Workshop Report

Bridging the Climate Information Gap

held at Argonne National Laboratory

September 29, 1999

by

John Taylor

Mathematics and Computer Science Division

&

Environmental Research Division


Argonne National Laboratory

This work was supported by the U.S. Department of Energy under Contract W-31-109-Eng-38.

 

 

 

Preface

This document summarizes the discussions held at a one-day workshop at Argonne National Laboratory on the topic of Bridging the Climate Information Gap. The meeting provided an opportunity for open discussion by scientists with an interest in regional climate science and in downscaling global climate model output for use in climate impact assessment for the Midwest and Great Plains. More than forty experts in the fields of regional climate science and high-performance computing attended the meeting and undertook discussions in five working groups. This document provides a record of those discussions; it is not intended to be a comprehensive summary of the field of regional climate science. Comments on the content of this document are welcome.

John Taylor

8 October 1999





In a recent report entitled The Regional Impacts of Climate Change it was concluded that

[T]he technological capacity to adapt to climate change is likely to be readily available in North America, but its application will be realized only if the necessary information is available (sufficiently far in advance in relation to the planning horizons and lifetimes of investments) and the institutional and financial capacity to manage change exists.

The report also acknowledged that one of the key factors that limit the ability to understand the vulnerability of subregions of North America to climate change, and to develop and implement adaptive strategies to reduce that vulnerability, is the lack of accurate regional projections of climate change, including extreme events.1 In particular, scientists need to account for the physical-geographic characteristics (e.g., the Great Lakes, coastlines, and mountain ranges) that play a significant role in the North America climate and also need to consider the feedback between the biosphere and atmosphere.1

The potential impacts of global climate change have long been investigated based on the results of climate simulations using global climate models with typical model resolutions on the order of hundreds of kilometers. However, assessment of the impacts of climate change at the regional and local level requires predictions of climate change at the 1-10 kilometer scale. Model predictions from global climate models with such high resolutions are not likely to become widely available in the near future.

Accordingly, researchers at Argonne National Laboratory have begun a program to develop and use regional climate models that lead to high-quality projections of regional climate at kilometer resolution; the focus is on the U.S. Midwest. These regional climate projections can be used both at Argonne and by the wider research community to assess the vulnerability of the U.S. Midwest to climate change; in turn, such assessments can be used by policy makers to develop appropriate response strategies.

Regional climate models typically are nested within a global climate model. The figure below illustrates the principle of nesting a regional model within a coarse-resolution global model.

Background to the Workshop

In conjunction with the Argonne effort to develop regional climate models, Argonne scientists are working to establish a Regional Collaborative Climate Center (RCCC). The primary objective in establishing such a center is to link the predictive global climate modeling capability with the impact assessment and policy-making communities. The primary technical challenge is to downscale global climate model output to the regional scale. The focus area is the Midwest and Great Plains region of the United States.

The necessary ingredients for a regional climate collaboration center include the following:

The intended users of the center are climate change researchers and members of the impacts analysis and assessment communities. These users must be able to perform large-scale processing of numerous, diverse, very large, and relatively raw data sets, to distill regionally significant information and to fulfill requests for information by policy makers. We assume most users will bring a high degree of problem-specific knowledge but will possess varying proficiency with computational, data handling, analysis, visualization, and remote access technologies.

In addition to these primary users, the center will engage other users, for example, students and educators at the university as well as K-12 levels studying climate change.

Since many of these users will be accessing the RCCC remotely, the center should be implemented as a virtual facility. The center should support a mix of computation and data access for unique runs and should be transparent with regard to how and where operations are performed, while ensuring adequate performance and appropriate levels of authentication and security.

The planned focus of efforts at the RCCC is as follows:

Outreach is intended to play a central role in the climate center activities. At Argonne we are particularly interested in assisting the scientific community working on Midwest and Great Plains climate issues. Accordingly, we arranged a meeting at Argonne National Laboratory entitled "Bridging the Climate Information Gap." The meeting provided an opportunity for open discussion by scientists with an interest in studying regional climate science and in downscaling global climate model output for use in climate impact assessment for the Midwest and Great Plains. Specifically, the purpose of the meeting was threefold:

Approximately forty researchers from laboratories and universities nationwide attended the workshop. The participants were divided into five working groups, as follows (the chairpersons are given in parentheses); for further information, see Appendixes 1 (the workshop schedule), 2 (a list of workshop participants), and 3 (the working group members).

