Attribution and projections of temperature extreme trends in South America based on CMIP5 models. Issue 1 (24th March 2021)

• Record Type: Journal Article
• Authors: Rusticucci, Matilde; Zazulie, Natalia
• Other Names: Gimeno Luis guestEditor.
• Is Part Of: Annals of the New York Academy of Sciences. Volume 1504:Issue 1(2021)
• Page Start: 154
• Page End: 166
• Publication Date: 2021-03-24
• Subjects: extreme temperature -- South America -- attribution -- climate change; Medical sciences -- Periodicals; Medicine -- Periodicals; Science -- Periodicals; 610
• DOI: 10.1111/nyas.14591
• Languages: English
• ISSNs: 0077-8923

Abstract

Abstract: Temperature extreme indices were analyzed for five continental regions of southern South America defined according to their climatic characteristics. Gridded observations, reanalysis, and global‐coupled climate models from CMIP5 were used with the approach of temperature extreme trend attribution analysis on fixed‐threshold and percentile‐based temperature extremes indices defined by the Expert Team on Climate Change Detection and Indices (ETCCDI). The largest positive trends are exhibited in the tropical nights index, and a clear anthropogenic signal is evident in the subtropical region. In the subtropical central Andes, there is a decrease in the frost days index and increases in the tropical nights and summer days indices, and an anthropogenic signal is evident. In the Patagonian region, all trends from the historical runs were significant, while the ones from the natural experiment were nonsignificant, showing the marked effect of anthropogenic forcing in this region in the extreme temperature events. Projected changes in extreme indices for the 21st century are consistent with a warming climate, and larger changes are expected in the warm nights index. Abstract : Temperature extreme indices were analyzed for five continental regions of southern South America defined according to their climatic characteristics. Gridded observations, reanalysis, and global‐coupled climate models from CMIP5 were used with the approach of temperature extreme trend attribution analysis on fixed‐threshold and percentile‐based temperature extremes indices defined by the Expert Team on Climate Change Detection and Indices (ETCCDI).