Capacity of U.S. Climate Modeling
In October of 1995 four U.S. climate researchers raised concerns in a letter (see Appendix A) to the USGCRP agency managers that the U.S. position of leadership in the development, improvement, and application of climate models had eroded. They offered various options for progress in these areas, emphasizing a well-coordinated, distributed national climate modeling program. While the specific recommendations of that letter are somewhat different than those of this report, the letter was one of the primary impetuses for the Climate Research Committee (CRC) of the National Research Council (NRC) and the USGCRP Program Office to hold a jointly sponsored forum on the “Quality and Infrastructure of Climate Modeling in the United States” on 11–12 June 1996 (see Appendix C, which contains the invitation letter to the forum and the agenda). About 70 scientists and federal program managers participated. In preparation for the forum, the USGCRP Program Office distributed a questionnaire to over 100 members of the climate-modeling community for their written comments on “the strengths and weaknesses of the present research and applications, related activities, and infrastructure for decadal-centennial scale climate modeling in the United States,” and received about 25 responses. Some of the findings in this report are based in part on the discussions at the forum and in answers to the questionnaire.
The U.S. government has pending before it the ratification of the Kyoto Protocol, an agreement to limit the emissions of greenhouse gases (GHGs), which is largely based on the threat GHGs pose to the global climate. Such an agreement would have significant economic and national security implications, and therefore any national policy decisions regarding this issue should rely in part on the best possible suite of scenarios from climate models.
This Protocol relating to GHGs is only one of a series of policy issues under consideration that involve climate and climate change. The Intergovernmental Panel on Climate Change (IPCC, 1998) lists several major areas of concern where climate changes would have a critical impact on policy decisions: ecosystems, hydrology and water resources, food and fiber production, coastal systems, human settlements, and human health. Governments, corporations, and the public are faced with a multitude of decisions in each one of these fundamental areas of concern. In terms of the daily lives of individuals, these decisions impact on jobs, food, economic well-being, livable environments, and general prosperity.
Issues bearing on the formulation of local, national, or global climate change policies are complex, and not always well defined. It could be just as disastrous to impose unnecessary restraints on society out of ignorance as it is to fail to act in time from indecision. Human, political, economic, and scientific considerations all come into play. These considerations can be at odds with each other in fundamental ways. Compromise rooted in knowledge is essential if progress is to be made.
Policy makers must have solid, credible information to define the issues, to generate realistic compromises, and to move the policy debates and decision processes forward. It is essential to provide the capability to produce well founded forecasts of the magnitudes and trends in climate change, as well as to identify the causative factorsnatural and anthropogenic. At the core of creating that capability is the
use of climate system models. These models, which may incorporate components including atmospheric, oceanic, and terrestrial dynamics, radiative characteristics, and chemistry, provide the only quantitative mechanism by which climate projections can be put in a context suitable for policy assessment and decisions.
Current Small and Intermediate Modeling Capabilities
The U.S. climate modeling community excels in conceiving and carrying out process and diagnostic studies that form the basis for climate model improvement. Likewise, the intermediate climate modeling research efforts, which a few years ago may have been referred to as high-end (see footnote 1), have been appropriately encouraged and supported. Evidence of this work are the coupled modeling contributions by the United States to the IPCC process, as well as the development of some of the leading mesoscale models (e.g., MM5, ETA, and COAMPS).3 U.S. leadership in this area has involved, for example, sensitivity studies, exploration of new hypotheses, and studies aimed at quantifying and understanding model uncertainties.
The relatively successful forecasts of the regional climate anomalies associated with the 1997–1998 ENSO event (COLA, 1998) and adaptations that were made in response to these forecasts, highlight the societal value of climate forecasting.4 The benefits that are being experienced as a result of this capability, underscore the potential utility of the development of long-term climate change scenarios, in particular, because future, long-term, anthropogenic
3 In highlighting the U.S. intermediate-level modeling expertise, it should not be overlooked that several foreign, intermediate modeling efforts, such as those of the ECMWF in weather forecasting, are at the cutting edge, sometimes leading those of the United States.