Each working group was asked to address the following points:-

The next section of this document presents the report of each working group. The last section summarizes the results and presents conclusions about Argonne’s role in establishing and operating a regional collaborative climate center for the Midwest.

Working Group Reports

 

Group 1: Downscaling

Long-Term Goals

The Downscaling group identified five areas of long-term research: downscaling methods, uncertainties in regional climate modeling, candidate regional climate models, data management issues, and regional climate runs.

(i) Downscaling methods

It was recognized that two key approaches to downscaling would provide the basis for a Midwest Regional Collaborative Climate Center at Argonne: physically based modeling; and statistical/empirical-based modeling.

Physically based modeling involves the development of regional climate models appropriate to the region of interest. For the Midwest a regional climate must include a set of physical parameterizations for processes associated with the influence of the Great Lakes, land surface parameterizations, improved representation of the planetary boundary layer, and radiative transfer that can take into account the role of particles.

Statistical/empirical-based modeling may also play a role in downscaling global climate model (GCM) output. A wide range of approaches to statistical modeling are available, and their suitability for downscaling over the Midwest needs to be investigated. Statistical-based methods would be limited to a few key climate variables for which adequate data sets of observations were available for calibration purposes. Very few comparisons between statistical/empirical and physically based downscaling have been undertaken to date, and such comparisons will be needed in the long term.

It was also recognized that downscaling could be both linear, in that it distributes the larger scale global climate model averages at a finer scale, and nonlinear, in that the GCM provides the boundary conditions to a regional climate model, which generates a nonlinear downscaling by taking into account the physical, biological, and chemical processes at a much finer scale than the parent GCM.

(ii) Uncertainties in regional climate modeling

The following were identified as key uncertainties that would need to be addressed in the development of a regional climate model for the Midwest:-

A key concern was the quality of the GCM inputs and their role in determining the ability of regional climate models to produce reliable predictions of climate change. Supported by lessons learned from PIRCS (summarized in the box below), the group emphasized the importance of continued development of GCMs in providing improved boundary conditions for regional climate modeling over the Midwest.

 

  1. Regional climate models

Possible candidates to provide the basis for the development of a regional climate model for the Midwest include the following:

The NCAR MM5v3 modeling system was considered the most appropriate basis for commencing development of a new generation of climate models. It was also recognized that considerable experience has already been gained using MM5v2 and RegCM and that model comparisons will play an important role in establishing the uncertainty associated with downscaled climate model predictions. Nevertheless, the group emphasized that performing regional climate simulations at 1-5 kilometer resolution must be regarded as a new research frontier.

  1. Data management issues

In the long term, a wide range of data products will be needed. Examples include the following:

To ensure accessibility, these data sets must be made available over the Web via interactive tools for analysis, display, and downloading.

Achieving the best possible data quality for regional climate simulations will necessitate several tasks:

  1. Duration of regional climate runs

Current computing resources allocated to regional climate modeling in the United States allow regional climate runs up to 10 years at 50 km resolution, but not on a routine basis. In the long term, the following needs have been identified:-

Given the uncertainties noted above, a wide range of sensitivity studies will be needed in order to evaluate and improve the quality of the downscaled climate projections. This translates into the need for a substantial increase in computing resources available for investigating the performance of regional climate models and for downscaling the output of GCMs.

Immediate Goals

In the more immediate term, four research goals were deemed feasible and of high priority: downscaling experiments with MM5v3, additional experiments, statistical downscaling, and development of analysis tools.

 

  1. MM5v3 downscaling experiments

An initial experiment was proposed that would build on the existing PIRCS effort. Specifically, model runs for the period 1978-1988 have been completed with the RegCM2 and HIRHAM regional climate models for the Midwest at a nominal 50 km resolution. It was recommended that

Sensitivity studies could also be undertaken with and without the OSU land-surface model and with the Grell and KF convective precipitation schemes. Extending the lateral boundary relaxation conditions will also require investigation; it was proposed that this experiment be undertaken using the ARPS model.

