History of climate model development
Scientists extensively use mathematical models of Earth’s climate, executed on the most powerful computers available, to examine hypotheses about past and present-day climates. Development of climate models is fully consistent with approaches being taken in many other fields of science dealing with very complex systems.
These climate simulations provide a framework within which enhanced understanding of climate-relevant processes, along with improved observations, are merged into coherent projections of future climate change.
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This article is drawn from Chapter 1 of CCSP, 2008: Climate Models: An Assessment of Strengths and Limitations. A Report by the U.S. Climate Change Science Program and the Subcommittee on Global Change Research D.C., C. Covey, W.J. Gutowski Jr., I.M. Held, K.E. Kunkel, R.L. Miller, R.T. Tokmakian and M.H. Zhang (Authors). Department of Energy, Office of Biological and Environmental Research, Washington, D.C., USA, 124 pp. A Table of Contents of other articles drawn from the report is included at the end of this article. |
The use of computers to simulate complex systems has grown in the past few decades to play a central role in many areas of science. Climate modeling is one of the best examples of this trend and one of the great success stories of scientific simulation. Building a laboratory analog of the Earth’s climate system with all its complexity is impossible. Instead, the successes of climate modeling allow us to address many questions about climate by experimenting with simulations—that is, with mathematical models of the climate system. Despite the success of the climate modeling enterprise, the complexity of our Earth imposes important limitations on existing climate models.
Climate modeling and forecasting grew from the desire to predict weather. The distinction between climate and weather is not precise. Operational weather forecasting has focused historically on time scales of a few days but more recently has been extended to months and seasons in attempts to predict the evolution of El Niño episodes. The goal of climate modeling can be thought of as the extension of forecasting to longer and longer time periods. The focus is not on individual weather events, which are unpredictable on long time scales, but on the statistics of these events and on the slow evolution of oceans and ice sheets. Whether the forecasting of individual El Niño episodes is considered weather or climate is a matter of convention. For the purpose of this report, we will consider El Niño forecasting as weather and will not address it directly. On the climate side we are concerned, for example, with the ability of models to simulate the statistical characteristics of El Niño variability or extratropical storms or Atlantic hurricanes, with an eye toward assessing the ability of models to predict how variability might change as the climate evolves in coming decades and centuries.
An important constraint on climate models not imposed on weather-forecast models is the requirement that the global system precisely and accurately maintain the global energy balance over very long periods of time. The Earth’s energy balance (or “budget”) is defined as the difference between absorbed solar energy and emitted infrared radiation to space. It is affected by many factors, including the accumulation of greenhouse gases, such as carbon dioxide, in the atmosphere. The decades-to-century changes in the Earth’s energy budget, manifested as climate changes, are just a few percent of the average values of that budget’s largest terms. Many decisions about model construction described in the article Global Climate System Models are based on the need to properly and accurately simulate the long-term energy balance.
This report will focus primarily on comprehensive physical climate models used for the most recent international Coupled Model Intercomparison Project (CMIP) coordinated experiments[1] sponsored by the World Climate Research Programme (WCRP). These coupled atmosphere-ocean general circulation models (AOGCMs) incorporate detailed representations of the atmosphere, land surface, oceans, and sea ice. Where practical, we will emphasize and highlight results from the three U.S. modeling projects that participated in the CMIP experiments. Additionally, this report examines the use of regional climate models (RCMs) for obtaining higher-resolution details from Atmosphere-Ocean General Circulation Model (AOGCM) simulations over smaller regions. Still, other types of climate models are being developed and applied to climate simulation. The more-complete Earth system models, which build carbon-cycle and ecosystem processes on top of AOGCMs, are used primarily for studies of future climate change and paleoclimatology, neither of which is directly relevant to this report. Another class of models not discussed here but used extensively, particularly when computer resources are limited, is Earth system models of intermediate complexity (EMICs). Although these models have many more assumptions and simplifications than are found in CMIP models (Claussen et al. 2002), they are particularly useful in exploring a wide range of mechanisms and obtaining broad estimates of future climate change projections that can be further refined with AOGCM experiments.
As numerical weather prediction was developing in the 1950s as one of the first computer applications, the possibility of also using numerical simulation to study climate became evident almost immediately. The feasibility of generating stable integrations of atmospheric equations for arbitrarily long time periods was demonstrated by Norman Phillips in 1956. About that time, Joseph Smagorinsky started a program in climate modeling that ultimately became one of the most vigorous and longest-lived GCM development programs at the National Oceanic and Atmospheric Administration’s Geophysical Fluid Dynamics Laboratory (GFDL) at Princeton University. The University of California at Los Angeles began producing atmospheric general circulation models (AGCMs) beginning in 1961 under the leadership of Yale Mintz and Akio Arakawa. This program influenced others in the 1960s and 1970s, leading to modeling programs found today at National Aeronautics and Space Administration (NASA) laboratories and several universities. At Lawrence Livermore National Laboratory, Cecil E. Leith developed an early AGCM in 1964. The U.S. National Center for Atmospheric Research (NCAR) initiated AGCM development in 1964 under Akira Kasahara and Warren Washington. Leith moved to NCAR in the late 1960s and, in the early 1980s, oversaw construction of the Community Climate Model, a predecessor to the present Community Climate System Model (CCSM).
