Skip to main content

Advertisement

Log in

Simulation of Indian summer monsoon rainfall, interannual variability and teleconnections: evaluation of CMIP6 models

  • Published:
Climate Dynamics Aims and scope Submit manuscript

Abstract

We analyse the performance of global climate models of 6\(\mathrm{th}\) generation of Coupled Model Intercomparison Project (CMIP6) in simulating climatological summer monsoon rainfall over India, interannual variability (IAV) of all-India summer monsoon rainfall (ISMR) and its teleconnections with rainfall variability over equatorial Pacific and Indian Oceans. The multimodel ensemble mean (MME) of 61 CMIP6 models shows the best skill in simulating mean monsoon rainfall over India compared to the MMEs of 6\(\mathrm{th}\) generation atmosphere-only models (AMIP6) and the previous generations of Atmospheric and Coupled Model Intercomparison Projects (AMIPs and CMIPs). Systematic improvement and reduction in bias are evident from lower to higher AMIPs/CMIPs. Still, there exists dry bias over a narrow region of the monsoon zone of central India besides wet and cold bias over the surrounding oceans. The persistence of errors in atmosphere-only models hints that the source of errors could be with atmosphere models. Fifteen CMIP6 models selected through objective criteria, perform the best in simulating mean monsoon, IAV of ISMR, the strong inverse relationship between ISMR and Boreal summer El Niño-Southern Oscillation (ENSO), and the inverse relationship between all-India rainfall and north–west tropical Pacific rainfall in June. Several models reproduce the dipole structure of Equatorial Indian Ocean Oscillation (EQUINOO) with the centres over western and eastern equatorial Indian Ocean. But, ISMR-EQUINOO relationship in many of them is opposite to the observed. Our analysis implies the need for capturing ISMR-EQUINOO link to improve the simulation of IAV of ISMR which is crucial for reliable monsoon prediction and projection.

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

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

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
Fig. 13
Fig. 14
Fig. 15
Fig. 16

Similar content being viewed by others

References

  • Adler RF, Huffman GJ, Chang A, Ferraro R, Xie P, Janowiak J, Rudolf R, Schneider U, Curtis S, Bolvin D, Gruber A, Susskind J, Arkin P, Nelkin E (2003) The version 2 Global Precipitation Climatology Project (GPCP) monthly precipitation analysis (1979-present). J Hydrometeorol 4:1147–1167

    Article  Google Scholar 

  • Annamalai H, Hamilton H, Sperber KR (2007) The South Asian summer monsoon and its relationship with ENSO in the IPCC AR4 simulations. J Clim 20:1071–1092

    Article  Google Scholar 

  • Ashok K, Guan Z, Saji NH, Yamagata T (2004) Individual and combined influences of ENSO and the indian ocean dipole on the indian summer monsoon. J Clim 17:3141–3155

    Article  Google Scholar 

  • Ashok K, Behera SK, Rao RA, Weng H, Yamagata T (2007) El Niño Modoki and its possible teleconnection. J Geophys Res 112:C11007. https://doi.org/10.1029/2006JC003798

    Article  Google Scholar 

  • Cai W, Cowan T (2013) Why is the amplitude of the Indian Ocean Dipole overly large in CMIP3 and CMIP5 climate models? Geophys Res Lett 40:1200–1205. https://doi.org/10.1002/grl.50208

    Article  Google Scholar 

  • Cess RD, Zhang MH, Potter GL, Barker HW, Coleman RA, Dazlich DA, Genio ADD, Esch M, Fraser JR, Galin V, Gates WL (1993) Uncertainties in carbon dioxide radiative forcing in atmospheric general circulation models. Science 262(5137):1252–1255

    Article  Google Scholar 

  • Charney JG, Shukla J (1981) Predictability of monsoons. In: Pearce RP (ed) Lighthill J. Cambridge University Press, Cambridge

  • Eyring V, Bony S, Meehl GA, Senior CA, Stevens B, Stouffer RJ, Taylor KE (2016) Overview of the coupled model intercomparison project phase 6 (CMIP6) experimental design and organization. Geo Model Dev 9(5):1937–1958

