Articles | Volume 26, issue 9
https://doi.org/10.5194/nhess-26-4291-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-26-4291-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Analysis of urban-scale typhoon precipitation characteristics and spatiotemporal patterns: a case study of Ningbo, China
Caiming Wu
Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), School of Atmospheric Science, Nanjing University of Information Science and Technology, Nanjing, 210044, China
State Key Laboratory of Severe Weather Meteorological Science and Technology (LaSW), and Center for Meteorological Impact and Risk Research, Chinese Academy of Meteorological Sciences, Beijing, 100081, China
Hong-Li Ren
State Key Laboratory of Severe Weather Meteorological Science and Technology (LaSW), and Center for Meteorological Impact and Risk Research, Chinese Academy of Meteorological Sciences, Beijing, 100081, China
Yi Lu
CORRESPONDING AUTHOR
Shanghai Typhoon Institute, China Meteorological Administration, Shanghai, 200030, China
Asia-Pacific Typhoon Collaborative Research Center, Shanghai, 200030, China
Fumin Ren
CORRESPONDING AUTHOR
State Key Laboratory of Severe Weather Meteorological Science and Technology (LaSW), and Center for Meteorological Impact and Risk Research, Chinese Academy of Meteorological Sciences, Beijing, 100081, China
Related authors
No articles found.
Pujun Liang, Jie Yin, Dandan Wang, Yi Lu, Yuhan Yang, Dan Gao, and Jianfeng Mai
Nat. Hazards Earth Syst. Sci., 25, 3545–3558, https://doi.org/10.5194/nhess-25-3545-2025, https://doi.org/10.5194/nhess-25-3545-2025, 2025
Short summary
Short summary
Coastal cities face growing flood risks due to climate change. This study explores emergency planning to help cities like Shanghai to prepare for extreme floods. Using GIS (geographic information system) and optimisation methods, we developed a framework to improve the equity and efficiency of emergency supply delivery. Analysis shows Shanghai’s current facilities may not handle a severe 1000-year flood well. This underscores the need for strategic investment and fair resource allocation.
Yuhan Yang, Jie Yin, Weiguo Zhang, Yan Zhang, Yi Lu, Yufan Liu, Aoyue Xiao, Yunxiao Wang, and Wenming Song
Nat. Hazards Earth Syst. Sci., 21, 3563–3572, https://doi.org/10.5194/nhess-21-3563-2021, https://doi.org/10.5194/nhess-21-3563-2021, 2021
Short summary
Short summary
This is the first time the compound flooding process of heavy rain and levee-breach-induced flooding has been modeled. Real-life cases of historical flooding events have been adequately investigated. Our results provide a comprehensive view of the spatial patterns of the flood evolution, the dynamic process, and mechanism of these cases, which can help decision makers to develop effective emergency response plans and flood adaptation strategies.
Cited articles
Amorim, R., Villarini, G., Kim, H., Jane, R. A., and Wahl, T.: A Practitioner's Approach to Process-Driven Modeling of Compound Rainfall and Storm Surge Extremes for Coastal Texas, J. Hydrol. Eng., 30, 04025025, https://doi.org/10.1061/JHYEFF.HEENG-6482, 2025.
Cannon, A. J. and Innocenti, S.: Projected intensification of sub-daily and daily rainfall extremes in convection-permitting climate model simulations over North America: implications for future intensity–duration–frequency curves, Nat. Hazards Earth Syst. Sci., 19, 421–440, https://doi.org/10.5194/nhess-19-421-2019, 2019.
Chan, F. K. S., Gu, X., Qi, Y., Thadani, D., Chen, Y. D., Lu, X., Li, L., Griffiths, J., Zhu, F., Li, J., and Chen, W. Y.: Lessons learnt from Typhoons Fitow and In-Fa: implications for improving urban flood resilience in Asian Coastal Cities, Nat. Hazards, 110, 2397–2404, https://doi.org/10.1007/s11069-021-05030-y, 2022.
