Skip to main content

Advertisement

Log in

Global extreme precipitation characteristics: the perspective of climate and large river basins

  • Original Article
  • Published:
Climate Dynamics Aims and scope Submit manuscript

Abstract

With global warming, extreme weather frequently and severely appears globally. Extreme precipitation is one of the extreme weather events that can cause many natural disasters, such as floods and waterlogging. In this study, Global Precipitation Climatology Project (GPCP) daily precipitation data were used to investigate extreme precipitation and its contribution to annual precipitation in different global climate regions and typical river basins. The climate types included equatorial climates (EC), arid climates (AC), warm temperate climates (WTC), snowy climates (SC) and polar climates (PC). R99p, Rx5day, CWD and R20 was selected as extreme precipitation indices in this study; extreme precipitation days were defined by CWD and R20. The results showed that EC and WTC had higher extreme precipitation level; SC and PC had lower extreme precipitation amounts and days than AC. R99p, Rx5day and CWD monitored higher extreme precipitation contribution degrees in AC; however, R20 monitored higher contribution degrees in EC and WTC. R99p, Rx5day and CWD showed higher extreme precipitation contribution degrees in North Africa, the Middle East, Australia and northwestern China; R20 showed higher contribution degrees in South America, the southeastern United States and South Asia. Based on historical observational data, Heilongjiang Basin (HB), Yellow River Basin (YERB), Yangtze River Basin (YARB), Ganges River Basin (GRB), Danube River Basin (DRB) and Mekong River Basin (MERB) had high-frequency extreme precipitation in summer. The research results are helpful for understanding the characteristics of extreme precipitation and provide a reference for flood control and disaster reduction in different climatic regions and main river basins.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

Data availability

The datasets generated during and analyzed during the current study are not publicly available due to Institutional confidentiality regulations and personal intentions but are available from the corresponding author on reasonable request.

References

  • Almazroui M, Saeed S (2020) Contribution of extreme daily precipitation to total rainfall over the Arabian Peninsula. Atmos Res 231:104672

    Google Scholar 

  • Chao L et al (2018) Geographically weighted regression based methods for merging satellite and gauge precipitation. J Hydrol 558:275–289

    Google Scholar 

  • Chen C-A, Hsu H-H, Liang H-C (2021) Evaluation and comparison of CMIP6 and CMIP5 model performance in simulating the seasonal extreme precipitation in the western North Pacific and East Asia. Weather Clim Extremes 31:100303

    Google Scholar 

  • Coumou D, Rahmstorf S (2012) A decade of weather extremes. Nat Clim Change 2(7):491–496

    Google Scholar 

  • de Beurs KM, Henebry GM, Owsley BC, Sokolik I (2015) Using multiple remote sensing perspectives to identify and attribute land surface dynamics in Central Asia 2001–2013. Remote Sens Environ 170:48–61

    Google Scholar 

  • De Michele C, Avanzi F (2018) Superstatistical distribution of daily precipitation extremes: a worldwide assessment. Sci Rep 8(1):14204

    Google Scholar 

  • Donat MG, Lowry AL, Alexander LV, O’Gorman PA, Maher N (2016) More extreme precipitation in the world’s dry and wet regions. Nat Clim Change 6(5):508–513

    Google Scholar 

  • Duan WL et al (2019) Evaluation and future projection of chinese precipitation extremes using large Ensemble High-Resolution Climate Simulations. J Clim 32(8):2169–2183

    Google Scholar 

  • Espinoza J-C, Marengo JA, Schongart J, Jimenez JC (2022) The new historical flood of 2021 in the Amazon River compared to major floods of the 21st century: atmospheric features in the context of the intensification of floods. Weather Clim Extremes 35:100406

    Google Scholar 

  • Ficchì A et al (2021) Beyond El Niño: unsung climate modes drive african floods. Weather Clim Extremes 33:100345

    Google Scholar 

  • Filizola N et al (2014) Was the 2009 flood the most hazardous or the largest ever recorded in the Amazon? Geomorphology 215:99–105

