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2025, 11, v.56 1-20
台风降水的WRF模拟:以福建省杜苏芮台风为例(英文)
基金项目(Foundation): National Natural Science Foundation of China (42271030); Fujian Provincial Funds for Distinguished Young Scientists (2022J06018); Natural Science Foundation of Fujian Province (2023J011334); “Young Eagle Plan” Top Talents of Fujian Province~~
邮箱(Email): jiewen.you@hotmail.com;
DOI: 10.13928/j.cnki.wrahe.2025.11.001
摘要:

【目的】基于WRF模式模拟并评估超强台风杜苏芮在福建省造成的降水事件,为中国东南沿海地区的台风降水模拟和预报提供参考依据。【方法】基于新一代中尺度数值天气预报模式WRF V4.3(The Weather Research and Forecasting Model)模拟了2023年杜苏芮台风在福建省造成的降水事件,并利用86个气象站的逐小时降水观测记录,使用相关系数R、均方根误差RMSE、平均绝对误差M AE、公平威胁评分ETS、命中率POD和误报率FAR等6个指标评估WRF模拟台风降水的性能。【结果】结果表明:(1)WRF模式有效地捕捉了杜苏芮台风期间降水的时空演变特征,2023年7月27日至29日期间降水强度呈现逐步增加的趋势,最大降水量集中在福建省北部和东部沿海区域。(2)R、 RMSE和MAE指标的结果存在差异,最大误差出现在莆田市,福建西南部的误差较小。6个指标的评估结果表明,相较于小时、三小时、六小时和十二小时降水,WRF模型对日降水的模拟表现最好。(3)WRF模式通过R95p指数能够捕捉到极端降水的总体空间分布,但在某些沿海区域高估了极端降水的强度。(4)尽管WRF模式能够正确识别出福建沿海地区是受灾最严重的区域,但未能精确模拟出降水空间分布和强度,模拟的降水中心与观测中心存在一定偏差。【结论】尽管WRF模式的模拟结果低估了逐小时降水量,但它捕捉到了杜苏芮台风期间福建省降水的时间演变和空间格局。WRF模式基本再现了福建省中部的暴雨中心,日降水总量峰值高达350 mm,凸显了杜苏芮台风引发的极端降水的严重性。

Abstract:

[Objective]Precipitation events caused by Super Typhoon Doksuri in Fujian Province were simulated and evaluated based on the WRF model to provide a reference for typhoon precipitation simulation and forecasting in southeast coastal areas of China. [Methods]The next-generation mesoscale numerical weather prediction model WRF V4. 3(The Weather Research and Forecasting Model) was used to simulate the precipitation caused by Typhoon Doksuri in Fujian Province in 2023. Observations from 86 meteorological stations with hourly rainfall records were used to evaluate the model's performance. Six evaluation indices were used, including the correlation coefficient(R), root mean square error(RMSE), mean absolute error(MAE), equitable threat score(ETS), probability of detection(POD), and false alarm ratio(FAR). [Results](1) The temporal and spatial evolution of precipitation during Typhoon Doksuri was effectively captured by the WRF model. Precipitation intensity increased gradually from July 27 to 29, 2023, with the heaviest rainfall concentrated in the northern and eastern coastal areas of Fujian Province.(2) Significant differences in model performance were observed in terms of R, RMSE, and MAE. The largest errors occurred in Putian City, while smaller errors were found in southwestern Fujian Province. The evaluation result of all six indices showed that the WRF model performed best in simulating daily precipitation compared to hourly, three-hourly, six-hourly, and twelve-hourly precipitation.(3) The R95p index indicated that the WRF model successfully captured the overall spatial distribution of extreme precipitation. However, extreme precipitation intensity was overestimated in certain coastal areas.(4) Despite accurately identifying the coastal regions of Fujian as being most affected, the WRF model failed to accurately simulate the spatial distribution and intensity of precipitation. The simulated precipitation centers showed discrepancies when compared with the observed centers. [Conclusion]Although the WRF model underestimated hourly precipitation, it successfully captured the temporal evolution and spatial distribution of rainfall caused by Typhoon Doksuri in Fujian Province. It reproduced the heavy rainfall centers in central Fujian Province, with daily precipitation peaks reaching up to 350 mm. This highlighted the severity of extreme rainfall caused by Typhoon Doksuri.