4 The computational requirements of these models, especially for operational production of ensembles of simulations, are enormously large, and the United States is at a competitive disadvantage, in this regard, compared to the major European modeling centers because of the greater access to appropriate computational resources outside the United States.
climate changes are likely to be larger than those that currently occur on the seasonal-to-interannual time frame of the ENSO phenomenon.
Current High-End Modeling Capabilities and Needs
Some of the earliest and defining climate change simulations and sensitivity experiments were carried out in the United States, and the contributions from the U.S. modeling community were essential to the overall understanding of various climate issues. That initial productivity has been difficult to sustain because of a lack of coordination and availability of the requisite computational and human resources.5 This may explain in part why, in contrast to some of the foreign modeling centers, U.S. modeling centers have found it difficult to perform coupled atmosphere-ocean climate change scenario simulations at the spatial resolutions (e.g., finer than 500 km × 800 km) of direct relevance to national policy actions presently being considered to mitigate future global change. According to discussions at the forum, at least some in the scientific community expressed the concern that the United States should have been able to contribute more in terms of high-end, coupled-model GHG and aerosol simulations to the recent IPCC assessment.
The computational capabilities that are required to incorporate various spatial resolutions in climate models are outlined in Table 1. It is apparent from Table 1 that several foreign modeling centers currently possess greater computing power than that of the U.S. centers. However, no modeling center currently has the computational ability to realistically depict small-scale/high-impact atmospheric processes in multi-century, transient simulations the type of simulation required to reduce uncertainties associated with assessments of the societal implications of climate change. Simulation of certain atmospheric features such as mesoscale convective complexes and hurricanes, even in a rudimentary fashion, requires a model spatial resolution of 10 km or less, which, in turn, requires
5 The view, repeatedly expressed at the forum, was that U.S. climate modeling research is at the forefront in most respects, but not all.
computational throughput more than three orders of magnitude greater than is presently available to U.S. climate modelers. This is at the upper range of the 40 teraflop (1012 floating point operations per second) capability proposed by the Advanced Climate Prediction Initiative (ACPI, 1998) for the year 2003.6
Current model deficiencies are not only in the realm of spatial, but also temporal resolution. For example, the current GFDL coupled model is generally run without a diurnal cycle, thereby precluding the ability to explicitly resolve critical variables such as daily maximum and minimum temperatures. The United States possesses the intellectual ability to put together models capable of better resolving many of these important climatic features. However, the current lack of coordinated computational capability limits the ability of U.S. scientists to develop such policy-relevant scenarios; it also limits the ability of U.S. scientists to diagnose and understand the physics of climate and climate change.
Currently, there are relatively few modeling centers anywhere in the world capable of producing relatively high-resolution (e.g., 250–300 km grid spacing), transient climate simulations. The differences in simulated climate produced by the various structures and compositions of these few models help to bound the range of outcomes that the climate system might produce given a certain forcing scenario. Thus, the state of climate modeling throughout the world is such that the addition or removal of even a single model could affect the confidence levels assigned to certain scenarios of future climate change. In other words, not only would the United States benefit from enhancements in its modeling capabilities but the international community would benefit as well.
In addition to the need for simulations produced by different climate models, estimates also need to be produced of the stochastic nature of climate change within a given model, i.e., ensembles of simulations, using slightly different initial conditions. Ideally, a new ensemble should be produced whenever significant improvements in a
6 The ACPI is an unfunded Department of Energy plan for increasing U.S. computing power for climate applications. The system and number of processors are currently unspecified.
model's code become available. The production of such ensembles to perform model diagnostics and climate change assessments in a timely fashion requires high computational throughput. Further increasing computational requirements is the use of regional, high-resolution models nested within medium-to-coarse resolution, global coupled models. U.S. climate modeling centers currently do not possess the computational resources required for these types of simulations.
