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Implementation of Model Data Interoperability for IOOS: Successes and Lessons Learned Rich Signell USGS Woods Hole, MA / NOAA Silver Spring USA Model Data.

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Presentation on theme: "Implementation of Model Data Interoperability for IOOS: Successes and Lessons Learned Rich Signell USGS Woods Hole, MA / NOAA Silver Spring USA Model Data."— Presentation transcript:

1 Implementation of Model Data Interoperability for IOOS: Successes and Lessons Learned Rich Signell USGS Woods Hole, MA / NOAA Silver Spring USA Model Data Interoperability is Low- Hanging Fruit!

2 US Integrated Ocean Observing System (IOOS ® ) IOOS ® Plan defines: IOOS ® Plan defines: Global ComponentGlobal Component Coastal ComponentCoastal Component  17 Federal Agencies  11 Regional Associations

3 HF radar DMAC approved services for Gridded Data and Model Outputs Table of Contents Metadata Data Values DataProvider CF Metadata QualityControl satellite griddedmodeloutputs OGC WCS (WebCoverageService) OPeNDAP/CF OPeNDAP/CF

4 The Problem: Stovepiped Model Access UCLA/JPL ROMS SCB Model Yi Chao, JPL ChesROMS Model Wen Long, UMaryland

5 Result: Inability to compare and assess model results & underutilization of model products The GoMOOS Nowcast/Forecast Circulation Model (University of Maine)

6 Issue: Ocean grids are not regularly spaced! Stretched surface and terrain following vertical coordinates Curvilinear orthogonal horizontal coordinates

7 Climate and Forecast (CF) Metadata Conventions Groups adopting CF: GO-ESSP: Global Organization for Earth System Science Portal IOOS-DMAC: Integrated Ocean Observing System ESMF: Earth System Modeling Framework OGC: Open Geospatial Consortium (via WCS netcdf encoding)

8 CF-Compliant Ocean Model File

9 NetCDF Java Library

10 NcML XML markup language for NetCDF

11 Data Interoperability Model

12 NJ Toolkit for Matlab http://njtbx.sourceforge.net Objective: Make it simple to access CF data Example function: [t, geo]=nj_tslice(URI,’temp’,1); t = 22x120x180 single geo = –lat: [120x180 single] –lon: [120x180 single] – z: [22x120x180 double] –time: 733582 (matlab datenum) nj_tslice works identically for ROMS, POM, ECOM, WRF, Wavewatch3 URI can be: local NetCDF, remote NetCDF, NcML, OpenDAP Data URL Coding by Sachin Kumar Bhate MSSTATE Objective: Make it simple to access CF data Example function: [t, geo]=nj_tslice(URI,’temp’,1); t = 22x120x180 single geo = –lat: [120x180 single] –lon: [120x180 single] – z: [22x120x180 double] –time: 733582 (matlab datenum) nj_tslice works identically for ROMS, POM, ECOM, WRF, Wavewatch3 URI can be: local NetCDF, remote NetCDF, NcML, OpenDAP Data URL Coding by Sachin Kumar Bhate MSSTATE

13 Comparing Models with Data in Matlab Model 1: UMASS-ECOM Model 2: UMAINE-POM Data: SST 2008-Sep-08 07:32

14 Buoy_comp.m: Model/Data comparison of Wave Height

15 Browser-based Mapping with ncWMS/Godiva2

16 3D Visualization with the Integrated Data Viewer (IDV)

