Extended Abstract

More documents

Recommendations

Info

Verification of Quantitative Precipitation Forecasts with In Situ Measurementsfor Flood Forecasting and Warning in JakartaKadarsahMeteorological Climatological and Geophysical AgencyJl.Angkasa I No.2 Kemayoran, Jakarta 10720Telp.(021)4246321 ext 2322, 2425, Fax.(021)65866238<strong>Abstract</strong>Keyword: Quantitative Precipitation Forecasts, flood forecasting, ROC CurveAlmost every rainy season in Indonesia, Jakarta experienced a flood disaster. The mostsignificant reason of the disaster is the high rate of rain, since the rainy season in Indonesiastarts in December until March. The rain intensity reached its peak in December-January-February, with the greatest intensity towards the end of the month. Eventually, water flowinginto Jakarta overflows some of the city's flood control systems and causes devastation inthese areas. Use of WRF model for process Quantitative Precipitation Forecasts have beenused, the results were verified by using ROC curves by comparing the results of the In Situmeasurements. Furthermore, the prediction model was built and flood warnings by using theresults from radar, satellite and rain gauge as a source of observational data-188-
New Model Evaluation Tools (MET) Software Capabilitiesfor QPF VerificationTressa L. FOWLER, Tara JENSEN, Edward I. TOLLERUD, John HALLEY GOTWAY,Paul OLDENBURG, and Randy BULLOCKNational Center for Atmospheric Research (NCAR, Boulder, CO USA)tressa@ucar.edu1. IntroductionVerification plays a crucial role in improvement of precipitation forecasts The Model EvaluationTools (MET) software was designed to provide the numerical weather prediction community withquality software incorporating the latest advances in forecast verification, including methods forverifying quantitative precipitation forecasts (QPF).The recent addition of probabilistic and ensemble verification capabilities to the MET softwarehas led to innovations demonstrated in the verification activities of two QPF projects in the UnitedStates. The Hydrometeorology Testbed (HMT) conducted an experiment examining heavy, prolongedwinter precipitation. Prediction of convective precipitation was one focus of the Hazardous WeatherTestbed (HWT) 2010 Spring Experiment. Examples from these projects demonstrating MET’s spatial,object-based verification of ensemble relative frequency (e.g. probability) and ensemble mean will bepresented and compared to traditional methods. In addition to verifying QPF, atmospheric river andradar reflectivity fields were evaluated using MET’s object based spatial verification. These examplesillustrate the enhanced diagnostic information available from spatial verification versus traditionalmetrics.2. MET SoftwareThe MET verification software is designed to provide the numerical weather predictioncommunity with a consistent means to verify model forecasts. Traditional verification measures forprecipitation are available in MET. For precipitation, traditional verification often utilizes skill scores,such as the Threat Score, computed for cases that exceed some minimum precipitation amount.Unfortunately, for this type of verification, a shift in time or space of the forecast precipitation area canlead to the so-called “double penalty”, where the forecast is a false alarm and observation is missedevent. Ensemble and probability forecasts contain more information than standard deterministicforecasts. Thus, though traditional methods and statistics can be applied, additional information is abenefit to the user.Recent additions to the MET software have enhanced the precipitation verification capabilitiesto address these issues. Ensemble means and probability values can be produced from a set of forecastsby a new MET preprocessing tool. Probabilistic forecasts are verified using traditional statistics such asBrier score, while ensemble mean and