    Article  Google Scholar 

  • Fan L, Liu Q, Wang C, Guo F (2017) Indian Ocean Dipole modes associated with different types of ENSO development. J Clim 30:2233–2249. https://doi.org/10.1175/jcli-d-16-0426.1

    Article  Google Scholar 

  • Fennessy MJ, KinterIII JL, Kirtman B, Marx L, Nigam S, Schneider E, Shukla J, Straus D, Vernekar A, Xue Y, Zhou J (1994) The simulated Indian monsoon: a GCM sensitivity study. J Clim 7(1):33–43

    Article  Google Scholar 

  • Gadgil S, Sajani S (1999) Monsoon precipitation in the AMIP runs. Clim Dyn 14(9):659–689

    Article  Google Scholar 

  • Gadgil S, Francis PA (2016) El Niño and the Indian rainfall in June. Curr Sci 110(6):1010–1022

    Article  Google Scholar 

  • Gadgil S, Vinayachandran PN, Francis PA, Gadgil S (2004) Extremes of the Indian summer monsoon rainfall, ENSO and equatorial Indian Ocean oscillation. Geophys Res Lett 31(12):L12213. https://doi.org/10.1029/2004GL019733

    Article  Google Scholar 

  • Gates L (1992) AMIP: the atmospheric model intercomparison project. Bull Am Meteor Soc 73:1962–1970

    Article  Google Scholar 

  • Gates WL, Boyle JS, Covey C, Dease CG, Doutriaux CM, Drach RS, Fiorino M, Gleckler PJ, Hnilo JJ, Marlais SM, Phillips TJ (1999) An overview of the results of the Atmospheric Model Intercomparison Project (AMIP I). Bull Am Meteorol Soc 80(1):29–56

  • Gates L, Cubasch U, Meehl GA, Mitchell JFB, Stouffer RJ (1993) An intercomparison of the control climates simulated by coupled atmosphere–ocean general circulation models. SGCCM, WCRP-82, WMO/TD 574:51

  • Gilchrist A (1977) The simulation of the Asian summer monsoon by general circulation models. Pure and Appl Geophys 115(5–6):1431–1448

    Article  Google Scholar 

  • Hahn DG, Manabe S (1975) The role of mountains in the south Asian monsoon circulation. J Atmos Sci 32(8):1515–1541

    Article  Google Scholar 

  • Hersbach H, Bell B, Berrisford P, Hirahara S, et al. (2020) The ERA5 global reanalysis. Quart J R Meteorol Soc 146(730 Part A):1999–2049

  • Jain S, Salunke P, Mishra SK, Sahany S, Choudhary N (2019) Advantage of NEX-GDDP over CMIP5 and CORDEX Data: Indian Summer Monsoon. Atmos Res 228:152–160

    Article  Google Scholar 

  • Jayasankar CB, Sajani S, Rajendran K (2015) Robust signals of future projections of Indian summer monsoon rainfall by IPCC AR5 climate models: role of seasonal cycle and interannual variability. Geophys Res Lett 42(9):3513–3520

    Article  Google Scholar 

  • Jourdain NC, Gupta AS, Taschetto AS, Ummenhofer CC, Moise AF, Ashok K (2013) The Indo-Australian monsoon and its relationship to ENSO and IOD in reanalysis data and the CMIP3/CMIP5 simulations. Clim Dyn 41:3073–3102

    Article  Google Scholar 

  • Ju J, Slingo J (1995) The Asian summer monsoon and ENSO. Quart J R Meteorol Soc 121(525):1133–1168

    Article  Google Scholar 

  • Kitoh A, Tokioka T (1987) A simulation of the tropospheric general circulation with the MRI atmospheric general circulation model Part III: the Asian summer monsoon. J Meteorol Soc Jpn II 65(2):167–187

    Article  Google Scholar 

  • Knutti R (2010) The end of model democracy? Clim Change 102(3–4):395–404

    Article  Google Scholar 

  • Knutti R, Sedlacek J, Sanderson BM, Lorenz R, Fischer EM, Eyring V (2017) A climate model projection weighting scheme accounting for performance and interdependence. Geophys Res Lett 44:1909–1918

