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The Atmospheric Data Modeling Workshop in Seattle

Meeting Minutes

Workshop participants represented NCAR, ESRI, Unidata, Meteorlogix, Raytheon, Pacific Disaster Center, US Air Force, National Weather Service, and several other NOAA labs (PMEL, NGDC, ATDD, USDOC). During the course of the meeting, the representatives from the atmospheric community worked closely with ESRI development staff to identify GIS approaches for handling atmospheric data more effectively and began the process of designing a community data model. The first data modeling meeting in Seattle centered upon the conceptual design of the atmospheric data model for GIS. Click here to view workshop agenda.

At the beginning Steve Grisé (ESRI) gave an overview of the data modeling process with emphasis on a conceptual design and presented some thoughts and ideas on bridging the gap between atmospheric and GIS data.

Click here to view Steve's power point slides.

The following points were brought up during a discussion:

  • Cannot build all encompassing data model from the beginning. Need to build an essential data model first and provide tools for it to be extended for different groups/purposes/directions.
  • Timeframe: Usually it takes 2-3 months after a data modeling meeting to develop a draft data model. A draft gets distributed for feedback and can be tested on real projects and use cases. After 6-12 months feedback is received and suggestions are incorporated into the data model. It took 3 years to build ArcHydro (hydrological data model) and about two years to build a Marine (oceanographic) data model.
  • Use cases: 1) GIS users getting atmospheric datasets; 2) Equation solving models using GIS data.
  • Atmospheric science - think about parameters / quantities, continuous sets of functions. How to bridge gap between discrete objects and functions?

Other points of discussion:

  • Analysis and data integration
  • Interface with land surface properties
  • Handling of interface between solid system dynamics (earth) and fluid system dynamics (atmosphere)
  • File systems as databases
  • Do we need to have a data type to represent NetCDF in a database or provide services to connect to data stored in NetCDF?
  • Data types and/or web services
  • N-dimensional views; indices

Following Steve's presentation and group discussion, Terri Betancourt (NCAR) lead a discussion about the scope of the atmospheric data model and summarized responses to the Conceptual Data Modeling questionnaire

Click here to view Terri's power point slides.

The discussion points included:

  • Build infrastructure for handling atmospheric data
  • Focus on the atmosphere and provide links to other models for integrated GIS work
  • Importance of scale of modeling: need to accommodate for different scales, both spatial and temporal

In the afternoon presentation, Joe Breman (ESRI) demonstrated current ArcGIS functionality using atmospheric, oceanographic, and hydrological data. In the discussion of ArcGIS functionality, the group identified the following points:

  • Analysis and display of vertical cross-section
  • Time query/analysis (user defined; time synchronized)
  • Vertical and temporal interpolation

After Joe's presentation the workshop participants formed four working groups. Each working group was asked to discuss the data model conceptual elements using use cases and focus on: atmospheric and related elements, data types, data formats, data processing functions, analytical functions, and presentation functions. Working group's reports are summarized below.

Report from Working Group I:

Steve Grisé (ESRI)
Terri Betancourt (NCAR)
Tiffany Vance (NOAA PMEL)
Edward Dumas (NOAA ATDD)
Brian Newton (U.S. Air Force Weather Agency)

Thematic Layer Stack WG1
(Focus on the mesoscale meteorology and common datasets used in operational weather forecasting)

I. Satellite data
(Geostationary, Polar Orbiting, SRTM, Aerial photography, down looking sensors)

a. Raw data
b. Processed data

Single Value
Multi-channel - all at one or more Z values

II. Radar data

a. Raw data
b. Derived products

Side note: Examples of radar coordinate systems:

Coordinate system
X, Y, Z units
CAPPI km, km, km
PPI km, km, degrees
Radial km, degrees, degrees

Important parameters to consider:

III. Weather data
(at the surface and all upper air mandatory levels)

Important parameters to consider:
Wind Speed
Wind Direction
Height (altitude)
Precipitation (amount, type)
Derived parameters and quantities

IV. Location of fixed observing stations

Example: Mesonet

V. Mobile observing stations

Example: flight path

VI. Surface data layer
(to be linked with the atmospheric data model but not included)

Topography used by the weather model
Topography for visualization
Land Use / Land Cover
Streets, roads, transportation lines, airports
Soil types
Vegetation types
Shorelines / Marine
Air/sea interface, fluxes
Solar radiation