spread can be used to calculate the continuous ranked probabilityscore (CRPS). Additionally, both types of forecasts can be used in advanced spatial verificationtechniques.MET’s object based spatial verification software, MODE (Method for Object-based DiagnosticEvaluation; Davis et al, 2009), can use ensemble means or ensemble probabilities to define forecastobjects then compare these to objects identified in gridded observation fields. This software wasdeveloped on precipitation fields. However, it has also been successfully applied to other spatiallycoherent fields, such as radar echo top, atmospheric rivers, cloud percent, and winds.Although the software was created to work with the weather and research forecasting (WRF)model, MET can be used with any model in GRIB format. Users have reported success using MET with-189-
Page 1:
World Meteorological OrganizationWW
Page 5 and 6:
ForewordWeather disasters often ari
Page 7 and 8:
CONFERENCE SCHEDULEThird WMO Intern
Page 9 and 10:
Conference program for the third WM
Page 11 and 12:
Conference program:A. High impact p
Page 13:
B3. 13:45-15:40 Session Chair: Rich
Page 17 and 18:
P. 19:15-20:30 19-20 Oct. 2010 Post
Page 19 and 20:
H. Conference summaryConvener: Chun
Page 21 and 22:
Session AHigh impact Precipitation
Page 23 and 24:
1. IntroductionSynoptic and Mesosca
Page 25 and 26:
and PS each accounting for about 20
Page 27 and 28:
ain-producing storms (Schumacher an
Page 29 and 30:
Houze, R. A., Jr., S. A. Rutledge,
Page 31 and 32:
Convection over the Taunus Mountain
Page 33 and 34:
in the southeast of the investigate
Page 35 and 36:
Spatial and Temporal Variations of
Page 37 and 38:
were normalized to sum 1 to give th
Page 39 and 40:
during the continuous one day (Rx1d
Page 41 and 42:
The Weather Research and Forecastin
Page 43 and 44:
Convective rainfall in wet runs is
Page 45 and 46:
On the Study of Tropical Cyclone Ra
Page 47 and 48:
Fig.2 Severe tropical storm Bilis (
Page 49 and 50:
Numerical simulation (Zhu H.Y, et a
Page 51 and 52:
Influence of Typhoon Songda (2004)
Page 53 and 54:
southeastern part of typhoon circul
Page 55 and 56:
the thermal structure is asymmetric
Page 57 and 58:
The estimation of TC quantitative p
Page 59 and 60:
from 0000 UTC on 8 August 2009 to 0
Page 61 and 62:
and 1.23:1 in 24h, indicates that t
Page 63 and 64:
in the latter 24-h, on average, the
Page 65 and 66:
4. Sensitivity experiment results1)
Page 67 and 68:
ReferencesChen, L., and Y. Ding, 19
Page 69 and 70:
of the documented intensity and tra
Page 71 and 72:
Figure 1b shows the distribution of
Page 73 and 74:
influence.In order to explain the v
Page 75 and 76:
torrential rain days in 2009. The d
Page 77 and 78:
over China mainland for the 32 typh
Page 79 and 80:
Advances in Understanding the “Pe
Page 81 and 82:
3. Contributions of the east-west o
Page 83 and 84:
Fig. 3. Hovmoller diagram of the ra
Page 85 and 86:
convective band over the Taiwan Str
Page 87 and 88:
The mechanism analysis of cloud and
Page 89 and 90:
The simulations were performed with
Page 91 and 92:
different sub-regions to interpret
Page 93 and 94:
An Idealized Numerical Study on the
Page 95 and 96:
The Effect of ENSO on the Summer Mo
Page 97 and 98:
Session BQuantitative Precipitation
Page 99 and 100:
Observations of Precipitation Proce
Page 101 and 102:
elevation angle. It grows and then
Page 103 and 104:
Figure 8: Outflow (above) and inflo
Page 105 and 106:
Figure 10: Model forecasts of vario
Page 107 and 108:
ReferencesPaul Joe, Chris Doyle, Al
Page 109 and 110:
produce the ‘predicted’ analysi
Page 111 and 112:
asis. First, co-located daily CMORP
Page 113 and 114:
used in this paper were obtained fr
Page 115 and 116:
with thresholds of 0.1mm (including
Page 117 and 118:
The Megha-Tropiques accumulated rai
Page 119 and 120:
Figure 1 shows the flow chart of th
Page 121 and 122:
Over the Ouémé site, the evolutio
Page 123 and 124:
Starting from June 15 , 2 001, t he
Page 125 and 126:
5. Year and Season-wise Comparison
Page 127 and 128:
QPE and QPF of Japan Meteorological
Page 129 and 130:
By multiply ing calibrated echo int
Page 131 and 132:
4.3 ACCURACY OF VSRFCritical Succes
Page 133 and 134:
Verification of Tropical Cyclones-R
Page 135 and 136:
To co mpare t he ab ilities of 3B 4
Page 137 and 138:
AllcasesLandfallTCsTable 3. TS, ETS
Page 139 and 140:
The representation of the rain gaug
Page 141 and 142:
3 Results16Percentage(%)14121086200
Page 143 and 144:
403530Related Error(%)25201510504 C
Page 145 and 146:
Recent Progresseson TC Precipitatio
Page 147 and 148:
fields, particularly taking account
Page 149 and 150:
form. The initial conditions of ens
Page 151 and 152:
Comparative Study on QPE Methods of
Page 153 and 154:
B3.2possible rain states that could
Page 155 and 156:
B3.4Figure 2: Spatial temporal samp
Page 157 and 158: A Radar-based Technique for the Ide
Page 159 and 160: et al. (2007), the HEM obtained exa
Page 161 and 162: these calibration algorithms.7. Con
Page 163 and 164: CINRAD Warning Indexof Local Extrem
Page 165 and 166: Research of Rainfall Estimation usi
Page 167 and 168: Figure 1 has shown the relationship
Page 169 and 170: 4. Summary and discussion(1) T he T
Page 171 and 172: Session CHydrologic prediction and
Page 173 and 174: Hydrological Perspective on QPE/QPF
Page 175 and 176: the river system in the basin. The
Page 177 and 178: (2) As input of the hydrological di
Page 179 and 180: satellite estimates) and the foreca
Page 181 and 182: NWP models’ Application in Flood
Page 183 and 184: Deltares’ Flood Early Warning Sys
Page 185 and 186: A further challenge for hydrologic
Page 187 and 188: 2.2 Test areaHuaihe Basin locates i
Page 189 and 190: Fig. 4 The same as Fig.3, but at Wa
Page 191 and 192: Third WMO International Conference
Page 193 and 194: There is a unimodal pattern in the
Page 195 and 196: Number of days with 1mm and above95
Page 197 and 198: homogeneous (Fig. 1). Thi s area is
Page 199 and 200: a, without precipitation in future
Page 201 and 202: Session DVerification of Precipitat
Page 203 and 204: Intercomparison of verification met
Page 205 and 206: intensity f or pr e- and pos t-defo
Page 207: Figure 1: From Gilleland et al. (20
Page 211 and 212: During the HWT project, precipitati
Page 213 and 214: Figure 4: Example showing atmospher
Page 215 and 216: Performance Evaluation of the AREM
Page 217 and 218: 0-24h and 24-48h, the improved mode
Page 219 and 220: Fig.4 24h accumulative precipitatio
Page 221 and 222: simple upscaling technique whereby
Page 223 and 224: (panel c) and 20mm/24h (panel d) fo
Page 225 and 226: A new field verification score base
Page 227 and 228: still overlapping the observed feat
Page 229 and 230: Case Description of forecast featur
Page 231 and 232: Quantitative Precipitation Forecast
Page 233 and 234: GFS60 and NAM60 at the lowest thres
Page 235 and 236: difference between the two models i
Page 237 and 238: Scale-related Issues involving veri
Page 239 and 240: of scores for the GFS at heavier ra
Page 241 and 242: Fig. 4. Comparison of probability o
Page 243 and 244: From these equations one can see th
Page 245 and 246: Figure 2. Verification scores as a
Page 247 and 248: Session EData assimilation for prec
Page 249 and 250: Progress in data assimilation for N
Page 251 and 252: Here, k is the number of ensemble m
Page 253 and 254: 0200pressure (hPa)400600800spread a
Page 255 and 256: Impacts of multiple radar data assi
Page 257 and 258: High Resolution Radar Accumulation
Page 259 and 260:
3. MethodThe non-hydrostatic versio
Page 261 and 262:
Figure 5: Accumulation in the Waipa
Page 263 and 264:
J(X ) Jb Jo Jc1 T 1T X X ) B ( X
Page 265 and 266:
prediction, and so forth, to observ
Page 267 and 268:
experiment, velocity assimilated ex
Page 269 and 270:
Cycle Forecasting System in China.
