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The physical concept of climate forcing

Beate G. Liepert

Wiley Interdisciplinary Reviews: Climate Change, 2010, vol. 1, issue 6, 786-802

Abstract: Since the beginning of the debate on global climate change, scientists, economists, and policy makers alike have been using ‘climate forcing’ as a convenient measure for evaluating climate change. Researchers who run complex computer models conceived the theoretical concept of climate forcing in the late 1960s (Charney Report, 1979). This overview describes the development and basics of the physical framework, as radiative energy imbalance in the atmosphere, inflicted by a perturbation in the climate system. Such disturbances and forced changes can alter processes in the climate system, which enhance or dampen the initial effects and thus introduce positive or negative feedback loops. With increased understanding of the nature of the climate system, this basic concept has become more complex and hence more difficult to interpret. The identification of additional anthropogenic disturbances, the interdependence of individual forcings, and difficulties to account for spatial and temporal variabilities of disturbances are only few issues that complicate the overall picture. Although numerous scientific studies exist that evaluate climate forcings by allocating watts per square meter values to individual forcings (Intergovernmental Panel on Climate Change (IPCC) reports, 2010), the actual number of publications that interpret the physical meaning of the climate‐forcing concept remains surprisingly small. Here, this overview focuses on explaining to an interdisciplinary audience the physical interpretation of the concept, including its limitations. It also examines new developments, such as polluter‐based emission scenarios, energy budget approaches, and climate impacts other than temperature change. WIREs Clim Change 2010 1 786–802 DOI: 10.1002/wcc.75 This article is categorized under: Paleoclimates and Current Trends > Climate Forcing Climate Models and Modeling > Knowledge Generation with Models

Date: 2010
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