Screen capture from the OpenClimateGIS Software website

OpenClimateGIS Software

With this downloadable software package, users gain ready access to climate model datasets in commonly used, modern geospatial formats used by GIS software, browser-based mapping tools, and virtual globes.

Important Notice for Using Climate Projections

Climate projections can be useful for making decisions about the future, but the limitations of climate models make it easy to misinterpret or misuse their results. Be aware that:

  • Climate projections are not predictions. Projections are based on assumptions about future human emissions of greenhouse gases and other policy choices.
  • Climate projections do not attempt to predict the timing of meteorological events such as storms, droughts, or El NiƱos. The location and timing of future extreme weather events cannot be deduced from climate model projections.
  • Projections vary from model to model: the best projection dataset for one location and purpose may not be the best for other situations. Considering a range of projections may help you gain a more complete picture of potential future risks.
  • The increased spatial resolution of statistically downscaled projections available for temperature and precipitation may not be available for all parameters. In addition, increased resolution does not necessarily equate to greater fidelity or reliability.

For decisions involving the use of climate model projections, you may want to consider seeking expertise.

OpenClimateGIS is a Python package designed for geoprocessing and computation on CF-compliant climate datasets. There is additional project content for OpenClimateGIS hosted on its CoG Site. Source code and issue tracking are hosted on GitHub. Visit the Contact Information page for support and mailing list addresses.

Features

GIS Capabilities:

  • Subsetting (e.g., intersects and intersection) of climate datasets by bounding box, Shapely geometries, or shapefiles (point or polygon) (e.g., city centroid, a single county or watershed, state boundaries).
  • Time and level range subsetting.
  • Single or multi-dataset requests (i.e., concatenation).
  • Area-weighted aggregation to selection geometries.
  • Alpha support for projected climate datasets.
  • Geometry wrapping and unwrapping to maintain logically consistent longitudinal domains.
  • Polygon and point geometric abstractions.

Data Conversion:

  • Access to local NetCDF data or data hosted remotely on a THREDDS (OPeNDAP protocol) data server. Only the piece of data selected by an area-of-interest is transferred from the remote server.
  • Stream climate data to multiple formats. Currently supported formats include keyed CSV-shapefile, shapefile, CSV, GeoJSON, NetCDF, and NumPy.
  • Extensible converter framework to add custom formats.
  • Automatic generation of request metadata.
  • Push data to a familiar format to perform analysis or keep the data as NumPy arrays, perform analysis, and dump to a supported format.

Computation:

  • Extensible computational framework for arbitrary inclusion of NumPy-based calculations.
  • Apply computations to entire data arrays or temporal groups.
  • Computed data may be streamed to any supported formats.
Last modified
16 June 2021 - 3:37pm