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1 Large-Scale Data Management Challenges Climate, Water, and Weather Data Kenneth Galluppi Director, Disaster and Environmental Programs Renaissance Computing.

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Presentation on theme: "1 Large-Scale Data Management Challenges Climate, Water, and Weather Data Kenneth Galluppi Director, Disaster and Environmental Programs Renaissance Computing."— Presentation transcript:

1 1 Large-Scale Data Management Challenges Climate, Water, and Weather Data Kenneth Galluppi Director, Disaster and Environmental Programs Renaissance Computing Institute University of North Carolina at Chapel Hill NOAA - National Climatic Data Center Ed Kearns

2 2 Goal of Collaborations Enable cutting edge, Grand Challenge multidisciplinary science through the federation of data-grids of climate, hydrological, and weather data, with other geospatially and socially relevant datasets. – Understanding of regional impacts of climate change on water availability and society trends – Understanding and prediction of catastrophic weather- driven events under climatatic change – Communicate risk/crisis knowledge non-specialists

3 3 Challenges of Data Integration of Large, Multidisciplinary Datasets – NCDC and NOAA Centers, SDSC, and others – Discover, access, integration, utility [not store/retrieve] Linkage of Datasets to Computational Models – Input/outputs for real-time model forecasting – Model-to-observation comparison – Climatic models for reanalysis and prediction Access to Large Reference Data – Climate Reanalysis Datasets, 1 PetaByte – NWS DataCube for aviation and emergencies

4 4 Collaboration and Datagrids National Climatic Data Center Emergency Management Research Program Federal Agencies Academic Research

5 NOAA Mission: Weather & Water Serve Societys Needs for Weather and Water Information Ecosystems Protect, Restore, and Manage the Use of Coastal and Ocean Resources through an Ecosystem Approach to Management Climate Understand Climate Variability and Change to Enhance Societys Ability to Plan and Respond To understand and predict changes in Earths environment and conserve and manage coastal and marine resources to meet our nations economic, social, and environmental needs NCDCs Place in NOAAs Mission Commerce & Transportation Support the Nations Commerce with Information for Safe, Efficient, and Environmentally Sound Transportation Mission Support Provide Critical Support for NOAAs Mission NOAA Goals: Data Supports NOAA/NCDC Mission

6 Data supports NOAA/NCDC Mission NCDC will need to function in a wider information landscape with a NOAA Federated Archive – Support distributed data management and services Interoperable with DataNet, Earth System Grid, GEO-IDE, EOSDIS, etc. – netCDF, LDM, CF conventions, ISO Move out of the Box and into the Cloud (networked) – Utilize highly distributed storage and computing (RENCI, Oak Ridge National Lab Implement supporting technologies to enable interoperability with Designated Communities (OGC, WMS/WFS) Institute rules-based data management to enable true federation of NOAA Centers of Data – iRODS

7 Comprehensive Large Array- data Stewardship System (CLASS) Storage (reanalysis) The National Environmental Data Archive

8 NOAAs Data Centers Will Function in a Wider Information Landscape ORNL, ESG NSF DataNet DAPs Data Mgmt IPCC International Sources NEAAT

9 Climate Services using Federated DBs NOAAs Data Centers will need to provide access to petabytes of data that are distributed across multiple NOAA facilities Be able to integrate these data with data from other disciplines (environmental, biological, social, etc..) that are distributed on other databases both in the public and private sector domain Export data to common data formats - Shapefile, Well-Known Text, Arc/Info ASCII GRID, Gridded and Raw NetCDF, GeoTIFF and KMZ (Google Earth) Support : Disaster reduction Human Health Climate Water Resources Weather Ocean Resources Agriculture & Land-Use Ecosystems

10 NOAA/NCDC Climate Services

11 11 NCDC-RENCI Potential Use Cases Catastrophic Event Modeling and Observations Climate Reanalysis Datasets – Climate records everywhere, for 30 years – 1-PetaByte – Regional and local sub-setting – Tens of thousands of users Multi-sensed Gridded Precipitation Climatology Extreme Event Climatology Green Energy, physical-social science Integration

12 12 High Level View of HIS Service Oriented Architecture As of October 2009, 1,867,108 sites and 4,336,790,286 data values where available through the HIS from federal, state, and academic data providers. There have been 543,144 GetValues data requests from Feb 2008 to Oct Hydrology Community

13 13 HIS Service Oriented Architecture

14 Maximize Data Access and Utility

15 15 Data and Model Integration Needed to Support Hydrologic Science Observations Hydrologic Models Weather and Climate Models Physical Data Socioeconomic Data CUAHSI HIS DFC

16 RHESSys TOPS ADAS Meteorology, Hydrology, Ecological Models WRF RHESSYS HEC-RAS ADCIRC Scientific Research Historical Re-Analysis Disaster Planning Disaster Response Agricultural Forecasts Ag Decision Support Public Dissemination Economic Planning etc … Sensor Data Bus TOPS State Climate Office Sensor Cloud National Weather Service Department of Transportation / FAA USGS NWIS, USFS Buoys, Stream Gauges, Soil Moisture People with mobile devices etc … CHPS Enablement

17 17 Use Case: National Water Model Terrain in the Neuse River Basin, NC constructed from 390 million LiDAR measurements Flooding in the Mississippi River Basin, August 1993 observed from satellite imagery Hydrologic scientist have expressed a grand research challenge of building a National Water Model for flood and drought applications. Achieving this goal will require a system like DFC to handle the massive data requirements. Source: Source:

18 18 CUAHSI Case Study Hydrology Grand Challenge Problem: National Water Model – How much water is available in the Nations water resources? – Currently, hydrologic models are implemented at the watershed-scale (county) – Hydrologists plan to scale physically-based models to national level Provide CI, Policies & Sustainability for Water Model Data – Gathering, analysis, dissemination and preservation – Policies for quality control, metadata harvesting, versioning and usage – Enables the data required for real-time analysis for flood and drought modeling – Enables integrating data from new sources – Enables new science, outreach, decision making and disaster recovery – Integration of Predictive Models, Real-time Data and Historic Data

19 Technical Solutions – Too many systems/solutions, home grown to programs (CUAHSI) – Standards (ODM, OGC, Virtual USA, etc. – Federal enterprises – NOAA, CLASS general, heavy system – Oracle front end to large tape system Unique Handling large sets with limited skills Multidisciplinary, formats are not enough, but knowledge Federal – Has to work, has to preserve – Observation systems are getting more complex – Users are more sophisticated and demanding more

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