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Fig. 2. Equitable Threat Scores (ETS) for ensemble model runs initiated at 1200 UTC17 January in the HMT-West domain. Individual ensemble ARW and NNM coremembers are as shown in legend; black curve is for the ensemble mean; and browncurve is for the deterministic GFS forecast. Lead times are in hours. Verification wasperformed using Stage IV 6h analyzed precipitation. Shaded bars indicate arealfrequency of observed precipitation for each 6h period.Fig. 3. Time series of precipitation,winds, and other quantities as shownfor the period 0000 UTC 19 January to1200 UTC 20 January 2010. StationsBBY and CZC are located on thePacific coastline and close by in thecoastal mountain range, respectively,about 50 km N. of San Francisco.Plots are generated by the PhysicalSciences and the Global SystemsDivisions of the Earth SystemResearch Laboratory and displayed athttp://www.esrl.noaa.gov/psd/data/obs/.-220-
Fig. 4. Comparison of probability of detection yes (PODY) scores for January 2010 inthe full HMT-West domain as verified using 24h gage totals (top) and 6h Stage IVestimates (bottom). Designation of individual ensemble members coded by color andline type is as in Fig. 2.-221-
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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
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 and 208: Figure 1: From Gilleland et al. (20
Page 209 and 210: New Model Evaluation Tools (MET) So
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: of scores for the GFS at heavier ra
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
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Page 289 and 290: 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
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Ongoing developments on Limited Are
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een done but much i s s till needed
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Hacker, J., S.-Y. Ha, C. Sn yder, J
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the initial field as possible based
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One advantage of ensemble forecasti
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southern hemisphere through the equ
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model results predict rate moves in
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Term growth forecast s, th e error
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ponent of the Brier score is reduce
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in the combined field (Fig.3c). For
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Probabilistic QPF from a realtime m
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to help assessing impacts from diff
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abFigure 3.ETS scores of the 3-h ac
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Flow chart of multi-model rainfall
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GermanJapan NCEP Ens Forecaster(a)E
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methodology. However, the operation
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Research and Operation on Quantitat
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A numerical study of aerosol effect
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maximum cloud water mixing ratio in
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an increase in concentration of clo
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perturbations. Blending combines th
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Figure 2. Comparison of CRPSSof 12h
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Global QPF and QPE: Where do we hav
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countries, the 1 o 1 o GPCC rainfa
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determine the origin of these diffe
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Fig. 2: The global distribution of
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Fig. 4: Scatter plots showing the c
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Multiscale Spectral Structures of T
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mountain ridges and are anticipated
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triggered convection conditions pre
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Rainfall forecasts from the Met Off
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Figure 2: (a) Domain-averaged rainf
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4. Summary and discussionWe have de
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G3itself it is incapable of providi
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G3Precipitation for February 2nd, 2
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Can Multi-model ensemble forecasts
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amounts over thresholds, 1, 3, 5, 1
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In addition to combination of all t
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-Carry out the verification for oth
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How sensitive are probabilistic pre
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CMORPH (Climate Prediction Center M
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Among the alternatives that have be
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Based on the daily mean temperature
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the individual models and the EMN t
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The Development of Ensemble Predict
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70(a)70(b)60AREM-SY AREM-CTL AREM-E
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Poster Presentations-379-
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Coupling Ensemble weather predictio
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sub-catchments to be used as inputs
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This work was supported by the Rese
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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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