    Google Scholar 

  • KrishnaKumar K, Rajagopalan B, Hoerling M, Bates G, Cane M (2006) Unraveling the mystery of Indian monsoon failure during El Niño. Science 314(5796):115–119

    Article  Google Scholar 

  • Manabe S, Hahn DG, Holloway JLJ (1974) The seasonal variation of the tropical circulation as simulated by a global model of the atmosphere. J Atmos Sci 31(1):43–83

    Article  Google Scholar 

  • McKenna S, Santoso A, Gupta AS, Taschetto AS, Cai W (2020) Indian Ocean Dipole in CMIP5 and CMIP6: characteristics, biases, and links to ENSO. Sci Rep 10:11500

    Article  Google Scholar 

  • Meehl GA, Covey C, Delworth T, Latif M, McAvaney B, Mitchell JF, Stouffer RJ, Taylor KE (2007) The WCRP CMIP3 multimodel dataset: a new era in climate change research. Bull Am Meteorol Soc 88(9):1383–1394

    Article  Google Scholar 

  • Meehl GA, Moss R, Taylor KE, Eyring V, Stouffer RJ, Bony S, Stevens B (2014) Climate model intercomparisons: preparing for the next phase. EOS Trans Am Geophys Union 95(9):77–78

    Article  Google Scholar 

  • Miller RL, Schmidt GA, Nazarenko LS, Tausnev N, Bauer SE, DelGenio AD, Kelley M, Lo KK, Ruedy R, Shindell DT, Aleinov I, Bleck MBR, Canuto V, Chen Y, Cheng Y, Clune TL, Faluvegi G, Hansen JE, Healy RJ, Kiang NY, Koch D, Lacis AA, LeGrande AN, Lerner J, Menon S, Oinas V, Garcia-Pando CP, Perlwitz JP, Puma MJ, Rind D, Romanou A, Russell GL, Sato M, Sun S, Tsigaridis K, Unger N, Voulgarakis A, Yao MS, Zhang J (2014) CMIP5 historical simulations (1850–2012) with GISS ModelE2. J Adv Model Earth Syst 6:441–478

    Article  Google Scholar 

  • Mishra SK, Sahany S, Salunke P, Kang IS, Jain SJ (2018) Fidelity of CMIP5 multi-model mean in assessing Indian monsoon simulations. Clim Atmos Sci 3(1):1–8

    Google Scholar 

  • Pai DS, Sridhar L, Rajeevan M, Sreejith OP, Satbhai NS, Mukhopadhyay B (2014) Development of a new high spatial resolution (\(0.25 \times 0.25\)) long period (1901–2010) daily gridded rainfall data set over India and its comparison with existing data sets over the region. Mausam 65(1):1–8

  • Palmer TN, Brankovic C, Viterbo P, Miller MJ (1992) Modeling interannual variations of summer monsoons. J Clim 5(5):399–417

    Article  Google Scholar 

  • Parthasarathy B, Munot AA, Kothawale DR (1988) Regression model for estimation of Indian foodgrain production from summer monsoon rainfall. Agric For Meteorol 42(2–3):167–182

    Article  Google Scholar 

  • Rajeevan M, Bhate J, Jaswal AK (2008) Analysis of variability and trends of extreme rainfall events over India using 104 years of gridded daily rainfall data. Geophys Res Lett 35(18):L18707. https://doi.org/10.1029/2008GL035143

    Article  Google Scholar 

  • Rajeevan M, Nanjundiah RS (2009) Coupled model simulations of twentieth century climate of the Indian summer monsoon. Plat Jubilee Spec Vol Ind Acad Sci: 537–567. https://www.ias.ac.in/public/Resources/Other_Publications/Overview/Current_Trends/537-567.pdf

  • Rajendran K, Kitoh A, Mizuta R, Sajani S, Nakazawa T (2008) High-resolution simulation of mean convection and its intraseasonal variability over the tropics in the MRI/JMA 20-km mesh AGCM. J Clim 21(15):3722–3739

    Article  Google Scholar 

  • Rajendran K, Gadgil S, Sajani S (2019) Monsoon season local control on precipitation over warm tropical oceans. Meteor Atmos Phys 131:1451–1465