参考文献

[1]PANDEY R S,LIOU Y A.Decadal behaviors of tropical storm tracks in the North West Pacific Ocean[J].Atmospheric Research,2020,246:105143.

[2]QIN X C,WU Y L,LIN T S,et al.Urban flood dynamic risk assessment based on typhoon rainfall process:a case study of Typhoon“Lupit”(2109) in Fuzhou,China[J].Remote Sensing,2023,15(12):3116.

[3]YANG X L,QIN X C,ZHOU X,et al.Assessment of disaster mitigation capability oriented to typhoon disaster chains:A case study of Fujian Province,China[J].Ecological Indicators,2024,167:112621.

[4]PENG Z,YUNXIA Z,YANG W,et al.Analysis of temporal-spatial patterns and impact factors of typhoon disaster losses in China from1978 to 2020[J].Tropical Geography,2024,44(6):1047-1063.

[5]HU L,WEN T,SHAO Y,et al.Economic impacts of tropical cyclone-induced multiple hazards in China[J].Earth’s Future,2023,11(9):e2023EF003622.

[6]ZHU L Y,QUIRING S M.Exposure to precipitation from tropical cyclones has increased over the continental United States from 1948 to2019[J].Communications Earth&Environment,2022,3(1):312.

[7]YIN S Y,LIN X H,YANG S N.Characteristics of rainstorm in Fujian induced by typhoon passing through Taiwan Island[J].Tropical Cyclone Research and Review,2022,11(1):50-59.

[8]QIU W Y,REN F M,WU L G,et al.Characteristics of tropical cyclone extreme precipitation and its preliminary causes in Southeast China[J].Meteorology and Atmospheric Physics,2019,131(3):613-626.

[9]GUO R,YU R L,YANG M Q,et al.Analysis of characteristics and evaluation of forecast accuracy for Super Typhoon Doksuri(2023)[J].Tropical Cyclone Research and Review,2024,13(3):219-229.

[10]ZHOU S H,LI J F,ZHANG J C,et al.Exploring Bayesian network model with noise filtering for rainfall-induced landslide susceptibility assessment in Fujian,China[J].Frontiers in Earth Science,2024,12:1444882.

[11]XIONG J N,PANG Q,FAN C K,et al.Spatiotemporal characteristics and driving force analysis of flash floods in Fujian Province[J].ISPRS International Journal of Geo-Information,2020,9(2):133.

[12]THORNTON J M,PEPIN N,SHAHGEDANOVA M,et al.Coverage of in situ climatological observations in the world’s mountains[J].Frontiers in Climate,2022,4:814181.

[13]YOU J W,WANG S,ZHANG B E.Spatially seamless and temporally continuous assessment on compound flood risk in Hong Kong[J].Journal of Hydrology,2024,645:132217.

[14]XIANG L,XIANG J,GUAN J P,et al.Spatiotemporal forecasting model based on hybrid convolution for local weather prediction postprocessing[J].Frontiers in Earth Science,2022,10:978942.

[15]TIAN J Y,LIU R H,DING L Q,et al.Evaluation of the WRFphysical parameterisations for typhoon rainstorm simulation in southeast coast of China[J].Atmospheric Research,2021,247:105130.

[16]DELFINO R J,BAGTASA G,HODGES K,et al.Sensitivity of simulating Typhoon Haiyan(2013) using WRF:The role of cumulus convection,surface flux parameterizations,spectral nudging,and initial and boundary conditions[J].Natural Hazards and Earth System Sciences,2022,22(10):3285-3307.

[17]DENG C,CHI Y X,HUANG Y S,et al.Sensitivity of WRF multiple parameterization schemes to extreme precipitation event over the Poyang Lake Basin of China[J].Frontiers in Environmental Science,2023,10:1102864.

[18]GAO L,WEI J H,LEI X Y,et al.Simulation of an extreme precipitation event using ensemble-based WRF Model in the Southeastern Coastal Region of China[J].Atmosphere,2022,13(2):194.

[19]SHI X M,WANG Y Y.Impacts of cumulus convection and turbulence parameterizations on the convection-permitting simulation of typhoon precipitation[J].Monthly Weather Review,2022,150(11):2977-2997.

[20]DI Z H,DUAN Q Y,SHEN C W,et al.Improving WRF typhoon precipitation and Intensity simulation using a surrogate-based automatic parameter optimization method[J].Atmosphere,2020,11(1):89.

