IPCC Report.pdf - Adam Curry

More documents

Recommendations

Info

Changes in Climate Extremes and their Impacts on the Natural Physical EnvironmentChapter 3Wet Day IntensityPercentage Days with Pr>Q95Fraction of Days with Pr>10mmJJADJFANN1.2 0.4 0 0.4 1.2Standard Deviation2 1 0 1 2Percentage of Days1.2 0.6 0 0.6 1.2Standard DeviationFigure 3-6 | Projected annual and seasonal changes in three indices for daily precipitation (Pr) for 2081-2100 with respect to 1980-1999, based on 17 GCMs contributing to theCMIP3. Left column: wet-day intensity; middle column: percentage of days with precipitation above the 95% quantile of daily wet day precipitation for that day of the year,calculated from the 1961-1990 reference period; right column: fraction of days with precipitation higher than 10 mm. The changes are computed for the annual time scale (top row)and two seasons (DJF, middle row, and JJA, bottom row) as the fractions/percentages in the 2081-2100 period (based on simulations under emission scenario SRES A2) minus thefractions/percentages of the 1980-1999 period (from corresponding simulations for the 20th century). Changes in wet-day intensity and in the fraction of days with Pr >10 mmare expressed in units of standard deviations, derived from detrended per year annual or seasonal estimates, respectively, from the three 20-year periods 1980-1999, 2046-2065,and 2081-2100 pooled together. Changes in percentages of days with precipitation above the 95% quantile are given directly as differences in percentage points. Color shading isonly applied for areas where at least 66% (i.e., 12 out of 17) of the GCMs agree on the sign of the change; stippling is applied for regions where at least 90% (i.e., 16 out of 17)of the GCMs agree on the sign of the change. Adapted from Orlowsky and Seneviratne (2011); updating Tebaldi et al. (2006) for additional number of indices and CMIP3 models,and including seasonal time frames. For more details, see Appendix 3.A.regions where the Clausius-Clapeyron constraint is not closely followed,it still appears to be a better predictor for future changes in extremeprecipitation than the change in mean precipitation in climate modelprojections (Pall et al., 2007). An observational study seems also to supportthis thermodynamic theory. Analysis of daily precipitation from theSpecial Sensor Microwave Imager over the tropical oceans shows adirect link between rainfall extremes and temperature: heavy rainfallevents increase during warm periods (El Niño) and decrease during coldperiods (Allan and Soden, 2008). However, the observed amplificationof rainfall extremes is larger than that predicted by climate models(Allan and Soden, 2008), due possibly to widely varying changes inupward velocities associated with precipitation extremes (O’Gormanand Schneider, 2008). Evidence from measurements in the Netherlandssuggests that hourly precipitation extremes may in some cases increase14% per degree of warming, which is twice as fast as what would beexpected from the Clausius-Clapeyron relationship alone (Lenderinkand Van Meijgaard, 2008), though this is still under debate (Haerter andBerg, 2009; Lenderink and van Meijgaard, 2009). A comparison betweenobserved and multi-model simulated extreme precipitation using anoptimal detection method suggests that the human-induced increase ingreenhouse gases has contributed to the observed intensification ofheavy precipitation events over large Northern Hemisphere land areasduring the latter half of the 20th century (Min et al., 2011). Pall et al.