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56 The climate change in Europe simulated by the regional climate model COSMO-CLM Kai S. Radtke and Klaus Keuler Brandenburg University of Technology, Environmental Meteorology, 03044 Cottbus, Germany, radtke@tu-cottbus.de 1. Introduction A small ensemble of regional climate simulations (Hollweg et al., 2008) was performed with the climate version (Böhm et al., 2006) of the numerical weather prediction model COSMO ('COnsortium for SMall scale Modelling', formerly known as LM) (Steppeler et al., 2003). The COSMO-CLM has been forced by output of the ECHAM5/MPIOM global climate model, which contributed to the fourth climate assessment report of the 'International Panel on Climate Change' (IPCC, 2007). The simulations were performed by the Model and Data group (M&D) of the Max Planck Institute for Meteorology. The configuration of the model was developed by the CLM Community (http://www.clmcommunity.eu/). In this context, three realisations of the climate of the 20th century (1961-2000) were simulated. Each of the IPCC scenarios A1B and B2 (Nakiećenović, 2000) for the climate of the 21st century (2001-2100) was simulated twice. The model grid has a resolution of 0.165° and covers Europe nearly complete. Here, the climate change signal and its variability with regard to the different scenarios, the different realisations and different time periods as well as regional and seasonal differences are considered. Simulation results for the 2 m air temperature and the precipitation sum are presented. 2. Temperature The annual mean temperature for the climate of the 20th century (1961-1990) amounts 280.77 K to 281.07 K for Central Europe. Thus, the different realisations vary up to 0.3 K. The 70-year climate change signals (2031-2060 vs. 1961- 1990) amount from 1.39 to 1.95 K for the A1B scenario (figure 1) and from 0.84 to 1.30 K for B1. The variability is caused by considering the different realisations. Six paired comparisons between the two realisations of the future climate and the three realisations of the climate of the 20th century were taken into account for both scenarios. These variability amounts to 0.56 K for the A1B scenario and to 0.46 K for B1, approximately 25-50% of the absolute value of the simulated climate change. The warming is 0.55 to 0.65 K larger in the A1B scenario than in B1 for Central Europe. The annual cycle of temperature change for the A1B scenario (figure 1) shows the strongest warming in summer and winter and a moderate warming in spring. The B1 scenario feature a similar shape of the seasonal distribution of climate change, but the warming is always lower. The 100-year climate change signal (2061-2090 vs. 1961- 1990) is more intense than the 70-year signal, but it shows for both scenarios a similar structure. The warming for Central Europe amounts from 2.81 to 3.19 K in the A1B scenario and from 1.79 to 2.13 K in the B1 scenario. The shape of the annual cycle of the climate change is similar to the 70-year signal, but the values are larger. For the B1 scenario, this increase in time is somewhat lower. The simulated warming is in southern, southwest and northern Europe relative strong, but in Central Europe more moderate. The increase in annual mean temperature for northern Europe (A1B, 70-year: 1.8 to 2.2 K for Scandinavia) and southern Europe (1.8 to 1.9 K for the Iberian Peninsula) has a similar magnitude. But the seasonal trends of global warming are completely different. The warming in southern Europe is strongest in summer. In contrast, it is strongest in winter time in northern Europe. This fact is characteristic for both scenarios. 2,5 1,5 0,5 -0,5 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Figure 1. The 70-year climate change (2031-2060 vs. 1961-1990) for the near surface temperatures for Central Europe for the scenario A1B in K. Six paired comparisons (A1B (realisation 1) minus climate of the 20-th century (realisation 1 to 3) and the same for A1B (realisation 2)) are given for any month. The line shows the average of all paired comparisons. 3. Precipitation The 30-year averages of annual precipitation sums vary for the climate of the 20th Century from 1021 to 1036 mm for Central Europe. The 70-year climate change signal amounts from 4 to 21 mm for A1B, from -17 to 34 mm for B1. So, the change of the precipitation in Central Europe is low (the largest value is lesser than 5% of the total precipitation amount). The variability of the simulated climate change for the different paired comparisons is relatively large. Increases as well as decreases are simulated. Thus, the simulations show no reliable change of the annual precipitation sum for Central Europe. But they feature a shift of precipitation from summer to winter. This shift is more clearly developed in the 100-year climate change signal (figure 2). Furthermore, it's stronger in the A1B scenario. The 100-year time period also does not show a reliable climate change for the annual precipitation sum for both scenarios for Central Europe. The changes amount from -16 to 12 mm for the A1B scenario and from -2.5 to 18 mm for the B1 scenario. Central Europe is in the transition zone between two domains in Europe. An increase of annual precipitation is simulated in the area of northern Europe (A1B, 70-year: 41 to 97 mm for Scandinavia). It's strongest in the winter. But, the model produces a decrease in annual precipitation for south and southwest Europe (-145 to +2 mm for the Iberian Peninsula). This decrease is mainly caused by the summer months. Both scenarios show that spatial pattern.
