The sun provides the energy that determines the climate and weather. Solar radiation passes through space and is largely absorbed by components of the global climate system (the atmosphere, oceans, and land, as well as the biosphere, which includes all living things); the remaining radiation is reflected. The solar radiation absorbed by the earth’s surface is released as infrared radiation. Some of this radiation passes back through the atmosphere, and some is absorbed in the atmosphere by the molecules of gas—principally water vapor, carbon dioxide, methane, and chlorofluorocarbons—known collectively as greenhouse gases. These gas molecules act as a partial thermal blanket, trapping much of the heat energy and redirecting it to the earth’s surface and lower atmosphere. This naturally occurring process, called the greenhouse effect (see fig. 1), helps to maintain the earth’s temperature at an average of approximately 60 degrees Fahrenheit.is reflected by the Earth and the atmosphere. by greenhouse gas molecules. The effect of this is to warm the Earth’s surface and the lower atmosphere. atmosphere. by the Earth’s surface and warms it. Earth’s surface. Additional atmospheric warming—called the enhanced greenhouse effect or global warming—appears to be associated with human activities. During the past century, as industry, agriculture, and transportation have grown, so, too, have atmospheric concentrations of heat-trapping greenhouse gases (see app. I). At the same time, the earth has gotten warmer, according to historical data. Recorded temperatures for the period from 1860 through 1993 show a warming trend that generally coincides with the increased use of fossil fuels during the Industrial Revolution—and, hence, with the increased emission of greenhouse gases. During the past 50 to 100 years, volcanic eruptions have combined with the increased combustion of fossil fuels and emission of greenhouse gases to increase the concentration of aerosols in the lower atmosphere. Scientists believe that because these aerosols deflect sunlight, they have partially offset the effects of global warming. As a result, scientists surmise, temperatures have not reached the levels projected by GCMs, which do not include the aerosols’ effects. To help understand the global climate system’s response to emissions of greenhouse gases, scientists use three types of GCMs: atmospheric, oceanic, and coupled. In general, atmospheric GCMs predict the physical behavior of the atmosphere. Oceanic GCMs represent the physics of the ocean. Coupled GCMs, which scientists regard as the most advanced of the models, physically join atmospheric and oceanic GCMs and treat the evolution of the climate in both domains. To improve predictions of the future climate, modelers are also striving to couple, and to some degree have coupled, (1) the land surface to the atmosphere and (2) the Antarctic sea ice to both the ocean and the atmosphere. All types of GCMs process vast quantities of data on variables affecting climate. Using complex mathematical equations to represent the actions and interactions of these variables, the GCMs process the data to project patterns of climatic conditions. (App. II shows how a coupled GCM works.) To test the accuracy of a model’s projections, modelers run the model with their best estimates of historical climatic data and compare the resulting projections with records of actual climatic conditions for the period being modeled. Modelers assume that if the model can accurately simulate actual climatic conditions for prior periods, then it can be used to accurately project future climatic conditions. Although the earth’s gradual warming since the mid-19th century is generally consistent with GCMs’ estimates of the effects of greenhouse gases (when adjusted for the effects of aerosols), scientists have not been able to attribute the warming conclusively to the enhanced greenhouse effect or to quantify its effects. Specifically, they have not been able to uniquely and quantitatively distinguish the effects of higher concentrations of greenhouse gases from the effects of other factors that can change the climate. Such factors include natural fluctuations in the global climate system, increases in atmospheric ozone, air pollution, and aerosols emitted into the atmosphere from volcanic eruptions. Until more is known about the relative influence of these various factors on the earth’s climate, GCMs’ estimates of global warming will remain uncertain. Over the last decade, GCMs have accurately simulated many elements of the observed climate, providing useful indications of some future climatic conditions. For example, atmospheric models have demonstrated some skill in portraying aspects of atmospheric variability, such as the surface temperature of the sea. Oceanic models have also simulated the general circulation of the ocean, including the patterns of the principal currents. Coupled models, though still prone to small-scale errors, have simulated the current climate on a large scale as well as portrayed large-scale atmospheric and oceanic structures. This progress notwithstanding, the models remain limited in their ability to estimate, with desired accuracy, the magnitude, timing, and regional distribution of future climatic changes. These limitations stem from scientists’ imperfect understanding of the global climate system and computers’ insufficient capacity to perform more detailed simulations. More specifically, the accuracy