Köppen–Geiger climate classification by different regional climate models according to the SRES A1B scenario in the 21st century

0447210 - ÚVGZ 2016 RIV CZ eng C - Conference Paper (international conference)
Szabó-Takács, Beáta - Farda, Aleš - Zahradníček, Pavel - Štěpánek, Petr
Köppen–Geiger climate classification by different regional climate models according to the SRES A1B scenario in the 21st century.
Global Change: A Complex Challenge : Conference Proceedings. Brno: Global Change Research Centre, The Czech Academy of Sciences, v. v. i., 2015 - (Urban, O.; Šprtová, M.; Klem, K.), s. 18-21. ISBN 978-80-87902-10-3.
[Global Change: A Complex Challenge /4th/. Brno (CZ), 23.03.2015-24.03.2015]
R&D Projects: GA MŠMT(CZ) EE2.3.20.0248
Institutional support: RVO:67179843
Keywords : climate models * climate classification * 21st century
Subject RIV: EH - Ecology, Behaviour

We investigate future climate conditions projected by six regional climate model (RCM) simulations driven by the SRES A1B emission scenario. As a diagnostic tool of climate change, we used the Köppen–Geiger climate classification as it is suitable for assessing climate change impacts on ecosystems. The analysis is based on a comparison of Köppen–Geiger climate subtypes during two future time slices (2021–2050 and 2070– 2100) with climate subtypes observed during 1961–2000. All RCMs showed expansion of the area covered by warmer climate types in the future, but the magnitude of the growth varied among RCMs. The differences stemmed from several sources, mainly boundary forcing provided by the driving global circulation models (GCMs) as well as different physical packages, resolution, and natural variability representation in individual GCMs. In general, RCMs driven by the ECHAM5-r3 GCM projected cooler climate conditions than did RCMs driven by the ARPÈGE GCM. This can be explained by two factors related to ECHAM5-r3: i) exaggerated transport of cool and moist air from the North Atlantic to Europe in summer, and ii) winter advection of cold air from the Artic owing to North Atlantic Oscillation blocking pattern alteration during solar minima as well as higher natural variability. RCM-related properties, such as physical package and spatial resolution, may also significantly affect climate predictions, although they do so to a smaller extent than does the driving GCM data.
Permanent Link: http://hdl.handle.net/11104/0249118