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About SNAP Data

SNAP produces downscaled, historical and projected climate data for sub-Arctic and Arctic regions of Alaska and Canada. We also share other types of project-specific data that cover much larger regions.

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Downscaled projected data come from one of 5 top ranked global circulation models or are calculated as a 5-model average. Each model also has 3 versions from one of 3 climate scenarios (SRES or RCPs, see sidebar for an explanation of these terms). Climate datasets include daily, monthly, and derived products (e.g., monthly decadal averages, specific seasonal averages).

We select the highest quality climate data for our region, rigorously evaluate model output, and downscale only the best models for use in other applications. Learn more about our data sources, model selection, and downscaling processes.

Data categories

  • Observed Historical: Variables directly observed in the past and then assembled into a coherent gridded dataset. Example: downscaled CRU time series 1901–2009

  • Modeled Historical: Variables modeled over a historical (past) time period. Example: historical (1850–2005) runs of GCMs

  • Modeled Projected: Variables modeled over one or more future time periods. Outputs (projections) also include several possible pathways (scenarios). Example: projected (2006–2100) runs of GCMs and their respective RCPs

Model term definitions

CMIP Phase 3 (CMIP3) 

  • Outputs from the IPCC’s Fourth Assessment Report (AR4). SNAP uses the first ensemble model run.
  • Scenarios: SRES 20C3m, B1, A1B, A2 where SRES = Special Report on Emissions Scenarios; B1, A1B, A2 = low, middle, high; 20c3m = 20th century

CMIP Phase 5 (CMIP5)

  • Outputs from the IPCC Fifth Assessment Report (AR5). SNAP uses the first ensemble model run.
  • Scenarios: Historical and RCPs 4.5, 6.0, 8.5 where RCP = Representative Concentration Pathways; 4.5, 6.0, 8.5 = low, middle, high

Format and file naming

GeoTiff: Most gridded outputs are in GeoTiff format, which can be interpreted by ArcGIS, QGIS, R, python, GDAL, and other software.

Naming scheme: We strive for consistent naming, although there may be slight variations across datasets. See the metadata for details on specific datasets.