Chen, G., Hou, J., Wang, T., Lv, J., Jing, J., Ma, X., Yang, S., Deng, C., Ma, Y., and Ji, G.: The effect of spatial-temporal characteristics of rainfall on urban inundation processes, Hydrol. Process., 36, e14655, https://doi.org/10.1002/hyp.14655, 2022.
Cheng, L.-W., Yu, C.-K., and Chen, S.-P.: Identifying mechanisms of tropical cyclone generated orographic precipitation with Doppler radar and rain gauge observations, npj Clim. Atmos. Sci., 8, 35, https://doi.org/10.1038/s41612-025-00921-4, 2025.
Costabile, P., Costanzo, C., Kalogiros, J., and Bellos, V.: Toward Street-Level Nowcasting of Flash Floods Impacts Based on HPC Hydrodynamic Modeling at the Watershed Scale and High-Resolution Weather Radar Data, Water Resour. Res., 59, e2023WR034599, https://doi.org/10.1029/2023wr034599, 2023.
DB 33/T 1191-2020: Zhejiang Province Department of Housing and Urban-Rural Development: Standard of rainfall intensity computation, Hangzhou, China, https://www.biaozhuns.com (last access: 27 August 2026), 2020 (in Chinese).
Emanuel, K.: Assessing the present and future probability of Hurricane Harvey's rainfall, P. Natl. Acad. Sci. USA, 114, 12681–12684, https://doi.org/10.1073/pnas.1716222114, 2017.
Feng, Z., Liao, C., and Zeng, J.: Comparative analysis of heavy rainfall area between landfalling typhoon LUPIT (2109) and typhoon LISA (9610), Trop. Cyclone Res. Rev., 13, 175–186, https://doi.org/10.1016/j.tcrr.2024.08.006, 2024.
GB/T 28592-2012: National Standardization Administration of China, General Administration of Quality Supervision, Inspection and Quarantine of the People's Republic of China: Grade of precipitation, China Standard Press, Beijing, China, https://openstd.samr.gov.cn/bzgk/gb (last access: 3 September 2026), 2012 (in Chinese).
Ghanmi, H., Bargaoui, Z., and Mallet, C.: Estimation of intensity-duration-frequency relationships according to the property of scale invariance and regionalization analysis in a Mediterranean coastal area, J. Hydrol., 541, 38–49, https://doi.org/10.1016/j.jhydrol.2016.07.002, 2016.
Gruss, Ł., Willems, P., Tomczyk, P., Pollert Jr., J., Pollert Sr., J., Märtner, C., Czaban, S., and Wiatkowski, M.: Evaluation of the Dual Gamma Generalized Extreme Value distribution for flood events in Poland, Hydrol. Earth Syst. Sci., 29, 5165–5184, https://doi.org/10.5194/hess-29-5165-2025, 2025.
Hawker, L., Uhe, P., Paulo, L., Sosa, J., Savage, J., Sampson, C., and Neal, J.: A 30 m global map of elevation with forests and buildings removed, Environ. Res. Lett., 17, 024016, https://doi.org/10.1088/1748-9326/ac4d4f, 2022.
He, L., Chen, S., and Guo, Y.: Observation characteristics and synoptic mechanisms of Typhoon Lekima extreme rainfall in 2019, J. Appl. Meteor. Sci., 31, 513–526, https://doi.org/10.11898/1001-7313.20200501, 2020.
Hoch, J., Probyn, I., Marra, F., Lucas, C., Savag, J., Win, O., Sampson, C., and Addor, N.: BURGER: A bottom up regionalization approach for global sub daily Intensity Duration Frequency data, Water Resour. Res., 61, e2024WR039773, https://doi.org/10.1029/2024WR039773, 2025.
Hosking, J. R. M.: L-Moments: Analysis and Estimation of Distributions Using Linear Combinations of Order Statistics, J. R. Stat. Soc. B, 52, 105–124, https://doi.org/10.1111/j.2517-6161.1990.tb01775.x, 1990.