[21]ZHANG Y C,DENG C,XU W L,et al.Long-term variability of extreme precipitation with WRF model at a complex terrain River Basin[J].Scientific Reports,2025,15(1):156.

[22]YANG Q Y,YU Z B,WEI J H,et al.Performance of the WRFmodel in simulating intense precipitation events over the Hanjiang River Basin,China-A multi-physics ensemble approach[J].Atmospheric Research,2021,248:105206.

[23]CHEN Y X,CHAN A,OOI C G,et al.Assessments of the WRFmodel in simulating 2021 extreme rainfall episode in Malaysia[J].Air Quality,Atmosphere&Health,2024,17:257-281.

[24]DAI D Q,CHEN L,MA Z G,et al.Evaluation of the WRF physics ensemble using a multivariable integrated evaluation approach over the Haihe river basin in northern China[J].Climate Dynamics,2021,57(1-2):557-575.

[25]MERINO A,GARCíA-ORTEGA E,NAVARRO A,et al.WRFhourly evaluation for extreme precipitation events[J].Atmospheric Research,2022,274:106215.

[26]SU Z Z,MA Y Q,JIA L,et al.Application of the improved dynamical-Statistical-Analog ensemble forecast model for landfalling typhoon precipitation in Fujian Province[J].Frontiers in Earth Science,2023,10:1018851.

[27]WANG Q,ZHAO D J,DUAN Y H,et al.Observational fine-scale evolutionary characteristics of concentric eyewall Typhoon Doksuri(2023)[J].Atmospheric Research,2024,310:107630.

[28]VU D H,HUANG C Y,NGUYEN T C.Numerical investigation of track and intensity evolution of Typhoon Doksuri(2023)[J].Atmosphere,2024,15(9):1105.

[29]LIN S N,ZHANG Y C,GUAN X J,et al.Sensitivity study of WRFparameterization schemes and initial fields on rainstorm simulation in Minjiang River Basin[J].Pearl River,2023,44(10):35-46.

[30]PAN J S,TENG D G,ZHANG F Q,et al.Dynamics of local extreme rainfall of super Typhoon Soudelor(2015) in East China[J].Science China Earth Sciences,2018,61(5):572-594.

[31]ZHOU Y S,WU T Y.Composite analysis of precipitation intensity and distribution characteristics of western track landfall typhoons over China under strong and weak monsoon conditions[J].Atmospheric Research,2019,225:131-143.

[32]ZENG Z,XU J J,YE G L,et al.The influence of different intensity of monsoon on typhoon precipitation:A comparative study of typhoons Soudelor and Maria[J].Frontiers in Earth Science,2023,11:1251711.

[33]POTTY J,OO S M,RAJU P V S,et al.Performance of nested WRFmodel in typhoon simulations over West Pacific and South China Sea[J].Natural Hazards,2012,63(3):1451-1470.

[34]ZHANG Y,WU Z H,ZHANG L F,et al.A comparison of spectral bin microphysics versus bulk parameterization in forecasting Typhoon In-Fa(2021) before,during,and after its landfall[J].Remote Sensing,2022,14(9):2169.

[35]SHIRAI T,ENOMOTO Y,WATANABE M,et al.Sensitivity analysis of the physics options in the Weather Research and Forecasting model for typhoon forecasting in Japan and its impacts on storm surge simulations[J].Coastal Engineering Journal,2022,64(4):506-532.

[36]ISLAM T,SRIVASTAVA P K,RICO-RAMIREZ M A,et al.Tracking a tropical cyclone through WRF-ARW simulation and sensitivity of model physics[J].Natural Hazards,2015,76(3):1473-1495.

[37]CHEN J J,XU D M,SHU A Q,et al.The impact of radar radial velocity data assimilation using WRF-3DVAR system with different background error length scales on the forecast of Super Typhoon Lekima(2019)[J].Remote Sensing,2023,15(10):2592.

[38]RENDFREY T S,BUKOVSKY M S,MCCRARY R R,et al.An assessment of tropical cyclones in North American CORDEX WRFsimulations[J].Weather and Climate Extremes,2021,34:100382.

[39]HON K K.Tropical cyclone track prediction using a large-area WRFmodel at the Hong Kong Observatory[J].Tropical Cyclone Research and Review,2020,9(1):67-74.