The box below summarizes current plans for the development of MM5v3 by NCAR for application to regional climate simulations.

(ii) Additional experiments

The experiment described above could usefully be extended to include additional lateral boundary condition data sets derived from reanalysis projects and global climate models after completion of the first phase of experiments. The following high-priority lateral boundary condition data sets were identified:

Performing ensemble runs was also recognized as an important tool for model evaluation. However, available resources currently limit our ability to undertake ensemble experiments.

  1. Statistical downscaling

A useful first step would be to undertake a comparison of regression, condition models, and neural net approaches commonly applied in statistical downscaling.

Further development of analysis tools for working with the output of regional climate simulations was also identified as a priority for enhancing productivity. It was proposed that useful short-term activities would be to

 

Group 2: Hydrology

Long-Term Goals

The Hydrology group identified two major long-term scientific objectives, each of which also has major implications for impact assessment and policy/decision making:

The group also developed a model evaluation strategy that has two key components aimed at an overall assessment of model uncertainties:

To undertake the first activity, the regional model (MM5) must be run for an appropriate Midwest domain, with NCEP, ECMWF, and/or DAO reanalyses providing the lateral boundary forcing. The domain has yet to be defined; but to accomplish the overall goals, it must contain at least one of the Great Lakes. Thus the initial domain will likely cover the upper Midwest region. After appropriate evaluation, the regional model will be forced at the lateral boundaries using a GCM (most likely the NCAR CCM). This is the same global model that will ultimately be used for climate change scenarios.

Two components are involved in the second activity. The first of these addresses questions of historical variability. GCM runs over the past 1000 years (currently being made at NCAR and elsewhere) will provide the boundary forcing, with historically appropriate land-use changes imposed. Examples include 17th-18th century runs with MM5, the medieval warm period from A.D. 1000 to A.D. 1400, and the "Little Ice Age" of the late 1600s. The second element involves study of paleoclimate (i.e., time periods previous to the historical record) for which geologic reconstructions for the upper Midwest are well known. An obvious example is simulations for 3k, 5k, 6k, 7k, 9k BP, for which considerable prior global modeling exists and for which extensive geologic reconstructions have been made.

Ultimately scientists will be moving toward simulations of possible future climatic change (e.g., under an enhanced greenhouse world), so that the two long-term scientific objectives can be realized.

Six other long-term issues meriting future work were identified during the meeting:

Immediate Goals

Our short-term goals for the next year are aimed at developing and implementing a regional model system that is capable of simulating climate for the upper Midwest, including the Great Lakes. The proposed region has yet to be defined fully, but is likely to be based on the north-central region of GCIP. Focusing on this limited-scale area will enable researchers to take advantage of the tremendous amount of work already being done for this region through GCIP; three members of the Hydrology team (Oglesby, Marshall, and Lapenta) are also current GCIP principal investigators.

The following are needed for model development:

Two factors must be kept in mind as this preliminary regional model run is designed and implemented:

If the necessary model developments are successfully undertaken, researchers should be able during the coming year to make an initial five-year run for the upper Midwest domain, using MM5v3 and the most suitable land surface package, forced by NCEP II.

 

Group 3: Energy

Long-Term Goals

The Energy group identified five primary objectives: (1) assessing energy consumption and generation scenarios over the next 100 years for the Midwest; (2) developing and collecting greenhouse gas source/sink estimates on a local scale; (3) developing and collecting emission scenarios for precursors of air pollution and aerosols on the local scale; (4) performing assessment calculations to evaluate the impacts of these emissions on climate and the effect of climate change on these estimates; and (5) preparing impact assessments for the regions’ air quality, agricultural production, and human health

(i) Energy production/consumption

Development of energy consumption/production scenarios is a crucial task because of the

proposed energy utilities deregulation and the possible decommissioning of aging nuclear energy generation infrastructure that generates a significant portion of the current Midwest energy supply. The choices made for future energy generation could dictate the location of the power plants and, as a result, the emissions of greenhouse gases and air pollution precursors in the region. The group identified potential parties that may be

actively pursuing this task, including some at Argonne. It was agreed that the relevant parties, starting with those located inside Argonne, should be included in future meetings and a discussion started with them immediately. Moreover, in developing and assessing currently available modeling frameworks for estimating regional energy requirements and consumption, consideration should be given to the impact of decisions made on a countrywide and international scale. There should be feedback from these model outputs into the global-scale models, in order to develop realistic assessment scenarios.

