 3 0, 12 Poland LM 14 GME +72h 3 0, 12 The relation between these models and the numbers of the SRNWP PEPS ensemble is anonymous. The SRNWP-PEPS 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 PEPS domain. THE PLEV data set could not be provided for PEPS. Grid description: xsize,ysize,xinc, yinc differ for ensemble members (see datasets) CDOM: xfirst: 6.0 yfirst: 47.0 xnpole: 0.0 ynpole: 0.0 DDOM: xfirst: 2.0 yfirst: 43.0 xnpole: 0.0 ynpole: 0.0

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    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

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    Monthly averages are calculated for each stationary points using data collected by voluntary observing ships in the South China Sea. The Following table shows the station names and the ranges where samples are collected within. ---------------------------------------------------------------- Station name, Location, Range ---------------------------------------------------------------- South China Sea (03N), 03N 105E, [ 1.50N, 4.50N], 105.0E South China Sea (06N), 06N 107E, [ 4.50N, 7.50N], 107.0E South China Sea (09N), 09N 109E, [ 7.50N,10.50N], 109.0E South China Sea (12N), 12N 111E, [10.50N,13.50N], 111.0E South China Sea (15N), 15N 113E, [13.50N,16.50N], 113.0E South China Sea (18N), 18N 113E, [16.50N,19.50N], 113.0E South China Sea (21N), 21N 114E, [19.50S,22.50N], 114.0E ----------------------------------------------------------------

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