Detection of Anthropogenic Changes in Climate Extremes

Texas A&M Research Foundation, College Station TX

Investigators

Abstract

The proposed work will use statistical optimal detection methods to improve the ratio of anthropogenic signal to internal climate variability and allow for an earlier detection of changes. 'Fingerprints' for the expected spatial and temporal evolution of changes in extremes will be derived from climate model simulations. A detection study first applying model data only, will be performed to explore which extreme value indices should show the earliest detectable changes. The PI will also examine which procedure of detection is most promising for an early detection of changes in extremes, as well as which variable or combination of variables can and should be applied. The most promising procedure will be applied to observations. The focus is on temperature extremes, length of wet and dry periods and precipitation extremes, particularly over several days. Daily observations from land stations, mainly from the US, Canada, Europe, Russia, China and Japan will be used. The work is important because it will lead to increased understanding on climate change detection techniques.