Side note:
Common Temporal Operators
Point in time
Offset in time
Buffer in time
GPS time vs UTC time
Temporal bounding box

Report from Working Group II:

Joe Breman (ESRI)
Olga Wilhelmi (NCAR)
Kathryn Hughes (NOAA/ USDOC)
Ted Habermann (NOAA/NGDC)
Jeff Logan (PDC)
Jim Block (Meteorologix)

Thematic Layer Stack WGII:
(General representation of atmospheric sciences: meteorology, climatology, impacts)

I. Remotely sensed observations

Radar data
Satellite data

Examples of parameters:
Lightning strikes
Wind speed
Wind Direction
Wind fields with barbs (should reflect terrain features)
Atmospheric chemistry

II. In-situ observations

Point observations (Coop, Buoy, Metar)
Examples of parameters:
Sea surface temperature
Side note: can organize by "things that cumulate"(i.e., precipitation) and "things that average" (i.e., temperature)

III. Numerical Models

a. Weather forecasting models
b. Climate prediction models
(gridded data sets)

IV. Earth surface characteristics - land, sea, ocean

Snow cover
Soil types
Urbanization and built environment
Land Cover

V. Socio-economic characteristics

Human dimensions elements
Land use
Greenhouse emissions
Population density

VII. Topography (terrain)

VIII. Boundaries


For all layers: important to address multiple dimensions: X, Y, Z1, Z2…, Zn, M1, M2…,Mn, t1, t2, …, tn (multiple attributes, vertical layers and times)

Side note:
Need to address and represent different scales:
…. also tools for downscaling and upscaling

Working Group 2 also discussed issues related to

  • Differences in terminology between GIS and atmospheric sciences (need a glossary)
  • Potential uses of data model (hazards, public health)
  • Data types, formats and semantic standards. To see power point slides that Ted Habermann (NOAA/NGDC) put together for the report click here.

Report from Working Group III:

Lori Armstrong (ESRI)
Zhumei Qian (ESRI)
Ben Domenico (Unidata)
Ken Waters (NOAA/MWS)
Scott Shipley (Raytheon)

Working group 3 presented many interesting use cases where atmospheric data were integrated into GIS. To view power point presentation by WG3 click here.

Report from Working Group IV:

Steve Kopp (ESRI)
Simon Evans (ESRI)
Nazila Merati (NOAA/PMEL)
Jack Settelmaier (NOAA/NWS)
Edward Amrhiem (US Air Force)
Bonnie Reed (Raytheon)

Last but not the least, Working Group 4 was able to address all assigned questions: from data types and formats to analysis and representations. To see power point presentation prepared by working group 4 click here.

After working groups' reports Steve Grisé lead a discussion on the atmospheric concepts of the data model. The concepts describing data collection process and further use of observational data to derive new variables are shown on a diagram below:

This diagram represents some of the initial concepts that emerged as relevant to an atmospheric data model. The diagram is neither complete nor a UML representation, but an initial identification of some key model concepts and their primary associations.

Group discussion also addressed the following points:

  • Interoperability and data formatting issues
    • OGC WCS connector as a mechanism to provide web services to gridded datasets
    • New ArcGIS interoperability extension
    • Efficiency and performance
  • Users of the data model
  • Potential case studies
  • Experience of Marine data model with multidimensional data
    • Placeholders
    • "Z-aware"
    • "M-aware"
  • Implications of representing grids as points
  • Topology issues

Next steps:

  • Draft data model to be distributed for feedback in the next 2-3 months
  • Writing conceptual framework design document (from first NCAR/ESRI meeting in Redlands to the outcome of this workshop)
  • Conduct case studies to test data model and provide feedback
  • Document methods, data conversion issues, limitations
  • Provide ESRI development team (contact Steve Kopp) with figures describing GIS applications in the atmospheric sciences along with descriptions on research questions, data processing, analysis tools and what can/need to be done to improve existing functionality.
  • Next meeting will take place at the ESRI User Conference in San Diego (present draft of the data model to the Atmospheric SIG)