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Advances in Science and Research The open-access proceedings of the European Meteorological Society (EMS)

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Adv. Sci. Res., 14, 71-75, 2017
http://www.adv-sci-res.net/14/71/2017/
doi:10.5194/asr-14-71-2017
© Author(s) 2017. This work is distributed
under the Creative Commons Attribution 3.0 License.
 
05 Apr 2017
Atmospheric circulation types and extreme areal precipitation in southern central Europe
Jucundus Jacobeit, Markus Homann, Andreas Philipp, and Christoph Beck Institute of Geography, University of Augsburg, Augsburg, Germany
Abstract. Gridded daily rainfall data for southern central Europe are aggregated to regions of similar precipitation variability by means of S-mode principal component analyses separately for the meteorological seasons. Atmospheric circulation types (CTs) are derived by a particular clustering technique including large-scale fields of SLP, vertical wind and relative humidity at the 700 hPa level as well as the regional rainfall time series. Multiple regression models with monthly CT frequencies as predictors are derived for monthly frequencies and amounts of regional precipitation extremes (beyond the 95 % percentile). Using predictor output from different global climate models (ECHAM6, ECHAM5, EC-EARTH) for different scenarios (RCP4.5, RCP8.5, A1B) and two projection periods (2021–2050, 2071–2100) leads to assessments of future changes in regional precipitation extremes. Most distinctive changes are indicated for the summer season with mainly increasing extremes for the earlier period and widespread decreasing extremes towards the end of the 21st century, mostly for the strong scenario. Considerable uncertainties arise from the predictor use of different global climate models, especially during the winter and spring seasons.

Citation: Jacobeit, J., Homann, M., Philipp, A., and Beck, C.: Atmospheric circulation types and extreme areal precipitation in southern central Europe, Adv. Sci. Res., 14, 71-75, doi:10.5194/asr-14-71-2017, 2017.
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Monthly frequencies of circulation types (derived by clustering fields of SLP, vertical wind and rel. humidity at 700 hPa and regional rainfall series) are used as predictors in regression models for monthly frequencies of regional precipitation extremes (> 95 % percentile). With predictor output from global climate models, changes in regional precipitation extremes for 2021–2050 and 2071–2100 are assessed, most distinctive in summer: increasing/decreasing extremes for the earlier/later period.
Monthly frequencies of circulation types (derived by clustering fields of SLP, vertical wind and...
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