Wednesday, 13 January 2016: 10:30 AM

La Nouvelle C ( New Orleans Ernest N. Morial Convention Center)

**Prashant D. Sardeshmukh**, CIRES, University of Colorado and PSD/ESRL/NOAA, Boulder, CO; and G. P. Compo, C. McColl, and C. Penland

Has 20th century global warming resulted in increases of extreme warm temperatures and decreases of extreme cold temperatures around the globe? One would certainly expect this to be so if the changes in the extreme temperature probabilities were determined only by the mean shift and not by changes in the width and/or shape of the temperature distribution. In reality, however, the latter two effects could also be important. Even ignoring changes of shape, it is easily shown that a 25% reduction of standard deviation, for example, can completely offset the effect of a mean positive shift of 0.5 standardized units on the probabilities of extreme positive values. A 25% increase of standard deviation can similarly offset the effect of the mean shift on the probabilities of extreme negative values. It is possible for such changes of standard deviation to occur in regions of large circulation and storminess changes associated with global warming.

With this caveat in mind, we have investigated the change in probability of extreme weekly averaged temperature anomalies, in both winter and summer, from the first half-century (1901-1950) to the last half-century (1960-2009) of the 1901 to 2009 period. We have done this using two newly available global atmospheric reanalysis datasets (ERA-20C and 20CR-v2c) and large ensembles of global coupled climate model simulations of this period, plus very large ensembles of uncoupled atmospheric model simulations of our own. The results are revealing. In the tropics, the changes in the extreme warm and cold temperature probabilities are indeed generally consistent with those expected from the mean shift of the distribution. Outside the tropics, however, they are generally significantly inconsistent with the mean temperature shift, with many regions showing little or no change in the positive temperature extremes and in some instances even a decrease. In such regions, it is clear that the change in the temperature standard deviation is important. The discrepancies in the estimated extreme changes among the model simulations and observational datasets are also largely attributable to the discrepancies in their estimated changes of standard deviation.

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