    Article  Google Scholar 

  • Rajendran K, Kitoh A (2008) Indian summer monsoon in future climate projection by a super high-resolution global model. Curr Sci 95(11):1560–1569

    Google Scholar 

  • Rasmusson EM, Carpenter TH (1982) Variations in tropical sea surface temperature and surface wind fields associated with the Southern Oscillation/El Niño. Mon Weather Rev 110(5):354–384

    Article  Google Scholar 

  • Rayner NA, Parker DE, Horton EB, Folland CK, Alexander LV, Rowell DP, Kent EC, Kaplan A (2003) Global analyses of sea surface temperature, sea ice, and night marine air temperature since the latenineteenth century. J Geophys Res Atmos 108(D14):4407. https://doi.org/10.1029/2002JD002670

    Article  Google Scholar 

  • Reichler T, Kim J (2008) How well do coupled models simulate today’s climate? Bull Am Met Soc 89:303–313

    Article  Google Scholar 

  • Ropelewski CF, Halpert MS (1987) Global and regional scale precipitation patterns associated with the El Niño/Southern oscillation. Mon Weather Rev 115:1606–1626

    Article  Google Scholar 

  • Sajani S, Gadgil S, Francis PA, Rajeevan M (2015) Prediction of Indian rainfall during the summer monsoon season on the basis of links with equatorial Pacific and Indian Ocean climate indices. Env Res Lett 10(9):094004

    Article  Google Scholar 

  • Sajani S, Gadgil S, Rajendran K, Varghese SJ, Kitoh A (2019) Monsoon rainfall over India in June and link with northwest tropical Pacific. Theor Appl Clim 135(3–4):1195–1213

    Google Scholar 

  • Saji NH, Goswami BN, Vinayachandran PN, Yamagata T (1999) A dipole mode in the tropical Indian Ocean. Nature 401(6751):360–363

    Google Scholar 

  • Shashikanth K, Salvi K, Ghosh S, Rajendran K (2014) Do CMIP5 simulations of Indian summer monsoon rainfall differ from those of CMIP3? Atmos Sci Lett 15(2):79–85

    Article  Google Scholar 

  • Shukla J, Mintz Y (1982) Influence of land-surface evapotranspiration on the earth’s climate. Science 215(4539):1498–1501

    Article  Google Scholar 

  • Shukla J, Paolino DA (1983) The southern oscillation and long range forecasting of summer monsoon rainfall over India. Mon Weather Rev 111:1830–1837

    Article  Google Scholar 

  • Shukla J, Wallace M (1983) Numerical simulation of the atmospheric response to equatorial Pacific sea surface temperature anomalies. J Atmos Sci 40(7):1613–1630

    Article  Google Scholar 

  • Shukla J, Fennessy MJ (1994) Simulation and predictability of monsoons. In: Tech Rep WCRP-84 edn. WCRP, Geneva, Switzerland

  • Sikka DR (1980) Some aspects of the large scale fluctuations of summer monsoon rainfall over India in relation to fluctuations in the planetary and regional scale circulation parameters. Proc Indian Acad Sci Earth Planet Sci 89(2):179–195

    Article  Google Scholar 

  • Sikka DR, Gadgil S (1980) On the maximum cloud zone and the ITCZ over Indian longitudes during the southwest monsoon. Mon Weather Rev 108(11):1840–1853

    Article  Google Scholar 

  • Soman MK, Slingo JM (1997) Sensitivity of the Asian summer monsoon to aspects of the sea surface temperature anomalies in the tropical Pacific Ocean. Quart J R Meteor Soc 123:309–336

    Article  Google Scholar 

  • Sperber KR, Palmer TN (1996) Interannual tropical rainfall variability in general circulation model simulations associated with the atmospheric model intercomparison project. J Clim 9(11):2727–2750

    Article  Google Scholar 

  • Sperber KR, Annamalai H, Kang IS, Kitoh A, Moise A, Turner A, Wang B, Zhou T (2013) The Asian summer monsoon: an intercomparison of CMIP5 vs. CMIP3 simulations of the late 20th century. Clim Dyn 41(9–10):2711–2744

