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          Institute: MPI für Meteorologie     Collection: Atmosphere in the Earth System     Display Documents

ID: 439092.0, MPI für Meteorologie / Atmosphere in the Earth System
Extremes and predictability in the European pre-industrial climate of a regional climate model
Authors:Tomassini, L; Hagemann, S.; Moseley, C.; Haumann, A.; Podzun, R.; Jacob, D.
Date of Publication (YYYY-MM-DD):2011
Title of Journal:Climate Dynamics
Start Page:2371
End Page:2397
Review Status:Peer-review
Audience:Not Specified
Abstract / Description:A high-resolution pre-industrial control simulation with the regional climate model REMO is analyzed in detail for different European subregions. To our knowledge, this is the first long pre-industrial control simulation by a regional climate model as well as at comparable resolution. We assess the ability of the climate model to reproduce the observed climate variability in various parts of the continent. In order to investigate the representation of extreme events in the model under pre-industrial greenhouse gas concentrations, selected seasons are examined with regard to the atmospheric circulation and other climatic characteristics that have contributed to the occurrences. A special focus is dedicated to land-atmosphere interactions. Extreme seasons are simulated by the model under various circumstances, some of them strongly resemble observed periods of extraordinary conditions like the summer 2003 or autumn 2006 in parts of Europe. The regional perspective turns out to be of importance when analyzing events that are constituted by meso-scale atmospheric dynamics. Moreover, the predictability of the European climate on seasonal to decadal time scales is examined by relating the statistics of surface variables to large-scale modes of variability impacting the North Atlantic sector like the Meridional Overturning Circulation, the El Niño Southern Oscillation, and the North Atlantic Oscillation. For this purpose, we introduce a measure of tail dependence that quantifies the correlation between extreme values in two variables that describe the state of the climate system. Significant dependence of extreme events can be detected in various situations.
External Publication Status:published
Document Type:Article
Communicated by:Carola Kauhs
Affiliations:MPI für Meteorologie/Atmosphere in the Earth System
MPI für Meteorologie/Land in the Earth System (2005-)
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