(ii) Greenhouse gas budgets

Developing tools for detailed analysis of greenhouse gas emissions and sinks on a local scale was considered a necessary priority for the center. In this context, the center could emulate the work performed by the Iowa Department of Natural Conservation in developing greenhouse gas sink/source estimates to the level of local farms. The focus of the Iowa effort was to develop policies to make that state a net zero greenhouse gas emitter. This type of inventory-making capability should be acquired by the center and a demonstration performed to show that better decision making would result from better tools.

(iii) Integrated assessment modeling

The most effective tool the center could develop to serve users across a broad cross-section of society, from research scientists to policy makers, is an integrated assessment model. These types of models are frequently used in the IPCC assessments on a global scale and integrate across a range of process-scale models representing energy production, consumption, emissions, and impacts of greenhouse gases and pollutants. Such models provide an excellent opportunity to study the feedback between climate and the biosphere, atmospheric trace gas abundance, and the energy production/consumption in various sectors of the economy in an integrated framework. The development of integrated assessment tools is still in its infancy, and the center could make a strong bid for leadership in this area..

(iv) Science issues

Science issues of interest include the impact of further urban sprawl on oxidants and aerosols, effects of land use change on regional climate, and impacts of agricultural practices on climate and chemistry. The relationship between energy use and agriculture, in particular, should be a focus of the center’s science activities. Below is a list of science issues that were discussed:

(v) Modeling tools

The group identified the following process models to evaluate the energy-chemistry-biosphere-climate interactions on a regional scale:

Several of these models are available within the group, and it was decided to examine available options for the remaining modules.

(vi) Uncertainties

The following uncertainties were listed as items for consideration in the regional-scale modeling efforts described above:

(vii) Computing and data storage and handling

The following list of priorities was discussed at the meeting:

Immediate Goals

In the short term, energy research should focus on GHG budgets and regional-scale assessment models.

(i) GHG budgets

Two activities were identified for immediate consideration:

 

  1. Integrated regional-scale assessment models

A prototype model calculation was recommended as a first step toward developing a comprehensive integrated assessment model for the regional scale. This calculation should involve development of interfaces between models calculating energy production/consumption based on sector analysis, an emissions calculation model that uses the output from the energy model to compute emissions of pollutants, and GHGs. This calculation in turn would feed into a chemistry-transport model linked to the

regional-scale climate model to drive the model transport. The chemical model boundary conditions would be set from global-scale CTM outputs, by developing couplers between the regional-scale code and the GCTM. The RCTM would be connected to a surface process model with the capability of computing deposition rates and emissions from biosphere. The final step would link this model to a crop-nutrient-cycle model to calculate soil emissions and effects of deposition from the gas phase on the nutrient-cycle

in the soil. The outputs would in turn be fed back to the energy component model to improve the decisions made on energy consumption/production in each sector of the economy, so as to minimize the impacts on the biosphere and air quality. The prototype would function with models readily available, and missing components would be filled with shell interfaces for the prototype calculation.

As a part of this process, the group identified the following issues to be analyzed and summarized in a report to be submitted by the end of next year:

The figure below shows the proposed prototype calculation setup.

 

Group 4: Planetary Boundary Layer

Long-Term Goals

Long-term goals for the planetary boundary layer (PBL) effort can be considered in three broad categories: service, data products, and research.

Service identifies the potential "customers," a useful consideration before defining research goals. These customers are involved in agriculture, hydrology, urban and regional planning, air pollution meteorology, ecology, economics, and research at a variety of private and government organizations.

Data products associated with the PBL include storm frequency, especially extremes in precipitation amounts; length of the growing season; extremes in winds (e.g., with regard to loading on buildings and soil erosion); extremes in temperature as they affect vegetation and soil freezing depth; and atmospheric stability as it affects the vertical and horizontal transport of trace substances. Parameters most directly involved with many of these data products are surface temperature, near-surface temperature and humidity, the diurnal variation of the PBL height and vertical density stratification, surface energy exchange, and local mesoscale circulations. Processes such as solar irradiance, water drainage, irrigation, and changes in land use patterns must also be considered.