Jayaweera, L., Wasko, C., Nathan, R., Syktus, J., and Eccles, R.: Evaluation and projection of extreme rainfall from a large ensemble of high–resolution regional climate models in Australia, Weather and Climate Extremes, 50, 100818, https://doi.org/10.1016/j.wace.2025.100818, 2025.
Ji, J., Wang, Y., Jiang, T., Zhai, J., Sang, W., and Wu, H.: Analysis of characteristics of heavy rainfall events induced by landfalling tropical cyclones in China from 1980 to 2020, Water Resources and Hydropower Engineering, https://doi.org/10.13928/j.cnki.wrahe.2026.03.006, 2026.
Jin, C., Yuan, W.-X., Zhou, H., et al.: Application of Partitioning Clustering in Short-duration Storm Pattern Design, China Water & Wastewater, 40, 113–119, https://doi.org/10.19853/j.zgjsps.1000-4602.2024.03.017, 2024 (in Chinese).
Kim, H., Villarini, G., Jane, R., Wahl, T., Misra, S., and Michalek, A.: On the generation of high-resolution probabilistic design events capturing the joint occurrence of rainfall and storm surge in coastal basins, Int. J. Climatol., 43, 761–771, https://doi.org/10.1002/joc.7825, 2023.
Kossin, J. P.: A global slowdown of tropical-cyclone translation speed, Nature, 558, 104–107, https://doi.org/10.1038/s41586-018-0158-3, 2018.
Kumar, M. S., Geethalakshmi, V., Pazhanivelan, S., Subrahmaniyan, K., Dheebakaran, G., Saravanakumar, V., Bhuvaneswari, K., and Pugazenthi, K.: Tropical cyclone-induced rainfall estimation using the distance approach: a systematic review, Nat. Hazards, 121, 22297–22339, https://doi.org/10.1007/s11069-025-07689-z, 2025.
Lai, Y., Gu, X., Wei, L., Wang, L., Slater, L. J., Li, J., Shi, D., Xiao, M., Wang, L., Guan, Y., Kong, D., and Zhang, X.: Slower-decaying tropical cyclones produce heavier precipitation over China, npj Clim. Atmos. Sci., 7, 99, https://doi.org/10.1038/s41612-024-00655-9, 2024.
Lanciotti, S., Ridolfi, E., Russo, F., and Napolitano, F.: Intensity-Duration-Frequency Curves in a Data-Rich Era: A Review, Water, 14, 3705, https://doi.org/10.3390/w14223705, 2022.
Li, L. and Chakraborty, P.: Slower decay of landfalling hurricanes in a warming world, Nature, 587, 230–234, https://doi.org/10.1038/s41586-020-2867-7, 2020.
Li, X., Hou, J., Wang, Z., Wang, T., Lv, J., and Li, D.: Numerical simulation of the influence of design rainstorm pattern on urban flood in narrow valley, Engineering Journal of Wuhan University, https://link.cnki.net/urlid/42.1675.T.20240830.0937.002 (last access: 18 April 2025), 2024 (in Chinese).
Li, Y. and Zhao, D. J.: Climatology of Tropical Cyclone Extreme Rainfall over China from 1960 to 2019, Adv. Atmos. Sci., 39, 320–332, https://doi.org/10.1007/s00376-021-1080-4, 2022.
Lima, C. H. R., Kwon, H. H., and Kim, J. Y.: A Bayesian beta distribution model for estimating rainfall IDF curves in a changing climate, J. Hydrol., 540, 744–756, https://doi.org/10.1016/j.jhydrol.2016.06.062, 2016.
Lin, B., Bonnin, G. M., Martin, D., Parzybok, T. M., Yekta, M., and Riley, D.: Regional frequency studies of annual extreme precipitation in the United States based on regional L-moments analysis, in: Proceedings of the World Environmental and Water Resources Congress, New York, American Society of Civil Engineers, 1, 16, https://doi.org/10.1061/40856(200)219, 2006.
