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Understanding the interannual variations of the zonal mean Indian summer monsoon seasonal rainfall

  • Sarvesh DubeyEmail author
  • Vasubandhu Misra
Article

Abstract

In this study, we seek to understand the variations of the zonal mean Indian summer monsoon (ISM). It is observed that the zonal mean precipitation anomalies explain about 20–30% of the total seasonal precipitation of the ISM. Additionally, we also show that the interannual anomalies of the ISM, at least for some of the most extreme seasons display significant zonal symmetry. Therefore, understanding the interannual variations of the zonal mean precipitation is quite relevant. Furthermore, the reduced and simplified dimensionality of the zonally symmetric framework is an additional attraction. Our study shows that the zonal mean precipitation anomalies of the ISM are significantly correlated with the corresponding anomalies of the vertically integrated moist static energy (H) at interannual scales. The forcing terms of the tendency of the zonal mean H of the ISM is dominated by the meridional flux of H by the Hadley cell followed by comparably smaller, yet, significant forcing terms of transverse boundary and vertical fluxes of H. We find that the individual correlations of the zonal mean precipitation anomalies of the ISM with each of these dominant terms of H are comparably weak in the core latitudes of the ISM. But some of the relatively weaker forcing terms of H like the radiative heating and the diffusion of the enthalpy fluxes display a very strong relationship with the corresponding zonal mean precipitation anomalies. These results suggest that although the description of the regional Hadley cell offers a heuristic model to describe the ISM variation, it belies the intricacies of the forcing terms that maintain it. Our study suggests that the challenge of the ISM seasonal rainfall anomaly prediction even in a reduced dimensional space of a zonally symmetric framework requires all the forcing terms of H with reasonable fidelity, irrespective of their contribution to the variations of H.

Notes

Acknowledgements

This work was partially funded by National Science Foundation Grant 1606296. First author received support from Department of Science & Technology, India under INSPIRE Faculty scheme (DST/INSPIRE/04/2017/001997).