    Article  Google Scholar 

  • Stouffer RJ, Eyring V, Meehl GA, Bony S, Senior C, Stevens B, Taylor KE (2017) CMIP5 scientific gaps and recommendations for CMIP6. Bull Am Meteorol Soc 98(1):95–105

    Article  Google Scholar 

  • Taylor KE (2001) Summarizing multiple aspects of model performance in a single diagram. J Geophys Res Atmos 106(D7):7183–7192

    Article  Google Scholar 

  • Taylor KE, Stouffer RJ, Meehl GA (2012) An overview of CMIP5 and the experiment design. Bull Am Meteorol Soc 93(4):485–498

    Article  Google Scholar 

  • Troup AJ (1965) The southern oscillation. Quart J R Meterol Soc 91:490–506

    Article  Google Scholar 

  • Walker GT (1924) Correlations in seasonal variations of weather. I. A further study of world weather. Mem Indian Meteorol Dep 24:275–332

    Google Scholar 

  • Walker GT, Bliss YEW (1932) World Weather V. Mem R Meterol Soc 4(36):53–84

    Google Scholar 

  • Walker J, Rowntree PR (1977) The effect of soil moisture on circulation and rainfall in a tropical model. Quart J R Met Soc 103(435):29–46

    Article  Google Scholar 

  • Wang B, Kang IS, Lee JY (2004) Ensemble simulations of Asian–Australian monsoon variability by 11 AGCMs. J Clim 17(4):803–818

    Article  Google Scholar 

  • Wang G, Cai W, Santoso A (2017) Assessing the impact of model biases on the projected increase in frequency of extreme positive Indian Ocean Dipole Events. J Clim 30:2757–2767. https://doi.org/10.1175/jcli-d-16-0509.1

    Article  Google Scholar 

  • WCRP (1992) Simulation of interannual and intraseasonal monsoon variability. In: WMP/TD-470, WCRP-68, WCRP, Geneva, Switzerland

  • Webster PJ, Magana VO, Palmer TN, Shukla J, Tomas RA, Yanai MU, Yasunari T (1998) Monsoons: processes, predictability, and the prospects for prediction. J Geophys Res Oceans 103(C7):14451–14510

    Article  Google Scholar 

  • Webster PJ, Moore AW, Loschnigg JP, Leben RR (1999) Coupled ocean-atmosphere dynamics in the Indian Ocean during 1997–1998. Nature 401:356–360

    Article  Google Scholar 

  • Yang J, He S, Bao Q (2021) Convective/large-scale rainfall partitions of tropical heavy precipitation in CMIP6 atmospheric models. Adv Atmos Sci 38:1020–1027

    Article  Google Scholar 

  • Yang B, Zhang Y, YQian, Song F, Leung LR, Wu P, Guo Z, Lu Y, Huang A (2019) Better monsoon precipitation in coupled climate models due to bias compensation. npj Clim Atmos Sci 2(43). https://doi.org/10.1038/s41612-019-0100-x

Download references

Acknowledgements

This study is supported by MoES National Monsoon Mission Phase II project GAP-1013. We acknowledge the World Climate Research Programme which is responsible for CMIP6, and all the climate modelling groups (listed in Tables 1, 2, 3, 4, 5) for making available their model datasets (https://esgf-node.llnl.gov/search/cmip6/).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Kavirajan Rajendran.

Ethics declarations

Conflict of interest

The authors declare that there are no conflicts of interest.

Additional information

Publisher's Note

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

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (pdf 15555 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Rajendran, K., Surendran, S., Varghese, S.J. et al. Simulation of Indian summer monsoon rainfall, interannual variability and teleconnections: evaluation of CMIP6 models. Clim Dyn 58, 2693–2723 (2022). https://doi.org/10.1007/s00382-021-06027-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00382-021-06027-w

Keywords

Navigation

pFad - Phonifier reborn

Pfad - The Proxy pFad of © 2024 Garber Painting. All rights reserved.

Note: This service is not intended for secure transactions such as banking, social media, email, or purchasing. Use at your own risk. We assume no liability whatsoever for broken pages.


Alternative Proxies:

Alternative Proxy

pFad Proxy

pFad v3 Proxy

pFad v4 Proxy