    Google Scholar 

  • Grams CM, Binder H, Pfahl S, Piaget N, Wernli H (2014) Atmospheric processes triggering the Central European floods in June 2013. Nat Hazards Earth Syst Sci 14(7):1691–1702

    Google Scholar 

  • Gu X et al (2020) Impacts of anthropogenic warming and uneven regional socio-economic development on global river flood risk. J Hydrol 590:125262

    Google Scholar 

  • Gu X et al (2022) Extreme precipitation in China: a review on statistical methods and applications. Adv Water Resour 163:104144. https://doi.org/10.1016/j.advwatres.2022.104144

  • Guo H et al (2021) Assessment of CMIP6 in simulating precipitation over arid Central Asia. Atmos Res 252:105451

    Google Scholar 

  • Hattermann FF et al (2018) Simulation of flood hazard and risk in the Danube basin with the future Danube Model. Clim Serv 12:14–26

    Google Scholar 

  • Huang J et al (2022) Historical global land surface air apparent temperature and its future changes based on CMIP6 projections. Sci Total Environ 816:151656. https://doi.org/10.1016/j.scitotenv.2021.151656

  • Huffman GJ et al (2009) Improving the global precipitation record: GPCP Version 2.1. Geophys Res Lett 36(17). https://doi.org/10.1029/2009gl040000

  • Ju J, Wu C, Yeh PJF, Dai H, Hu BX (2021) Global precipitation-related extremes at 1.5°C and 2°C of global warming targets: projection and uncertainty assessment based on the CESM-LWR experiment. Atmos Res 264:105868

    Google Scholar 

  • Kehui Z (2011) The impacts of global climate change on extreme weather events in Beijing–Tianjin–Hebei area and the countermeasures for disaster prevention. J Arid Land Resour Environ 25(10):122–125

    Google Scholar 

  • Kottek M, Grieser J, Beck C, Rudolf B, Rubel F (2006) World Map of the Köppen-Geiger climate classification updated. Meteorol Z 15(3):259–263

    Google Scholar 

  • Kotz M, Levermann A, Wenz L (2022) The effect of rainfall changes on economic production. Nature 601(7892):223–227

    Google Scholar 

  • Kyselý J, Beguería S, Beranová R, Gaál L, López-Moreno JI (2012) Different patterns of climate change scenarios for short-term and multi-day precipitation extremes in the Mediterranean. Glob Planet Change 98–99:63–72

    Google Scholar 

  • Lakshmi V, Fayne J, Bolten J (2018) A comparative study of available water in the major river basins of the world. J Hydrol 567:510–532

    Google Scholar 

  • Lehner B, Döll P (2004) Development and validation of a global database of lakes, reservoirs and wetlands. J Hydrol 296(1–4):1–22

    Google Scholar 

  • Lehner B, Grill G (2013) Global river hydrography and network routing: baseline data and new approaches to study the world’s large river systems. Hydrol Process 27(15):2171–2186

    Google Scholar 

  • Li P, Yu Z, Jiang P, Wu C (2021) Spatiotemporal characteristics of regional extreme precipitation in Yangtze River basin. J Hydrol 603:126910

    Google Scholar 

  • Litvinov AS et al (2009) Chapter 2—Volga River Basin. In: Tockner K, Uehlinger U, Robinson CT (eds) Rivers of Europe. Academic Press, London, pp 23–57

    Google Scholar 

  • Liu S et al (2017) Identification of the non-stationarity of extreme precipitation events and correlations with large-scale ocean-atmospheric circulation patterns: a case study in the Wei River Basin, China. J Hydrol 548:184–195

    Google Scholar 

  • Liu Y, Guo L, Huang Z, López-Vicente M, Wu G-L (2020) Root morphological characteristics and soil water infiltration capacity in semi-arid artificial grassland soils. Agric Water Manag 235:106153

