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Fig. 3: Scatter plots showing the correlations between (a) GFS and GPCC (Africa, 1000-kmscale), (b) CMORPH and GPCC (Africa, 1000-km scale), (c) GFS and GPCC (monsoon, 1000-km scale), (d) CMORPH and GPCC (monsoon, 1000-km scale), (e) GFS and GPCC (SouthAmerica, 200-km scale), (f) CMORPH and GPCC (South America, 200-km scale), (g) GFS andGPCC (North America), and (h) CMORPH and GPCC (North America, 200-km) for monthlyaveraged precipitation.-338-
Fig. 4: Scatter plots showing the correlations between (a) GFS and GPCC (Mediterranean, 1000-km scale), (b) CMORPH and GPCC (Mediterranean, 1000-km scale), (c) GFS and GPCC (NorthAmerica, 1000-km scale), (d) CMORPH and GPCC (North America, 1000-km scale), (e) GFSand GPCC (Africa, 200-km scale), (f) CMORPH and GPCC (Africa, 200-km scale), (g) GFS andGPCC (Monsoon, 200-km scale), (h) CMORPH and GPCC (Monsoon, 200-km), GFS and GPCC(South America, 200-km scale), (h) CMORPH and GPCC (South America, 200-km) for monthlyaveraged precipitation.-339-
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World Meteorological OrganizationWW
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ForewordWeather disasters often ari
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CONFERENCE SCHEDULEThird WMO Intern
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Conference program for the third WM
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Conference program:A. High impact p
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B3. 13:45-15:40 Session Chair: Rich
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P. 19:15-20:30 19-20 Oct. 2010 Post
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H. Conference summaryConvener: Chun
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Session AHigh impact Precipitation
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1. IntroductionSynoptic and Mesosca
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and PS each accounting for about 20
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ain-producing storms (Schumacher an
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Houze, R. A., Jr., S. A. Rutledge,
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Convection over the Taunus Mountain
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in the southeast of the investigate
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Spatial and Temporal Variations of
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were normalized to sum 1 to give th
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during the continuous one day (Rx1d
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The Weather Research and Forecastin
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Convective rainfall in wet runs is
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On the Study of Tropical Cyclone Ra
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Fig.2 Severe tropical storm Bilis (
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Numerical simulation (Zhu H.Y, et a
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Influence of Typhoon Songda (2004)
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southeastern part of typhoon circul
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the thermal structure is asymmetric
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The estimation of TC quantitative p
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from 0000 UTC on 8 August 2009 to 0
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and 1.23:1 in 24h, indicates that t
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in the latter 24-h, on average, the
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4. Sensitivity experiment results1)
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ReferencesChen, L., and Y. Ding, 19
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of the documented intensity and tra
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Figure 1b shows the distribution of
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influence.In order to explain the v
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torrential rain days in 2009. The d
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over China mainland for the 32 typh
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Advances in Understanding the “Pe
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3. Contributions of the east-west o
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Fig. 3. Hovmoller diagram of the ra
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convective band over the Taiwan Str
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The mechanism analysis of cloud and
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The simulations were performed with
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different sub-regions to interpret
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An Idealized Numerical Study on the
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The Effect of ENSO on the Summer Mo
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Session BQuantitative Precipitation
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Observations of Precipitation Proce
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elevation angle. It grows and then
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Figure 8: Outflow (above) and inflo
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Figure 10: Model forecasts of vario
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ReferencesPaul Joe, Chris Doyle, Al
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produce the ‘predicted’ analysi
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asis. First, co-located daily CMORP
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used in this paper were obtained fr
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with thresholds of 0.1mm (including
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The Megha-Tropiques accumulated rai
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Figure 1 shows the flow chart of th
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Over the Ouémé site, the evolutio
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Starting from June 15 , 2 001, t he
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5. Year and Season-wise Comparison
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QPE and QPF of Japan Meteorological
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By multiply ing calibrated echo int
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4.3 ACCURACY OF VSRFCritical Succes
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Verification of Tropical Cyclones-R
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To co mpare t he ab ilities of 3B 4
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AllcasesLandfallTCsTable 3. TS, ETS
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The representation of the rain gaug
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3 Results16Percentage(%)14121086200
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403530Related Error(%)25201510504 C
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Recent Progresseson TC Precipitatio
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fields, particularly taking account
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form. The initial conditions of ens
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Comparative Study on QPE Methods of
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B3.2possible rain states that could
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B3.4Figure 2: Spatial temporal samp
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A Radar-based Technique for the Ide
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et al. (2007), the HEM obtained exa
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these calibration algorithms.7. Con
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CINRAD Warning Indexof Local Extrem
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Research of Rainfall Estimation usi
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Figure 1 has shown the relationship
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4. Summary and discussion(1) T he T
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Session CHydrologic prediction and
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Hydrological Perspective on QPE/QPF
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the river system in the basin. The
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(2) As input of the hydrological di
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satellite estimates) and the foreca
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NWP models’ Application in Flood
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Deltares’ Flood Early Warning Sys
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A further challenge for hydrologic
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2.2 Test areaHuaihe Basin locates i
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Fig. 4 The same as Fig.3, but at Wa
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Third WMO International Conference
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There is a unimodal pattern in the
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Number of days with 1mm and above95
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homogeneous (Fig. 1). Thi s area is
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a, without precipitation in future
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Session DVerification of Precipitat
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Intercomparison of verification met
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intensity f or pr e- and pos t-defo
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Figure 1: From Gilleland et al. (20
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New Model Evaluation Tools (MET) So
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During the HWT project, precipitati
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Figure 4: Example showing atmospher
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Performance Evaluation of the AREM
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0-24h and 24-48h, the improved mode
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Fig.4 24h accumulative precipitatio
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simple upscaling technique whereby
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(panel c) and 20mm/24h (panel d) fo
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A new field verification score base
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still overlapping the observed feat
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Case Description of forecast featur
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Quantitative Precipitation Forecast
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GFS60 and NAM60 at the lowest thres
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difference between the two models i
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Scale-related Issues involving veri
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of scores for the GFS at heavier ra
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Fig. 4. Comparison of probability o
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From these equations one can see th
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Figure 2. Verification scores as a
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Session EData assimilation for prec
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Progress in data assimilation for N
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Here, k is the number of ensemble m
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0200pressure (hPa)400600800spread a
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Impacts of multiple radar data assi
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High Resolution Radar Accumulation
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3. MethodThe non-hydrostatic versio
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Figure 5: Accumulation in the Waipa
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J(X ) Jb Jo Jc1 T 1T X X ) B ( X
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prediction, and so forth, to observ
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experiment, velocity assimilated ex
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Cycle Forecasting System in China.
