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Kharin (2004), Detectability of anthropogenic changes in annual temperature and precipitation extremes
| Venue: | J. Clim |
| Citations: | 25 - 7 self |
BibTeX
@ARTICLE{Hegerl_kharin(2004),,
author = {Gabriele C. Hegerl and Francis W. Zwiers and Peter A. Stott and Viatcheslav V. Kharin},
title = {Kharin (2004), Detectability of anthropogenic changes in annual temperature and precipitation extremes},
journal = {J. Clim},
year = {},
pages = {3683--3700}
}
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Abstract
This paper discusses a study of temperature and precipitation indices that may be suitable for the early detection of anthropogenic change in climatic extremes. Anthropogenic changes in daily minimum and maximum tem-perature and precipitation over land simulated with two different atmosphere–ocean general circulation models are analyzed. The use of data from two models helps to assess which changes might be robust between models. Indices are calculated that scan the transition from mean to extreme climate events within a year. Projected changes in temperature extremes are significantly different from changes in seasonal means over a large fraction (39%–66%) of model grid points. Therefore, the detection of changes in seasonal mean temperature cannot be substituted for the detection of changes in extremes. The estimated signal-to-noise ratio for changes in extreme temperature is nearly as large as for changes in mean temperature. Both models simulate extreme precipitation changes that are stronger than the corresponding changes in mean precipitation. Climate change patterns for precipitation are quite different between the models, but both models simulate stronger increases of precipitation for the wettest day of the year (4.1 % and 8.8%, respectively, over land) than for annual mean precipitation (0% and 0.7%, respectively). A signal-to-noise analysis suggests that changes in moderately extreme precipitation should become more robustly detectable given model uncertainty than changes in mean precipitation. 1.
Keyphrases
anthropogenic change precipitation extreme annual temperature mean precipitation seasonal mean temperature cannot corresponding change extreme precipitation early detection precipitation index model uncertainty climate change pattern extreme precipitation change signal-to-noise analysis mean temperature climate event extreme temperature estimated signal-to-noise ratio annual mean precipitation maximum tem-perature large fraction temperature extreme model grid point seasonal mean climatic extreme ocean general circulation model daily minimum
