Models And Climate Change Analysis

Models provided information that ultimately increased public concern about the Earth's climate. As a result, the validity of models themselves became an issue of increasing importance. By the 1990s, projects were initiated in which models were systematically compared to one another, in relation to a growing and uniformed body of climate data. Such projects provided the science of climate modeling with a form of quality control and a standard of reproducibility of results. Using data about conditions during the most recent ice age (which were gained primarily from ice-core measurements), one way of testing the validity of models was to see how well they could simulate the climatic and oceanic conditions characteristic of glacial periods. An additional test of validity involved using models to predict consequences of unique, real-time events, such as climatic responses to volcanic eruptions. Models were successful in these various tests. Models gained further credibility as they served as the primary source of data for the newly-formed Intergovernmental Panel on Climate

Change (IPCC). In the mid-1990s, the IPCC used climate model data to draw its conclusion that a human influence on climate had been detected.

Models that have developed over the past several years are extremely complex. Relative to the simple models that emerged in the 1950s, current models can carry out simulations in much shorter time periods and represent many component processes simultaneously, including the atmosphere, oceans, glaciers and ice sheets, land surfaces, and biological and chemical activities linked with human economic life. Models now inform understanding of a range of possible future climatic changes and their impacts. Current models that simulate the present climate and account for CO2 show a severe risk of future global warming. Based on these data, the broadly accepted view among scientists, policymakers, and the public is that rising CO2 levels are warming the Earth.

The success of complex models has not eliminated the need for simple models. The latter models still provide valuable information about independent processes and climatic changes occurring on small spatial and temporal scales. Thus, they serve to develop basic theoretical understanding that enables complex models to simulate broader interactions between the atmosphere, oceans, biosphere, and other component processes. Along with models of intermediate complexity, such as those used to study long time-series corresponding to glacial processes, simple models are regarded as part of a hierarchy of models upon which complex models are based.

In the future, models will continue to generate highly-complex, detailed three-dimensional representations of climate dynamics. Nevertheless, challenges remain that prevent models from providing a perfect simulation of real climate. Scientific understanding of many of the key process that control climate sensitivity (such as clouds, vegetation, and ocean convection) is incomplete. Consequently, these processes cannot be represented in detail in climate models. Additionally, the predictive capabilities of climate models are linked to their performance in reproducing the historical record, which is largely limited to geological data and relatively recent global temperature observations. Processes could exist on a longer temporal scale that even the highly-complex models of today cannot take into consideration. For example, the presence of non-linear processes could potentially change the behavior of climate abruptly. Future progress of climate modeling will depend on the continued commitment to developing improved mathematical and computational techniques, more data, and better theoretical understanding of climate dynamics.

sEE ALso: Climate Models; Climatic Data, Historical Records; Computer Models; History of Climatology.

BIBLIoGRAPHY. P.N. Edwards, "A Brief History of Atmospheric General Circulation Modeling," D.A. Randall, ed., General Circulation Model Development (Academic Press, 2000); IPCC, Climate Change 2007: The Physical Science Basis (Cambridge University Press, 2007); Frederik Nebeker, Calculating the Weather: Meteorology in the 20th Century (Academic Press, 1995).

Andrew S. Backe Office of International Science and Engineering National Science Foundation

Renewable Energy 101

Renewable Energy 101

Renewable energy is energy that is generated from sunlight, rain, tides, geothermal heat and wind. These sources are naturally and constantly replenished, which is why they are deemed as renewable. The usage of renewable energy sources is very important when considering the sustainability of the existing energy usage of the world. While there is currently an abundance of non-renewable energy sources, such as nuclear fuels, these energy sources are depleting. In addition to being a non-renewable supply, the non-renewable energy sources release emissions into the air, which has an adverse effect on the environment.

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