While trying to catch up with foreign, high-end modeling efforts, the necessity of adequate model testing should not be overlooked. Testing, diagnosis, and documentation of model characteristics must be an intrinsic part of the procedure for developing climate change scenarios for assessment purposes. Again, the computational and human resources for this facet are substantial and are not sufficiently available to U.S. climate modelers.
Access to Foreign Model Output
A further hindrance to the sub-optimal high-end U.S. modeling capabilities is that the United States is not assured full, open, and timely access to output from foreign models. Ready access to foreign model output could alleviate some of the need for high-end domestic capabilities. It is acknowledged that in many instances the output from foreign models is readily forthcoming, such as in the case of the Atmospheric and Coupled Model Intercomparison Projects (AMIP/CMIP), the LINK project at the U.K. Climatic Research Unit, as well as countless other formal and informal data transmittals. However, the committee is concerned that access to foreign model output is not guaranteed. In several recent instances, access to foreign atmospheric data has either been denied or only occurred at considerable expense to U.S. entities (see Appendix D). As the commercial value of these data becomes more apparent, the possibility of greater restrictions exists, particularly with the movement towards privatization of meteorological agencies.
This issue of data accessibility is important for at least two reasons, and ultimately points towards the need for a high level of
domestic Earth system modeling capability. First, if political decisions are to be based upon the most current and reliable information, access to those data must be ensured. The NRC Pathways report (NRC, 1998b) addressed this in its statement that “the USGCRP must foster the development and application of models at the scale of time and space needed to understand and project the specific mechanisms controlling changes in the state of the Earth system thus providing the information required to support important policy processes.” Second, because the commercial value of data is in part a function of its timeliness, potential commercial opportunities may be lost if prompt access to climate model data is not guaranteed. These needs can be met by furthering the development, running, and testing of high-end models within the United States.
A further point is that the more difficult it is to access a model and its output, the more opaque are the model's results. If the United States is to fully capitalize upon the most recent model products, it must have researchers directly involved in the modeling process who understand the details of a given model's underpinnings so that they can be in a position to comprehend and interpret nuances of that model's simulations. If U.S. scientists are not directly involved in the high-end modeling itself, they may miss opportunities to gain valuable insights into the underlying processes that are critical to subsequent modeling investigations. In this regard the issue of accessibility is much more than just a commercial and political issue; in order to most effectively advance the science in the United States, researchers need to have access to both model output and the models to iteratively diagnose the output, advance our knowledge of climate, and improve the model's predictive capabilities. To some extent this can be addressed by enhancing collaborations with foreign climate modeling groups, but ultimately this can go only so far.
The concerns regarding the need for U.S. high-end modeling capabilities are also based, in part, on the possibility that decisions that might substantially affect the U.S. economy might be founded upon considerations of simulations produced by countries with different priorities than those of the United States. While the leading climate models are global in scale, their ability to represent small-scale,
regionally dependent processes (e.g., hurricanes and extreme flooding events) can currently only be depicted in them using high-resolution, nested grids. It is reasonable to assume that foreign modeling centers will implement such nested grids to most realistically simulate processes on domains over their respective countries which may not focus on or even include the United States.
The information gathered from active climate researchers and agency program managers at the CRC/USGCRP modeling forum indicated that climate modeling priorities are established primarily within individual agencies, specifically, DOE, NASA, NOAA, and NSF. Individual agency program managers appear to be aware of modeling activities in other agencies through informal personal exchanges of information and through the USGCRP Integrated Modeling and Prediction Working Group (IMAP) (No analogous coordinating activity involving the directors of U.S. climate modeling centers exists.). Although these limited harmonization efforts may provide some context for setting funding priorities, we conclude that research funding decisions are mainly driven by the missions of the individual agencies without strong interagency coordination.