    Google Scholar 

  • Madsen H, Lawrence D, Lang M, Martinkova M, Kjeldsen TR (2014) Review of trend analysis and climate change projections of extreme precipitation and floods in Europe. J Hydrol 519:3634–3650

    Google Scholar 

  • Mondal SK et al (2022) Changes in extreme precipitation across South Asia for each 0.5°C of warming from 1.5°C to 3.0°C above pre-industrial levels. Atmos Res 266:105961

    Google Scholar 

  • Ni S et al (2017) Global Terrestrial Water Storage changes and connections to ENSO events. Surv Geophys 39(1):1–22

    Google Scholar 

  • Nogueira M (2020) Inter-comparison of ERA-5, ERA-interim and GPCP rainfall over the last 40 years: process-based analysis of systematic and random differences. J Hydrol 583:124632

    Google Scholar 

  • Ombadi M (2023) A warming-induced reduction in snow fraction amplifies rainfall extremes. Nature 619(7969):305–310. https://doi.org/10.1038/s41586-023-06092-7

  • Palash W, Akanda AS, Islam S (2020) The record 2017 flood in South Asia: state of prediction and performance of a data-driven requisitely simple forecast model. J Hydrol 589:125190

    Google Scholar 

  • Pan T, Zhang L, Zhang H, Ren C, Li Y (2020) Spatiotemporal patterns and variations of winter extreme precipitation over terrestrial northern hemisphere in the past century (1901–2017). Phys Chem Earth Parts A/B/C 115:102828

    Google Scholar 

  • Peel MC, Finlayson BL, McMahon TA (2007) Updated world map of the Koppen–Geiger climate classification. Hydrol Earth Syst Sci 11:1633–1644

    Google Scholar 

  • Pfahl S, O’Gorman PA, Fischer EM (2017) Understanding the regional pattern of projected future changes in extreme precipitation. Nat Clim Change 7(6):423–427

    Google Scholar 

  • Shi S et al (2021) Quantitative contributions of climate change and human activities to vegetation changes over multiple time scales on the Loess Plateau. Sci Total Environ 755(Pt 2):142419

    Google Scholar 

  • Shi W et al (2021) Multi-model comparison and high-resolution regional model forecast analysis for the 7·20 Zhengzhou severe heavy rain. Trans Atmos Sci 44(5):688–702

    Google Scholar 

  • Shi X et al (2021) Impacts and socioeconomic exposures of global extreme precipitation events in 1.5 and 2.0 degrees C warmer climates. Sci Total Environ 766:142665

    Google Scholar 

  • Shi Z et al (2021) Distinct holocene precipitation trends over arid Central Asia and linkages to westerlies and asian monsoon. Q Sci Rev 266:107055

    Google Scholar 

  • Sommerwerk N et al (2009) Chapter 3—the Danube River Basin. In: Tockner K, Uehlinger U, Robinson CT (eds) Rivers of Europe. Academic Press, London, pp 59–112

    Google Scholar 

  • Sun X, Renard B, Thyer M, Westra S, Lang M (2015) A global analysis of the asymmetric effect of ENSO on extreme precipitation. J Hydrol 530:51–65

    Google Scholar 

  • Tuel A, Martius O (2021) A global perspective on the sub-seasonal clustering of precipitation extremes. Weather Clim Extremes 33:100348

    Google Scholar 

  • Wang XL, Lin A (2015) An algorithm for integrating satellite precipitation estimates with in situ precipitation data on a pentad time scale. J Geophys Res Atmos 120(9):3728–3744

    Google Scholar 

  • Wang H, Chen Y, Pan Y, Li W (2015) Spatial and temporal variability of drought in the arid region of China and its relationships to teleconnection indices. J Hydrol 523:283–296

    Google Scholar 

  • Wang P et al (2021) Increasing annual and extreme precipitation in permafrost-dominated Siberia during 1959–2018. J Hydrol 603:126865