Lin, R., Zheng, F., Ma, Y., Duan, H.-F., Chu, S., and Deng, Z.: Impact of Spatial Variation and Uncertainty of Rainfall Intensity on Urban Flooding Assessment, Water Resour. Manag., 36, 5655–5673, https://doi.org/10.1007/s11269-022-03325-8, 2022.
Liu, L. and Wang, Y.: Trends in Landfalling Tropical Cyclone–Induced Precipitation over China, J. Climate, 33, 2223–2235, https://doi.org/10.1175/JCLI-D-19-0693.1, 2020.
Lu, X., Yu, H., Ying, M., Zhao, B., Zhang, S., Lin, L., Bai, L., and Wan, R.: Western North Pacific tropical cyclone database created by the China Meteorological Administration, Adv. Atmos. Sci., 38, 690–699, https://doi.org/10.1007/s00376-020-0211-7, 2021.
Lu, Y., Chen, P., Yu, H., Fang, P., Gong, T., Wang, X., and Song, S.: Parameterized Tropical Cyclone Precipitation Model for Catastrophe Risk Assessment in China, J. Appl. Meteorol. Clim., 61, 1291–1303, https://doi.org/10.1175/JAMC-D-21-0157.1, 2022.
Luo, Y., Wu, M., Ren, F., Li, J., and Wong, W.-K.: Synoptic Situations of Extreme Hourly Precipitation over China, J. Climate, 29, 8703–8719, https://doi.org/10.1175/JCLI-D-16-0057.1, 2016.
Meng, D., Liao, Y., Deng, Z., Chen, Y., Lai, C., Chen, X., and Wang, Z.: Spatially moving non-uniform rainstorms may exacerbate urban flooding disasters, J. Hydrol., 660, 133374, https://doi.org/10.1016/j.jhydrol.2025.133374, 2025.
Ministry of Land, Infrastructure, Transport and Tourism (MLIT), Water Management and National Land Protection Bureau: Methods for setting design maximum external forces for creating flood and internal water inundation assumptions[R], Tokyo: Ministry of Land, Infrastructure, Transport and Tourism, https://www.mlit.go.jp/river/shishin_guideline/pdf/shinsuisoutei_honnbun_1507.pdf (last access: 27 August 2026), 2015 (in Japanese).
Ministry of Land, Infrastructure, Transport and Tourism (MLIT), Water Management and National Land Protection Bureau, River Environment Department, Flood Control Planning Office and National Institute for Land and Infrastructure Management (NILIM), River Research Department, Flood Disaster Research Laboratory: Guidelines for the examination and creation of multi-stage flood inundation assumption maps and flood risk maps[R], Tokyo: Ministry of Land, Infrastructure, Transport and Tourism., https://www.mlit.go.jp/river/shishin_guideline/pdf/guideline_kouzuishinsui_2301.pdf (last access: 27 August 2026), 2023 (in Japanese).
Morin, G., Boudreault, M., and García-Franco, J. L.: A Global Multi-Source Tropical Cyclone Precipitation (MSTCP) Dataset, Sci. Data, 11, 609, https://doi.org/10.1038/s41597-024-03395-w, 2024.
Nasr, A. A., Wahl, T., Rashid, M. M., Jane, R. A., Camus, P., and Haigh, I. D.: Temporal changes in dependence between compound coastal and inland flooding drivers around the contiguous United States coastline, Weather Clim. Extremes, 41, 100594, https://doi.org/10.1016/j.wace.2023.100594, 2023.
Qi, W., Ma, C., Xu, H., and Zhao, K.: Urban flood response analysis for designed rainstorms with different characteristics based on a tracer-aided modeling simulation, J. Clean. Prod., 355, 131797, https://doi.org/10.1016/j.jclepro.2022.131797, 2022.
Ren, F., Wang, Y., Wang, X., and Li, W.: Estimating tropical cyclone precipitation from station observations, Adv. Atmos. Sci., 24, 700–711, https://doi.org/10.1007/s00376-007-0700-y, 2007.
