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Attribution of tropical sea surface temperature change on extreme precipitation over the Yangtze River Valley in 2020

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Abstract

Record-breaking extreme precipitation occurred over the Yangtze River Valley (YRV) in June–July 2020. The impact of climate change on this event is examined from the perspectives of key physical processes including synoptic-scale circulation pattern and tropical sea surface temperature (SST) forcing based on self‐organizing map approach and the regularized optimal fingerprinting method. The results indicate that the increase in extreme precipitation over the YRV has accounted for 69% of the increase in total precipitation since 1961. Both the amount and frequency of extreme rainfall during the Meiyu period in 2020 broke the historical record since 1961. The SST warming in tropical Indian Ocean (TIO) and tropical Atlantic Ocean (TAO) lead to the anomalous anticyclone in the Northwest Pacific, which further aggravate the occurrence of extreme precipitation in the YRV. Human influence is the primary cause for the observed SST rise in TIO and TAO since 1961, to which anthropogenic greenhouse gas emissions contribute the most. Quantitatively, the changes of TIO and TAO SST caused by anthropogenic forcing are 0.12 °C/10a and 0.08 °C/10a, respectively. Such SST warming drives the frequency change of synoptic-scale circulation patterns through air sea interaction. The higher occurrence likelihood of circulation patterns conducive to precipitation in all forcing experiment than that in natural forcing proves that the extreme precipitation in the YRV in 2020 is attributable to human-induced climate change.

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Data availability

The data used in the present study are downloaded from the following websites: daily observed precipitation data: http://www.nmic.cn/site/index.html. Monthly HadISST data: https://www.metoffice.gov.uk/hadobs/hadisst/. NCEP/NCAR reanalysis data: https://psl.noaa.gov/data/gridded/data.ncep.reanalysis.html. ERA5 data: https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5. CMIP6 models’ outputs: https://esgf-node.llnl.gov/projects/cmip6/. HadGEM3-A models’ outputs: t https://data.ceda.acuk/badc/eucleia/data/EUCLEIA/output/MOHC/HadGEM3-A-N216.

References

  • Allen M, Stott P (2003) Estimating signal amplitudes in optimal fingerprinting, Part I. Theory Clim Dyn 21(5):477–491. https://doi.org/10.1007/s00382-003-0313-9

    Article  Google Scholar 

  • Ashok K, Behera SK, Rao SA, Weng H, Yamagata T (2007) El Niño Modoki and its possible teleconnection. J Geophys Res 112:C11. https://doi.org/10.1029/2006JC003798

    Article  Google Scholar 

  • Bi BG, Zhang X, Dai K (2017) Characteristics of 2016 severe convective weather and extreme rainfalls under the background of super El Niño. Chin Sci Bull 62(9):928–937 ((in Chinese))

    Article  Google Scholar 

  • Bindoff NL et al (2013) Detection and attribution of climate change: from global to regional. Climate change 2013: the physical science basis. In: Stocker TF et al (eds) Climate change 2013: the physical science basis. Cambridge University Press, Cambridge, pp 867–952

    Google Scholar 

  • Chen H, Sun J (2017) Contribution of human influence to increased daily precipitation extremes over China. J Geophys. Res. 44(5):2436–2444

    Google Scholar 

  • Chen Y, Zhai P (2013) Persistent extreme precipitation events in China during 1951–2010. Clim Res 57(2):143–155

    Article  Google Scholar 

  • Chen W, Lee JY, Lu R, Dong B, Ha KJ (2014) Intensified impact of tropical Atlantic SST on the western North Pacific summer climate under a weakened Atlantic thermohaline circulation. Clim Dyn 45(7–8):2033–2046

    Google Scholar 

  • Christidis N, Stott PA, Scaife AA, Arribas A, Jones GS, Copsey D, Knight JR, Tennant WJ (2013) A new HadGEM3-A-based system for attribution of weather and climate-related extreme events. J Clim 26:2756–2783

    Article  Google Scholar 

  • Ding Y, Liu Y, Hu ZZ (2021) The record-breaking Meiyu in 2020 and associated atmospheric circulation and tropical SST anomalies. Adv Atmos Sci 38(12):1980–1993. https://doi.org/10.1007/s00376-021-0361-2

