High Resolution Climate Modelling with the CCLM Regional Model for Europe and Africa

The High Performance Computing System (HPC) CRAY XE6 operated by HLRS is a powerful tool to study various aspects of the regional climate. Employing the regional climate model (RCM) COSMO-CLM, the research focus of IMK-TRO is on the regional atmospheric water cycle, especially on extremes, and different goals are pursued in individual research projects (MiKlip, KLIMOPASS and KLIWA). The simulation regions comprise Germany, Europe, and Africa with resolutions varying from 50 km to 2.8 km. Furthermore, different time spans are investigated. Decadal simulations are performed to assess decadal regional climate predictability. Projections of the future climate consider periods up to the end of the twenty-first century. To quantify the uncertainty of climate projections and predictions as well as the quality of the models, ensembles are built by different techniques. The Soil-Vegetion-Atmosphere-Transfer model (SVAT) VEG3D is coupled to COSMO-CLM via OASIS3-MCT to investigate the effect of soil and vegetation processes on decadal climate predictions. High resolution (2.8 km) experiments are performed for the State of Baden–Wurttemberg to study the potential added value and extremes. Computational capacities from 100 to 650 node–hours per simulated year (Wall Clock Time) are required for these simulations.

[1]  T. D. Mitchell,et al.  An improved method of constructing a database of monthly climate observations and associated high‐resolution grids , 2005 .

[2]  Mark A. Liniger,et al.  Seasonal Ensemble Forecasts: Are Recalibrated Single Models Better than Multimodels? , 2009 .

[3]  Jay Walter Larson,et al.  The Model Coupling Toolkit: A New Fortran90 Toolkit for Building Multiphysics Parallel Coupled Models , 2005, Int. J. High Perform. Comput. Appl..

[4]  D. Wilhite,et al.  Objective Quantification of Drought Severity and Duration , 1999 .

[5]  Hans-Jürgen Panitz,et al.  High Resolution Climate Modeling with the CCLM Regional Model , 2013, High Performance Computing in Science and Engineering.

[6]  P. Jones,et al.  A European daily high-resolution gridded data set of surface temperature and precipitation for 1950-2006 , 2008 .

[7]  G. Schädler.  Triggering of atmospheric circulations by moisture inhomogeneities of the earth's surface , 1990 .

[8]  Hans-Jürgen Panitz,et al.  High-resolution sensitivity studies with the regional climate model COSMO-CLM , 2009 .

[9]  P. Linden,et al.  ENSEMBLES: Climate Change and its Impacts - Summary of research and results from the ENSEMBLES project , 2009 .

[10]  Van Genuchten,et al.  A closed-form equation for predicting the hydraulic conductivity of unsaturated soils , 1980 .

[11]  A. Sterl,et al.  The ERA‐40 re‐analysis , 2005 .

[12]  D. Jacob,et al.  Determination of precipitation return values in complex terrain and their evaluation , 2010 .

[13]  M. Baldauf,et al.  Operational Convective-Scale Numerical Weather Prediction with the COSMO Model: Description and Sensitivities , 2011 .

[14]  Christoph Kottmeier,et al.  The regional MiKlip decadal forecast ensemble for Europe , 2013 .

[15]  S. Valcke,et al.  The OASIS3 coupler: a European climate modelling community software , 2012 .

[16]  G. Schädler,et al.  Generation of regional climate ensembles using Atmospheric Forcing Shifting , 2014 .

[17]  O. Johansen.  Thermal Conductivity of Soils , 1977 .