(2011) linked human influence on global warming patterns with anincreased risk of England and Wales flooding in autumn (September-November) 2000 that is associated with a displacement in the NorthAtlantic jet stream. The present assessment based on evidence from newstudies and those used in the AR4 is that there is medium confidencethat anthropogenic influence has contributed to changes in extremeprecipitation at the global scale. However, this conclusion may bedependent on the season and spatial scale. For example, there is nowabout a 50% chance that an anthropogenic influence can be detectedin UK extreme precipitation in winter, but the likelihood of the detectionin other seasons is very small (Fowler and Wilby, 2010).Projected Changes and UncertaintiesRegarding projected changes in extreme precipitation, the AR4 concludedthat it was very likely that heavy precipitation events, that is, thefrequency of heavy precipitation or proportion of total precipitationfrom heavy precipitation, would increase over most areas of the globe144
Chapter 3Changes in Climate Extremes and their Impacts on the Natural Physical Environment806040200208060402020Alaska/N.W. Canada - 10204665 208100W. North America - 3204665 2081002080604020020C. North America - 4204665 208100Central America/Mexico - 6806040200204665 208100806040200208060402002080604020020E. Canada/Greenl./Icel. - 2204665 208100E. North America - 5204665 208100Amazon - 7204665 208100W. Coast South America - 980604020020N.E. Brazil - 8204665 20810080Central 50%intermodel range60Full model range4020020Scenarios:B1 A1B A2MedianΔ Precipitation (%)862880604020020204665 20810080604020020S.E. South America - 10204665 20810080604020020C. Europe - 12204665 208100S. Europe/Mediterranean - 1380604020020204665 2081008060402002080604020020204665 208100N. Europe - 11204665 2081003780604020020W. Africa - 15204665 20810080604020020Sahara - 14S. Africa - 178060402002080604020020204665 208100W. Asia - 19204665 208100E. Africa - 16204665 2081008060402002080604020020204665 20810080604020020C. Asia - 20S. Asia - 23204665 208100N. Asia - 18204665 20810080604020020Tibetan Plateau - 21204665 20810080604020020E. Asia - 22204665 208100899480604020020S.E. Asia - 24100204665 20810080604020020N. Australia - 25204665 208100S. Australia/New Zealand - 2680604020020204665 208100204665 208100Legend80604020020Globe (Land only)20-year return value (%)204665 20810080604020020mean (%)204665 208100Figure 3-7a | Projected changes (%) in 20-year return values of annual maximum 24-hour precipitation rates. The bar plots (see legend for more information) show results for regionally averaged projections for two time horizons,2046 to 2065 and 2081 to 2100, as compared to the late 20th century (1981-2000), and for three different SRES emission scenarios (B1, A1B, A2). Results are based on 14 GCMs contributing to the CMIP3. See Figure 3-1 for definedextent of regions. Values are computed for land points only. The ‘Globe’ analysis (inset box) displays the change in 20-year return values of the annual maximum 24-hour precipitation rates computed using all land grid points (left),and the change in annual mean 24-hour precipitation rates computed using all land grid points (right). Adapted from the analysis of Kharin et al. (2007). For more details, see Appendix 3.A.145
Page 1:
MANAGING THE RISKS OF EXTREMEEVENTS
Page 5 and 6:
Managing the Risks of Extreme Event
Page 7:
ContentsSection IForeword .........
Page 10 and 11:
ForewordForewordThis Special Report
Page 12 and 13:
Prefacein understanding and managin
Page 16 and 17:
Summary for PolicymakersA.ContextTh
Page 18 and 19:
Summary for PolicymakersFigure SPM.
Page 20 and 21:
Summary for Policymakerssettlements
Page 22 and 23:
Summary for PolicymakersC.Disaster
Page 24 and 25:
Summary for Policymakers20103146957
Page 26 and 27:
Summary for Policymakers50201053W.