Research necessary to ensure an adequate description of the PBL in regional climate scenarios requires both the accurate simulation or parameterization of PBL processes and the achievement of a sufficiently fine spatial resolution. The daytime PBL over homogeneous terrain with known properties is fairly well understood, but the effects of

surface heterogeneity and of very stable conditions at night remain subjects of research. Models with high spatial and temporal resolution must continue to be developed. These models can be used to develop parameterizations for regional- and large-scale models or be used as nested models in regional-scale models. Also needed are intensive observations using both in situ and remote sensing systems. In addition, long-term

observations are often necessary to examine the full range of conditions that occur throughout the year; data sets need to be made readily available to researchers. Such observations provide information necessary to improve PBL models and parameterizations and can serve as a benchmark for evaluating nested models.

To achieve fine spatial resolution, extensive data bases are needed on surface quantities such as soil moisture, vegetative types, green leaf areas, senescent vegetative coverage, agricultural practices, extent of urbanization, and fractional snow cover. Remote sensing data obtained from satellites provide an important source of such information, especially when used with surface stations for "ground truth." For example, mesoscale models require periodic updates on soil moisture conditions to avoid "drift" in simulate soil moisture content, which is important in affecting evapotranspiration rates and cloud formation, surface temperatures, and atmospheric stability. The nondimensional difference vegetation index, infrared temperature, and microwave surface brightness in the L-band are examples of parameters based on surface radiances detected from satellites that can used to estimate soil moisture content. However, because spatial variability in the surface properties can be large on very fine scales, often less than 200 m in the Midwest and the Great Plains, methods of aggregrating descriptions of surface properties are often necessary to provide effective inputs to regional- and large-scale models. Better methods of describing surface conditions such as aerodynamic surface roughness, surface energy balance components, soil moisture content, and surface temperature averages over scales spanning large changes in surface conditions need to be developed.

 

Immediate Goals

Several ongoing research efforts in which progress is possible during the next year or so were identified with regard to PBL processes:

 

Group 5: Computing

Argonne has been working closely with the NCAR Mesoscale and Microscale Meteorology Division, Pacific Northwest National Laboratory, and a number of collaborating institutions (see http://www.mmm.ucar.edu/mm5/CRCM) to develop a Community Regional Climate Model based on MM5, the fifth-generation Penn State/NCAR Mesoscale Model. The CRCM effort will fold previous MM-based Regional Climate Models (RegCM, PNNL RCM, IFU RegCM) into a single community resource developed and maintained as part of the parallel MM5 community mesoscale model. Many capabilities for long climate-scale regional simulations already exist in MM5, including the ability to run on large distributed SMP-cluster parallel computers. Additional enhancements for regional climate are described in the table below; these include both long-term and short-term efforts.

Such enhancements will require significant computing capabilities. Currently, we estimate that a typical experiment will involve a number of computationally intensive and data-intensive runs of a regional climate model to downscale large global reanalysis or climate model data sets over a period of several months to years. The regional model would be run at significantly higher (and therefore more costly) resolution (3-10 kilometers per grid cell) than the input (50-200 kilometers). To achieve one year’s simulation for a domain 1000 km square, a regional climate model run at 10 km resolution will require 40 Gflop/second sustained performance for 24-hour turnaround and will generate 50 Gbytes of hourly history output. To run the same domain at 3.33 kilometers resolution requires 27 times the performance, 1.1 Tflop/second, and generates 9 times the data volume.

We expect a more complete picture of computing and infrastructure requirements to emerge over time, as a result of interactions and planning with the scientific users,

 

Long-Term Goals

For the long term, we propose that the RCCC have at least enough dedicated supercomputer resources to support the equivalent of several (5-10) 10-year high-resolution (3 km or less) studies per year. In addition to computational requirements, the center will require multiterabyte data storage and archiving capabilities, presumably in concert within a larger DOE metacomputing infrastructure (e.g., the Earth System Grid project). Also required will be Web-enabled visualization and analysis software and hardware, desktop and workspace remote collaboration tools, network connectivity and bandwidth, quality of service, and secure access to support the virtual concept of the RCCC.