Early weather models focused on fluid dynamics rather than on radiative transfer and the atmosphere’s energy budget, which are centrally important for climate simulations. Additions to the original AGCMs used for weather analysis and prediction were needed to make climate simulations possible. Furthermore, because climate simulation focuses on time scales longer than a season, oceans and sea ice must be included in the modeling system in addition to the more rapidly evolving atmosphere. Thus, ocean and ice models have been coupled with atmospheric models. The first ocean GCMs were developed at GFDL by Bryan and Cox in the 1960s and then coupled with the atmosphere by Manabe and Bryan in the 1970s. Paralleling events in the United States, the 1960s and 1970s also were a period of climate- and weather-model development throughout the world, with major centers emerging in Europe and Asia. Representatives of these groups gathered in Stockholm in August 1974, under the sponsorship of the Global Atmospheric Research Programme to produce a seminal treatise on climate modeling[2]. This meeting established collaborations that still promote international cooperation today.
The use of climate models in research on carbon dioxide and climate began in the early 1970s. The important study, “Inadvertent Climate Modification”[3], endorsed the use of GCM-based climate models to study the possibility of anthropogenic climate change. With continued improvements in both climate observations and computer power, modeling groups furthered their models through steady but incremental improvements. By the late1980s, several national and international organizations formed to assess and expand scientific research related to global climate change. These developments spurred interest in accelerating the development of improved climate models. The primary focus of Working Group 1 of the United Nations Intergovernmental Panel on Climate Change (IPCC), which began in 1988, was the scientific inquiry into physical processes governing climate change. IPCC’s first Scientific Assessment[4] stated, “Improved prediction of climate change depends on the development of climate models, which is the objective of the climate modeling programme of the World Climate Research Programme.”
The United States Global Change Research Program (USGCRP), established in 1989, designated climate modeling and prediction as one of the four high-priority integrating themes of the program[5]. The combination of steadily increasing computer power and research spurred by WCRP and USGCRP has led to a steady improvement in the completeness, accuracy, and resolution of AOGCMS for climate simulation and prediction. An often-used illustration from the Third IPCC Working Group 1 Scientific Assessment of Climate Change in 2001 depicts this evolution (see Fig. 1.1). Even more comprehensive climate models produced a series of coordinated numerical simulations for the third international Climate Model Intercomparison Project (CMIP3), which were used extensively in research cited in the recent Fourth IPCC Assessment[5]. Contributions came from three groups in the United States (GFDL, NCAR, and the NASA Goddard Institute for Space Studies) and others in the United Kingdom, Germany, France, Japan, Australia, Canada, Russia, China, Korea, and Norway.
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Climate Models: An Assessment of Strengths and Limitations - Table of Contents
- Strengths and limitations of climate models: Executive Summary
- History of climate model development
- Global Climate System Models
- Downscaling and Regional Climate Models
- Model Climate Sensitivity
- Model Simulation of Major Climate Features
- Future Climate Model Development
- Applications of Climate Model Results
References
This article was initially drawn from CCSP, 2008: Climate Models: An Assessment of Strengths and Limitations. A Report by the U.S. Climate Change Science Program and the Subcommittee on Global Change Research D.C., C. Covey, W.J. Gutowski Jr., I.M. Held, K.E. Kunkel, R.L. Miller, R.T. Tokmakian and M.H. Zhang (Authors). Department of Energy, Office of Biological and Environmental Research, Washington, D.C., USA, 124 pp.
- {note" style="font-style: normal">[[#ref_1}]Meehl, G.A., et al., 2006: Climate change projections for the Twenty-First Century and climate change commitment in the CCSM3. J. Climate, 19, 2597–2616.
- {note|^]] Our Changing Planet: The FY 1992 U.S. Global Change Research Program. 1991. A Report by the Committee on Earth and Environmental Sciences. A Supplement to the U.S. President’s Fiscal Year 1992 Budget.
Citation
Energy, D. (2012). History of climate model development. Retrieved from http://editors.eol.org/eoearth/wiki/History_of_climate_model_development- ↑ Meehl, G.A., et al., 2006: Climate change projections for the Twenty-First Century and climate change commitment in the CCSM3. J. Climate, 19, 2597–2616.
- ↑ GARP, 1975: The Physical Basis of Climate Modeling, Global Atmospheric Research Program (GARP), Publication Series #16, April 1975.
- ↑ SMIC, 1971: Inadvertent Climate Modification: Report of the Study of Man’s Impact on Climate, Massachusetts Institute of Technology Press, Cambridge, Mass., 308 pp.
- ↑ IPCC, 1990: Climate Change: The IPCC Scientific Assessment, ed. J.T. Houghton, G.J. Jenkins, and J.J. Ephraums. Cambridge University Press, Cambridge, U.K.
- ↑ IPCC, 2007a: Couplings Between Changes in the Climate System and Biogeochemistry. In Climate Change 2007: The Physical Science Basis. Contribution of Working Group 1 to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, ed. S. Solomon et al. Cambridge University Press, Cambridge, U.K., and New York (www.ipcc.ch).-- IPCC, 2007b: Summary for Policymakers. In Climate Change 2007: The Physical Science Basis. Contribution of Working Group 1 to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, ed. S. Solomon et al. Cambridge University Press, Cambridge, U.K., and New York (www.ipcc.ch).
