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The physical basis for increases in precipitation extremes in simulations of 21st-century climate change
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Communicated by Kerry A. Emanuel, Massachusetts Institute of Technology, Cambridge, MA, July 14, 2009 (received for review March 24, 2009)

Abstract
Global warming is expected to lead to a large increase in atmospheric water vapor content and to changes in the hydrological cycle, which include an intensification of precipitation extremes. The intensity of precipitation extremes is widely held to increase proportionately to the increase in atmospheric water vapor content. Here, we show that this is not the case in 21st-century climate change scenarios simulated with climate models. In the tropics, precipitation extremes are not simulated reliably and do not change consistently among climate models; in the extratropics, they consistently increase more slowly than atmospheric water vapor content. We give a physical basis for how precipitation extremes change with climate and show that their changes depend on changes in the moist-adiabatic temperature lapse rate, in the upward velocity, and in the temperature when precipitation extremes occur. For the tropics, the theory suggests that improving the simulation of upward velocities in climate models is essential for improving predictions of precipitation extremes; for the extratropics, agreement with theory and the consistency among climate models increase confidence in the robustness of predictions of precipitation extremes under climate change.
Footnotes
- 1To whom correspondence should be addressed. E-mail: pog{at}mit.edu
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Author contributions: P.A.O. and T.S. designed research; P.A.O. and T.S. performed research; P.A.O. analyzed data; and P.A.O. and T.S. wrote the paper.
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The authors declare no conflict of interest.
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This article contains supporting information online at www.pnas.org/cgi/content/full/0907610106/DCSupplemental.
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↵† Models and observations may agree more closely in our study than in some other studies in part because we use percentiles of precipitation including all days (dry and wet) and because we spatially average observations to typical model resolution. The precipitation extremes scaling discussed below implies that if models approximately reproduce the distribution of vertical velocities but inaccurately simulate the frequency of wet days, inclusion of all days in the percentile analysis will give the most favorable comparison.
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↵‡ Analysis of the covariability of monthly mean precipitation and surface temperature also reveals a positive correlation between temperature anomalies and precipitation at high latitudes in winter, but different correlations in other seasons and regions (24); these results are not directly comparable with our study because we use daily data and extremes of precipitation.
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↵§ The scaling used here is more general than that used in ref. 8, where it was assumed that the extreme upward velocity scales with the root-mean-square vertical velocity.
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