[40]RAJESWARI J R,SRINIVAS C V,MOHAN P R,et al.Impact of boundary layer physics on tropical cyclone simulations in the Bay of Bengal using the WRF Model[J].Pure and Applied Geophysics,2020,177(11):5523-5550.

[41]ZHANG H,DUAN W S,ZHANG Y C.Using the orthogonal conditional nonlinear optimal perturbations approach to address the uncertainties of tropical cyclone track forecasts generated by the WRFModel[J].Weather and Forecasting,2023,38(10):1907-1933.

[42]YAN Y Y,GAO L,CHEN R D,et al.Analysis of disaster and damage process caused by No.2305“Doksuri”Typhoon disaster chain in Fuzhou City[J].Journal of Catastrophology,2024,39(4):228-234.

[43]YING M,ZHANG W,YU H,et al.An overview of the China meteorological administration tropical cyclone database[J].Journal of Atmospheric and Oceanic Technology,2014,31(2):287-301.

[44]DUDHIA J.Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model[J].Journal of the Atmospheric Sciences,1989,46(20):3077-3107.

[45]MLAWER E J,TAUBMAN S J,BROWN P D,et al.Radiative transfer for inhomogeneous atmospheres:RRTM,a validated correlated-k model for the longwave[J].Journal of Geophysical Research:Atmospheres,1997,102(D14):16663-16682.

[46]TIAN J Y,LIU J,LI C Z,et al.Preliminary study on mesoscale numerical model WRF for hydrology and meteorology[J].South-toNorth Water Transfers and Water Science&Technology,2015,13(6):1025-1030+1050.

[47]SKAMAROCK W C,KLEMP J B,DUDHIA J,et al.A description of the advanced research WRF Model Version 4[R].UCAR/NCAR,2019.

[48]XU H X,DUAN Y H,XU X D.Evaluating AI’s capability to reflect physical mechanisms:A case study of tropical cyclone impacts on extreme rainfall[J].Environmental Research Letters,2024,19(10):104006.

[49]WANG X J,MA H.Progress of application of the Weather Research and Forecast(WRF) model in China[J].Advances in Earth Science,2011,26(11):1191-1199.

[50]SUN L,CHEN S Y,PAN X,et al.Sensitivity analysis of model initial value of a rainstorm in the warm sector of South China[J].Journal of the Meteorological Sciences,2022,42(3):356-367.

[51]LI Q Y,SHEN F F,XU D M,et al.Influence of different initial fields on numerical simulation of Typhoon Saomai[J].Meteorological Science and Technology,2019,47(3):460-468.

[52]VU D H,HUANG C Y,NGUYEN T C.Numerical investigation of track and intensity evolution of Typhoon Doksuri(2023)[J].Atmosphere,2024,15(9):1105.

[53]JIANG X L,REN F M,QIU W Y,et al.High-resolution numerical simulation of topographic influence on the heavy rainfall of Typhoon Rammasun[J].Theoretical and Applied Climatology,2022,150(3/4):1337-1351.

[54]CHEN J J,XU D M,SHU A Q,et al.The impact of radar radial velocity data assimilation using WRF-3DVAR system with different background error length scales on the forecast of Super Typhoon Lekima(2019)[J].Remote Sensing,2023,15(10):2592.

[55]LI X R,KE F,ENTAO Y.Hindcast of extreme rainfall with highresolution WRF:Model ability and effect of physical schemes[J].Theoretical and Applied Climatology,2020,139(1/2):639-658.

[56]CHEN C J,CHI M H,YE J R.Assessing hydroclimate response to land use/cover change using coupled atmospheric-hydrological models[J].Geoscience Letters,2023,10(1):54.

基本信息:

DOI:10.13928/j.cnki.wrahe.2025.11.001

中图分类号:P444;P426.6

引用信息:

[1]吴静雯,颜悠逸,殷方旭,等.台风降水的WRF模拟:以福建省杜苏芮台风为例(英文)[J].水利水电技术(中英文),2025,56(11):1-20.DOI:10.13928/j.cnki.wrahe.2025.11.001.

基金信息:

National Natural Science Foundation of China (42271030); Fujian Provincial Funds for Distinguished Young Scientists (2022J06018); Natural Science Foundation of Fujian Province (2023J011334); “Young Eagle Plan” Top Talents of Fujian Province~~

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