final_program_abstracts[1]

More documents

Recommendations

Info

11 IMSC Session Program Controls on rainfall variability on Southern Africa: An analysis based on generalized linear model Tuesday - Parallel Session 5 Chiara Ambrosino 1 , Richard E. Chandler 2 and Martin C. Todd 3 1 University College London, Department of Geography, London, UK 2 University College London, Department of Statistical Science, London, UK 3 University of Sussex, Department of Geography, Brighton, UK Southern Africa is particularly prone to adverse effects of changes in the climate system. In particular global warming may cause intensification of the hydrological cycle, with changes in frequencies and amplitudes of periods of below normal rainfall and associated scarcity in water availability and drought compromising the availability of water for rain-fed agriculture. To reduce the vulnerability advancement in the climate research needs to be advocated and provision of climate information is necessary for planning adaptation and mitigation measures. As a first step towards the provision of such information, it is helpful to understand the important climatological controls of rainfall variability in the region. There is already an extensive literature investigating the association between rainfall in southern Africa and individual climate indices such as ENSO, ... However, as far as we are aware there has been little work done to date that attempts to quantify how the various indices work in combination to control the rainfall variability of the region. This talk will describe an analysis based on generalised linear models (GLMs) that aims to address this issue. The GLM-based framework is being used increasingly in climatology: here, it has been employied to identify a small number of key climate indices from a large list of candidates taken from the literature, and to quantify the seasonal and regional effects of these indices upon southern African precipitation. GLMs are fitted to 20 th century observational gridded datasets to characterise the dependence of precipitation upon geographical and climate indicators of interest . As well as characterising the effect of the covariates upon precipitation, GLMs are explicitly probabilistic and therefore provide the opportunity to simulate continuous multiple precipitation sequences useful for impact study applications that are consistent with any given set of atmospheric drivers while recognising that the dependence is not deterministic. The relationships revealed by the GLM analysis can be exploited in principle to downscale large-scale output from general circulation models (GCMs) to scales that are suitable for use in studies that aim to assess the hydrological impacts of climate change. However, such procedures are based on an assumption the relationships will continue to hold in the future. Although this assumption is untestable, some reassurance may be gained by comparing equivalent relationships obtained from GCM simulations for the 20 th and 21 st centuries. If these relationships are similar (and regardless of whether the GCMs are able to reproduce the observed relationships), one can reasonably infer that their stability is at least consistent with our best available knowledge of climate dynamics. The talk will conclude by presenting some preliminary work in this direction. Abstracts 143
11 IMSC Session Program Construction of high resolution monthly temperature scenarios for North America Tuesday - Parallel Session 5 Guilong Li 1 , Xuebin Zhang 2 and Francis Zwiers 2 1 Atmospheric Science and Application Unit — MSC Ontario Region, Environment Canada, Canada 2 Climate Research Division — ASTD, Environment Canada, Canada This presentation provides a framework in which dynamical and statistical downscaling methods are combined to construct monthly temperature scenarios over North America at 45x45 km resolution. Monthly temperatures from outputs of three GCMs are dynamically downscaled by three regional climate models (RCMs) participating the North America Regional Climate Change Assessment Program. The dynamically downscaled high resolution temperature and low resolution GCM outputs for the periods 1968-2000 and 2038-2070 are then used to establish statistical models to link small scale and large scale temperatures. These statistical models are then applied to GCM projected future temperature changes available from the CMIP3 database, to construct high resolution monthly temperature scenarios for North America. Uncertainties due to difference in GCMs, in emission scenarios, and internal variability are analyzed. The end product provides projected monthly temperature changes in the future at 45 km resolution with different uncertainty ranges. Abstracts 144