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successfully forecast by AREM-RUC a
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Session FPrecipitation variability
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FRepresentation of Monsoon Systems
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4 ResultsFigure 2: Monsoon mean pre
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explained by higher sea surface tem
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Variability of Rainfall, Increasing
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(a)(b)Figure 1 : (a) Change of Temp
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According the analy sis of rainfall
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the rainfall v ariability will high
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Regional Impact of Climate Change i
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Figure 2. Map of the classified wea
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Table 3. The num ber of weather st
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such a mo del. Second, we ha ve o b
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Joint fuzzy an alysis o f SST , SAT
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Variability of Equatorial East Afri
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(d)2.5 4.0 5.5(c)-10 0 10(b)-10 0 5
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Figure 4: (a) The first spatial mod
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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
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Page 315 and 316: One advantage of ensemble forecasti
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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
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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
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Page 355 and 356: determine the origin of these diffe
Page 357: Fig. 2: The global distribution of
Page 361 and 362: Multiscale Spectral Structures of T
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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
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Page 405 and 406: This work was supported by the Rese
Page 407 and 408: 3. DataFor the investigation the we
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Flash flood forecasting by coupling
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gauges. Fig. 1 shows the event accu
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The floods were sim ulated with bot
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Comparison of calibration technique
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10.10.010.00110.10.010.0010 0.2 0.4
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24-h rainfall forecast. Nevertheles
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ANALYSIS FOR TURBULENCE AND WIND GU
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Research and Application of Typhoon
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[3] TIAN H, MA K Y,LIN Z S. Analysi
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What’s more, th e tw o curves als
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precipitation in southern areas of
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Chen Huai, Wang Yongbo, Shi N eng,
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An hourly updated convection-allowi
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GFS dataset or any other reason, th
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Downscaling precipitation for weath
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abFig.2. The 24h accumulated precip
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A Kalman Filter based QPF calibrati
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Scale Parameter10090807060504030rai
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It is clear that the values of scal
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THE IMPACT OF NORTH PACIFIC SUBTROP
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negative in the northern hemisphere
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Establishment and Verification of M
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Multi-model Ensemble QPF for Southe
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(4)andcan be estimated for all mode
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Table 4 The number of observations
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gauge coverage is definitely not sa
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It would be an attractive result if
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Analysis on a permanent elongate co
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PECS grow. The evolution of meso-sc
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3 rd Conference on QPE /QPF an
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QPF verification using object-orien
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measure the S and A components resp
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5. ConclusionsSeveral problems aris
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2.1 MethodologyIn the EOF analysis,
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calculated respectively, the compar
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IntroductionProbabilistic predictio
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Once the models are obtained, they
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REFERENCES- Charles Mutai: 2000, Di
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This paper selects the process of w
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(b1)cntl (b2)snd (b3)cmwFig.5the cl
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(2) There is no much difference in
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Analysis of Convective Precipitatio
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F(per/6min)30025020015010050F(per/6
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Research on the Relationship betwee
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Fig.1 The k-Z relationship for smal
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esearch on the correction for atten
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22224diction of the heavy precipita
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Study on Mechanism of an Extra Rain
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which promoted the shear line devel
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References[1] SUN Shu-Qing and ZHOU
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the main p oints in our estimation
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QC test to reject the bogus faulty
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-499-
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The Impact of Parameterization of C
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LinThompsonMilbrandt-YauMorrisonFig
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MOST (Grant No. GYHY20070 6036), th
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National Meteorological Center (NMC
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Fig. 4 Comparison of percentile are
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Impact of Different Boundary Layer
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(a)observed rainfall,(b)simulated r
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In te rms of ener getics, the hea v
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The Estimation of Rainstorm Forecas
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Fig. 2 TS Score of accumulated 24h
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Study on the 3D Structure of Typhoo
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abFig.1 (a) Total precipitation (mm
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satellite images at 12:00BST on 18
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