    Article  Google Scholar 

  • Donat MG, Lowry AL, Alexander LV, O’Gorman PA, Maher N (2017) More extreme precipitation in the world’s dry and wet regions. Nat Clim Change 6(5):508–513

    Article  Google Scholar 

  • Dong S, Sun Y, Li C (2020) Detection of human influence on precipitation extremes in Asia. J Clim 33(12):5293–5304

    Article  Google Scholar 

  • Field CB et al (2014) Impacts, adaptation, and vulnerability. Part A: global and sectoral aspects. Cambridge University Press, Cambridge, p 1132

    Google Scholar 

  • Fischer EM, Beyerle U, Knutti R (2013) Robust spatially aggregated projections of climate extremes. Nat Clim Change 3:1033–1038. https://doi.org/10.1038/nclimate2051

    Article  Google Scholar 

  • Han W, Vialard J, McPhaden MJ, Lee T, Masumoto Y, Feng M, De Ruijter WP (2014) Indian Ocean decadal variability: a review. Bull Am Meteorol Soc 95(11):1679–1703

    Article  Google Scholar 

  • Hersbach H, Bell B, Berrisford P et al (2020) The ERA5 global reanalysis. Q J R Meteorol Soc 146:1999–2049. https://doi.org/10.1002/qj.3803

    Article  Google Scholar 

  • Hewitson BC, Crane RG (2002) Self-organizing maps: applications to synoptic climatology. Clim Res 22(1):13–26

    Article  Google Scholar 

  • Hu Y, Liu Y, Wu Q, Wang X (2017) Preceding oceanic influences on the inter-annual variation of spring persistent rain in Jiangnan of China and the possible mechanism. Chin J Atmos Sci 41(02):395–408 ((in Chinese))

    Google Scholar 

  • Huang G, Qu X, Hu KM (2011) The impact of the tropical Indian Ocean on South Asian high in boreal summer. Adv Atmos Sci 28:421–432. https://doi.org/10.1007/s00376-010-9224-y

    Article  Google Scholar 

  • IPCC (2012) Managing the risks of extreme events and disasters to advance climate change adaptation. A special report of working groups I and II of the intergovernmental panel on climate change. In: Field CB, Barros V, Stocker TF et al (eds) Cambridge University Press, Cambridge, p 582

  • IPCC (2013) Climate change 2013: the physical science basis. Contribution of working group I to the fifth assessment report of the intergovernmental panel on climate change. In: Stocker TF, Qin D, Plattner G-K et al (eds) Cambridge University Press, Cambridge, p 1535

  • Kalnay E, Kanamitsu M, Kistler R et al (1996) The NCEP/NCAR 40-year reanalysis project. Bull Am Meteorol Soc 77:437–471. https://doi.org/10.1175/1520-0477(1996)077%3c0437:TNYRP%3e2.0.CO;2

    Article  Google Scholar 

  • Kendall M (1975) Rank correlation methods, 4th edn. Charles Griffin, London, p 202

    Google Scholar 

  • Kohonen T (2001) Self-organizing maps. Springer, Berlin

    Book  Google Scholar 

  • Kosaka Y, Xie SP, Nakamura H (2011) Dynamics of interannual variability in summer precipitation over East Asia. J Clim 24:5435–5453. https://doi.org/10.1175/2011JCLI4099.1

    Article  Google Scholar 

  • Li J, Su J (2020) Comparison of Indian Ocean warming simulated by CMIP5 and CMIP6 models. Atmos Ocean Sci Lett 13(6):604–611

    Article  Google Scholar 

  • Li C, Zwiers F, Zhang X, Li G (2018) How much information is required to well constrain local estimates of future precipitation extremes? Earth’s Future 7:11–24. https://doi.org/10.1029/2018EF001001

    Article  Google Scholar 

  • Li Y, Ma B, Feng J, Lu Y (2019) Influence of the strongest central Pacific El Niño-Southern Oscillation events on the precipitation in eastern China. Int J Climatol 39:3076–3090. https://doi.org/10.1002/joc.6004

    Article  Google Scholar 

  • Liu MH, Ren LH, Zhang WJ, Ren PF (2018) Influence of super El Niño events on the frequency of spring and summer extreme precipitation over eastern China. Acta Meteorol Sin 76(4):539–553

