Abstract
Using the CRAY XE-6 at the HLRS high performance computing facilities provides the possibility to study various aspects of the regional climate employing the regional climate model COSMO-CLM. The research activities of the group “Regional Climate and Water Cycle” at the KIT focus on the regional atmospheric water cycle and, especially, on extremes and different goals are pursued in the individual research projects. Different regions and orographies are studied using different resolutions from 50 to 3 km. Furthermore, different time spans are investigated and computational capacities from 2 to 500 node-hours per year (Wall Clock Time) are required. The analyses comprise decadal climate simulations of Germany, Europe and Africa to assess regional decadal climate predictability. Further, climate projections are carried out for Baden-Württemberg (Germany) and novel ensemble generating techniques are implemented to better describe the involved uncertainties. High resolution (3 km) experiments are performed for Baden-Württemberg to study extremes and the effects of climate change on soil erosion. Moreover, the possibilities of adaption to climate change for Baden-Württemberg are analysed, with focus on extremes and combination of extremes (such as dry soil and extreme precipitation).
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
M. Baldauf, A. Seifert, J. Förstner, D. Majewski, M. Raschendorfer, Operational convective-scale numerical weather prediction with the COSMO model: description and sensitivities. Mon. Weather Rev. 139, 3887–3905 (2011). doi:10.1175/MWR-D-10-05013.1
G. Doms, U. Schättler, A description of the nonhydrostatic regional model LM, Part I: dynamics and numerics. COSMO Newslett. 2, 225–235 (2002)
C. Meissner, G. Schädler, Modelling the regional climate of Southwest Germany: sensitivity to simulation setup, in High Performance Computing in Science and Engineering ’07, ed. by W.E. Nagel, D. Kröner, M. Resch (Springer, Berlin, 2007). ISBN 978-3-540-74738-3
B. Rockel, A. Will, A. Hense, Regional climate modelling with COSMO-CLM (CCLM). Meteorol. Z. 17(4) (2008). ISSN 0941-2948 (special issue)
C. Meissner, G. Schädler, H.-J. Panitz, H. Feldmann, C. Kottmeier, High resolution sensitivity studies with the regional climate model COSMO-CLM. Meteorol. Z. 18, 543–557 (2009). doi:10.1127/0941-2948/20090400
R.T. Sutton, D.L.R. Hodson, Atlantic ocean forcing of North American and European summer climate. Science 309, 115–118 (2005). doi:10.1126/science.1109496
H.-J. Panitz, P. Berg, G. Schädler, G. Fosser, Modelling regional climate change for Germany and Africa, in High Performance Computing in Science and Engineering ’11, ed. by W.E. Nagel, D. Kröner, M. Resch (Springer, Berlin, 2012), pp. 503–512. doi:10.1007/ 978-3-642-23869-7
A. Simmons, S. Uppala, D. Dee, S. Kobayashiera, New ECMWF reanalysis products from 1989 onwards. ECMWF Newslett. 110, 25–35 (2006) (Winter 2006/07)
W.A. Müller, J. Baehr, H. Haak, J.H. Jungclaus, J. Kröger, D. Matei, D. Notz, H. Pohlmann, J.S. von Storch, J. Marotzke, Forecast skill of multi-year seasonal means in the decadal prediction system of the Max-Planck Institute for Meteorology. Geophys. Res. Lett. 39, L22707 (2012). doi:10.1029/2012/GL053326
C.J. Willmott, K. Matsuura, D.R. Legates, Global air temperature and precipitation: regridded monthly and annual climatologies (version 2.01) (1998). Available online at http://climate.geog.udel.edu/~climate/
R. Sasse, G. Schädler Generation of regional climate ensembles using atmospheric forcing shifting. Int. J. Climatol. (2013 submitted)
H.-J. Panitz, G. Fosser, R. Sasse, A. Sehlinger, H. Feldmann, G. Schädler, Modelling near future regional climate change for Germany and Africa, in High Performance Computing in Science and Engineering ’12, ed. by W.E. Nagel, D. Kröner, M. Resch (2013)
I. Schlüter, G. Schädler, Sensitivity of heavy precipitation forecasts to small modifications of large-scale weather patterns for the Elbe river. J. Hydrometeorol. 11, 770–780 (2010). doi:10.1175/2010JHM1186.1
B. Früh, H. Feldmann, H.-J. Panitz, G. Schädler, D. Jacob, P. Lorenz, K. Keuler, Determination of precipitation return values in complex terrain and their evaluation. J. Climate 23, 2257–2274 (2010). doi:10.1175/2009JCLI2685.1
H. Feldmann, G. Schädler, H.-J. Panitz, C. Kottmeier, Near future changes of extreme precipitation over complex terrain in Central Europe derived from high resolution RCM ensemble simulations. Int. J. Climatol. (2012). doi:10.1002/joc.3564
S. Wagner, P. Berg, G. Schädler, H. Kunstmann, High resolution regional climate model simulations for Germany, Part II: projected climate changes. Climate Dyn. (2012). doi:10.1007/s00382-012-1510-1
G. Roeckner, G. Baeuml, L. Bonaventura, R. Brokopf, M. Esch, M. Giorgetta, S. Hagemann, I. Kirchner, L. Kornblueh, E. Manzini, A. Rhodin, U. Schlese, U. Schulzweida, A. Tompkins The atmospheric general circulation model ECHAM 5, Part I: model description. Technical Report 349, Max-Planck-Institut für Meteorologie, Hamburg (2003)
G. Schädler, P. Berg, D. Düthmann, H. Feldmann, J. Ihringer, H. Kunstmann, J. Liebert, B. Merz, I. Ott, S. Wagner, Flood hazards in a changing climate. Project Report, p. 83. Centre for Disaster Management and Rsik Reduction Technology (CEDIM) (2012), http://www.cedim.de/download/FloodHazardsinaChangingClimate.pdf
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer International Publishing Switzerland
About this paper
Cite this paper
Panitz, HJ. et al. (2013). High Resolution Climate Modeling with the CCLM Regional Model. In: Nagel, W., Kröner, D., Resch, M. (eds) High Performance Computing in Science and Engineering ‘13. Springer, Cham. https://doi.org/10.1007/978-3-319-02165-2_35
Download citation
DOI: https://doi.org/10.1007/978-3-319-02165-2_35
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-02164-5
Online ISBN: 978-3-319-02165-2
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)