References

  1. Adames AF, Ming Y (2018) Moisture and moist static energy budgets of south asian monsoon low pressure systems in GFDL AM4.0. J Atmos Sci 75:2107–2123.  https://doi.org/10.1175/JAS-D-17-0309.1 CrossRefGoogle Scholar
  2. Bretherton CS, Smolarkiewicz PK (1989) Gravity waves, compensating subsidence and detrainment around cumulus clouds. J Atmos Sci 46:740–759.  https://doi.org/10.1175/1520-0469(1989)046,0740:GWCSAD.2.0.CO;2 CrossRefGoogle Scholar
  3. Bretherton CS, Peters ME, Back LE (2004) Relationships between water vapor path and precipitation over the tropical oceans. J Climate 17:1517–1528CrossRefGoogle Scholar
  4. Dee DP et al (2011) The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q J R Meteorol Soc 137(656):553–597CrossRefGoogle Scholar
  5. Goswami BN (1994) Dynamical predictability of seasonal monsoon rainfall: problems and prospects. Proc Indian Natl Sci Acad 60:101–120Google Scholar
  6. Goswami BN, Xavier PK (2003) Potential predictability and extended range prediction of Indian summer monsoon breaks. Geophys Res Lett 30(18):1966.  https://doi.org/10.1029/2003GL017.810.2003 CrossRefGoogle Scholar
  7. Goswami BN, Krishnamurthy V, Annamalai H (1999) A broad-scale circulation index for the interannual variability of the Indian summer monsoon. R Meteorol Soc 125:611–633CrossRefGoogle Scholar
  8. Hadley G (1735) Concerning the cause of the general trade-winds. Philos Trans 29:58–62Google Scholar
  9. Held IM, Hou AY (1980) Nonlinear axially symmetric circulations in a nearly inviscid atmosphere. J Atmos Sci 37:515–533.  https://doi.org/10.1175/1520-0469(1980)0372.0.CO;2 CrossRefGoogle Scholar
  10. Inoue K, Back L (2015) Column-integrated moist static energy budget analysis on various time scales during TOGA COARE. J Atmos Sci 72:1856–1871CrossRefGoogle Scholar
  11. Johanson CM, Fu Q (2009) Hadley cell widening: model simulations versus observations. J Climate 22:2713–2725.  https://doi.org/10.1175/2008JCLI2620.1 CrossRefGoogle Scholar
  12. Johnson RH, Ciesielski PE (2000) Rainfall and radiative heating rates from TOGA COARE atmospheric budgets. J Atmos Sci 57:1497–1514.  https://doi.org/10.1175/1520-0469(2000)057,1497:RARHRF.2.0.CO;2 CrossRefGoogle Scholar
  13. Joseph PV (1978) Subtropical westerlies in relation to large scale failure of Indian summer monsoon. Indian J Meteorol Hydrol Geophys 29:412–418Google Scholar
  14. Kang I-S, An I-S, Jin F-F (2001) A systematic approximation of the SST anomaly equation for ENSO. J Meteorol Soc Japan 79:1–10CrossRefGoogle Scholar
  15. Kiranmayi L, Maloney ED (2011) Intraseasonal moist static energy budget in reanalysis data. J Geophys Res 116:D21117.  https://doi.org/10.1029/2011JD016031 CrossRefGoogle Scholar
  16. Krishnamurthy V, Goswami BN (2000) Indian monsoon–ENSO relationship on interdecadal timescale. J Climate 13:579–595.  https://doi.org/10.1175/1520-0442(2000)013%3c0579:IMEROI%3e2.0.CO;2 CrossRefGoogle Scholar
  17. Krishnamurthy V, Shukla J (2000) Intraseasonal and interannual variability of rainfall over India. J Climate 13:4366–4377.  https://doi.org/10.1175/1520-0442(2000)013%3c0001:IAIVOR%3e2.0.CO;2 CrossRefGoogle Scholar
  18. Krishnamurthy V, Shukla J (2007) Intraseasonal and seasonally persisting patterns of Indian monsoon rainfall. J Climate 20:3–20.  https://doi.org/10.1175/JCLI3981.1 CrossRefGoogle Scholar
  19. Li J, Wang B (2016) How predictable is the anomaly pattern of the Indian summer rainfall? Climate Dyn.  https://doi.org/10.1007/s00382-015-2735-6 Google Scholar
  20. Lorenz EN (1967) The nature and theory of the general circulation in the atmosphere. WMO Publ, p 218Google Scholar
  21. Lu J, Vecchi GA, Reichler T (2007) Expansion of the Hadley cell under global warming. Geophys Res Lett 34:L06805.  https://doi.org/10.1029/2006GL028443 Google Scholar
  22. Neelin JD, Held IM (1987) Modeling tropical convergence based on the moist static energy budget. Mon Weather Rev 115:3–12CrossRefGoogle Scholar
  23. Nigam S, Ruiz-Barradas A, Sengupta A (2018) Laboratory for experimental hydroclimate prediction. http://monsoon.umd.edu
