Last year we worked closely with the US World Wildlife Fund to develop the capability to upload and share climate modeling data through GeoIQ. Today you can explore the changing world at Climascope. Partnerships with the Tyndall Centre for Climate Change Research, University of East Anglia, and Zekiah collaborated to build the user interface to explore through the complex models and data. Users can explore temperature, precipitation, cloud cover, wetness days and more extremely valuable data through an easy map interface. You can even filter the data by ranges and click to dive into the data at individual locations and times.
The intended results are to give planners and practioners access to the data they need to prepare for climate change (adaptation in particular) and to provide the range of information, from the [different climate] scenarios to show policymakers spatially explicit climate implications for different emission scenario decisions.
ClimaScope provides spatially explicit climate change data for 18 climate model patterns, for the new IPCC RCP scenarios, the old SRES scenarios, and specific adaptation scenarios for 2C, 3C and 4C warming. There are 8 climate varibales – maximum, minimum and average temperatue, sea surface temperature, precipitation, wet day frequency, cloud cover and vapor pressure. All for annual, seasonal and monthly time periods for a range of 30-year periods. This is done by turning the complex climate data into spatially explicit georeferenced maps. These files can then easily be layered to allow users to look, for example, at all emission scenarios for a given climate model or all climate models for a given emission scenario for a given point.
By working to develop this with GeoIQ (grant funded) the overall goal was to easily be able to federate this data with other data. As World Bank’s Mapping for Results uses the same platform and open standards, then this federation is easily accomplished such that all World Bank Projects currently in Mapping for Results can be overlaid on ClimaScope data (see examples in the Featured Maps section of Climascope). Thus, users could click on the World Bank data and get information on that project, and click on arrow keys to see how the climate was projected to change at that site. Similarly propposed solar projects could be overlaid on the cloud frequency map to see if projected changes in cloudiness would help or hinder the project, precipitation and wet day frequency could be used to aid in assessing any water project.
Welcome to the Esri DC Development Center blog. We write about features of our work on big data analytics, open platforms, and open data, what is new and exciting in the Esri and community, and general industry thought leadership and discussions of geospatial data visualization and analysis.
Please explore what we're working on and let us know if you have any questions or ideas!