 

Short-Term Goals

The relatively modest requirements for a short-term (first-year) set of downscaling experiments (see Downscaling section) may be met by purchasing time on resources currently available to participating institutions:

Software resources available to support first-year center prototype goals include the following:

Conclusions

Providing high-resolution regional climate information has long been recognized as critical information necessary for the assessment the impacts of climate change and to develop and implement adaptive strategies to reduce that vulnerability. The discussion, as reported above, provides a concise summary of the many high-priority scientific and technical challenges that must be addressed if region-specific climate information is to be used on a routine basis to assess the potential impacts of climate change on the Midwest. If the challenges identified above are to be addressed, then the development of strong interdisciplinary research programs and research teams that can provide comprehensive coverage of the scientific and technical issues is urgently, and inevitably, needed.

 

Appendix 1: Meeting Agenda

Bridging the Climate Information Gap

Argonne National Laboratory

September 29, 1999

Agenda

 

7:45 - 8:15AM Shuttle van from Argonne Guest House Entrance to Bldg. 221 Lobby

8:00 - 8:30AM Registration and Travel Reimbursement

Coffee and Rolls

8:30 - 8:40AM Welcome - Rick Stevens, Director MCS

8:40 - 9:00AM Introduction to ANL Regional Climate Group & Meeting Objectives

John Taylor, ANL

9:00 - 10:30AM Working Groups - Long term scientific goals

Downscaling - John Taylor - Bldg. 221-A216

Energy - Rao Kotamarthi and Don Wuebbles - Bldg. 203-C230

Water - Bob Oglesby and Jay Larson - Bldg. 221-A261

PBL - Marv Wesely - Bldg. 203-E142

Computing - Ian Foster and John Michalakes - Bldg. 221-C101

10:30-10:45AM BREAK - Coffee in A216

10:45-11:30AM Working Groups – cont.

11:30 - 12:30PM Plenary Session - Long term scientific goals - Bldg. 221-A216

12:30 - 1:30PM No Host Lunch - Dining Room A in Cafeteria - Bldg. 213

1:30-2:00PM Regionalization Strategies for Climate Change Scenario Development: Perspectives from the IPCC Third Assessment Report (TAR)– Linda Mearns, NCAR

2:00-3:30PM Working Groups - Immediate scientific goals

Downscaling - John Taylor - Bldg. 221-A216

Energy - Rao Kotamarthi and Don Wuebbles - Bldg. 203-C230

Water - Bob Oglesby and Jay Larson - Bldg. 221-A261

PBL - Marv Wesely - Bldg. 203-E142

Computing - Ian Foster and John Michalakes - Bldg. 221-C101

3:30-3:45PM BREAK – Refreshments in A216

3:45-5:00PM Working Groups – cont.

5:00 - 6:00PM Plenary Session - Immediate scientific goals - Bldg. 221-A216

6:00PM Adjourn - Shuttle van from Bldg. 221 Lobby to the Argonne Guest House



Appendix 2: List of Participants

Arritt, Raymond

Associate Professor

Iowa State University

3010 Agronomy Hall

Ames, Iowa 50011

rwarritt@iastate.edu

515-294-9870

515-294-2619


Carmichael, Gregory

Professor, Center for Global & Regional

Environmental Research & Dept. of Chemical & Biochemical Engrg.

University of Iowa

204 IATL

Iowa City, IA 52240

gcarmich@icaen.uiowa.edu

319-335-3333

319-335-3337


Chen, Fie

Scientist-I

NCAR

3450 Mitchell Lane

Boulder, CO 80301-2260

feichen@ucar.edu

303-497-8454

303-497-8401


Dudhia, Jimy

Dr., MMM Division

NCAR

P.O. Box 3000

Boulder, CO 80307-3000

dudhia@ucar.edu

303-497-8950

303-497-8171


Evard, Remy

Manager of Advanced Computing Technologies and Networking (ACTN)

