CCIP Demo Storyboard

intro climate challenge splash page and credits

Welcome to OGC's Climate Challenge Interoperability Plugfest 2009. Sponsored by the Australian Bureau of Meteorology, 52 North Gmbh, and CSIRO.

The Climate Challenge Interoperability Plugfest, or CCIP 2009, was a four month experiment to test the capability of OGC's data delivery standards to serve the needs of climate scientists.

The project brought together an international group of software developers to address climate study through open standards for data sharing. These pioneering organizations included 52 North, ERDAS, ESRI, Jacobs University, lat/lon, LISAsoft, OpenGeo, STFC, Unidata

topic setting and background basics on climate science
simple modeling to more complexity

Climate models, in their most basic form, always account for solar radiation coming in, the longwave radiation from the Earth's surface, and the emissivity of longwave radiation in the atmosphere, which is the greenhouse effect. Note that the solar radiation measure also includes the impact of albedo, which is the extent to which an object diffusely reflects sunlight.

The simplest climate models are called Energy Balance Models (or EBMs). They can give you a rough idea of temperature at a single place at a single time, but to get a more realistic picture, you have to add more complexity. For instance, you probably want to understand change over time. Therefore your model must be able to change based on climate in previous years. Also, you may want to add in the effect of the oceans, sea ice, precipitation, and more. And then since you probably also want your science to impact national or local policy, you'll need to get very specific information about the region you're studying.

These region-specific factors are the bread and butter of General Circulation Models (or GCMs), which are the data hungry, CPU-intensive climate models we generally think of when we hear about climate modeling. The benefit, and challenge, of using GCMs is twofold. The highly detailed data sets they require are scattered throughout data collection institutions around the world. And the expertise needed to describe how various natural processes behave is also scattered around the world.

the vision collaboration = better science
OGC wants to advance this
greater dissemination of model results
the discipline of publishing
mix&match data inputs/algorithms
If one believes that better scientific results can come from better collaboration between scientists and quicker, broader dissemination of results, then the information systems we use to perform climate study must be designed to support this, being more transparent and readily configurable by researchers separated by space and time.
project goals take common climate model outputs--temp, rainfall and see how OGC services measure up to task of supporting result sharing/exploration

CCIP 2009 is a first step towards this vision.Each day, the world's archives of meteorological data increase substantially. Some examples of types of meteorological data are: satellite imagery, radar observations, weather observations (such as air temperature and pressure, precipitation, cloud cover, and wind speed and direction), and also ocean currents, sea surface temperatures, and more.

Also on a daily basis, many of these observations are transformed into weather forecast models that generate a set of three dimensional grids with values at various altitudes through the troposphere. These data comprise the world's climate record. In a time of growing concern as to the affects of climate change, it is becoming increasingly important to be able to back up claims with reference to factual data.

OGC services used WCS, WMS, WCPS, SOS
show/talk about orgs serving same data sets
In this initiative we experimented with ways to share the world's meteorological and weather forecast data through open standards for geospatial information sharing. Participants used the OpenGIS Web Coverage Service and Web Coverage Processing Service standards, which are designed to share and perform computations on satellite imagery and other types of gridded data via the Web, and the OpenGIS Sensor Observation Service, which is designed to share the data originating from devices that take discrete measurements of the earth's processes such as temperature and stream heights.

The point of a "Plugfest" is to help software developers ensure that their products work well together. The essence of interoperability is making sure that information requests are bug-free between servers and clients that conform to open standards, and that they are not dependent upon any particular pairing of client and server. In other words, any server that implements the Web Coverage Service standard should communicate seamlessly with any client software that does the same. The Plugfest environment gives them a forum in which they can test interoperability in a near-to-real-world setting. This process can expose any issues with their software, or with the standards themselves.
demo scenario - BoM WCS enablement AusBoM: service-enablement of end results
  • ERDAS WCS interoperability * ERDAS Apollo web client discovers available BOM coverages from the Apollo CSW. User refines CSW query and conducts point querying comparison across two temporal periods. Demo

  • ArcMap WCS interoperability
    • ArcMap brings in X data via WCS from A software and does Z computation
    • ArcMap brings in X data via WCS from B software and does Z computation
demo scenario -- South Esk: a region at risk of flooding South Esk: a region at risk--flooding ??
ArcMap displays SOS data
  • ERDAS Apollo web client discovers and executes a WPS slope analysis model on the South Esk region to supplement the SOS analysis??. Demo
  • demo scenario --flexible coverage data processing several 1D through 4D data sets Having seen several climate-related application scenarios, let's now explore for a moment the functionality the WCS suite offers.


    The upcoming WCS 2.0 will consist of a WCS Common based on the GML coverage model. A minimal core will define the basics, extensions will add functionality, but also accommodate different user communities. One such already existing extension is the Web Coverage Processing Service, WCPS.


    It defines a multi-dimensional raster language standard, similar to SQL - therefore, it might be dubbed "SQL for coverages". Its functionality allows for ad-hoc navigation, extraction, aggregation, and analysis of multi-dimensional spatio-temporal coverage data.


    In the first scenario climate researchers want to obtain slices from 3-D and 4-D data sets. Prefabricated, wrapped WCPS requests allow to efficiently obtain the slices.


    The second scenario is about the Hakon-Mosby mud volcano, twelve hundred meters deep on the ocean floor. Bathymetry data and video mosaics are combined into a visual navigation as known from Web Map Services.


    The third and last scenario focuses on computing the vegetation index from hyperspectral satellite imagery. Via a slider, a threshold value can be chosen by the user. The parametrized query remains hidden.


    Concluding, WCPS is a powerful extension to WCS which enables ad-hoc navigation, extraction, aggregation, and analysis without any programming. Ultimately, the flexibility and power of the WCPS language, as an "SQL for coverages", introduces coverages into the Semantic Web.


    CCIP future go deeper into the model to expose more data and processing steps

    Climate Challenge Integration Plugfest 2009 is demonstrating that Climate data is just like other spatial and earth observation data and that it too can be shared and utilised via open standards.

    CCIP is part of a series of efforts to advance data sharing in the climate domain. The Global Earth Observation Systems of Systems (GEOSS) is also acting as pathfinder, demonstrating that Earth Observation data can be shared and utilised via open standards, particularly Open Geospatial Consortium (OGC) standards and ISO 19100 series standards. Also, the World Meteorological Organization's Weather Information System is another related effort that the CCIP work strives to support.

    In future CCIP initiatives we plan to explore the Climate domain in more depth to ensure that we remove barriers to open standards and open data sharing and geo-processing with Climate data.

    -- RajSingh - 04 Oct 2009
    Topic revision: r5 - 12 Oct 2009, ChrisTweedie
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