17 Single Point of Access Catalog: GEO-IDE => IOOS Regions http://ferret.pmel.noaa.gov/thredds/geoideCatalog.html

18 Working with Data in ArcGIS using the NOAA/ASA Environmental Data Connector

19 14 Different Ocean Forecast Models Spanning CONUS Waters in IDV

20 OOI-CI OSSE (Sep-Oct, 2009)

21 Models being used for BP Spill

22 Successes Existing Unidata technology allowed for standards- based delivery of aggregated geospatial data from native model grids that put little or no effort on the data provider Demonstrated interoperability with 17 THREDDS servers in 11 IOOS Regions What did we get? –Single point of access for regional model results –Interoperable software –More eyes on the model results –More usage of model results –Faster feedback to modelers –Improved models –Increased community support for standards-based access Existing Unidata technology allowed for standards- based delivery of aggregated geospatial data from native model grids that put little or no effort on the data provider Demonstrated interoperability with 17 THREDDS servers in 11 IOOS Regions What did we get? –Single point of access for regional model results –Interoperable software –More eyes on the model results –More usage of model results –Faster feedback to modelers –Improved models –Increased community support for standards-based access

23 What Next? Continue work on a high-level scientific toolbox for standardized access to model data. (Matlab toolbox based on NetCDF-Java) Develop unstructured grid support: Common Data Model implemented in NetCDF-Java with methods comparable to structured grid Applications need to be modified to read standardized data via OPeNDAP instead of home-grown files Work on discovery and documentation Continue work on a high-level scientific toolbox for standardized access to model data. (Matlab toolbox based on NetCDF-Java) Develop unstructured grid support: Common Data Model implemented in NetCDF-Java with methods comparable to structured grid Applications need to be modified to read standardized data via OPeNDAP instead of home-grown files Work on discovery and documentation

24 Lessons Learned Honor the existing practices Users are best served by developing infrastructure for Developers Focus on success: find something that works, clone it, and build off it Honor the existing practices Users are best served by developing infrastructure for Developers Focus on success: find something that works, clone it, and build off it

25 Questions, Feedback? Dr. Richard P. Signell +1 (508) 457-2229 rsignell@usgs.gov rsignell@usgs.gov

26 Role of Regions Develop customized THREDDS catalogs for regional users Report status of services (e.g. NetCheck) Assess and help with gridded data standards compliance following UAF-developed techniques Develop end-user applications that access gridded data, using CF-compliant OPeNDAP Help educate regional scientists, developers, consultants that standardized services, libraries and tools are available Develop customized THREDDS catalogs for regional users Report status of services (e.g. NetCheck) Assess and help with gridded data standards compliance following UAF-developed techniques Develop end-user applications that access gridded data, using CF-compliant OPeNDAP Help educate regional scientists, developers, consultants that standardized services, libraries and tools are available

27 Late Breaking News

28 THREDDS When people say “THREDDS”, they can mean a catalog or a data server –THREDDS Catalogs are XML files that define metadata, datasets and services –THREDDS Data Server is a Java data server application developed by Unidata, a simple and flexible way for delivering CF-compliant data via OPeNDAP When people say “THREDDS”, they can mean a catalog or a data server –THREDDS Catalogs are XML files that define metadata, datasets and services –THREDDS Data Server is a Java data server application developed by Unidata, a simple and flexible way for delivering CF-compliant data via OPeNDAP

29 OPeNDAP When people say “OPeNDAP”, they can mean protocol, a server, or an organization –OPeNDAP (or just DAP) protocol: a remote data access service protocol with multiple responses DDS – describes the format of the data DAS – describes associated attributes DDX – XML response containing the DDS & DAS DODS – the actual data –OPeNDAP server: a server capable of serving the DAP protocol (e.g. THREDDS Data Server, Hyrax, Pydap, GrADS Data Server) –OPeNDAP organization: Defines and maintains the DAP protocol, develops servers and clients, provide custom OPeNDAP solutions When people say “OPeNDAP”, they can mean protocol, a server, or an organization –OPeNDAP (or just DAP) protocol: a remote data access service protocol with multiple responses DDS – describes the format of the data DAS – describes associated attributes DDX – XML response containing the DDS & DAS DODS – the actual data –OPeNDAP server: a server capable of serving the DAP protocol (e.g. THREDDS Data Server, Hyrax, Pydap, GrADS Data Server) –OPeNDAP organization: Defines and maintains the DAP protocol, develops servers and clients, provide custom OPeNDAP solutions


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