57 These structures are more intense in the 100-year climate change signal. 40 30 20 10 0 -10 -20 -30 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Figure 2. The 100-year climate change (2061-2090 vs. 1961-1990) for the precipitation sum for Central Europe for the scenario A1B in %. Six paired comparisons (A1B (realisation 1) minus climate of the 20-th century (realisation 1 to 3) and the same for A1B (realisation 2)) are given for any month. The line shows the average of all paired comparisons. References Böhm, U., M. Kücken, W. Ahrens, A. Block, D. Hauffe, K. Keuler, B. Rockel, A. Will, CLM – The climate version of LM: Brief description and long-term application. Proceedings from the COSMO General Meeting 2005, COSMO Newsletter, No. 6, pp. 225 – 235, 2006 Hollweg, H.-D., U. Böhm, I. Fast, B. Hennemuth, K. Keuler, E. Keup-Thiel, M. Lautenschlager, S. Legutke, K. Radtke, B. Rockel, M. Schubert, A. Will, M. Woldt, C. Wunram, Ensemble Simulations over Europe with the Regional Climate Model CLM forced with IPCC AR4 Global Scenarios, Max Planck Institute for Meteorology, M&D Series, Technical Report, No. 3, pp. 152, 2008 IPCC, Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K. B. Averyt, M. Tignor, H. L. Miller (Eds.), IPCC Fourth Assessment Report, Intergovernmental Panel on Climate Change, The Physical Science Basis, IPCC, Cambridge University Press, pp. 996, 2007 Nakiećenović, N., R. Swart (Eds.), Special report on emissions scenarios, Intergovernmental Panel on Climate Change, IPCC, Cambridge University Press, pp. 599, 2000 Steppeler, J., G. Doms, U. Schättler, H. W. Bitzer, A. Gassmann, U. Damrath, G. Gregoric, Meso-gamma scale forecasts using the non-hydrostatic model LM, Meteorol. Atmos. Phys., No. 82, pp. 75-96, 2003
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2 nd International Lund RCM Worksho
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Associated Organisations ENSEMBLES
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Preface This Second Lund Regional-s
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II High-resolution dynamical downsc
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IV Investigation of added value at
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VI Soil organic layer: Implications
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VIII Session 4: Regional Observatio
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X Predicting water resources in Wes
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XII The impact of atmospheric therm
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XIV Observation and simulation with
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4 (+/- 5 days) were used to increas
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107 Simulation of the precipitation
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109 Climate simulations over North
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111 Soil organic layer: Implication
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113 4. Results The method how to do
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115 Figure 1. Observed (a) and simu
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119 Simulating aerosols in the regi
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127 a) Knutson, T.R., J.J. Sirutis,
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129 Effects of variations in climat
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131 3.2. Precipitation The ensemble
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133 knowledge is essential to asses
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135 pronounced biases in the simula
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137 variability was concentrated at
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139 Investigation of ‘Hurricane K
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141 Evaluation of seasonal forecast
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143 NASH J. E., SUTCLIFFE J. V., 19
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145 Climate change assessment over
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149 responsible for the excessive s
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151 and 30km). Domains D1 (90 and 6
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153 can be seen in Fig. 2, where th
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155 High-resolution simulation of a
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157 MesoClim - A mesoscale alpine c
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159 Observed and modeled extremes i
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161 analyzed the surface wind behav
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163 summer particularly in the Paci
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165 since 01.01.2004. For the Meteo
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167 Wind, m/s 12 10 8 6 4 2 Vilsand
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169 heterogeneity. For example, lar
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171 Analysis of surface air tempera
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173 Environmental database and the
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Climate change and water pollution
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177 During summer, winds over the M
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179 followed nearly the correct pat
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181 Verification of simulated near
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183 The North American Regional Cli
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185 An atmosphere-ocean regional cl
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187 different rainfall characterist
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189 with increasing temperature. Mo
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191 Inter-comparison of Asian monso
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193 On the validation of RCMs in te
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195 AMMA-Model Intercomparison Proj
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199 Evaluation of European snow cov
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201 Projections of eastern Mediterr
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203 Atmospheric river induced heavy
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205 CLARIS project: Towards climate
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207 Influence of soil moisture init
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209 Projection of the Changes in th
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211 Regional climate model studies
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213 ENSEMBLES regional climate mode
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215 Assessing the performance of se
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217 Applying the Rossby Centre Regi
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219 Interactions between European s
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221 ALADIN-Climate/CZ simulation of
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223 experiment of recreating the pr
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225 Figure 2. the 10-year averaged
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227 Use of regional climate models
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229 Wave estimations using winds fr
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231 Figure 1. Model domain for the
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233 A coupled regional climate mode
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235 Arctic regional coupled downsca
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237 Convection-resolving regional c
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239 4. Outlook Currently a coupled
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241 distribution within the Netherl
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243 Very high-resolution regional c
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245 Impact of convective parameteri
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249 Regional climate change impact
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251 River runoff projection of futu
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253 Application of regional-scale c
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255 Local air mass dependence of ex
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257 Impact of vegetation on the sim
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259 Climate change impacts on the w
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261 Influence of soil moisture-near
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263 Forest damage in a changing cli
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265 Future challenges for regional
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267 Linking climate factors and ada
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269 GCMs. In the end of the 21 st c
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271 Climate change impacts on extre
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273 Winter storms with high loss po
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275 The impact of land use change a
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277 6. Analysis of Results (Rain) T
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279 (a) (b) Figure 3. Impact of veg
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281 that cold (Fig. 5). Winter temp
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283 Streamflow in the upper Mississ
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285 Dynamical downscaling of urban
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287 Souma, K., K. Tanaka, E. Nakaki
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289 In April 2000, the fire emissio
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291 Impacts of vegetation on global
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International BALTEX Secretariat Pu
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No. 34: BALTEX Phase II 2003 - 2012
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