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We theoretically study long-term trends in the statistics of record-breakingdaily temperatures and validate these predictions using Monte Carlo simulationsand data from the city of Philadelphia, for which 126 years of dailytemperature data is available. Using extreme statistics, we derive the numberand the magnitude of record temperature events, based on the observed Gaussiandaily temperatures distribution in Philadelphia, as a function of the number ofelapsed years from the start of the data. We further consider the case ofglobal warming, where the mean temperature systematically increases with time.We argue that the current warming rate is insufficient to measurably influencethe frequency of record temperature events over the time range of theobservations, a conclusion that is supported by numerical simulations and thePhiladelphia temperature data.Comment: 11 pages, 6 figures, 2-column revtex4 format. For submission to  Journal of Climate. Revised version has some new results and some errors  corrected. Reformatted for Journal of Climate. Second revision has an added  reference. In the third revision one sentence that explains the simulations  is reworded for clarity. New revision 10/3/06 has considerable additions and  new results. Revision on 11/8/06 contains a number of minor corrections and  is the version that will appear in Phys. Rev.

Role of global warming on the statistics of record-breaking temperatures