  24. Oort AH, Rasmusson EM (1970) On the annual variation of the monthly mean meridional circulation. Mon Weather Rev 98:423–442CrossRefGoogle Scholar
  25. Oort AH, Yienger JJ (1996) Observed interannual variability in the Hadley circulation and its connection to ENSO. J Climate 9:2751–2767CrossRefGoogle Scholar
  26. Palmen EH (1963) General circulation of the tropics. In: Proceedings of the symposium on tropical meteorology, Rotorua, November 1963, Wellington, pp 3–30Google Scholar
  27. Palmen EH, Vuorela L (1963) On the mean meridional circulations in the northern hemisphere during the winter season. Q J Roy Meteorol Soc 89:131–138CrossRefGoogle Scholar
  28. Rajeevan M, Gadgil S, Bhate J (2010) Active and break spells of the Indian summer monsoon. J Earth Syst Sci 119:229–247CrossRefGoogle Scholar
  29. Raymond DJ (2000) Thermodynamic control of tropical rainfall. Q J R Meteorol Soc 126:889–898.  https://doi.org/10.1002/qj.49712656406 CrossRefGoogle Scholar
  30. Riehl H (1963) Stationary aspects of the tropical general circulation. Geofisica Internacional 3(3/4):53–68Google Scholar
  31. Schulmann LI (1973) On the summer hemisphere Hadley cell. R Meteorol Soc 99:197–201CrossRefGoogle Scholar
  32. Slingo JM, Annamalai H (2000) 1997: the El Niño of the century and the response of the Indian summer monsoon. Mon Weather Rev 128:1778–1797CrossRefGoogle Scholar
  33. Sobel AH, Bretherton CS (2000) Modeling tropical precipitation in a single column. J Climate 13:4378–4392.  https://doi.org/10.1175/1520-0442(2000)013,4378:MTPIAS.2.0.CO;2 CrossRefGoogle Scholar
  34. Sobel A, Wang S, Kim D (2014) Moist static energy budget of the MJO during DYNAMO. J Atmos Sci 71:4276–4291CrossRefGoogle Scholar
  35. Tucker GB (1959) Mean meridional circulations in the atmosphere. Q J R Meteorol. Soc 85:209–224.  https://doi.org/10.1002/qj.49708536504 CrossRefGoogle Scholar
  36. Vuorela LA, Tuominen I (1964) On the mean zonal and meridional circulations and the flux of moisture in the northern hemisphere during the summer season. Pure Appl Geophys 57:167–180CrossRefGoogle Scholar
  37. Waliser DE, Shi Z, Lanzante JR, Oort AH (1999) The Hadley circulation: assessing NCEP/NCAR reanalysis and sparse in situ estimates. Climate Dyn 15:719–735CrossRefGoogle Scholar
  38. Wang B, Xiang BQ, Li J, Webster PJ, Rajeevan MN, Liu J, Ha KJ (2015) Rethinking Indian monsoon rainfall prediction in the context of recent global warming. Nat Commun 6:7154.  https://doi.org/10.1038/ncomms8154 CrossRefGoogle Scholar
  39. Waugh DW, Garfinkel CI, Polvani LM (2015) Drivers of the recent tropical expansion in the southern hemisphere: changing SSTs or ozone depletion? J Climate 28:6581–6586 (in press) CrossRefGoogle Scholar
  40. Webster PJ, Yang S (1992) Monsoon and Enso: selectively interactive systems. Q J R Meteorol Soc 118:877–926.  https://doi.org/10.1002/qj.49711850705 CrossRefGoogle Scholar
  41. Webster PJ, Magana VO, Palmer TN, Shukla J, Tomas RA, Yanai TM, Yasunari T (1998) Monsoons: processes, predictability, and the prospects for prediction. J Geophys Res 103:14451–14510CrossRefGoogle Scholar
  42. Yanai M, Esbensen S, Chu J (1973) Determination of bulk properties of tropical cloud clusters from large-scale heat and moisture budgets. J Atmos Sci 30:611–627.  https://doi.org/10.1175/1520-0469(1973)030%3c0611:DOBPOT%3e2.0.CO;2 CrossRefGoogle Scholar
  43. Yasunaga K, Mapes B (2012) Differences between more divergent and more rotational types of convectively coupled equatorial waves. Part I: space-time spectral analyses. J Atmos Sci 69:3–16.  https://doi.org/10.1175/JAS-D-11-033.1 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Centre for Atmospheric SciencesIndian Institute of Technology DelhiNew DelhiIndia
  2. 2.Department of Earth, Ocean and Atmospheric ScienceFlorida State UniversityTallahasseeUSA
  3. 3.Center for Ocean-Atmospheric Prediction StudiesFlorida State UniversityTallahasseeUSA
  4. 4.Florida Climate InstituteFlorida State UniversityTallahasseeUSA

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