Argonne National Laboratory

MCS 221, 9700 S. Cass Avenue

Argonne, IL 60439

evard@mcs.anl.gov

630-252-5963

630-252-5986


Foster, Ian

Senior Computer Scientist

Argonne National Laboratory

MCS 221, 9700 S. Cass Avenue

Argonne, IL 60439

foster@mcs.anl.gov

630-252-4619

630-252-5986


Grimmond, Sue

Associate Professor

Indiana University

Dept. of Geography, Atm. Science Program

701 E. Kirkwood Ave

Bloomington, IN 47405-7100

grimmon@indiana.edu

812-855-7971

812-855-1661


Hammond, Steve

Head, Computational Science Section

NCAR

1850 Table Mesa Drive

Boulder, CO 80303

hammond@ncar.ucar.edu

303-497-1811

303-497-1286

 


Jacob, Robert

Research Associate, Dept. of Geophysical Sciences

University of Chicago

5734 S. Ellis Ave.

Chicago, IL 60637

rob@geosci.uchicago.edu

773 834-2788

773 702-9505


Jain, Atul

Dr., Dept. of Atmospheric Sciences

University of Illinois

105 South Gregory Street

Urbana, IL 61801

jain@atmos.uiuc.edu

(217) 333-2128

(217) 244-4393


Johnson, Tom

Director and Professor

Large Lakes Observatory

Univ. of Minnesota-Duluth

Duluth, MN 55812

tcj@d.umn.edu

218-726-8128

218-726-6679


Kotamarthi, Rao

Meteorologist

Argonne National Laboratory

Bldg. 203, J-177

9700 S. Cass Ave.

Argonne, IL 60439

vrkotamarthi@anl.gov

630-252-7164

630-252-5498


Kristovich, David

Professional Scientist

Illinois State Water Survey

Department of Natural Resources and

University of Illinois at Urbana-Champaign

2204 Griffith Drive

Champaign, IL 61820-7495

dkristo@uiuc.edu

217-333-7399

217-333-6540


Lapenta, William

Atmospheric Research Scientist

Global Hydrology and Climte Center

NASA

977 Explorer Blvd.

Huntsville, AL 35806

bill.lapenta@msfc.nasa.gov

256-922-5834

256-922-5723


Larson, Jay

Earth System Science Interdisciplinary Center

Univ. of Maryland

NASA

Code 910.3 - NASA GSFC

Greenbelt, MD

jlarson@dao.gsfc.nasa.gov

301-614-6246

301-614-6297


Larson, Sue

Associate Professor

University of Illinois

Dept. of Civil & Environmental Engrg., 3230 Newmark Cel, MC-250 N. Mathews Ave.

Urbana, IL 61801

smlarson@uiuc.edu

217-333-0047

217-333-6968


Liang, Xin-Zhong

Assoc. Professional Scientist

Illinois State Water Survey

Department of Natural Resources and

University of Illinois at Urbana-Champaign

2204 Griffith Drive

Champaign, IL 61820-7495

xliang@uiuc.edu

217-244-6864

217-244-0220


Marshall, Susan

University of North Carolina-Charlotte

Department of Geography and Earth Sciences-9201 University City Boulevard

Charlotte, NC 28223

susanm@uncc.edu

704-547-3498

704-547-3182


Mearns, Linda

Scientist III

NCAR

P.O. Box 3000

Boulder, CO 80307-3000

lindam@ucar.edu

303-497-8124

303-497-8125


Michalakes, John

Software Engineer/Visiting Scientist

NCAR, MMM Division

3450 Mitchell Lane

Boulder, CO 80301

michalak@ucar.edu

303-497-8181


Moore, Thomas L.

Geologist

Energy Systems Division

Argonne National Laboratory

9700 South Cass Avenue – Bldg. 362

Argonne, IL 60439

tmoore@anl.gov

630-252-5856

630-252-9281


Nefedova, Veronika

Postdoctoral Appt

Argonne National Laboratory

MCS 221, 9700 S. Cass Avenue

Argonne, IL 60439

nefedova@mcs.anl.gov

630-252-5666

630-252-5986


Oglesby, Bob

Associate Professor

Purdue University

Dept. of Earth & Atmospheric Sciences

West Lafayette, IN 47906

roglesby@purdue.edu

765-494-9531

765-496-1210


Reilly, Chris

Director, Environmental Reseach

Argonne National Laboratory

ER 203, 9700 S. Cass Avenue

Argonne, IL 60439

creilly@anl.gov

630-252-3879

630-252-2959


Rowe, Clinton M.

