3 datasets found
  1. a

    Temperature Climate Projections from LOCA2 & STAR Downscaling

    • hub.arcgis.com
    Updated May 26, 2025
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    National Climate Resilience (2025). Temperature Climate Projections from LOCA2 & STAR Downscaling [Dataset]. https://hub.arcgis.com/maps/nationalclimate::temperature-climate-projections-from-loca2-star-downscaling/explore
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    Dataset updated
    May 26, 2025
    Dataset authored and provided by
    National Climate Resilience
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Description

    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.

  2. Climate Land Cover (LANDFIRE Derived)

    • data.ca.gov
    • data.cnra.ca.gov
    • +5more
    Updated Apr 15, 2022
    + more versions
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    California Natural Resources Agency (2022). Climate Land Cover (LANDFIRE Derived) [Dataset]. https://data.ca.gov/dataset/climate-land-cover-landfire-derived
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    arcgis geoservices rest api, htmlAvailable download formats
    Dataset updated
    Apr 15, 2022
    Dataset authored and provided by
    California Natural Resources Agencyhttps://resources.ca.gov/
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description
    Based primarily on the most recent release of LANDFIRE v2.0.0, this generalized land cover dataset provides full coverage of California including to the three nautical mile limit offshore. It represents a ground condition of 2016 divided into 30mx30m cells across the entire state.

    The state is grouped into the following land cover classes: forests, shrublands and chaparral, grasslands, croplands, wetlands, seagrasses and seaweeds, developed lands, and sparsely vegetated lands. The mapped area has been extended offshore to three nautical miles. Lakes, reservoirs, rivers, and oceans that do not overlay seagrasses and seaweeds are identified in as “open water.”

    LANDFIRE v.2.0.0 provides the source for much of the land cover and is an integrated dataset with many layers. The Existing Vegetation Type (EVT) and Biophysical Settings (BPS) layers provide inputs to this data set. The EVT layer contains data on life form (tree, shrub, herb, developed, agriculture, sparse, barren, snow-ice, or water), a named vegetation type, and notes on recent disturbance. These are used to assign a likely generalized land cover type to each pixel. This result is then refined using the BPS layer to suggest the land cover that might exist in recently disturbed (fire or logging) areas absent that disturbance.

    These results are then supplemented through the creation of a seagrasses and seaweeds dataset by combining data on the presence of eelgrass and kelp canopy and replacing the water category with seagrasses and seaweeds where it is present.

    These data result from the integration of remote sensing (satellite imagery analysis), with field data, using computer algorithms under the oversight of the LANDFIRE team or the teams developing the seagrass and kelp maps. Errors are expected in all data and while every attempt is made to minimize and understand them, they cannot be eliminated. As a result, the cells in the data represent an estimate of what is on the ground at that specific location. Validation techniques used in the production of the data help identify and allow for correction of gross errors, but individual pixels, or even small groupings of them may differ from real world conditions. Similarly, while efforts are made to be consistent with the selection of the source satellite data, the difference between seasons or a wet versus dry year do impact the final maps, notably water and wetlands.

    Data Sources
    LANDFIRE: LANDFIRE Existing Vegetation Type layer.(2013 - 2021). U.S. Department of Interior, Geological Survey.[Online]. Available: https://landfire.gov/version_download.php [Accessed: February 3, 2021].

    LANDFIRE: LANDFIRE Biophysical Setting layer.(2013 - 2021). U.S. Department of Interior, Geological Survey.[Online]. Available: https://landfire.gov/version_download.php [Accessed: February 3, 2021].

    Bell, T, K. Cavanaugh, D. Siegel. 2020. SBC LTER: Time series of quarterly NetCDF files of kelp biomass in the canopy from Landsat 5, 7 and 8, since 1984 (ongoing) ver 13. Environmental Data Initiative. https://doi.org/10.6073/pasta/5d3fb6fd293bd403a0714d870a4dd7d8. Accessed 2021-04-08. (Data extraction performed by T. Bell April 8, 2021)

    Eelgrass Survey GIS Data version 2.0 (2017, updated 2020), National Marine Fisheries Service West Coast Region. Available: https://www.sfei.org/data/eelgrass-survey-gis-data#sthash.u94SjLu7.afUwqGJA.dpbs [Accessed: April 6, 2021)
  3. d

    Wind Speed, LV Watershed, raster, 1/2000 to 12/2015

    • search.dataone.org
    • dataverse.harvard.edu
    Updated Nov 21, 2023
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    Hamilton, Stuart (2023). Wind Speed, LV Watershed, raster, 1/2000 to 12/2015 [Dataset]. http://doi.org/10.7910/DVN/VI4LPV
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    Dataset updated
    Nov 21, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Hamilton, Stuart
    Time period covered
    Jan 1, 2000 - Dec 31, 2015
    Description

    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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National Climate Resilience (2025). Temperature Climate Projections from LOCA2 & STAR Downscaling [Dataset]. https://hub.arcgis.com/maps/nationalclimate::temperature-climate-projections-from-loca2-star-downscaling/explore

Temperature Climate Projections from LOCA2 & STAR Downscaling

Explore at:
Dataset updated
May 26, 2025
Dataset authored and provided by
National Climate Resilience
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Area covered
Description

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.

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