U.S. funding agencies rely heavily on working scientists to shape the climate modeling program. This system promotes a healthy competition among modeling groups and has given rise to a rich diversity of climate modeling efforts that is highly valued by the scientific community. This system, however, does not necessarily promote research that addresses the questions of most importance to policy makers or U.S. society at large, particularly if no agency considers a given issue to be among its priorities.
The approach that has been used in the United States to set research priorities for climate modeling can be contrasted with some European countries, especially the United Kingdom and Germany, where a stronger top-down management approach is used for setting research priorities. These countries, which have smaller GDPs than
the United States, have leveraged their funding of research to more directly serve policy needs (at the partial expense of fundamental climate research). To facilitate progress, the United States should establish a set of priorities that carefully balances both policy and science needs and avoids a top-down prioritization of research activities driven by short-term agency agendas that might ultimately dissipate scientific resources.
The lack of national coordination and funding, and thus sustained interest, are substantial reasons why the United States is no longer in the lead in high-end climate modeling.7 Many scientists at the time of the forum believed that the current major U.S. modeling centers were not adequately responding to the challenges of integrating component models of the atmosphere, oceans, land surface, and atmospheric chemistry, that are needed for climate change scenario studies. At that time, some members of the academic community averred that their expertise was not being effectively utilized in the development of these comprehensive models. Moreover, the coordination of model development activities seemed to be fragmented even within the major climate modeling centers.
The USGCRP could assume increased responsibility for identifying, from an interagency perspective, any gaps or imbalances in the research priorities established by the individual agencies. The USGCRP is, however, limited in this area because some agencies have excluded from their USGCRP budgets the computational and human resources allocated to support some major U.S. climate modeling efforts. Although ideally any imbalances identified should be rectified, it appears that the USGCRP does not currently have the means to ensure this. Thus, this may be a fundamental weakness of the current approach to setting climate modeling priorities.
7 This view is supported by Finding 6 of NRC (1998b): “Advances in developing and most importantly in testing and evaluating models are needed. The United States is no longer in the lead in this critical field.”
As in setting priorities, the establishment of a coordinated modeling strategy in the United States should carefully balance both policy and science needs. The implementation of these priorities should not come at the expense of small and intermediate modeling, which currently form a solid base of expertise in the United States. Although better coordination of U.S. climate modeling activities is advocated and is likely to lead to substantial enhancements in overall capabilities, coordination alone is not sufficient. U.S. modelers cannot produce the high-resolution, multi-decade, ensemble simulations necessary to perform detailed assessments of anthropogenic climate change without an increase in the computational capability available to U.S. scientists.
With the development of coupled models, including the atmosphere, oceans, and biosphere, there are common problems that must be addressed by the overall model framework that links the components of the system. It is possible that movement towards increased modularity among model components and a common component interface, sometimes referred to as a “flux coupler,” might speed improvement of these comprehensive climate models. In principle, independently developed individual atmosphere or ocean model components could be interchanged in different combinations to generate various coupled models that could be assembled for particular applications. Current coupled model development, however, is proceeding independently at various laboratories and universities with little coordination.
Many field programs are justified in part by arguments that their efforts will lead to model improvements. It is not easy, however, to fashion new parameterizations from even the most carefully designed field programs and it is also not certain that even well-conceived new parameterizations will lead to overall model improvement. Often the difficult task of developing new parameterizations is carried out by small, academia-based research groups. The subsequent labor-intensive testing of the parameterizations in climate models requires a tailoring of code so that it complies with the unique requirements of each host model. This work could again be
minimized by encouraging coding standards that facilitate sharing of common subroutines among models (e.g., subroutines for short-wave radiative transfer or for trace species transport and diffusion). While such coding standards should be encouraged when possible, it is recognized that, because some processes may be parameterized somewhat independently in one model but closely coupled in another, it may in some cases be difficult to standardize their treatment across models. Thus, it would not be appropriate to require all models to abide by a rigid set of coding standards.
