***18. Grand Challenges in Observations, Modeling, and Information
Systems***

**December 4, 2002 - 2:00-4:00**

**Rapporteur: Margarita Conkright (NOAA/CCSP)**

Moderator: Richard Williams (USGS)

Overview: Jack Kaye (NASA)

Rapporteurs: James Andrews (ONR), Margarita Conkright (NOAA/CCSP)

Panelists: Tim Barnett (Univ. of California), Peter Cornillon (Univ. of
Rhode Island), Robert Malone (Los Alamos Nat'l. Lab.), Bernard Minster
(Univ. of California), James O'Brien (Florida State Univ.), Steven
Running (Univ. of Montana)

**Tim Barnett**

Presented a study from the "Accelerated Climate Prediction Initiative"
which looked at impact of global warming on water resources in the
Western U.S. This study incorporated current state of the ocean with
models, regional impact scenarios. It was a multi-disciplinary study
with a combination of data, modeling, resources, and people.

Study related to strategic plan in that it identifies the following:

-   Requirement of multiple disciplines and how they will interact

-   What budget is available

-   Success is due to dedicated super computers

-   Need a distributed data management system

-   Regional Impacts of climate change

Suggestion: a grand challenge project, like that described above it the
approach to take

**Peter Cornillon**

-   Vision for data management is the correct one: interoperable data
    system providing seamless access

-   Not much emphasis on biological variables -- future problems will be
    the integration of physical and biological variables

-   Focus on human interactions with data systems

    -   Variables, data systems are too large

    -   Organization of data changes

    -   Aggregated data a high priority

    -   ***Requirement for machine-to-machine interoperability***

-   Program must focus on open access -- this is a barrier to
    machine-to-machine interoperability

-   Consideration should be given to security precautions

-   Data volume could become a major consideration in a
    machine-to-machine system

-   Currently few users are accessing large volumes of data

**Robert Malone:**

Presented a synthesis of nine reviewers from the DOE labs -- comments
divided into three sections: (1) GCOS; (2) Modeling; (3) Data

**1) GCOS**

-   Requirement of long-term, dedicated in-situ and satellite
    measurement -- needs continuity, maintenance of equipment, and
    ability to expand its scope

-   Priority section is a list of objectives with no priorities

-   Priorization suggested but not applied

> ***CHALLENGE:*** finding and reaching agreement on priorities

**2) Modeling**

-   Section does not specify which model

-   Need diversity of models especially to understand uncertainty

-   Modeling priorities were unprioritized objectives

> ***CHALLENGE:*** need high-end dedicated computer facilities and
> agreement on priorities

**3) Data**

> ***CHALLENGE:*** agreement from organizations on tools, storage,
> metadata, and interfaces

**General Comments:**

-   Is research being proposed as an alternative?

-   Need to monitor the strength of the conveyor belt

-   Requirement for data on past climates

-   No mention of ongoing programs addressing key issues (DOE ARM and
    Earth System Grid projects, ESMF at NASA)

-   Need error bars on modeling results provided for assessment

-   High-end computing capabilities were barely mentioned

**Bernard Minster**

1)  ***Information System***

    -   Transition to operational (integration, need to keep track of
        pedigree, transition to information systems)

    -   Threat to full/open data exchange -- database legislation and
        commercialization of data -- need to educate scientists on these
        issues

2)  ***Modeling***

-   Need to talk to other disciplines and interest them in our issues

-   Systems will behave in unpredictable ways

-   Develop new mathematics as well as numerical schemes

3)  ***Data and Information***

-   Challenge is to find data needed within the data systems --
    discovery of data should be automatic

-   Data migration is not covered in the plan

-   Funding -- there is an exponential growth in data holdings and users
    and the budgets are flat

-   For modeling data needs, need to increase resolution, visualization
    requirements may be beyond our current capabilities

-   Tools for decision-making processes are primitive

**Jim O'Brien**

There are no grand challenges in the chapter -- the following are the
challenges:

-   High-end computing -- we need to find simple ways to explain to
    funding officials why this is a requirement (i.e. Regional
    assessment had to use international models because the US does not
    have the capabilities)

-   Need funding over the long-term rather than a yearly funding cycle

-   Government does not provide good access to data -- need distributed
    data centers

-   No metadata associated with the re-analysis

-   Climate change is not just gases but also population growth

**Steve Running**

1)  Observations

    -   Grand challenge is the need for ecological observations and the
        need for new ideas on how to represent the biosphere globally

2)  Information Systems

-   Data storage is not a challenge -- the challenge is the integration,
    and automated search and access

3)  Modeling

-   Different time constants and spatial domains for land, oceans,
    atmosphere -- need to start with global perspective and zoom into
    regional scales

There was no grand vision "digital" or "virtual earth" are examples of a
vision. This was procedural rather than a vision

**COMMENTS FROM THE FLOOR**

**Julia Slingo**

-   Need to choose a problem which should push the envelope of our state
    of knowledge (i.e. increase model resolution)

-   Look at new mathematics developed by other disciplines

-   Look at weather prediction as a guide

-   Address issue of integrating time and space scales

**Randy Arnell (Pennsylvania State University) ?? Possible misspelling
of name (could be Brent Yarnal)**

-   Need to link this chapter and decision-support (need to find their
    needs and requirements and the links between scientists and
    decision-makers and decision support tools)