Page 271 and 272:
successfully forecast by AREM-RUC a
Page 273 and 274:
Session FPrecipitation variability
Page 275 and 276:
FRepresentation of Monsoon Systems
Page 277 and 278:
4 ResultsFigure 2: Monsoon mean pre
Page 279 and 280:
explained by higher sea surface tem
Page 281 and 282:
Variability of Rainfall, Increasing
Page 283 and 284:
(a)(b)Figure 1 : (a) Change of Temp
Page 285 and 286:
According the analy sis of rainfall
Page 287 and 288:
the rainfall v ariability will high
Page 289 and 290:
Regional Impact of Climate Change i
Page 291 and 292:
Figure 2. Map of the classified wea
Page 293 and 294:
Table 3. The num ber of weather st
Page 295 and 296:
such a mo del. Second, we ha ve o b
Page 297 and 298:
Joint fuzzy an alysis o f SST , SAT
Page 299 and 300:
Variability of Equatorial East Afri
Page 301 and 302:
(d)2.5 4.0 5.5(c)-10 0 10(b)-10 0 5
Page 303 and 304:
Figure 4: (a) The first spatial mod
Page 305 and 306:
Session GQuantitative Precipitation
Page 307 and 308:
Ongoing developments on Limited Are
Page 309 and 310:
een done but much i s s till needed
Page 311 and 312:
Hacker, J., S.-Y. Ha, C. Sn yder, J
Page 313 and 314:
the initial field as possible based
Page 315 and 316:
One advantage of ensemble forecasti
Page 317 and 318:
southern hemisphere through the equ
Page 319 and 320:
model results predict rate moves in
Page 321 and 322:
Term growth forecast s, th e error
Page 323 and 324:
ponent of the Brier score is reduce
Page 325 and 326:
in the combined field (Fig.3c). For
Page 327 and 328:
Probabilistic QPF from a realtime m
Page 329 and 330:
to help assessing impacts from diff
Page 331 and 332:
abFigure 3.ETS scores of the 3-h ac
Page 333 and 334:
Flow chart of multi-model rainfall
Page 335 and 336:
GermanJapan NCEP Ens Forecaster(a)E
Page 337 and 338:
methodology. However, the operation
Page 339 and 340:
Research and Operation on Quantitat
Page 341 and 342:
A numerical study of aerosol effect
Page 343 and 344:
maximum cloud water mixing ratio in
Page 345 and 346:
an increase in concentration of clo
Page 347 and 348:
perturbations. Blending combines th
Page 349 and 350:
Figure 2. Comparison of CRPSSof 12h
Page 351 and 352:
Global QPF and QPE: Where do we hav
Page 353 and 354:
countries, the 1 o 1 o GPCC rainfa
Page 355 and 356:
determine the origin of these diffe
Page 357 and 358:
Fig. 2: The global distribution of
Page 359 and 360:
Fig. 4: Scatter plots showing the c
Page 361 and 362:
Multiscale Spectral Structures of T
Page 363 and 364:
mountain ridges and are anticipated
Page 365 and 366:
triggered convection conditions pre
Page 367 and 368:
Rainfall forecasts from the Met Off
Page 369 and 370:
Figure 2: (a) Domain-averaged rainf
Page 371 and 372:
4. Summary and discussionWe have de
Page 373 and 374:
G3itself it is incapable of providi
Page 375 and 376:
G3Precipitation for February 2nd, 2
Page 377 and 378:
Can Multi-model ensemble forecasts
Page 379 and 380:
amounts over thresholds, 1, 3, 5, 1
Page 381 and 382:
In addition to combination of all t
Page 383 and 384:
-Carry out the verification for oth
Page 385 and 386:
How sensitive are probabilistic pre
Page 387 and 388:
CMORPH (Climate Prediction Center M
Page 389 and 390:
Among the alternatives that have be
Page 391 and 392:
Based on the daily mean temperature
Page 393 and 394:
the individual models and the EMN t
Page 395 and 396:
The Development of Ensemble Predict
Page 397 and 398:
70(a)70(b)60AREM-SY AREM-CTL AREM-E
Page 399 and 400:
Poster Presentations-379-
Page 401 and 402:
Coupling Ensemble weather predictio
Page 403 and 404:
sub-catchments to be used as inputs
Page 405 and 406:
This work was supported by the Rese
Page 407 and 408:
3. DataFor the investigation the we
Page 409 and 410:
Flash flood forecasting by coupling
Page 411 and 412:
gauges. Fig. 1 shows the event accu
Page 413 and 414:
The floods were sim ulated with bot
Page 415 and 416:
Comparison of calibration technique
Page 417 and 418:
10.10.010.00110.10.010.0010 0.2 0.4
Page 419 and 420:
24-h rainfall forecast. Nevertheles
Page 421 and 422:
ANALYSIS FOR TURBULENCE AND WIND GU
Page 423 and 424:
Research and Application of Typhoon
Page 425 and 426:
[3] TIAN H, MA K Y,LIN Z S. Analysi
Page 427 and 428:
What’s more, th e tw o curves als
Page 429 and 430:
precipitation in southern areas of
Page 431 and 432:
Chen Huai, Wang Yongbo, Shi N eng,
Page 433 and 434:
An hourly updated convection-allowi
Page 435 and 436:
GFS dataset or any other reason, th
Page 437 and 438:
Downscaling precipitation for weath
Page 439 and 440:
abFig.2. The 24h accumulated precip
Page 441 and 442:
A Kalman Filter based QPF calibrati
Page 443 and 444:
Scale Parameter10090807060504030rai
Page 445 and 446:
It is clear that the values of scal
Page 447 and 448:
THE IMPACT OF NORTH PACIFIC SUBTROP
Page 449 and 450:
negative in the northern hemisphere
Page 451 and 452:
Establishment and Verification of M
Page 453 and 454:
Multi-model Ensemble QPF for Southe
Page 455 and 456:
(4)andcan be estimated for all mode
Page 457 and 458:
Table 4 The number of observations
Page 459 and 460:
gauge coverage is definitely not sa
Page 461 and 462:
It would be an attractive result if
Page 463 and 464:
Analysis on a permanent elongate co
Page 465 and 466:
PECS grow. The evolution of meso-sc
Page 467 and 468:
3 rd Conference on QPE /QPF an
Page 469 and 470:
Page 471 and 472:
Page 473 and 474:
Page 475 and 476:
QPF verification using object-orien
Page 477 and 478:
measure the S and A components resp
Page 479 and 480:
5. ConclusionsSeveral problems aris
Page 481 and 482:
2.1 MethodologyIn the EOF analysis,
Page 483 and 484:
calculated respectively, the compar
Page 485 and 486:
IntroductionProbabilistic predictio
Page 487 and 488:
Once the models are obtained, they
Page 489 and 490:
REFERENCES- Charles Mutai: 2000, Di
Page 491 and 492:
This paper selects the process of w
Page 493 and 494:
(b1)cntl (b2)snd (b3)cmwFig.5the cl
Page 495 and 496:
(2) There is no much difference in
Page 497 and 498:
Analysis of Convective Precipitatio
Page 499 and 500:
F(per/6min)30025020015010050F(per/6
Page 501 and 502:
Research on the Relationship betwee
Page 503 and 504:
Fig.1 The k-Z relationship for smal
Page 505 and 506:
esearch on the correction for atten
Page 507 and 508:
22224diction of the heavy precipita
Page 509 and 510:
Study on Mechanism of an Extra Rain
Page 511 and 512:
which promoted the shear line devel
Page 513 and 514:
References[1] SUN Shu-Qing and ZHOU
Page 515 and 516:
the main p oints in our estimation
Page 517 and 518:
QC test to reject the bogus faulty
Page 519 and 520:
-499-
Page 521 and 522:
The Impact of Parameterization of C
Page 523 and 524:
LinThompsonMilbrandt-YauMorrisonFig
Page 525 and 526:
MOST (Grant No. GYHY20070 6036), th
Page 527 and 528:
National Meteorological Center (NMC
Page 529 and 530:
Fig. 4 Comparison of percentile are
Page 531 and 532:
Impact of Different Boundary Layer
Page 533 and 534:
(a)observed rainfall,(b)simulated r
Page 535 and 536:
In te rms of ener getics, the hea v
Page 537 and 538:
The Estimation of Rainstorm Forecas
Page 539 and 540:
Fig. 2 TS Score of accumulated 24h
Page 541 and 542:
Study on the 3D Structure of Typhoo
Page 543 and 544:
abFig.1 (a) Total precipitation (mm
Page 545 and 546:
satellite images at 12:00BST on 18
show all

Extended Abstract

Create successful ePaper yourself

Delete template?

Save as template?