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- J. Hansen
- NASA Goddard Institute for Space Studies New York New York USA
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- M. Sato
- Columbia University Earth Institute New York New York USA
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- R. Ruedy
- SGT Incorporated New York New York USA
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- L. Nazarenko
- Columbia University Earth Institute New York New York USA
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- A. Lacis
- NASA Goddard Institute for Space Studies New York New York USA
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- G. A. Schmidt
- NASA Goddard Institute for Space Studies New York New York USA
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- G. Russell
- NASA Goddard Institute for Space Studies New York New York USA
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- I. Aleinov
- Columbia University Earth Institute New York New York USA
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- M. Bauer
- Columbia University Earth Institute New York New York USA
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- S. Bauer
- Columbia University Earth Institute New York New York USA
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- N. Bell
- Columbia University Earth Institute New York New York USA
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- B. Cairns
- Department of Applied Physics and Applied Mathematics Columbia University New York New York USA
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- V. Canuto
- NASA Goddard Institute for Space Studies New York New York USA
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- M. Chandler
- Columbia University Earth Institute New York New York USA
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- Y. Cheng
- SGT Incorporated New York New York USA
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- A. Del Genio
- NASA Goddard Institute for Space Studies New York New York USA
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- G. Faluvegi
- Columbia University Earth Institute New York New York USA
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- E. Fleming
- NASA Goddard Space Flight Center Greenbelt Maryland USA
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- A. Friend
- Laboratoire des Sciences du Climat et de l'Environnement Orme des Merisiers Gif‐sur‐Yvette France
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- T. Hall
- NASA Goddard Institute for Space Studies New York New York USA
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- C. Jackman
- NASA Goddard Space Flight Center Greenbelt Maryland USA
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- M. Kelley
- Laboratoire des Sciences du Climat et de l'Environnement Orme des Merisiers Gif‐sur‐Yvette France
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- N. Kiang
- NASA Goddard Institute for Space Studies New York New York USA
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- D. Koch
- Columbia University Earth Institute New York New York USA
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- J. Lean
- Naval Research Laboratory Washington, D. C. USA
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- J. Lerner
- Columbia University Earth Institute New York New York USA
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- K. Lo
- SGT Incorporated New York New York USA
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- S. Menon
- Lawrence Berkeley National Laboratory Berkeley California USA
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- R. Miller
- NASA Goddard Institute for Space Studies New York New York USA
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- P. Minnis
- NASA Langley Research Center Hampton Virginia USA
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- T. Novakov
- Lawrence Berkeley National Laboratory Berkeley California USA
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- V. Oinas
- SGT Incorporated New York New York USA
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- Ja. Perlwitz
- Department of Applied Physics and Applied Mathematics Columbia University New York New York USA
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- Ju. Perlwitz
- Columbia University Earth Institute New York New York USA
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- D. Rind
- NASA Goddard Institute for Space Studies New York New York USA
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- A. Romanou
- NASA Goddard Institute for Space Studies New York New York USA
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- D. Shindell
- NASA Goddard Institute for Space Studies New York New York USA
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- P. Stone
- Center for Meteorology Massachusetts Institute of Technology Cambridge Massachusetts USA
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- S. Sun
- NASA Goddard Institute for Space Studies New York New York USA
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- N. Tausnev
- SGT Incorporated New York New York USA
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- D. Thresher
- Department of Earth and Environmental Sciences Columbia University New York New York USA
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- B. Wielicki
- NASA Langley Research Center Hampton Virginia USA
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- T. Wong
- NASA Langley Research Center Hampton Virginia USA
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- M. Yao
- SGT Incorporated New York New York USA
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- S. Zhang
- Columbia University Earth Institute New York New York USA
書誌事項
- 公開日
- 2005-09-27
- 権利情報
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- http://onlinelibrary.wiley.com/termsAndConditions#vor
- DOI
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- 10.1029/2005jd005776
- 公開者
- American Geophysical Union (AGU)
この論文をさがす
説明
<jats:p>We use a global climate model to compare the effectiveness of many climate forcing agents for producing climate change. We find a substantial range in the “efficacy” of different forcings, where the efficacy is the global temperature response per unit forcing relative to the response to CO<jats:sub>2</jats:sub> forcing. Anthropogenic CH<jats:sub>4</jats:sub> has efficacy ∼110%, which increases to ∼145% when its indirect effects on stratospheric H<jats:sub>2</jats:sub>O and tropospheric O<jats:sub>3</jats:sub> are included, yielding an effective climate forcing of ∼0.8 W/m<jats:sup>2</jats:sup> for the period 1750–2000 and making CH<jats:sub>4</jats:sub> the largest anthropogenic climate forcing other than CO<jats:sub>2</jats:sub>. Black carbon (BC) aerosols from biomass burning have a calculated efficacy ∼58%, while fossil fuel BC has an efficacy ∼78%. Accounting for forcing efficacies and for indirect effects via snow albedo and cloud changes, we find that fossil fuel soot, defined as BC + OC (organic carbon), has a net positive forcing while biomass burning BC + OC has a negative forcing. We show that replacement of the traditional instantaneous and adjusted forcings, Fi and Fa, with an easily computed alternative, Fs, yields a better predictor of climate change, i.e., its efficacies are closer to unity. Fs is inferred from flux and temperature changes in a fixed‐ocean model run. There is remarkable congruence in the spatial distribution of climate change, normalized to the same forcing Fs, for most climate forcing agents, suggesting that the global forcing has more relevance to regional climate change than may have been anticipated. Increasing greenhouse gases intensify the Hadley circulation in our model, increasing rainfall in the Intertropical Convergence Zone (ITCZ), Eastern United States, and East Asia, while intensifying dry conditions in the subtropics including the Southwest United States, the Mediterranean region, the Middle East, and an expanding Sahel. These features survive in model simulations that use all estimated forcings for the period 1880–2000. Responses to localized forcings, such as land use change and heavy regional concentrations of BC aerosols, include more specific regional characteristics. We suggest that anthropogenic tropospheric O<jats:sub>3</jats:sub> and the BC snow albedo effect contribute substantially to rapid warming and sea ice loss in the Arctic. As a complement to a priori forcings, such as Fi, Fa, and Fs, we tabulate the a posteriori effective forcing, Fe, which is the product of the forcing and its efficacy. Fe requires calculation of the climate response and introduces greater model dependence, but once it is calculated for a given amount of a forcing agent it provides a good prediction of the response to other forcing amounts.</jats:p>
収録刊行物
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- Journal of Geophysical Research: Atmospheres
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Journal of Geophysical Research: Atmospheres 110 (D18), D18104-, 2005-09-27
American Geophysical Union (AGU)