    Google Scholar 

  • Wang S, Zhang L, She D, Wang G, Zhang Q (2021) Future projections of flooding characteristics in the Lancang-Mekong River Basin under climate change. J Hydrol 602:126778

    Google Scholar 

  • Wang X, Hou X, Zhao Y (2021) Changes in consecutive dry/wet days and their relationships with local and remote climate drivers in the coastal area of China. Atmos Res 247:105138

    Google Scholar 

  • Wasko C, Nathan R, Stein L, O’Shea D (2021) Evidence of shorter more extreme rainfalls and increased flood variability under climate change. J Hydrol 603:126994

    Google Scholar 

  • Wimhurst JJ, Greene JS (2021) Updated analysis of gauge-based rainfall patterns over the western tropical Pacific Ocean. Weather Clim Extremes 32:100319

    Google Scholar 

  • Wu P, Ding Y, Liu Y (2017) Atmospheric circulation and dynamic mechanism for persistent haze events in the Beijing–Tianjin–Hebei region. Adv Atmos Sci 34(4):429–440

    Google Scholar 

  • Xiong J et al (2022) Projected changes in terrestrial water storage and associated flood potential across the Yangtze River basin. Sci Total Environ 817:152998

    Google Scholar 

  • Yao J et al (2021) Intensification of extreme precipitation in arid Central Asia. J Hydrol 598:125760

    Google Scholar 

  • Zhang J-l, Shang Y-z, Liu J-x, Fu J, Cui M (2020) Improved ecological development model for lower Yellow River floodplain, China. Water Sci Eng 13(4):275–285

    Google Scholar 

  • Zhang L et al (2020) Changes of winter extreme precipitation in Heilongjiang province and the diagnostic analysis of its circulation features. Atmos Res 245:105094

    Google Scholar 

  • Zhang M, Xu M, Wang Z, Lai C (2021) Assessment of the vulnerability of road networks to urban waterlogging based on a coupled hydrodynamic model. J Hydrol 603:127105

    Google Scholar 

  • Zhao Y et al (2019) Analysis of changes in characteristics of flood and sediment yield in typical basins of the Yellow River under extreme rainfall events. CATENA 177:31–40

    Google Scholar 

  • Zhou Z et al (2020) Is the cold region in Northeast China still getting warmer under climate change impact? Atmos Res 237:104864. https://doi.org/10.1016/j.atmosres.2020.104864

  • Zhou K, Li J, Zhang T, Kang A (2021a) The use of combined soil moisture data to characterize agricultural drought conditions and the relationship among different drought types in China. Agric Water Manag 243:106479

    Google Scholar 

  • Zhou Z et al (2021b) Investigating the propagation from meteorological to hydrological drought by introducing the nonlinear dependence with directed information transfer index. Water Resour Res 57. https://doi.org/10.1029/2021wr030028

  • Zittis G, Bruggeman A, Lelieveld J (2021) Revisiting future extreme precipitation trends in the Mediterranean. Weather Clim Extremes 34:100380

    Google Scholar 

Download references

Acknowledgements

This study was funded by the National Natural Science Foundation of China (grant no. 52179015), and the Key Technologies R & D and Promotion program of Henan (232102110025).

Funding

The National Natural Science Foundation of China (grant no. 52179015), and the Key Technologies R & D and Promotion program of Henan (232102110025).

Author information

Authors and Affiliations

Authors

Contributions

Methodology: LZ; Formal analysis: YL, LL; Validation: PY, LZ, XL; Supervision: LZ, LL, ZZ, YD; Writing - original draft: YD, YL, ZZ; Writing - review & editing: HZ, LZ.

Corresponding author

Correspondence to Lusheng Li.

Ethics declarations

Conflict of interest

The authors declare no conflict of interest.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhao, L., Li, L., Li, Y. et al. Global extreme precipitation characteristics: the perspective of climate and large river basins. Clim Dyn 62, 1013–1030 (2024). https://doi.org/10.1007/s00382-023-06961-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00382-023-06961-x

Keywords

Navigation