The “Climate Explorer” The US Climate Resilience Toolkit Interactive Mapping and Graph...
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Transcript of The “Climate Explorer” The US Climate Resilience Toolkit Interactive Mapping and Graph...
The “Climate Explorer”The US Climate Resilience Toolkit Interactive
Mapping and Graph Application
February, 2015
James Fox, Greg Dobson, Mark Phillips, Jeff Hicks
David Herring, David Stroud
http://toolkit.climate.gov/
Online Map Viewer
Interactive Map Functionality
Layer Transparency and Base Map Toggle
Legend (Layer Information)
Historical Climate Data, with Normals
Taking Action Case Study – New Jersey
Permalink allows ability to link to Case Studies
Taking Action Case Study – South Florida
Map Library (OpenLayers)
config.json
Climate Explorer (JavaScript, jQuery)
Multigraph
Client Tier
WMS/REST
Service
Permalink
Graph Builder
Data Source(NCDC)
CSV files
Data Transformer
Data ProcessingServer
Nightly cron job gets latest data
Historical station data repositoryFile storage (all data consists of flat files)
Data Tier
UIconfig.json
template.html
Web Browser
CSV files
ContainerModule
Application Data
Key
Climate Explorer
Data TransformerTakes large yearly GHCND datasets and turns them into small station files. It also can calculate derived data (e.g., YTD Precip)
MultigraphInteractive graph library
Graph BuilderUtilities for formatting the graphs and for doing some data massage.
Map LibraryLightweight map library built on OpenLayers. Uses JSON config.
CEUIConverts a mockup HTML file into a usable client application based on various config pieces (topics and sub topics, etc) and controls UI interactions with the data app
PermalinkAllows a dynamic client application (like CE) to have its state persisted via the URL. As the user changes things in the application, a link is generated that can be shared.
Transforms data files into optimal format for interactive use
Where does the data come from?
• Overlays are WMS or REST– Sources: US Drought Monitor, NOAA Coastal Services
Center, Homeland Security, USGS, FEMA, USDA, NASA
• Historical data is Global Historical Climatology Network-Daily (GHCN-D)– Thousands of stations– Compared against 1981-2010 Climate Normals– Precipitation is a derived yearly cumulative
GHCN-D Data Conversion
• In: yearly multi-GB files for all vars/all stations2014.csv
USC00273626,20140225,TMIN,-106,,,H,1800 USC00273626,20140225,TOBS,-56,,,H,1800...
• Out: 1000’s of multi-KB files, one-var/one-stationUSC00273626/TMIN.csv
20140225,-106
20140226,-150...
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A Few Parting Thoughts…Key Metrics for Decision Support Tools
• Data must be accurate, current and scaled for the decision• Visualizations make data meaningful and locally relevant• Storytelling is critical for policy makers to understand
uncertainty and follow a decision making process• Group Decision Making is a continuing, iterative process that
needs to be actively supported with appropriate technologies and toolsets
• Collaboration is key – the three sectors of government, academia and industry must work together to meet this challenge
Thank you! [email protected]