Page 28 and 29:
Summary for PolicymakersOscillation
Page 30 and 31:
Summary for PolicymakersTable SPM.1
Page 32 and 33:
Summary for Policymakersimportance
Page 34 and 35:
Summary for Policymakers22
Page 37 and 38:
1Climate Change:New Dimensions inDi
Page 39 and 40:
Chapter 1Climate Change: New Dimens
Page 41 and 42:
Page 43 and 44:
Page 45 and 46:
Page 47 and 48:
Page 49 and 50:
Page 51 and 52:
Page 53 and 54:
Page 55 and 56:
Page 57 and 58:
Page 59 and 60:
Page 61 and 62:
Page 63 and 64:
Page 65 and 66:
Page 67 and 68:
Page 69 and 70:
Page 71 and 72:
Page 73 and 74:
Page 75 and 76:
Page 77 and 78:
2Determinantsof Risk:Exposure and V
Page 79 and 80:
Chapter 2Determinants of Risk: Expo
Page 81 and 82:
Page 83 and 84:
Page 85 and 86:
Page 87 and 88:
Page 89 and 90:
Page 91 and 92:
Page 93 and 94:
Page 95 and 96:
Page 97 and 98:
Page 99 and 100:
Page 101 and 102:
Page 103 and 104:
Page 105 and 106: Chapter 2Determinants of Risk: Expo
Page 121 and 122: 3Changesin Climate Extremesand thei
Page 123 and 124: Chapter 3Changes in Climate Extreme
Page 149 and 150: 137in annual extremes (20-year extr
Page 155: Chapter 3Changes in Climate Extreme
Page 207 and 208:
Chapter 3Changes in Climate Extreme
Page 209 and 210:
Page 211 and 212:
Page 213 and 214:
Page 215 and 216:
Page 217 and 218:
Page 219 and 220:
Page 221 and 222:
Page 223 and 224:
Page 225 and 226:
Page 227 and 228:
Page 229 and 230:
Page 231 and 232:
Page 233 and 234:
Page 235 and 236:
Page 237 and 238:
Page 239 and 240:
Page 241 and 242:
Page 243 and 244:
4Changesin Impactsof Climate Extrem
Page 245 and 246:
Chapter 4Changes in Impacts of Clim
Page 247 and 248:
Page 249 and 250:
Page 251 and 252:
Page 253 and 254:
Page 255 and 256:
Page 257 and 258:
Page 259 and 260:
Page 261 and 262:
Page 263 and 264:
Page 265 and 266:
Page 267 and 268:
Page 269 and 270:
Page 271 and 272:
Page 273 and 274:
Page 275 and 276:
Page 277 and 278:
Page 279 and 280:
Page 281 and 282:
Page 283 and 284:
Page 285 and 286:
Page 287 and 288:
Page 289 and 290:
Page 291 and 292:
Page 293 and 294:
Page 295 and 296:
Page 297 and 298:
Page 299 and 300:
Page 301 and 302:
Page 303 and 304:
5Managingthe Risksfrom Climate Extr
Page 305 and 306:
Chapter 5Managing the Risks from Cl
Page 307 and 308:
Page 309 and 310:
Page 311 and 312:
Page 313 and 314:
Page 315 and 316:
Page 317 and 318:
Page 319 and 320:
Page 321 and 322:
Page 323 and 324:
Page 325 and 326:
Page 327 and 328:
Page 329 and 330:
Page 331 and 332:
Page 333 and 334:
Page 335 and 336:
Page 337 and 338:
Page 339 and 340:
Page 341 and 342:
Page 343 and 344:
Page 345 and 346:
Page 347 and 348:
Page 349 and 350:
Page 351 and 352:
6National Systemsfor Managing the R
Page 353 and 354:
Chapter 6National Systems for Manag
Page 355 and 356:
Page 357 and 358:
Page 359 and 360:
Page 361 and 362:
Page 363 and 364:
Page 365 and 366:
Page 367 and 368:
Page 369 and 370:
Page 371 and 372:
Page 373 and 374:
Page 375 and 376:
Page 377 and 378:
Page 379 and 380:
Page 381 and 382:
Page 383 and 384:
Page 385 and 386:
Page 387 and 388:
Page 389 and 390:
Page 391 and 392:
Page 393 and 394:
Page 395 and 396:
Page 397 and 398:
Page 399 and 400:
Page 401 and 402:
Page 403 and 404:
Page 405 and 406:
7Managingthe Risks:International Le
Page 407 and 408:
Chapter 7Managing the Risks: Intern
Page 409 and 410:
Page 411 and 412:
