Table of Contents

Subcommittee on Global Change Research, Participating Agencies and Executive Offices

Ad hoc Working Group on Climate Modeling

Foreword

Executive Summary

1. Background

2. Summary of Findings

3. Summary of recommen- dations

4. Final Comments

Charge to the Working Group 

Main Report

1. Purpose

2. Current Situation

3. Scope of Document / Underlying Definitions and Assumptions

4. Elements of Climate Science

5. Issues of Computational Systems

6. Human resources

7. Management / Business Practices / Institutional models

8. Recommen- dations

9. Reference Documents

10. Endnotes

Full Report (PDF)

The benefits of weather forecasting to both civil and military enterprises of the United States are well established. As the capabilities of the weather and climate modeling community have increased, the expectations for products have expanded. Now, there are societal needs for seasonal and interannual predictions, environmental assessments, and sophisticated model-assimilated data sets to aid in the quantification of the physical and chemical processes that determine the balance of key environmental parameters (i.e. temperature, water, winds, ozone, etc.). Historically, many of the capabilities to meet these needs have grown out of successful research activities that have expanded to take on the responsibility to provide these products.

A number of factors external to the research community have changed in recent years that stress these capabilities. In fact, the report Capacity of U.S. Climate Modeling to Support Climate Change Assessment Activities (National Academy Press, 1998) concludes that there are serious deficiencies in the country's ability to provide the necessary products for climate assessment. While the general quality of climate science in the U.S. remains competitive with any in the world, there is little doubt that the ability of centers in Europe, Canada, Japan, and other countries to perform computational experimentation far exceeds that of their U.S. counterparts. Foreign centers are able to run more comprehensive models, use more observations, and increasingly capture the intellectual interest of the extended scientific community. In fact, observational capabilities developed by U.S. agencies and breakthroughs by scientists at U.S. research centers and universities are often being more effectively exploited abroad.

There are a series of complex problems that must be addressed if the capabilities of U.S. climate science are going to be boosted to meet the expectations of the Nation. The solutions to these problems are not straightforward and are entangled with a number of issues that are outside of the direct control of climate scientists or the managers within the agencies that fund climate science. There are three major problems that sit at the foundation of the crisis currently facing the U.S. climate-science enterprises.

I. The high performance computing industry has fundamentally changed. While this has provided better computational resources to many individual researchers, those applications that require the highest level of computing are struggling to remain viable. The tension is heightened by U.S. policy on supercomputers, which leaves U.S. scientists with a significant usability and performance gap compared with their foreign counterparts.

II. There are not enough people to provide either the scientific or information technology expertise needed to sustain all of the U.S. modeling and assimilation projects that strive to provide comprehensive capabilities. Key positions are going unfilled and students are not being trained to fill either the scientific research positions or the esoteric niches of computational science and software engineering required for a successful high-end climate capability.

III. The multi-agency culture that developed to support discovery-driven research activities is not well suited to support a more product-oriented climate service. A multitude of sub-critical activities reside in the different agencies, and there is not an effective business plan with a consistent incentive structure to allow concerted concentration of these resources towards common product-oriented goals.

In addition to these three major problems, the growth of high-quality climate-science capabilities outside the U.S. places the U.S. climate-science community in a difficult position. Line managers at all U.S. institutions feel the pressure to compete, especially with the European Center for Medium-range Weather Forecasts (ECMWF), The Hadley Center, and The Max Planck Institute for Meteorology (Hamburg). In many cases weather and climate products from these centers are held up as the standard, and there is little hope of the U.S. meeting these standards in the immediate future. Thus, the public and both government and private sector institutions are deprived of the benefits of the best possible capabilities. Further, as model assessments of environmental changes and their impact play a more important role in determination of a wide variety of policy decisions, simulations provided by non-U.S. centers lay the foundation on which these decisions are made. It is in the self-interest of the U.S. to be able to generate state-of-the-art environmental modeling and model-assimilated data products.

These three major problems, coupled with the competitive pressures that come from many non-U.S. centers, place the climate-science community in an unprecedented situation. Simply adding funds to the existing organizations will not yield a cost-effective, robust, and flexible high-end climate-science capability. The problems are not purely technical, but require addressing sociological and business problems that sit at the foundation of the U.S. multi-agency scientific culture. Solutions are not straightforward and have significant risk of failure. Computational issues are at the center of this risk, but the sociological and business issues are as daunting and important. This report will expose the elements of these issues more fully and then suggest strategies with which to confront these issues.