Ren, Z., Sang, Y. F., Cui, P., Chen, F., and Chen, D.: A dataset of gridded precipitation intensity-duration-frequency curves in Qinghai-Tibet Plateau, Scientific Data, 12, 3, https://doi.org/10.1038/s41597-024-04362-1, 2025.
Sivapalan, M. and Blöschl, G.: Transformation of point rainfall to areal rainfall: Intensity-duration-frequency curves, J. Hydrol., 204, 150–167, https://doi.org/10.1016/S0022-1694(97)00117-0, 1998.
Soil Conservation Service: Urban hydrology for small watersheds, Technical Release No. 55 (TR-55), US Department of Agriculture, Washington, DC, https://www.nrcs.usda.gov/publications/WinTR-55setupV2.0.0on16July2022.exe (last access: 3 September 2026), 1986.
Su, Z., Ren, F., Wei, J., Lin, X., Shi, S., and Zhou, X.: Changes in Monsoon and Tropical Cyclone Extreme Precipitation in Southeast China from 1960 to 2012, Trop. Cyclone Res. Rev., 4, 12–17, https://doi.org/10.6057/2015TCRR01.02, 2015.
Sun, S., Shi, C., Pan, Y., Bai, L., Xu, B., Zhang, T., Han, S., and Jiang, L.: Applicability Assessment of the 1998–2018 CLDAS Multi-Source Precipitation Fusion Dataset over China, J. Meteorol. Res., 34, 879–892, https://doi.org/10.1007/s13351-020-9101-2, 2020.
Tang, Q., Bao, Y., Chen, C., Wang, T., Wu, J., Yu, T., and Zheng, X.: Spatio-temporal characteristics of rainstorm in Kunshan and reckoning of designed rainstorm intensity formula, J. Trop. Meteorol., 36, 683–698, https://doi.org/10.16032/j.issn.1004-4965.2020.062, 2020 (in Chinese).
Wang, J., Li, S., Guan, X., He, Y., Cao, C., Lian, L., and Zhang, L.: Unveiling the Link Between Extreme Precipitation Events and Flood Disasters in China: From 3D Perspective, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2025-4728, 2025.
Wang, S., Ruan, W., Li, X., and Yao, H.: Divergences in typhoon and non-typhoon extreme rainfall trends and their spatial variations at multiple timescales in typical region of southeastern China, Atmos. Res., 330, 108590, https://doi.org/10.1016/j.atmosres.2025.108590, 2026.
Wu, M., Dong, M., Chen, F., and Chen, Y.: Characteristics of extreme hourly precipitation induced by tropical cyclones in Zhejiang, China: A comparative analysis based on two different datasets, Atmos. Res., 311, 107712, https://doi.org/10.1016/j.atmosres.2024.107712, 2024.
Xu, H., Tian, Z., Sun, L., Ye, Q., Ragno, E., Bricker, J., Mao, G., Tan, J., Wang, J., Ke, Q., Wang, S., and Toumi, R.: Compound flood impact of water level and rainfall during tropical cyclone periods in a coastal city: the case of Shanghai, Nat. Hazards Earth Syst. Sci., 22, 2347–2358, https://doi.org/10.5194/nhess-22-2347-2022, 2022.
Xu, S., Wang, Q., Yu, J., Zhao, G., Ji, H., Yue, Q., Zheng, Y., Xu, H., Li, H., and Yao, X.: The impact of the spatiotemporal structure of rainfall on flood response over a piedmont urban basin: An approach coupling machine learning and hydrologic modeling, J. Hydrol., 659, 133160, https://doi.org/10.1016/j.jhydrol.2025.133160, 2025.
Yan, Z., Xia, J., Song, J., Zhao, L., and Pang, G.: Research progress on design hyetographs in small and medium-scale basins, Progress in Geography, 39, 1224–1235, https://doi.org/10.18306/dlkxjz.2020.07.014, 2020 (in Chinese).