Under current competition for funding, there is little incentive to coordinate development of various analysis tools among projects funded by different agencies. In particular because modeling groups engage in many common activities (e.g., model development and model evaluation), there may be opportunities to minimize duplication of effort, which might ultimately reduce the costs necessary to maintain the multiple visualization and analysis software packages that are currently supported by climate research funds. Enhanced coordination could foster the production of tools that could be used by many modeling groups, and could also be beneficial in the process of defining the types of model runs that are used in inter-model comparisons and in climate change assessments. Ultimately, enhanced coordination may yield cost savings by increasing the efficiency with which scientists can produce, visualize, and analyze model output.
Another way enhanced coordination might be manifested is in facilitating the standardization of model output. Clearly, such standardization would make it possible for common software utility routines to be developed that would aid model intercomparison and improvement efforts. Moreover, this standardization would also make it easier for scientists in other disciplines (e.g., the ecological impacts community) to access data from different models. As a relatively few widely used formats emerge, notably, netCDF and HDF, it is likely that the availability of powerful software that can only accommodate such formats will provide increasing incentives to conform to these formats, thus minimizing duplication of effort among modeling groups.
Specialists can efficiently analyze the output from several different models if standard simulations are performed and if output is archived in a standard format. Agency program managers may not need to modify their current strategies much because international projects such as AMIP and CMIP are already fostering this and attracting considerable participation and cooperation. These projects, which should be encouraged, serve to coordinate the efforts of the broader community of climate scientists evaluating climate models and make it possible for smaller groups to submit their models for closer and more comprehensive scrutiny than their own resources would permit. In principle, a single expert in a particular area can evaluate the performance of all models in the intercomparison projects with little more effort than it would take to evaluate a single model. The efficiency of this approach is becoming more evident as these projects mature. To facilitate the intercomparison of separate model analyses, the development of compatible diagnostic algorithms should be encouraged.
For intercomparison efforts to be successful, the models being analyzed must use the same initial and boundary conditions so that it is differences in the representation of model physics that are being assessed, not differences in the forcings. At present, there is no uniform set of land-surface data for use as boundary conditions in the climate models of the major U.S. modeling centers. Consistency in this regard can be maintained through enhanced coordination of U.S. high-end modeling efforts among these centers.
One way to establish the credibility of the climate models used for making climate assessments is to test their performance when run in a weather- or short-term climate-forecast mode. However, in the United States there are serious impediments to cooperation between the operational forecast facility (NCEP) and the climate modeling community. Operational forecasting facilities in the United States currently provide little support for activities other than operational ones, and therefore, inadequate human resources for collaboration with external climate modeling groups or individuals. An increase in collaborative opportunities between these entities could be beneficial to both.
Some comments were also received from members of the academic community who are eager to have early access to output from some of the computationally most demanding climate model simulations. The potential scientific benefits resulting from broad participation in the analysis of these simulations must be balanced by a recognition that the development of the models used to generate these simulations can take years, and the scientists who have developed these models deserve to reap the first rewards of their efforts in terms of publishable research.
Productive climate modeling efforts require an appropriate division of resources between support for personnel (including both climate and computer scientists) and computer facilities. Also essential is access to the results of process studies that lead to improved model formulations, and the collection and analysis of observational data for use in evaluating models, but these needs are outside of the scope of this report and will not be considered here.
Although the total computer resources available to the U.S. climate modeling community are substantial, inadequate access to the world's most powerful mainframes by U.S. modelers in universities and the national centers is significantly limiting progress. This view is supported by Table 1 and its accompanying text and by evidence put together by Dr. Bill Buzbee, the director of NCAR's Scientific Computing Division (see Appendix E). Buzbee has compared NCAR capabilities to those at GFDL and six research labs around the world. He has shown that “international colleagues now enjoy a substantial computational advantage over U.S. modelers.” This view is further buttressed by the USGCRP National Assessment program's current reliance on climate change scenarios developed by foreign modeling groups and by recent special arrangements to use computers at foreign institutions in order to produce complementary simulations for the National Assessment with the NCAR climate system model.