Page 2 and 3:
Bus map of city centre
Page 4 and 5:
Edinburgh Centre to Pollock Halls A
Page 7 and 8:
Tips and advice for travelling in E
Page 9 and 10:
Information for Presenters: for pos
Page 11 and 12:
11 IMSC Session Program 11 IMSC Ses
Page 13 and 14:
11 IMSC Session Program Monday, Jul
Page 15 and 16:
11 IMSC Session Program 15:15 - 15:
Page 17 and 18:
Page 19 and 20:
Page 21 and 22:
Page 23 and 24:
Page 25 and 26:
Page 27 and 28:
Page 29 and 30:
11 IMSC Session Program Thursday, J
Page 31 and 32:
Page 33 and 34:
11 IMSC Session Program Evaluation
Page 35 and 36:
11 IMSC Session Program Friday, Jul
Page 37 and 38:
11 IMSC Session Program 18. Markus
Page 39 and 40:
Page 41 and 42:
11 IMSC Session Program Are there l
Page 43 and 44:
11 IMSC Session Program HOMER: A hi
Page 45 and 46:
11 IMSC Session Program Softcore an
Page 47 and 48:
11 IMSC Session Program Towards the
Page 49 and 50:
11 IMSC Session Program Past sea le
Page 51 and 52:
11 IMSC Session Program Vidal, J.-P
Page 53 and 54:
11 IMSC Session Program precipitati
Page 55 and 56:
11 IMSC Session Program Structural
Page 57 and 58:
11 IMSC Session Program Modeling an
Page 59 and 60:
11 IMSC Session Program Probabilist
Page 61 and 62:
11 IMSC Session Program Multi-model
Page 63 and 64:
11 IMSC Session Program Climate var
Page 65 and 66:
11 IMSC Session Program Reconstruct
Page 67 and 68:
11 IMSC Session Program Variational
Page 69 and 70:
11 IMSC Session Program Intercompar
Page 71 and 72:
11 IMSC Session Program Gridding of
Page 73 and 74:
11 IMSC Session Program Reconstruct
Page 75 and 76:
11 IMSC Session Program A new algor
Page 77 and 78:
11 IMSC Session Program Assessing c
Page 79 and 80:
11 IMSC Session Program importance
Page 81 and 82:
11 IMSC Session Program Changing th
Page 83 and 84:
11 IMSC Session Program Probabilist
Page 85 and 86:
11 IMSC Session Program Mechanistic
Page 87 and 88:
11 IMSC Session Program Quantifying
Page 89 and 90:
11 IMSC Session Program Deriving dy
Page 91 and 92:
11 IMSC Session Program A new monso
Page 93 and 94:
11 IMSC Session Program Extreme var
Page 95 and 96:
11 IMSC Session Program Cai, W., A.
Page 97 and 98:
11 IMSC Session Program Uncertainti
Page 99 and 100:
11 IMSC Session Program How good do
Page 101 and 102:
11 IMSC Session Program Bridging th
Page 103 and 104: 11 IMSC Session Program Climate cha
Page 105 and 106: 11 IMSC Session Program The Variati
Page 107 and 108: 11 IMSC Session Program Calibrating
Page 109 and 110: 11 IMSC Session Program Analysis of
Page 111 and 112: 11 IMSC Session Program Statistical
Page 113 and 114: 11 IMSC Session Program No title pr
Page 115 and 116: 11 IMSC Session Program The survey
Page 117 and 118: 11 IMSC Session Program Detecting s
Page 119 and 120: 11 IMSC Session Program Measure-cor
Page 121 and 122: 11 IMSC Session Program Trend evalu
Page 123 and 124: 11 IMSC Session Program Methodologi
Page 125 and 126: 11 IMSC Session Program Trends in d
Page 127 and 128: 11 IMSC Session Program Assimilatio
Page 129 and 130: 11 IMSC Session Program - monthly a
Page 131 and 132: 11 IMSC Session Program Non-linear
Page 133 and 134: 11 IMSC Session Program What can we
Page 135 and 136: 11 IMSC Session Program Constructin
Page 137 and 138: 11 IMSC Session Program An intercom
Page 139 and 140: 11 IMSC Session Program Historical
Page 141 and 142: 11 IMSC Session Program Variance-pr
Page 143 and 144: 11 IMSC Session Program A Bayesian
Page 145 and 146: 11 IMSC Session Program CORDEX: Dev
Page 147 and 148: 11 IMSC Session Program Downscaling
Page 149 and 150: 11 IMSC Session Program Constructin
Page 151 and 152: 11 IMSC Session Program A functiona
Page 153: 11 IMSC Session Program Downscaling
Page 157 and 158: 11 IMSC Session Program Intercompar
Page 159 and 160: 11 IMSC Session Program Detecting a
Page 161 and 162: 11 IMSC Session Program New techniq
Page 163 and 164: 11 IMSC Session Program detected wi
Page 165 and 166: 11 IMSC Session Program New develop
Page 167 and 168: 11 IMSC Session Program A change po
Page 169 and 170: 11 IMSC Session Program The analysi
Page 171 and 172: 11 IMSC Session Program Memory in c
Page 173 and 174: 11 IMSC Session Program Blending an
Page 175 and 176: 11 IMSC Session Program Bowen, A. a
Page 177 and 178: 11 IMSC Session Program Statistical
Page 179 and 180: 11 IMSC Session Program Vidal, J.-P
Page 181 and 182: 11 IMSC Session Program Classificat
Page 183 and 184: 11 IMSC Session Program Downscaling
Page 185 and 186: 11 IMSC Session Program Impact of c
Page 187 and 188: 11 IMSC Session Program Comparison
Page 189 and 190: 11 IMSC Session Program When is a m