Associate Professor

University of Nebraska-Lincoln

Dept. of Geosciences, 305C Bessey Hall

Lincoln, NE 68588-0340

crowe1@unl.edu

402-472-1946

402-472-4917


Salisbury, Chuck

Scientific Programmer

Argonne National Laboratory

9700 S. Cass Avenue

Argonne, IL 60439

salisbur@mcs.anl.gov

630-252-7573

630-252-6104


Schmid, Hans Peter (HaPe)

Assistant Professor

Indiana University

Dept. of Geography, Atm. Science Program

701 E. Kirkwood Ave

Bloomington, IN 47405-7100

hschmid@indiana.edu

812-855-6125

812-855-1661


Shepson, Paul

Professor

Purdue University

1393 Brown Building

West Lafayette, IN 47906

pshepson@purdue.edu

765-494-7441

765-494-0239


Sorbjan, Zbigniew

Res. Assoc. Professor

Marquette University

Dept of Physics

Milwaukee, WI 53201

sorbjanz@mu.edu

414-288-7458

414-288-3989


Stevens, Rick

Director, MCS Diviision

Argonne National Laboratory

Bldg. 221, A-209, 9700 S. Cass Ave.

Argonne, IL 60439

stevens@mcs.anl.gov

630-252-3378

630-252-6333


Taylor, John

Computational Scientist

Argonne National Laboratory

Bldg. 203, C-245, 9700 S. Cass Ave.

Argonne, IL 60439

jtaylor@mcs.anl.gov

630-252-4213

630-252-5986


Ting, Mingfang

Assoc Prof. UIUC/FRA at ANL

Argonne National Laboratory

Bldg. 203, J-158, 9700 S. Cass Ave.

Argonne, IL 60439

ting@anl.gov

630-252-1152

630-252-5498


Tobis, Michael

Research Scientist

University of Wisconsin

1225 W. Dayton St.

Madison, WI 53706

tobis@ssec.wisc.edu

608-263-2566

608-249-3321


Wesely, Marv

Senior Meteorlogist

Argonne National Laboratory

Bldg. 203, J-143, 9700 S. Cass Ave.

Argonne, IL 60439

mlwesely@anl.gov

630-252-5827

630-252-7164


Wilhelmson, Bob

Professor of Meteorology

University of Illinois

105 South Gregory Drive

Urbana, IL 61801

bw@ncsa.uiuc.edu

217-333-8651

217-244-4393


Wuebbles, Donald

Head, Dept. of Atmospheric Sciences

University of Illinois

105 South Gregory Street

Urbana, IL 61801

wuebbles@atmos.uiuc.edu

217-244-1568

217-244-4393


Xu, Yiwen

Posdoctoral Appt.

Argonne National Laboratory

ER 203, 9700 S. Cass Avenue

Argonne, IL 60439

yiwen_xu@anl.gov

630-252-6139

630-252-5498


Xue, Ming

Senior Research Scientist

University of Oklahoma

SEC, Rm 1110, 100 E. Boyd

Norman, OK 73019

mxue@ou.edu

405-325-6037

405-325-7614

 

Appendix 3: Working Groups

John Taylor
Downscaling
Aritt, Raymond
Dudia, Jimy
Liang, Xi-Zhong
Mearns, Linda
Xue, Ming


Ian Foster
Computing
Evard, Remy
Hammond, Steve
Jacob, Robert
Michalakes, John
Nefedova, Veronika
Salisbury, Chuck
Tobis, Michael
Wilhelmson, Bob

Bob Oglesby
Hydrology
Johnton, Tom
Lapenta, William
Larson, Jay
Marshall, Susan
Moore, Thomas
Rowe, Clinton
Ting, Mingfang


Rao Kotamarthi
Energy
Carmichael, Gregory
Jain, Atul
Larson, Sue
Shepson, Paul
Wuebbles, Donald


Marv Wesely
PBL
Chen, Fie
Grimmond, Sue
Kristovich, David
Schmid, Hans Peter
Sorbjan, Zbigniew
Xu, Yiwen