Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The Climate Resilience Information System (CRIS) provides data and tools for developers of climate services. This image service provides access to downscaled climate projections for 27 threshold values of temperature for the contiguous United States for 2 SSP climate scenarios from 1950-2100. These services are intended to support analysis of climate exposure for custom geographies and time horizons. Sixteen downscaled global circulation models (GCMs) were chosen to be included in a weighted ensemble, optimized for the contiguous United States. More details on the models included in the ensemble and the weighting methodologies can be found in Understanding CRIS Data.Time RangesPixel values for each variable were calculated for each year from 2005 to 2100. Additionally, a modeled history runs from 1950 - 2005. The modeled history and future projections have been merged into a single time series. These annual increments support deriving a temporal average, such as a decadal or thirty-year period centered on a specific year. These time steps should not be used to make predictions about conditions for a specific year, especially at a pixel-level. Climate ScenariosClimate models use estimates of future greenhouse gas concentrations and human activities to predict overall change. These different scenarios are called the Shared Socioeconomic Pathways (SSPs). Two different SSPs are presented here: 2-4.5 and 5-8.5. The 2- or 5- represents the socioeconomic growth model. The 4.5 or 8.5 number indicates the amount of radiative forcing (watts per meter square) associated with the greenhouse gas concentration scenario in the year 2100 (higher forcing = greater warming). It is unclear which scenario will be the most likely, but SSP2-4.5 aligns closest with the international targets of the COP-26 agreement for no greater than 2oC average global warming. SSP3-7.0 may be the most likely scenario based on current emission trends. SSP5-8.5 acts as a cautionary tale, depicting a worst-case scenario if reductions in greenhouse gasses are not undertaken. Variable DefinitionsSee the variable list and definitions here. Additional ServicesThree versions of the gridded climate projections are available from CRIS:LOCA2 Ensemble: a statistically downscaled 6-km resolution model. LOCA2 has SSP2-4.5, 3-7.0 and 5-8.5STAR-ESDM Ensemble: a statistically downscaled 4-km resolution model. STAR-ESDM has SSP2-4.5 and 5-8.5NCA5 Blended Ensemble: a merging of LOCA2 and STAR-ESDM ensembles at a 6-km resolution, as was done for the 5th National Climate Assessment (2023). NCA Blended Ensemble has SSP2-4.5 and 5-8.5Using the Imagery LayerThe ArcGIS Tiled Imagery Service has a multidimensional structure -- a data cube with variable, SSP, and time dimensions. Methods for accessing the different dimensions will depend on the software/client being used. For more details, please see the CRIS Developer’s Hub along with this instructional StoryMap. To run analysis, first use the multidimensional tools Aggregate or Subset in ArcGIS Pro to copy the necessary data locally.Data ExportData export is enabled on the services if using an ArcGIS client. NetCDF or Zarr files are also available from the NOAA Open Data Distribution system on Amazon Web Services.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Wind Speed, LV Watershed, raster, 1/2000 to 12/2015 Reference Information and Units: GCS: EPSG:4326 (http://spatialreference.org/). Projection: Data has not been projected. Pixel Size: 0.125 degrees, approx. 14km at the equator. Units: m/s-1. At surface. Data values are monthly means of daily means. File Naming Convention: WS_Year_month Data Origin: ERA Interim, Monthly Means of Daily Means, and was developed by the European Centre for Medium-Range Weather Forecasts (ECMWF). http://apps.ecmwf.int/datasets/data/interim-full-moda/levtype=sfc/ Sensor: Various, "Reanalysis (as well as analysis) is a process by which model information and observations of many different sorts are combined in an optimal way to produce a consistent, global best estimate of the various atmospheric, wave and oceanographic parameters." Code: for %A in ("C:\temp*.nc") do gdal_translate -of GTiff -ot FLOAT32 -a_srs "+init=epsg:4326" -unscale -co "COMPRESS=PACKBITS" "%A" "%A.tif Data Development/Processing: Converted TIFF data was validated against the parent NetCDF file for correct cell size and pixel value. Output TIFFs were flipped. This was remedied via batch flipping in ArcGIS (Flip tool). The GCS was batch defined in ArcGIS as SR-ORG:14. Processed data was then batch clipped to Lake Victoria and the surrounding lakes and statistics were calculated.
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Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The Climate Resilience Information System (CRIS) provides data and tools for developers of climate services. This image service provides access to downscaled climate projections for 27 threshold values of temperature for the contiguous United States for 2 SSP climate scenarios from 1950-2100. These services are intended to support analysis of climate exposure for custom geographies and time horizons. Sixteen downscaled global circulation models (GCMs) were chosen to be included in a weighted ensemble, optimized for the contiguous United States. More details on the models included in the ensemble and the weighting methodologies can be found in Understanding CRIS Data.Time RangesPixel values for each variable were calculated for each year from 2005 to 2100. Additionally, a modeled history runs from 1950 - 2005. The modeled history and future projections have been merged into a single time series. These annual increments support deriving a temporal average, such as a decadal or thirty-year period centered on a specific year. These time steps should not be used to make predictions about conditions for a specific year, especially at a pixel-level. Climate ScenariosClimate models use estimates of future greenhouse gas concentrations and human activities to predict overall change. These different scenarios are called the Shared Socioeconomic Pathways (SSPs). Two different SSPs are presented here: 2-4.5 and 5-8.5. The 2- or 5- represents the socioeconomic growth model. The 4.5 or 8.5 number indicates the amount of radiative forcing (watts per meter square) associated with the greenhouse gas concentration scenario in the year 2100 (higher forcing = greater warming). It is unclear which scenario will be the most likely, but SSP2-4.5 aligns closest with the international targets of the COP-26 agreement for no greater than 2oC average global warming. SSP3-7.0 may be the most likely scenario based on current emission trends. SSP5-8.5 acts as a cautionary tale, depicting a worst-case scenario if reductions in greenhouse gasses are not undertaken. Variable DefinitionsSee the variable list and definitions here. Additional ServicesThree versions of the gridded climate projections are available from CRIS:LOCA2 Ensemble: a statistically downscaled 6-km resolution model. LOCA2 has SSP2-4.5, 3-7.0 and 5-8.5STAR-ESDM Ensemble: a statistically downscaled 4-km resolution model. STAR-ESDM has SSP2-4.5 and 5-8.5NCA5 Blended Ensemble: a merging of LOCA2 and STAR-ESDM ensembles at a 6-km resolution, as was done for the 5th National Climate Assessment (2023). NCA Blended Ensemble has SSP2-4.5 and 5-8.5Using the Imagery LayerThe ArcGIS Tiled Imagery Service has a multidimensional structure -- a data cube with variable, SSP, and time dimensions. Methods for accessing the different dimensions will depend on the software/client being used. For more details, please see the CRIS Developer’s Hub along with this instructional StoryMap. To run analysis, first use the multidimensional tools Aggregate or Subset in ArcGIS Pro to copy the necessary data locally.Data ExportData export is enabled on the services if using an ArcGIS client. NetCDF or Zarr files are also available from the NOAA Open Data Distribution system on Amazon Web Services.