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228 References Anderson, C. J., and PIRCS coauthors, Hydrological processes in regional climate model simulations of the central United States Flood of June-July 1993, J. Hydrometeor., Vol. 4, No. 3, pp. 584—598, 2003. CCSP, Weather and climate extremes in a changing climate. A report by the U. S. Climate Change Science Program and the Subcommittee on Global Change Research, [Thomas R. Karl, Gerald A. Meehl, Christopher D. Miller, Susan J. Hassol, Anne M. Waple, and William L. Murray (eds.)], Department of Commerce, NOAA’s National Climatic Data Center, Washington, D. C., USA, pp. 164, 2008. IPCC, Climate Change 2007: The physical science basis. Contribution of working group I to the fourth assessment report of the intergovernmental panel on climate change [Solomon, S., D. Qin, et al. (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, pp. 996, 2007
229 Wave estimations using winds from RCA, the Rossby regional climate model Barry Broman 1 and Ekaterini.E. Kriezi 2 1 Swedish Meteorological and Hydrological Institute, Rossby Centre, Norrköping, Sweden; Barry.Broman@smhi.se 2 Swedish Meteorological and Hydrological Institute, Göteborg, Sweden; Ekaterini.Kriezi@smhi.se 1. Introduction Waves have now been used in the projections of the climate. The model SWAN running with winds from the Rossby Regional Climate Atmospheric model, (RCA). The first results of this were presented at the International Symposium US/EU-Baltic 2008 in Tallinn. 2. Future Wave Climate Hind casts of waves were made with winds from RCA. When the results were compared to measurements they were to low. The reason is that the winds in RCA are too week due to among other thing averaging over the grid cell. In order to get better results a method were used to “correct” the winds by using both winds and gusts. This was a great improvement but more work is needed. In maps and graphs the comparisons will be given. Below in figure 1 you se an example of the climate effect on winds after taking the difference between a reference period and a future projection. Figure 1. example of results with the SWAN model (significant wave heights ): differences in percentiles between control period and future projection 3. Future plans The plan is to use results from a coming coupled run between RCA, the atmospheric model and RCO the oceanographic model. These will give both winds and ice which is needed in order to make estimation of eventually changing wave climate in the Baltic References Booij, N., Ris, R.C., Holthuijsen, L.H., 1999. A thirdgeneration wave model for coastal regions, 1. Model description and validation. J. Geophys. Res. 104 (C4), 7649–7666. Broman B, 2007. Estimation of the wave climate for the Baltic Sea. Poster, Baltic Science Conference, Rostock 2007. Broman, B., Hammarklint T., Soomere T., Valdmann A., 2006, Trends and extremes of wave fields in the northeastern part of the Baltic Proper" ,OCEANOLOGICA,48,2006 pp 165-184. Davis F. and Newstein H. 1968. The variation of Gust Factors with Mean wind Speed and with Height. Journal of Applied Meteorology, Jume 1968, volume 7, 372-378 Gill G.C. 1969. Comments on “The variation of Gust Factors with Mean wind Speed and with Height”. Journal of Applied Meteorology, Notes and correspondence, february 1969, 167 Grabemann I. and Weisse R. 2007 Climate changes Impact on Extreme Wave conditions in the Noth Sea: An Esemble Study. Ocean Dynamics, Submitted Häggmark L., Ivarsson K-I., Gollvik S. and Olofsson P-O, 2000. Mesan, an operational mesocale analysis system. Tellus,52 A,2-20 Kjellström E., Bärring L., Gollvik S., Hansson U., Jones C, Samuelsson P, Rummukainen M., Ullerstig A., Willén U. and Wyser K., 2005. A 140-year simulation European climate with new version of the Rossby Centre regional atmospheric climate model (RCA3), SMHI, Reports Meteorology and climatology 108 Jönsson A., Broman B., and Rahm L., 2003. Variations in the Baltic Sea wave fields. Ocean Engineering, Volume 30, Issue 1, January 2003, 107-126 Nerheim S. 2008. Growing demands for downscaling of climate information – examples from predictions of future sea levels. US/EUBaltic2008 International Symposium, Tallinn Estonia, 27-29 May 2008 Ris, R. C. 1997: Spectral modelling of wind waves in coastal areas. PhD Thesis, Delft University of Technology, Delft, Netherlands. Räisänsen J, Hansson U, Ullerstig A., Döscher R., Graham L.P., Jones C., Meier M., Samuelsson R., Willén U., 2003. GCM driven simulations of recent and future climate with the Rossby Centre coupled Atmospheric – Baltic Sea regional climate model RCAO. SMHI, Reports Meteorology and climatology 101 Van der Westhuysen, A.J., M. Zijlema and J.A. Battjes, 2007. Nonlinear saturation-based whitecapping dissipation in SWAN for deep and shallow water. Coastal Engineering, 54, 151-170. Ekrietsi E. and Broman B. Past and future wave climate in the Baltic Sea produced by SWAN model with forcing from the regional climate model RCA of the Rossby Centre. US/EU-Baltic 2008, Tallinn may 27 -29 2008.
