noVolc1985 is an experiment of the CMIP5 - Coupled Model Intercomparison Project Phase 5 ( https://pcmdi.llnl.gov/mips/cmip5 ). CMIP5 is meant to provide a framework for coordinated climate change experiments for the next five years and thus includes simulations for assessment in the AR5 as well as others that extend beyond the AR5. noVolc1985 (1.3 hindcast without volcanoes (1985)) - Version 2: Hindcast without volcanoes. Additional 10yr run for experiment 1.1 from 1985 without including the Agung, El Chichon and Pinatubo eruptions. Experiment design: https://pcmdi.llnl.gov/mips/cmip5/experiment_design.html List of output variables: https://pcmdi.llnl.gov/mips/cmip5/datadescription.html Output: time series per variable in model grid spatial resolution in netCDF format Earth System model and the simulation information: CIM repository Entry name/title of data are specified according to the Data Reference Syntax ( https://pcmdi.llnl.gov/mips/cmip5/docs/cmip5_data_reference_syntax.pdf ) as activity/product/institute/model/experiment/frequency/modeling realm/MIP table/ensemble member/version number/variable name/CMOR filename.nc .
Historical monthly models of mean minimum temperature and maximum temperature, and total precipitation
rcp26 is an experiment of the CMIP5 - Coupled Model Intercomparison Project Phase 5 ( https://pcmdi.llnl.gov/mips/cmip5 ). CMIP5 is meant to provide a framework for coordinated climate change experiments for the next five years and thus includes simulations for assessment in the AR5 as well as others that extend beyond the AR5. 4.3 rcp26 (4.3 RCP2.6) - Version 1: Future projection (2006-2100) forced by RCP2.6. RCP2.6 is a representative concentration pathway which approximately results in a radiative forcing of 2.6 W m-2 at year 2100, relative to pre-industrial conditions. Experiment design: https://pcmdi.llnl.gov/mips/cmip5/experiment_design.html List of output variables: https://pcmdi.llnl.gov/mips/cmip5/datadescription.html Output: time series per variable in model grid spatial resolution in netCDF format Earth System model and the simulation information: CIM repository Entry name/title of data are specified according to the Data Reference Syntax ( https://pcmdi.llnl.gov/mips/cmip5/docs/cmip5_data_reference_syntax.pdf ) as activity/product/institute/model/experiment/frequency/modeling realm/MIP table/ensemble member/version number/variable name/CMOR filename.nc .
rcp85 is an experiment of the CMIP5 - Coupled Model Intercomparison Project Phase 5 ( https://pcmdi.llnl.gov/mips/cmip5 ). CMIP5 is meant to provide a framework for coordinated climate change experiments for the next five years and thus includes simulations for assessment in the AR5 as well as others that extend beyond the AR5. 4.2 rcp85 (4.2 RCP8.5) - Version 1: Future projection (2006-2100) forced by RCP8.5. RCP8.5 is a representative concentration pathway which approximately results in a radiative forcing of 8.5 W m-2 at year 2100, relative to pre-industrial conditions. RCPs are time-dependent, consistent projections of emissions and concentrations of radiatively active gases and particles. Experiment design: https://pcmdi.llnl.gov/mips/cmip5/experiment_design.html List of output variables: https://pcmdi.llnl.gov/mips/cmip5/datadescription.html Output: time series per variable in model grid spatial resolution in netCDF format Earth System model and the simulation information: CIM repository Entry name/title of data are specified according to the Data Reference Syntax ( https://pcmdi.llnl.gov/mips/cmip5/docs/cmip5_data_reference_syntax.pdf ) as activity/product/institute/model/experiment/frequency/modeling realm/MIP table/ensemble member/version number/variable name/CMOR filename.nc . There are five component models: atmosphere, surface land, ocean, sea ice and surface wave models.
The data covers the calculated yields of wind farms in German territory and the German exclusive economic zone (EEZ) and the relevant wind conditions under the assumption of an expansion of offshore wind energy defined in different scenarios. The calculations were carried out with the numerical weather model WRF using a parameterization of wind farms according to Fitch. The data are available in 10-minute temporal and 2 km x 2 km spatial resolution for the North Sea for the meteorological year 2006. The variables of the data set are wind speed (WS) and wind direction (WD) at 9 height levels between 50 m and 350 m, the power (POWER) of the wind turbines from each grid cell and the air density. A detailed description of the variables can be found in the files.
The data covers the calculated yields of wind farms in German territory and the German exclusive economic zone (EEZ) and the relevant wind conditions under the assumption of an expansion of offshore wind energy defined in different scenarios. The calculations were carried out with the numerical weather model WRF using a parameterization of wind farms according to Fitch. The data are available in 10-minute temporal and 2 km x 2 km spatial resolution for the North Sea for the meteorological year 2006. The variables of the data set are wind speed (WS) and wind direction (WD) at 9 height levels between 50 m and 350 m, the power (POWER) of the wind turbines from each grid cell and the air density. A detailed description of the variables can be found in the files.
The data covers the calculated yields of wind farms in German territory and the German exclusive economic zone (EEZ) and the relevant wind conditions under the assumption of an expansion of offshore wind energy defined in different scenarios. The calculations were carried out with the numerical weather model WRF using a parameterization of wind farms according to Fitch. The data are available in 10-minute temporal and 2 km x 2 km spatial resolution for the North Sea for the meteorological year 2006. The variables of the data set are wind speed (WS) and wind direction (WD) at 9 height levels between 50 m and 350 m, the power (POWER) of the wind turbines from each grid cell and the air density. A detailed description of the variables can be found in the files.
The data covers the calculated yields of wind farms in German territory and the German exclusive economic zone (EEZ) and the relevant wind conditions under the assumption of an expansion of offshore wind energy defined in different scenarios. The calculations were carried out with the numerical weather model WRF using a parameterization of wind farms according to Fitch. The data are available in 10-minute temporal and 2 km x 2 km spatial resolution for the North Sea for the meteorological year 2006. The variables of the data set are wind speed (WS) and wind direction (WD) at 9 height levels between 50 m and 350 m, the power (POWER) of the wind turbines from each grid cell and the air density. A detailed description of the variables can be found in the files.
The data covers the calculated yields of wind farms in German territory and the German exclusive economic zone (EEZ) and the relevant wind conditions under the assumption of an expansion of offshore wind energy defined in different scenarios. The calculations were carried out with the numerical weather model WRF using a parameterization of wind farms according to Fitch. The data are available in 10-minute temporal and 2 km x 2 km spatial resolution for the North Sea for the meteorological year 2006. The variables of the data set are wind speed (WS) and wind direction (WD) at 9 height levels between 50 m and 350 m, the power (POWER) of the wind turbines from each grid cell and the air density. A detailed description of the variables can be found in the files.
The data covers the calculated yields of wind farms in German territory and the German exclusive economic zone (EEZ) and the relevant wind conditions under the assumption of an expansion of offshore wind energy defined in different scenarios. The calculations were carried out with the numerical weather model WRF using a parameterization of wind farms according to Fitch. The data are available in 10-minute temporal and 2 km x 2 km spatial resolution for the North Sea for the meteorological year 2006. The variables of the data set are wind speed (WS) and wind direction (WD) at 9 height levels between 50 m and 350 m, the power (POWER) of the wind turbines from each grid cell and the air density. A detailed description of the variables can be found in the files.