    Google Scholar 

  • Liu B, Yan Y, Zhu C, Ma S, Li J (2020) Record-breaking Meiyu rainfall around the Yangtze River in 2020 regulated by the subseasonal phase transition of the North Atlantic Oscillation. Geophys Res Lett 47(22):e2020GL090342

    Article  Google Scholar 

  • Lu R, Dong B (2005) Impact of Atlantic sea surface temperature anomalies on the summer climate in the western North Pacific during 1997–1998. J Geophys Res Atmos 110(D16):1–11

    Google Scholar 

  • Lu C, Lott FC, Sun Y, Stott PA, Christidis N (2020) Detectable anthropogenic influence on changes in summer precipitation in China. J Clim 33(13):5357–5369

    Article  Google Scholar 

  • Luo JJ, Sasaki W, Masumoto Y (2012) Indian Ocean warming modulates Pacific climate change. Proc Natl Acad Sci 109(46):18701–18706

    Article  Google Scholar 

  • Ma Y, Chen W, Feng R, Liang J, Liang Y (2012) Interannual and interdecadal variations of precipitation over eastern China during Meiyu season and their relationships with the atmospheric circulation and SST. Chin J Atmos Sci 36(2):397–410 ((in Chinese))

    Google Scholar 

  • Ma SM, Zhou TJ, Stone DA et al (2017) Detectable anthropogenic shift toward heavy precipitation over Eastern China. J Clim 30:1381–1396

    Article  Google Scholar 

  • National Academies of Sciences, Engineering, and Medicine (NAS) (2016) Attribution of extreme weather events in the context of climate change. The National Academies Press, Washington, DC. https://doi.org/10.17226/21852

  • Rayner NA et al (2003) Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J Geophys Res. https://doi.org/10.1029/2002JD002670

    Article  Google Scholar 

  • Ribes A, Terray L, Planton S (2013) Application of regularized optimal fingerprinting to attribution. Part I: method, properties and idealised analysis. Clim Dyn 41(11):2817–2836. https://doi.org/10.1007/s00382-013-1735-7

    Article  Google Scholar 

  • Rong XY, Zhang RH, Li T (2010) Impacts of Atlantic sea surface temperature anomalies on Indo-East Asian summer monsoon-ENSO relationship. Chin Sci Bull 55(22):2458–2468

    Article  Google Scholar 

  • Sen PK (1968) Estimates of the regression coefficient based on Kendall’s Tau. J Am Stat Assoc 63:1379–1389. https://doi.org/10.1080/01621459.1968.10480934

    Article  Google Scholar 

  • Stott PA, Christidis N, Otto FE et al (2016) Attribution of extreme weather and climate-related events. Wires Clim Change 7(1):23–41

    Article  Google Scholar 

  • Takaya Y, Ishikawa I, Kobayashi C, Endo H, Ose T (2020) Enhanced Meiyu-Baiu rainfall in early summer 2020: aftermath of the 2019 super IOD event. Geophys Res Lett 47(22):e2020GL090671

    Article  Google Scholar 

  • Trenberth KE, Dai A, Rasmussen RM, Parsons DB (2003) The changing character of precipitation. Bull Amer Meteor Soc 84(9):1205–1218

    Article  Google Scholar 

  • Walters D, Boutle I, Brooks M et al (2017) The met office unified model global atmosphere 6.0/6.1 and JULES global land 6.0/6.1 configurations. Geosci Model Dev 10(4):1487–1520

    Article  Google Scholar 

  • Wang C (2019) Three-ocean interactions and climate variability: a review and perspective. Clim Dyn 53(7):5119–5136

    Article  Google Scholar 

  • Wang L, Yu JY, Paek H (2017) Enhanced biennial variability in the Pacific due to Atlantic capacitor effect. Nat Commun 8(1):1–7

    Google Scholar 

  • Wang D, Wang A, Xu L, Kong X (2020) The linkage between two types of El Niño events and summer streamflow over the Yellow and Yangtze River Basins. Adv Atmos Sci 37(2):160–172. https://doi.org/10.1007/s00376-019-9049-2

    Article  Google Scholar 

  • Wu J, Gao X (2013) A gridded daily observation dataset over China region and comparison with the other datasets. Chin J Geophys CH 56:1102–1111 ((in Chinese))