Page 191 and 192: 11 IMSC Session Program Objective a
Page 193 and 194: 11 IMSC Session Program Weighting o
Page 195 and 196: 11 IMSC Session Program Are current
Page 197 and 198: 11 IMSC Session Program Uncertainty
Page 199 and 200: 11 IMSC Session Program Verifying e
Page 201 and 202: 11 IMSC Session Program The metaver
Page 203 and 204: 11 IMSC Session Program An intercom
Page 205 and 206:
11 IMSC Session Program Use of hidd
Page 207 and 208:
11 IMSC Session Program Analysis of
Page 209 and 210:
11 IMSC Session Program Volcanoes a
Page 211 and 212:
11 IMSC Session Program Statistical
Page 213 and 214:
11 IMSC Session Program No title pr
Page 215 and 216:
11 IMSC Session Program Intermitten
Page 217 and 218:
Page 219 and 220:
11 IMSC Session Program No title pr
Page 221 and 222:
Page 223 and 224:
11 IMSC Session Program Enhanced ev
Page 225 and 226:
11 IMSC Session Program A comparati
Page 227 and 228:
11 IMSC Session Program Wavelet and
Page 229 and 230:
11 IMSC Session Program Understandi
Page 231 and 232:
11 IMSC Session Program curve signa
Page 233 and 234:
11 IMSC Session Program Novel advan
Page 235 and 236:
11 IMSC Session Program Skill in la
Page 237 and 238:
11 IMSC Session Program Evaluating
Page 239 and 240:
11 IMSC Session Program for each mo
Page 241 and 242:
11 IMSC Session Program Designing e
Page 243 and 244:
Page 245 and 246:
11 IMSC Session Program Using a per
Page 247 and 248:
11 IMSC Session Program Present-day
Page 249 and 250:
11 IMSC Session Program Model evalu
Page 251 and 252:
11 IMSC Session Program Constrainin
Page 253 and 254:
11 IMSC Session Program Forecast en
Page 255 and 256:
11 IMSC Session Program How can RCM
Page 257 and 258:
11 IMSC Session Program Extreme var
Page 259 and 260:
11 IMSC Session Program Extreme val
Page 261 and 262:
11 IMSC Session Program Detecting c
Page 263 and 264:
11 IMSC Session Program Subsampling
Page 265 and 266:
11 IMSC Session Program Predicting
Page 267 and 268:
11 IMSC Session Program Detection o
Page 269 and 270:
Page 271 and 272:
11 IMSC Session Program On the stat
Page 273 and 274:
11 IMSC Session Program A relaxes B
Page 275 and 276:
11 IMSC Session Program The limited
Page 277 and 278:
11 IMSC Session Program Prediction
Page 279 and 280:
11 IMSC Session Program Towards sys
Page 281 and 282:
11 IMSC Session Program The MVL dia
Page 283 and 284:
11 IMSC Session Program SVD on ICE
Page 285 and 286:
11 IMSC Session Program Crossing cr
Page 287 and 288:
11 IMSC Session Program Water resou
Page 289 and 290:
11 IMSC Session Program The spread
Page 291 and 292:
Page 293 and 294:
11 IMSC Session Program Towards an
Page 295 and 296:
11 IMSC Session Program Trends in E
Page 297 and 298:
11 IMSC Session Program Climate cha
Page 299 and 300:
11 IMSC Session Program Shift of se
Page 301 and 302:
11 IMSC Session Program Implication
Page 303 and 304:
11 IMSC Session Program Bottom-up v
Page 305 and 306:
11 IMSC Session Program Attributing
Page 307 and 308:
11 IMSC Session Program Monitoring
Page 309 and 310:
11 IMSC Session Program Anthropogen
Page 311 and 312:
Page 313 and 314:
11 IMSC Session Program Variability
Page 315 and 316:
11 IMSC Session Program Spatial pat
Page 317 and 318:
11 IMSC Session Program An analysis
Page 319 and 320:
11 IMSC Session Program Changes on
Page 321 and 322:
11 IMSC Session Program Can gridded
Page 323 and 324:
11 IMSC Session Program Estimating
Page 325 and 326:
11 IMSC Session Program The limits
Page 327 and 328:
11 IMSC Session Program Variability
Page 329 and 330:
11 IMSC Session Program Nonparametr
Page 331 and 332:
11 IMSC Session Program exception,
Page 333 and 334:
Page 335 and 336:
11 IMSC Session Program Change in t
Page 337 and 338:
Page 339 and 340:
11 IMSC Session Program Comparison
Page 341 and 342:
11 IMSC Session Program Storm activ
Page 343 and 344:
11 IMSC Session Program Comparison
Page 345 and 346:
11 IMSC Session Program Modelling e
Page 347 and 348:
11 IMSC Session Program European we
Page 349 and 350:
11 IMSC Session Program Regression
Page 351 and 352:
11 IMSC Session Program 3 Keef, C.,
Page 353 and 354:
11 IMSC Session Program New indices
Page 355 and 356:
11 IMSC Session Program Sources of
Page 357 and 358:
11 IMSC Session Program sites in th
Page 359 and 360:
11 IMSC Session Program Communicati
Page 361 and 362:
11 IMSC Session Program Detection a
Page 363 and 364:
11 IMSC Session Program Comparing t
Page 365 and 366:
11 IMSC Session Program Spatial cha
Page 367 and 368:
11 IMSC Session Program Ocean heat
Page 369 and 370:
11 IMSC Session Program Observation
Page 371 and 372:
show all

final_program_abstracts[1]

Create successful ePaper yourself

Delete template?

Save as template?