The ability of the climate community to acquire state-of-the-art mainframes is severely hampered by a Department of Commerce “antidumping order” prescribing a financial penalty in excess of 400 percent on the purchase price of the world's most powerful commercial supercomputers, which are Japanese in origin. The climate community has not been provided with the financial or computational resources to overcome this barrier and has, therefore, been unable to fully capitalize on the scientific potential within the United States. In effect, if total resource availability remains fixed, the cost of any increase in access to fast machines could require a comparable reduction in the scientific and technical personnel who develop, test, and apply models.
In allocating resources for climate modeling, agency managers should understand that there is an inherent pyramid structure in climate research. The broad base of understanding that is required in constructing climate models is obtained through a multitude of observational programs and individual process studies. The small and intermediate modeling efforts (usually involving a single component of the climate system) incorporate the relevant portions of the underlying research both during model development and in model applications. The most sophisticated high-end models are essentially built by integrating the various climate system components. U.S. agencies spend most of their resources on small and intermediate modeling. The results of this work are published in journals and are therefore freely available to the climate modeling community.
The full benefits of investing in the foundations of the pyramid can not be realized without sufficient support for the high-end modeling needed for impacts and policy purposes. A non-trivial element of a comprehensive high-end modeling system is the dissemination of the output from these models to the wider climate research and user communities something that is largely unfunded in the United States.
In Europe a relatively high priority has been given to funding research at the top of the pyramid, which relies in part on the fundamental research carried out in the United States. There is,
unfortunately, a certain nonreciprocity in this arrangement because the results of the U.S.-funded research can feed directly into the high-end modeling efforts in Europe, but, as mentioned previously, the United States does not necessarily have full, open, and timely access to output from foreign models. Solutions to this problem should not involve the imposition of access restrictions to U.S. data.
Simply acquiring hardware alone is not sufficient. We also need to invest in the development of scientific expertise and the dissemination of that knowledge. Conversely, while the United States is an intellectual leader in this field, it needs the hardware to make effective use of this intellectual capability. Thus, one of the fundamental reasons for considering additional investment in U.S. high-end modeling infrastructure is that the incremental returns on investment could be very large, as the added effort in high-end modeling could be encouraged to interact with the existing vast U.S. expertise in small/intermediate modeling. The synergism of interaction could be expected to yield substantially more than the sum of the individual modeling efforts.
Recent Developments Relevant to this Report: Computational Capabilities and Coordination
Since the climate modeling forum two years ago, there have been indications of several significant developments and changes in the U.S. climate modeling effort. Among these are the following:
• An NCAR proposal to acquire an NEC SX-4 computer was effectively denied by a Department of Commerce “antidumping order” prescribing a 400 percent financial penalty. This has precluded certain applications of the NCAR Climate System Model (CSM) and slowed its use in studies requiring multi-century simulations and may also retard the production of regionally resolved climate scenarios for the USGCRP National Assessment. This lack of routine access by climate researchers to the world's most powerful computers has become a quite serious problem that increasingly affects the international competitiveness of the U.S.
climate modeling community. This precedent-setting decision seems to have discouraged other institutions within the United States from considering the purchase of foreign computers, even though these computers might prove superior in climate model applications.
• Responding to encouragement to interface more effectively with the outside community, NCAR has made notable changes, as evidenced by their annual Climate System Model (CSM) Workshop and their CSM working group meetings, with heavy involvement of the academic community. Furthermore, the publication of a series of papers describing results from the NCAR CSM in a special journal issue (J. Climate 11, 1998) is a good sign that U.S. coupled atmosphere-ocean modeling efforts are progressing.
• A new DOE initiative (ACPI, 1998) is under development, which, if funded, will attempt to increase by a few orders of magnitude the amount of computing power available for climate modeling applications. Under this initiative, massively parallel computing machines, currently under development for other DOE purposes, would be applied to climate modeling, including the production of multi-century, high-resolution simulation ensembles.