Page 413 and 414:
Page 415 and 416:
Page 417 and 418:
Page 419 and 420:
Page 421 and 422:
Page 423 and 424:
Page 425 and 426:
Page 427 and 428:
Page 429 and 430:
Page 431 and 432:
Page 433 and 434:
Page 435 and 436:
Page 437 and 438:
Page 439 and 440:
Page 441 and 442:
Page 443 and 444:
Page 445 and 446:
Page 447 and 448:
Page 449 and 450:
8Towarda Sustainableand Resilient F
Page 451 and 452:
Chapter 8Toward a Sustainable and R
Page 453 and 454:
Page 455 and 456:
Page 457 and 458:
Page 459 and 460:
Page 461 and 462:
Page 463 and 464:
Page 465 and 466:
Page 467 and 468:
Page 469 and 470:
Page 471 and 472:
Page 473 and 474:
Page 475 and 476:
Page 477 and 478:
Page 479 and 480:
Page 481 and 482:
Page 483 and 484:
Page 485 and 486:
Page 487 and 488:
Page 489 and 490:
Page 491 and 492:
Page 493 and 494:
Page 495 and 496:
Page 497 and 498:
Page 499 and 500:
9 Case StudiesCoordinating Lead Aut
Page 501 and 502:
Chapter 9Case StudiesExecutive Summ
Page 503 and 504:
Chapter 9Case StudiesTable 9-1 | Ma
Page 505 and 506:
Chapter 9Case Studiesbecause heat-r
Page 507 and 508:
Chapter 9Case Studiesneed for other
Page 509 and 510:
Chapter 9Case StudiesAustralian coa
Page 511 and 512:
Chapter 9Case Studiesthat 1.3 milli
Page 513 and 514:
Chapter 9Case Studies• Iron dzud:
Page 515 and 516:
Chapter 9Case Studiesof impact. Bas
Page 517 and 518:
Chapter 9Case StudiesTropical cyclo
Page 519 and 520:
Chapter 9Case Studies9.2.6.5. Outco
Page 521 and 522:
Chapter 9Case Studieswith increased
Page 523 and 524:
Chapter 9Case StudiesThe developmen
Page 525 and 526:
Chapter 9Case StudiesSuch devastati
Page 527 and 528:
Chapter 9Case Studiesbuildings have
Page 529 and 530:
Chapter 9Case Studies• Wind defle
Page 531 and 532:
Chapter 9Case Studiesdeveloped, som
Page 533 and 534:
Chapter 9Case Studiesbeen establish
Page 535 and 536:
Chapter 9Case StudiesTable 9-3 | Ex
Page 537 and 538:
Chapter 9Case Studieswhile they pro
Page 539 and 540:
Chapter 9Case Studiesexperiential l
Page 541 and 542:
Chapter 9Case StudiesThe Philippine
Page 543 and 544:
Chapter 9Case StudiesBeg, N., J.C.
Page 545 and 546:
Chapter 9Case StudiesFlyvbjerg, B.,
Page 547 and 548:
Chapter 9Case StudiesJeuland, M. an
Page 549 and 550:
Chapter 9Case StudiesMétéo France
Page 551 and 552:
Chapter 9Case StudiesRepublic of So
Page 553 and 554:
Chapter 9Case StudiesUNESC, 2000: A
Page 555:
IV Annexes I to IV
Page 558 and 559:
Authors and Expert ReviewersAnnex I
Page 560 and 561:
Page 562 and 563:
Page 564 and 565:
Page 566 and 567:
Page 568 and 569:
Glossary of TermsAnnex IIAbrupt cli
Page 570 and 571:
Glossary of TermsAnnex IIor anthrop
Page 572 and 573:
Glossary of TermsAnnex IIFrozen gro
Page 574 and 575:
Glossary of TermsAnnex IIand time s
Page 576 and 577:
Glossary of TermsAnnex IImain track
Page 578 and 579:
AcronymsAnnex IIIAAO Antarctic Osci
Page 580 and 581:
AcronymsAnnex III568
Page 582 and 583:
List of Major IPCC ReportsAnnex IVC
Page 584 and 585:
List of Major IPCC ReportsAnnex IV5
Page 586 and 587:
IndexIndex | KeyTerms defined in th
Page 588 and 589:
IndexDemographic changes, 80, 234-2
Page 590 and 591:
Indexregional impacts, 259vulnerabi
Page 592 and 593:
IndexOcean acidification, 185, 261O
Page 594:
Indextipping points, 122, 351, 458-
show all

IPCC Report.pdf - Adam Curry

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?