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WIREs Clim Change
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Changes in climate and weather extremes in the 21st century

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Abstract Climate and weather extremes are sporadically recurring events that may have major local or regional impacts on the society and the environment. These events are typically related to unusually high or low temperature, prolonged dry or wet conditions, heavy precipitation, or extreme winds. Extreme events are part of the overall climate and weather alongside average conditions and variability, and thus are not unexpected as such. Climate change is expected to affect not only means but also variability and extremes. Some inferences can be based on past and present observations, but analyses of especially rare events are hampered by the availability of long time series. Over time, depending on how far the on‐going global warming takes us from the present and the past climate conditions, the weather and climate statistics may well come to shift in ways that are well outside observational data. This may lead to shifts in frequency, intensity and geographical distribution of different extremes. Indeed, projected changes in some extremes over the 21st century are quite robust, such as generally increasing warm and decreasing cold extremes. Possible changes in some other aspects, for example storms, remain much more uncertain. Science‐based information both on robust findings and on relevant uncertainties on changing extremes can provide useful information for sectorial planning, disaster risk prevention and overall reduction of societal vulnerability related to climate and weather. WIREs Clim Change 2012, 3:115–129. doi: 10.1002/wcc.160 This article is categorized under: Climate Models and Modeling > Knowledge Generation with Models

Schematic showing the effect on extreme temperatures when (a) the mean temperature increases, (b) the variance increases, and (c) when both the mean and variance increase for a normal distribution of temperature (Figure 2.32 in Ref 7. Copyright 2001 Intergovernmental Panel on Climate Change).

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Averaged multimodel annual 99th percentile of the 10 m mean wind speed (m s−1) and vectors for the period 2081–2100 relative to 1981–2000 (%) where more than 66% of the models agree on the sign of the change. Black stippling indicates areas where more than 90% of the models agree on the sign of the change. Red stippling indicates areas where more two out of three of the models agree on a small change between ±2% (Figure 5b in Ref 72). (Reprinted with permission from Ref 72. Copyright 2011 John Wiley & Sons Ltd.)

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Past and extrapolated changes in Atlantic hurricane power dissipation index (PDI), shown as anomalies relative to 1981–2000. Anomalies are regressed onto tropical Atlantic SSTs (upper panel) or tropical Atlantic SST relative to tropical mean SST (panel b). These regression models are then used to statistically estimate PDI for the future from global climate models. The green bar denotes the range of the PDI anomaly from statistical/dynamical calculations. The green symbols to the right denote values from high‐resolution model projections. The region is 20°W–70°W, 7.5°N–22.5°N. (Reprinted with permission from Ref 20. Copyright 2008 AAAS)

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Fractional changes in the 99.9th percentile of daily precipitation (blue), zonally averaged atmospheric water content (green) and saturation water vapor content of the troposphere (black dotted). (The dashed lines are for two scalings, see Ref 40 for details.) The changes are normalized fractional changes relative to 20th century values. The lines show multimodel medians and the shading shows multimodel interquartile range (Figure 2 in Ref 40). (Reprinted with permission from Ref 40. Copyright 2009 PNAS)

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The difference between 2090–2099 and 1990–1999 of T100 (100‐year return value of the annual‐maximum 2 m‐temperature), expressed as a multiple of the ensemble mean temperature change during the same period. Red (blue) colors mean that T100 grows faster (slower) than the mean temperature (Figure 3a in Ref 30). (Reprinted with permission from Ref 30. Copyright 2008 AGU)

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Upper: Characteristics of the summer 2003 heat wave based on observed Swiss monthly and seasonal summer temperatures for 1864–2003. A fitted gaussian distribution is in green. The values in the lower left corner of each panel show the standard deviation of the data as well as the 2003 anomaly normalized by the 1864–2000 standard deviation. Lower: Results from an RCM climate change scenario representing current (CTRL 1961–90) and future (SCEN 2071–2100) summertime conditions for one grid point in Switzerland, both for individual simulated years and a fitted normal distribution (Figure 1 and part of Figure 3 in Ref 23). Note the difference in the horizontal scale between the upper and the lower part of the figure. (Reprinted with permission from Ref 23. Copyright 2004 Macmillan Publishers Ltd)

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