• At the request of USGCRP and with support from NSF, NCAR has agreed to develop some climate change scenario runs with the CSM for the USGCRP National Assessment. Some of these runs are being completed in Japan and Australia because of the current scarcity in the United States of the kind of computing resources needed for this type of model.
• A sharply upgraded version of the GFDL MOM3 ocean model has recently been released to its worldwide user community, which includes most of the major climate modeling centers.
• Two workshops were recently held at the Goddard Institute for Space Studies (GISS) one on ocean modeling and the other on land surface modeling to encourage involvement of the academic community in the GISS modeling effort.
• In August 1998, a workshop was held at NCEP, sponsored jointly by NCEP and NSF, to investigate the question of whether a common modeling infrastructure could enhance the degree of collaboration between NCEP and the weather and climate research
communities in the United States.
• An ad hoc working group, currently chaired by Steven Zebiak and Robert Dickinson, has been formed in response to one of the recommendations of the NCEP/NSF meeting that a group is needed to formulate coding and data standards to facilitate exchanges of data and promotion of interactions between modeling groups and the academic community. At a first meeting in Tucson in October 1998, initial steps were taken to develop standards for model parameterizations and approaches for facilitating involvement of a wider community in their development. Steps were also taken to develop agreements on standard data formats. In addition, suggestions were presented as to how standard data sets for model boundary conditions should be developed.
With respect to this report, these developments, among others, indicate that the climate modeling effort is evolving. In some cases (e.g., the denied purchase of an SX-4), a problem identified by the climate modeling community has been exacerbated, but in another, (e.g., the potential increase in computational resources through the DOE initiative), there are indications that U.S. computational capabilities could dramatically increase sometime in the future. Emerging efforts to encourage more collaboration across institutional barriers is promising. The U.S. climate modeling community will likely remain behind the rest of the world in terms of computational facilities for the next several years. Nevertheless, the United States can maintain many aspects of scientific leadership through its major satellite-based climate observing system and fostering of research and development in climate processes. Unfortunately, the U.S. community may, to some extent, have to be content to see these advances implemented in foreign models.
Through our analysis of the discussions at the climate modeling forum, responses to the USGCRP questionnaire, personal contacts with the climate modeling community, and deliberations within the CRC, we have reached initial conclusions in our evaluation
of the organization and infrastructure of climate modeling in the United States. These conclusions are reported in the context of the three questions referred to the CRC by the USGCRP program managers.
1. Do USGCRP agencies have a coordinated approach for prioritizing from a national perspective their climate modeling research and assessment efforts?
We find that:
• USGCRP agencies do not have a coordinated approach.
Climate modeling priorities within the USGCRP are primarily established by individual agencies with substantial input to each agency from climate researchers, but with little formal inter-agency coordination. There is no effective integrating national strategy and little formal consideration of the needs of the policy community.
2. Are resources allocated effectively to address such priorities?
We find that:
• There are few monetary resources dedicated to high-end climate modeling. Further, there is insufficient access to computers powerful enough to take advantage of the U.S. intellectual capability to design and run the climate models needed to answer critical science and policy questions. In addition, there is no coordinated mechanism for establishing the priority of these questions. The lack of resources and the inefficient assignment of those that are available are hampering progress, both in theoretical understanding of climate and in performing simulations of direct relevance to policy decisions concerning natural and anthropogenic climate variability and change.
3. How can the U.S. climate modeling community make more efficient use of its available resources?
We find that:
• First, a national set of goals and objectives that are agreed to by the USGCRP agencies is essential. These goals and objectives would be aimed at establishing the major themes for climate research, and would be set in the context of scientific priorities and national policy decisions. By formulating these goals and objectives, the USGCRP agencies should also agree to seek coordinated funding initiatives directed at achieving them.
