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Status of Open Environmental Information Services. Edward Johnson NWS Strategic Planning and Policy Office Ben Kyger NCEP Central Operations David Michaud Office of the Chief Information Officer NWS Partners Meeting August 4, 2014. Outline. Introduction / Overview – Ed Johnson
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Status of Open Environmental Information Services Edward Johnson NWS Strategic Planning and Policy Office Ben Kyger NCEP Central Operations David Michaud Office of the Chief Information Officer NWS Partners Meeting August 4, 2014
Outline • Introduction / Overview – Ed Johnson • NOAA Big Data Partnership – Dave Michaud • NCEP Model Data Access – Ben Kyger • Discussion Presentation Title
NOAA Big Data PartnershipGoals and approach Goals • Unleash full potential of NOAA data through innovative approaches • Enable private sector to build businesses and create jobs • Improve compliance with Open Data policy Approach • Position NOAA’s data with analytic, compute and storage capabilities • Create sustainable private/public partnership where industry: • Moves NOAA data to cloud at no net cost to government • Provides free public access to NOAA data • Creates new profitable value-added services
NOAA Big Data Partnership - Architectural Concept consumer Consumer 1 Consumer 2 Consumer 3 Custom Product/ App #2 Custom Product/ App #1 Custom Product/ App #3 application & product providers cloud provider integration functions analysis functions working copy of data network service provider agency security boundary Agency Service Tier agency-provided services Catalog Access Services Metadata Formatting master copy of data Earth Observations Earth Observations Model Outputs
Challenges • Build partnerships for all NOAA data - not just weather data • Encourage competitive market forces to drive efficiency of partners while protecting the integrity of mission systems • Account for all the costs to implement partnership • Define expectations upfront to protect equity of access and non-exclusivity of data • Establish appropriate SLAs to protect data integrity and bound liability • Use data access methods based upon open standards
Customer Data Access Project Status as of: 23-July 2014 Y Project Information and Highlights Scheduling Y G • Leads: • David Michaud, Ben Kyger • Scope: • Increase accessibility of Department of Commerce Data (DOC) • Develop standards for data access and measurement • Improve data interoperability across DOC • Meet with customers to surface and deliver on current unmet needs • Upgrade NOMADS capacity if necessary Issues/Risks Funding Sources and Obligation Status YTD G Y • Issues/Risks: • Issue – Change in strategy from original CRADA intent • Issue – Increasing spacial and temporal resolution to models is a common theme but will require significant coding changes • Issue - Increasing resolution will consume additional unplanned high performance computing (HPC) and dissemination resources • Mitigation: • Work directly with customers to meet current unmet requirements • Allow for these requirements to be added over the next 2-3 years • Resource planning • For HPC, allocate additional resources at the expense of other plans • For Dissemination, leverage FY16 budget increase to address this limitation TBD Y G R
Participants Thus Far • AccuWeather Corp • Weather Analytics • Delta Airlines • Synoptic Data Corp (including MesoWest and WeatherFlow) • Commodity Weather Group, LLC • University of British Columbia
Themes • Models of interest • GFS, GEFS, NAM, HIRESW, RTMA, RAP, HRRR, NDAS, Wave Watch 3 • What additional output is sought • Greater temporal resolution - hourly • Native spatial resolution for all parameters • Maximum vertical levels (60+) • Larger domains, especially to include full coverage of North America • More consistent delivery time for GEFS forecast hours • Additional BUFR sounding data for international stations • Simulated radar and satellite data from the GFS • ATCF guidance • Higher spatial resolution from the GEFS • Post-processed grids from NCEP centers • NOMADS-like slice/dice features • Any format is fine, but GRIB2 is preferred • How long to evaluate new datasets • A few weeks • Two years