    Google Scholar 

  • Wu GX, Liu P, Liu YM, Li WP (2000) Impacts of the sea surface temperature anomaly in the Indian Ocean on the subtropical anticyclone over the western Pacific-Two-stage thermal adaptation in the atmosphere. Acta Meteorol Sin 58(5):513–522. https://doi.org/10.3321/j.issn:0577-6619.2000.05.001.(inChinese)

    Article  Google Scholar 

  • Xie SP, Hu K, Hafner J, Tokinaga H, Du Y, Huang G, Sampe T (2009) Indian Ocean capacitor effect on Indo–western Pacific climate during the summer following El Niño. J Clim 22(3):730–747

    Article  Google Scholar 

  • Xie SP, Kosaka Y, Du Y, Hu K, Chowdary JS, Huang G (2016) Indo-western Pacific ocean capacitor and coherent climate anomalies in post-ENSO summer: a review. Adv Atmos Sci 33(4):411–432

    Article  Google Scholar 

  • Yuan Y, Gao H, Li W, Liu Y, Chen L, Zhou B, Ding Y (2017) The 2016 summer floods in China and associated physical mechanisms: a comparison with 1998. J Meteorol Res 31(2):261–277. https://doi.org/10.1007/s13351-017-6192-5〹

    Article  Google Scholar 

  • Zhai P, Zhang X, Wan H, Pan X (2005) Trends in total precipitation and frequency of daily precipitation extremes over China. J Clim 18:1096–1108. https://doi.org/10.1175/JCLI-3318.1

    Article  Google Scholar 

  • Zhai P, Yu R, Guo Y, Li Q, Ren X, Wang Y, Xu W, Liu Y, Ding Y (2016) The strong El Nino of 2015/16 and its dominant impacts on global and China’s climate. J Meteorol Res 30(3):283–297. https://doi.org/10.1007/s13-351-016-6101-3

    Article  Google Scholar 

  • Zhang X, Zwiers FW, Li G, Wan H, Cannon AJ (2017) Complexity in estimating past and future extreme short-duration rainfall. Nat Geosci 10(4):255–259

    Article  Google Scholar 

  • Zheng J, Wang C (2021) Influences of three oceans on record-breaking rainfall over the Yangtze River Valley in June 2020. Sci China Earth Sci 64(10):1607–1618

    Article  Google Scholar 

  • Zhou B, Zhai P, Chen Y (2020) Contribution of changes in synoptic-scale circulation patterns to the past summer precipitation regime shift in eastern China. Geophys Res Lett 47:e2020GL087728

    Article  Google Scholar 

  • Zhou B, Zhai P, Tett SF, Lott FC (2021a) Detectable anthropogenic changes in daily-scale circulations driving summer rainfall shifts over eastern China. Environ Res Lett 16:074044

    Article  Google Scholar 

  • Zhou ZQ, Xie SP, Zhang R (2021b) Historic Yangtze flooding of 2020 tied to extreme Indian Ocean conditions. Proc Natl Acad Sci 118(12):e2022255118

    Article  Google Scholar 

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Acknowledgements

This study was supported by the National Natural Science Foundation of China (41905082 and U2142205). We acknowledge the World Climate Research Program’s Working Group on Coupled Modeling and thank the climate modeling groups for producing and sharing their model outputs.

Funding

This study was supported by the National Natural Science Foundation of China (41905082 and U2142205).

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Authors and Affiliations

  1. State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, No. 46 Zhong-Guan-Cun South Street, Haidian District, Beijing, 100081, China

    Qian Wang, Panmao Zhai & Baiquan Zhou

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  1. Qian Wang
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  2. Panmao Zhai
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  3. Baiquan Zhou
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Contributions

QW: data collection, methodology, software, data analysis, writing-original draft. PZ: conceptualization, editing, supervision. BZ: methodology, data collection, editing.

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Correspondence to Baiquan Zhou.

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Wang, Q., Zhai, P. & Zhou, B. Attribution of tropical sea surface temperature change on extreme precipitation over the Yangtze River Valley in 2020. Clim Dyn 61, 3417–3429 (2023). https://doi.org/10.1007/s00382-023-06752-4

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