of the models’ predictions is limited by (1) incomplete or inadequate representations of the processes affecting climate and (2) insufficient computer power. Research is being conducted to overcome both the scientific and the technical limitations affecting the accuracy of GCMs’ estimates. According to the U.S. Global Change Research Program, most GCMs include the most important processes that affect climate, such as radiation, convection, and land surface exchanges. However, some models do not include or fully incorporate some processes, and even the most advanced models do not adequately represent the interactions of some processes. None of the models fully incorporates certain components of the global climate system, called feedbacks or feedback mechanisms, and none adequately represents the interactions of these mechanisms with greenhouse gases, called feedback processes. Atmospheric and oceanic GCMs include fewer processes than coupled GCMs, and their simulations are, therefore, more limited and, in some cases, less accurate. Atmospheric models do not fully portray the influence of oceanic pressures (currents) and fluctuations in climate, while oceanic models do not fully account for the effects of atmospheric surface winds. The omission or incomplete incorporation of some processes may introduce errors into these models’ projections. For example, atmospheric models tested in 1991 produced systematic errors in their projections of sea level pressure, temperature, zonal wind, and precipitation. Compared with atmospheric and oceanic GCMs, coupled GCMs include more processes and interactions at the ocean-atmosphere interface, but even they do not include critical biospheric and chemical interactions with the atmosphere. The U.S. Global Change Research Program is supporting efforts by modeling groups to include more complete sets of processes in their models and to identify systematic errors in the models. Although coupled GCMs produce more comprehensive simulations of current climatic conditions than either atmospheric or oceanic GCMs, their simulations still differ from actual conditions. Modelers believe that these models are impaired by a condition known as climatic drift, which results from imbalances in the models’ analyses of heat and moisture variables. These imbalances cause the models’ estimates of temperature and precipitation to deviate from actual conditions. For example, in an experiment conducted by the National Center for Atmospheric Research in 1988, the models estimated wintertime ocean temperatures that were 7 degrees warmer than observed temperatures for the icebound region of Antarctica and 9 degrees colder than observed temperatures for the tropics. Modelers either accept climatic drift or try to correct its effects by inserting adjustments, called flux adjustments. Because flux adjustments artificially improve the models’ performance, their use is controversial. Scientists believe that an increased understanding of the interactions between atmospheric and oceanic variables—and, hence, a more accurate mathematical representation of these interactions—may eventually remove the need for flux adjustments. Reducing the need for flux adjustments is an objective of coupled model research. GCMs include many of the most important feedback mechanisms, such as vegetation, water vapor, ice cover, clouds, and the ocean. However, the models do not yet adequately represent the interactions of these mechanisms with greenhouse gases. Such interactions can amplify, dampen, or stabilize the warming produced by increased concentrations of greenhouse gases. The influence of feedback mechanisms on climate is likely to increase as concentrations of greenhouse gases increase; however, modelers do not fully understand the effects of these mechanisms and have not learned how to represent them with sufficient accuracy in models. Although they have clarified the role of water vapor and improved their ability to model its effects, they are still seeking to understand and accurately model the effects of clouds, which have the greatest potential of all the feedback mechanisms to amplify or moderate global warming. Recent studies have shown that different schemes for modeling cloud formation processes can lead to substantially different projections of the earth’s temperature. In 1989, for instance, two simulations, which varied only in their treatment of the cloud feedback process, produced estimates of the increase in the earth’s annual average surface temperature of 4.9 and 9.4 degrees, respectively. Insufficient computer power affects the accuracy of GCMs’ estimates because even the most powerful computers are limited in their ability to store and analyze the vast quantity of data required to accurately simulate changes in the global climate. Modelers have tried to overcome these limitations by introducing assumptions into their models that deliberately oversimplify some operations in order to free the GCMs’ capacity and time for other, more critical operations. For example, modelers have assumed that the ocean was not warmed by emissions of greenhouse gases before 1985. Although this assumption gains capacity for the GCMs, it introduces an error, called the cold start error, that increases the uncertainty of the GCMs’ predictions. Another oversimplification, the division of the earth into relatively large grids for analytical purposes, prevents the GCMs from accurately predicting regional changes in climate.