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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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XVI Favot F .......................
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XVIII Ruoho-Airola T...............
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2 5. Influence of SN on the Ensembl
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4 (+/- 5 days) were used to increas
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6 Dynamical downscaling: Assessment
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8 Improvement of long-term integrat
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10 air temperature annual cycle (Fi
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12 Sensitivity study of CRCM-simula
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14 Regional precipitation anomalies
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16 Assessment of precipitation as s
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18 The Asian summer monsoon in ERA4
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20 Added value of limited area mode
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22 Sensitivity of CRCM basin annual
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24 High-resolution dynamical downsc
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26 There is nevertheless a large ag
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28 technique, as it is based on the
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30 4. Heating mechanism In order to
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32 The geographical distribution of
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34 The CCM scheme reveals a distinc
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36 Performance of pattern scaling i
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38 Evaluation of the analyzed large
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40 Sensitivity studies with a stati
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42 5SL, the results suggest that 5S
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44 are however occasional episodes
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46 this season, as well as the high
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48 Figure 1. Precipitation rate (mm
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50 References Biau. G., E. Zorita,
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52 Investigation of regional climat
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54 Selected examples of the added v
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56 The climate change in Europe sim
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58 Simulation of South Asian summer
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7.5 8.5 9.5 10.5 60 For the climato
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62 precipitation field was more clo
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64 3. Results Fig. 2 shows the anal
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66 Is the position of the model dom
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68 question E. Finally a 10-member
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Figure 2. Same as in Fig.1 but for
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72 Will, A., M. Baldauf, B. Rockel,
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74 ( ) with i = 1,K,n; j = 1,K,m;
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76 Investigation of precipitation o
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78 Impacts of the spectral nudging
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80 Extremes and predictability in t
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82 Large-scale skill in regional cl
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84 Figure 3: As Figure 1 but for Wi
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86 The models capture this pattern
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88 of the simulations due to the di
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91 Examining the relative roles con
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93 Dynamical coupling of the HIRHAM
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95 A parameterization of aircraft i
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97 Stratospheric variability and it
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99 Effects of numerical methods on
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101 Development of a climate model
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103 Study of the capability of the
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105 Evaluation of the land surface
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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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117 Evaluation of the Rossby Centre
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119 Simulating aerosols in the regi
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121 Moisture availability and the r
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123 Temperature and precipitation s
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125 4. Preliminary results for down
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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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147 For relative operating characte
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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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Page 207 and 208: 181 Verification of simulated near
Page 209 and 210: 183 The North American Regional Cli
Page 211 and 212: 185 An atmosphere-ocean regional cl
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Page 217 and 218: 191 Inter-comparison of Asian monso
Page 219 and 220: 193 On the validation of RCMs in te
Page 221 and 222: 195 AMMA-Model Intercomparison Proj
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Page 225 and 226: 199 Evaluation of European snow cov
Page 227 and 228: 201 Projections of eastern Mediterr
Page 229 and 230: 203 Atmospheric river induced heavy
Page 231 and 232: 205 CLARIS project: Towards climate
Page 233 and 234: 207 Influence of soil moisture init
Page 235 and 236: 209 Projection of the Changes in th
Page 237 and 238: 211 Regional climate model studies
Page 239 and 240: 213 ENSEMBLES regional climate mode
Page 241 and 242: 215 Assessing the performance of se
Page 243 and 244: 217 Applying the Rossby Centre Regi
Page 245 and 246: 219 Interactions between European s
Page 247 and 248: 221 ALADIN-Climate/CZ simulation of
Page 249 and 250: 223 experiment of recreating the pr
Page 251 and 252: 225 Figure 2. the 10-year averaged
Page 253: 227 Use of regional climate models
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Page 265 and 266: 239 4. Outlook Currently a coupled
Page 267 and 268: 241 distribution within the Netherl
Page 269 and 270: 243 Very high-resolution regional c
Page 271 and 272: 245 Impact of convective parameteri
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Page 275 and 276: 249 Regional climate change impact
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Page 279 and 280: 253 Application of regional-scale c
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Page 283 and 284: 257 Impact of vegetation on the sim
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Page 287 and 288: 261 Influence of soil moisture-near
Page 289 and 290: 263 Forest damage in a changing cli
Page 291 and 292: 265 Future challenges for regional
Page 293 and 294: 267 Linking climate factors and ada
Page 295 and 296: 269 GCMs. In the end of the 21 st c
Page 297 and 298: 271 Climate change impacts on extre
Page 299 and 300: 273 Winter storms with high loss po
Page 301 and 302: 275 The impact of land use change a
Page 303 and 304: 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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