The elevation dependency of 21st century European climate change: an RCM ensemble perspective. (13th January 2015)

• Record Type: Journal Article
• Authors: Kotlarski, Sven; Lüthi, Daniel; Schär, Christoph
• Is Part Of: International journal of climatology. Volume 35:Number 13(2015)
• Page Start: 3902
• Page End: 3920
• Publication Date: 2015-01-13
• Subjects: Climatology -- Periodicals; Climat -- Périodiques; Climatologie -- Périodiques; 551.605
• DOI: 10.1002/joc.4254
• Languages: English
• ISSNs: 0899-8418

Abstract

<abstract abstract-type="main" id="joc4254-abs-0001"> <title>ABSTRACT</title> <p id="joc4254-para-0001">The ENSEMBLES regional climate model (RCM) ensemble is analysed with respect to the elevation‐dependency of 21st century near‐surface climate change over Europe. Fifteen experiments carried out by 11 different RCMs, driven by 6 different global climate models (GCMs) are considered, all of them assuming the SRES A1B emission scenario. Model evaluation for the historical period yields an approximate reproduction of observed temperature–elevation and precipitation–elevation profiles, but some distortion due to high‐elevation cold and wet biases. Climate change signals until the end of the 21st century show characteristic elevation dependencies over many parts of Europe and in many seasons. Except for northern Europe maximum warming typically occurs at medium to high elevations, leading to a decrease of near‐surface temperature lapse rates. The model agreement on the vertical temperature change profile is high; it does not depend on the driving GCM although the latter strongly determines the overall warming magnitude. Warming anomalies can often be related to changes of surface snow cover, and a contribution of the snow‐albedo feedback to the anomalous medium‐ and high‐elevation warming is likely. Also climate change signals of seasonal precipitation sums can considerably depend on elevation, but peculiarities highly depend on the region and season considered. Moreover, the vertical precipitation change profile appears to be less related to elevation itself but is strongly influenced by horizontal change patterns within the individual analysis domains and by the relative location of grid cells with respect to major orographic obstacles. Medium‐ to high‐elevation anomalies of large‐scale climate change signals as identified in this work represent an added value of dynamical downscaling as these elevations are typically not represented by the driving GCMs.</p> </abstract>