• Second, a concerted effort by the relevant agencies is needed to establish a coordinated national strategy for climate modeling. That strategy may call for the allocation of resources to be distributed at a number of locations, and it must have the capability to deal with the complexity of high-end climate modeling. A number of formats exist for the establishment of such a resource. Appendix A identifies several possibilities, and there likely are others. What must be encouraged in such an endeavor is the increased coordination and integration of activities between national laboratories and universities. What must be avoided is a top-down prioritization of research activities driven by short-term agency agendas.
The current approach to climate modeling in the United States produces a rich diversity of research driven by individual researchers. The purpose has to be to focus that research, not subject it to the “problem of the month,” which ultimately will dissipate scientific resources. While difficult to specify a priori, a carefully considered balance must be struck between policy- and science-driven research. Several examples of how the recommended coordination might be manifested are given in the body of this report.
• Third, in order to optimally use existing scientific capabilities, adequate resources, including adequate supercomputing capabilities, need to be provided to the
climate modeling community.
At present, the U.S. modeling community on the whole is not supported to produce climate change scenarios for the GHG-driven climate change assessments, such as IPCC and the USGCRP National Assessment. This is in part because of the limited funding for these activities and in part because of the inability of U.S. climate modeling centers to acquire state-of-the-art supercomputers. U.S. scientists do participate to the extent possible in climate change assessment activities by reprogramming resources within their limited budgets. Participation in these activities is of necessity on a volunteer, often uncoordinated and normally aperiodic basis. Unfortunately, standard tenure-track systems, which emphasize frequent, first-authored publications, do not always reward such participation. Longer-term research, which may require years of effort to achieve results, in fact, is penalized in the race to produce early papers.
The provision of financial resources should be based upon peer-reviewed proposals that advance the main themes of the agreed upon science and policy objectives. Those resources need to be committed for periods commensurate with the time required to achieve definitive results.
We agree with certain aspects of the discussions on funding in Appendix A. Merely adding funds to budgets is not effective. We agree with other statements in Appendix A that “the option of accelerating progress by simply adding funding will fail without also making major changes in the management and institutional cultures of existing centers.”
• Fourth, the reliance of the United States upon other countries for high-end climate modeling must be redressed. This issue is rooted in both science and policy, but can only be resolved through governmental intervention. The European modeling centers, for example, benefit from pioneering research by the United States in intermediate climate
modeling; the CRC strongly supports this element of free and open exchange of climate data. Unfortunately, the United States is not guaranteed equivalent access to European model output or methodologies, although, at present, access to transient climate change simulations from foreign models is generally available to the U.S. research community. The concern over data access is due in large part to European national policies that restrict the free and open exchange of some information in favor of enhancing national commercial advantages (see Appendix D).
Until the gap in climate modeling capabilities between the United States and other countries is closed, decisions that could substantially affect the U.S. economy might be based upon interpretations of simulations (e.g., nested-grid runs) produced by countries with different priorities than those of the United States.
There is real concern that if U.S. scientists lose involvement in advanced modeling activities, they will miss opportunities to gain valuable insights into the underlying processes that are critical to subsequent modeling investigations Further, the state of climate modeling throughout the world is such that the addition or removal of even a single model would affect the confidence levels assigned to certain scenarios of future climate change. In other words, not only would the United States benefit from enhancements in its modeling capabilities, the international community would benefit from these efforts as well.
In essence, the CRC finds that the United States lags behind other countries in its ability to model long-term climate change. What computational and intellectual capability it does possess is neither well focused nor well financed. Those deficiencies have a significant and negative impact on the United States:
1. to predict future climate states and thus:
a) assess the national and international value and impact of
b) formulate policies that will be consistent with national objectives and be compatible with global commitments;
2. to most effectively advance understanding of the underlying scientific issues pertaining to climate variability and change.
Thus, to facilitate future climate assessments, climate treaty negotiations, and our understanding and predictions of climate, it is appropriate to develop now a national climate modeling strategy that includes the provision of adequate computational and human resources and that is integrated across agencies.