Yang, Z., Wang, J., Liu, J., Wang, H., Mei, C., and Li, F.: Construction of urban rainfall scenario database and matching technology for predicting rain fall, Water Resources and Hydropower Engineering, 55, 13–24, https://doi.org/10.13928/j.cnki.wrahe.2024.10.002, 2024 (in Chinese).
Ying, M., Zhang, W., Yu, H., Lu, X., Feng, J., Fan, Y., Zhu, Y., and Chen, D.: An overview of the China Meteorological Administration tropical cyclone database, J. Atmos. Ocean. Tech., 31, 287–301, https://doi.org/10.1175/JTECH-D-12-00119.1, 2014.
Yong DX/JS 021-2023: Ningbo Housing and Urban-Rural Development Bureau: Rules for Urban Flooding Prevention and Control in Ningbo, Ningbo, China, http://zjw.ningbo.gov.cn (last access: 3 September 2026), 2023 (in Chinese).
Yu, C., Xu, Q., Yang, Y., Ma, G., and Gao, X.: Intensity formula and design hyetograph for long-duration storm in Xiong'an New District, Journal of Meteorology and Environment, 37, 78–85, https://doi.org/10.3969/j.issn.1673-503X.2021.05.012, 2021 (in Chinese).
Yu, Z., Wang, Y., Xu, H., Davidson, N., Chen, Y., Chen, Y., and Yu, H.: On the Relationship between Intensity and Rainfall Distribution in Tropical Cyclones Making Landfall over China, J. Appl. Meteorol. Clim., 56, 2883–2901, https://doi.org/10.1175/JAMC-D-16-0334.1, 2017.
Zhang, H. and Fan, K.: K-means clustering analysis of autumn rainfall patterns over West China and their underlying mechanisms, Atmos. Res., 334, 108745, https://doi.org/10.1016/j.atmosres.2026.108745, 2026.
Zhang, M., Xu, M., Wang, Z., and Lai, C.: Assessment of the vulnerability of road networks to urban waterlogging based on a coupled hydrodynamic model, J. Hydrol., 603, 127105, https://doi.org/10.1016/j.jhydrol.2021.127105, 2021.
Zhang, Q., Lai, Y., Gu, X., Shi, P., and Singh, V. P.: Tropical cyclonic rainfall in China: Changing properties, seasonality, and causes, J. Geophys. Res.-Atmos., 123, 4476–4489, https://doi.org/10.1029/2017JD028119, 2018.
Zhang, X.: The Features of Summer Precipitation and the Influence of Design Storm in Beijing Area, Nanjing University of Information Science and Technology, https://www.cnki.net (last access: 4 September 2026), 2015 (in Chinese).
Zhao, Y., Zhang, Q., Ju, X., Xiao, D., Yang, H., Chen, J., Liao, J., and Deng, Y.: Analysis of the Characteristics of Short Term Extreme Precipitation in China in the Last 30 Years, Chinese Journal of Atmospheric Sciences, 48, 1144–1156, https://doi.org/10.3878/j.issn.1006-9895.2212.22118, 2024 (in Chinese).
Zhou, C., Chen, P., Yang, S., Zheng, F., Yu, H., Tang, J., Lu, Y., Chen, G., Lu, X., Zhang, X., and Sun, J.: The impact of Typhoon Lekima (2019) on East China: a postevent survey in Wenzhou City and Taizhou City, Front. Earth Sci., 16, 109–120, https://doi.org/10.1007/s11707-020-0856-7, 2022.
Short summary
This study assessed regional-scale typhoon rainfall characteristics and spatiotemporal patterns. Current intensity-duration-frequency curves underestimate long-duration rainfall contributions, especially in northern regions where increases are largest. Typhoon rainfall shows significant spatiotemporal non-uniformity due to interactions with topography, typhoon characteristics, etc. These findings are critical for coastal urban defense against systematic hazards of typhoon rainfall.
This study assessed regional-scale typhoon rainfall characteristics and spatiotemporal patterns....
Altmetrics
Final-revised paper
Preprint