Skip to main content
Log in

March of buoyancy elements during extreme rainfall over India

Climate Dynamics Aims and scope Submit manuscript

Cite this article


A major rain storm in Uttarakhand (India) caused heavy rains and major loss of life from floods and land slide during 16–18 June, 2013. The observed daily maximum rainfall rates (3-hourly) during the 16th and 17th June were 220 and 340 mm respectively. This event is addressed via sensitivity studies using a cloud resolving non-hydrostatic model with detailed microphysics. The streaming of moist air from the east-south-east and warmer air from the south-west contributed to the sustained large population and amplitude of buoyancy and the associated CAPE contributed to the longer period of heavy rains. This study addresses the concept of Buoyancy as a means for large vertical accelerations, stronger vertical motions, extreme rain rates and the mechanisms that relate to the time rates of change. A post-processing algorithm provides an analysis of time rate of change for the buoyancy. Moist air streams and warm/moist air intrusions into heavily raining clouds are part of this buoyancy enhancement framework. Improvements in modeling of the extreme rain event came from adaptive observational strategy that showed lack of moisture data sets in these vital regions. We show that a moist boundary layer near the Bay of Bengal leads to moist rivers of moisture where the horizontal convergence confines a large population of buoyancy elements with large magnitudes of buoyancy that streams towards the region of extreme orographic rains. The areas covered in this study include: (i) Use of high resolution cloud modeling (1-km), (ii) Now casting of rains using physical initialization with a Newtonian relaxation, (iii) Use of an adaptive observational strategy, (iii) Sensitivity of the evolution of fields and population of buoyancy elements to boundary layer moisture, (iv) Role of orography and details of buoyancy budget.

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.

Institutional subscriptions

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
Fig. 17
Fig. 18


  • Baumhefner DP (1988) Forecast skill and predictability at the extended range using Monte-Carlo ensemble integrations from a general circulation model. In: ECMWF workshop ‘predictibility in the medium and extended range’, 16–18 May 1988, pp 25–44

  • Biswas MK, Krishnamurti TN (2010) Distinguishing developing versus non-developing African easterly waves using adaptive observational strategies. Mar Geod 33:356–377

    Article  Google Scholar 

  • Dash SK, Kulkarni MA, Mohanty UC, Prasad K (2009) Changes in the characteristics of rain events in India. J Geophys Res 114:D10. doi:10.1029/2008JD010572

    Article  Google Scholar 

  • Draxler RR, Hess GD (1998) An overview of the HYSPLIT_4 modeling system of trajectories, dispersion, and deposition. Aust Meteorol Mag 47:295–308

    Google Scholar 

  • Dube A, Ashrit R, Ashish A, Sharma K, Iyengar GR, Rajagopal EN, Basu S (2014) Forecasting the heavy rainfall during Himalayan flooding—June 2013. Weather Clim Extrem 4:22–34. doi:10.1016/j.wace.2014.03.004

    Article  Google Scholar 

  • Dudhia J (1989) Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model. J Atmos Sci 46:3077–3107

    Article  Google Scholar 

  • DurgaRao KHV, Rao VV, Dadhwal VK, Diwakar PG (2014) Kedarnath flash floods: a hydrological and hydraulic simulation study. Curr Sci 106:598–603

    Google Scholar 

  • Hong S-Y, Pan H-L (1996) Nonlocal boundary layer vertical diffusion in a medium-range forecast model. Mon Weather Rev 124:2322–2339

    Article  Google Scholar 

  • Houze RA Jr, Wilton DC, Smull BF (2007) Monsoon convection in the Himalayan region as seen by the TRMM precipitation radar. Q J R Meteorol Soc 133:1389–1411

    Google Scholar 

  • Houze RA Jr, Rasmussen KL, Medina S, Brodzik SR, Romatschke U (2011) Anomalous atmospheric events leading to the summer 2010 floods in Pakistan. Bull Am Meteorol Soc 92:291–298

    Article  Google Scholar 

  • Kain JS, Fritsch JM (1993) Convective parameterization for mesoscale models: the Kain–Fritsch scheme. In: Emanuel KA, Raymond DJ (eds) The representation of cumulus convection in numerical models, chap 16, vol 24. AMS Press, Boston

    Google Scholar 

  • Kotal SD, SenRoy S, Roy Bhowmik SK (2014) Catastrophic heavy rainfall episode over Uttarakhand during 16–18 June 2013—observational aspects. Curr Sci 107:1–12

    Google Scholar 

  • Krishnamurti TN, Kumar J (2016) Physical initialization in tropical cyclone forecasting. In: Mohanty UC, Gopalakrishnan (eds) Advanced numerical modeling and data assimilation techniques for tropical cyclone predictions. Capital Publishing Company, New Delhi, India, p 450

  • Krishnamurti TN, Xue J, Bedi HS, Ingles K, Oosterhof D (1991) Physical initialization for numerical weather prediction over the tropics. Tellus 43A:53–81

    Article  Google Scholar 

  • Krishnamurti TN, Bedi HS, Rohaly GD, Ingles K, Oosterhof D, Torres RC, Williford E, Surgi N (1997) Physical initialization. Atmos Ocean 35:369–398. doi:10.1080/07055900.1997.9687357

    Article  Google Scholar 

  • Krishnamurti TN, Stefanova L, Misra V (2013) Tropical meteorology: an introduction. Springer, Berlin

    Book  Google Scholar 

  • Lau K-M, Wu H-T (2011) Climatology and changes in tropical oceanic rainfall characteristics inferred from Tropical Rainfall Measuring Mission (TRMM) data (1998–2009). J Geophys Res 116:D17111. doi:10.1029/2011JD015827

    Article  Google Scholar 

  • Lin Y-L, Rareley RD, Orville HD (1983) Bulk parameterization of the field in a cloud model. J Appl Meteorol 22:1065–1092

    Article  Google Scholar 

  • Mitra AK, Bohra AK, Rajeevan M, Krishnamurti TN (2009) Daily Indian precipitation analyses formed from a merged of rain-gauge with TRMM TMPA satellite derived rainfall estimates. J Meteorol Soc Japan 87A:265–279

    Article  Google Scholar 

  • Mlawer EJ, Taubman SJ, Brown PD, Iacono MJ, Clough SA (1997) Radiative transfer for inhomogeneous atmosphere: RRTM, a validated correlated-k model for the longwave. J Geophys Res 102:16663–16682

    Article  Google Scholar 

  • Mullen SL, Baumhefner DP (1994) Monte Carlo simulations of explosive cyclogenesis. Mon Weather Rev 122:1548–1568

    Article  Google Scholar 

  • Nesbitt SW, Anders AM (2009) Very high resolution precipitation climatologies from the Tropical Rainfall Measuring Mission precipitation radar. Geophys Res Lett 36:L15815. doi:10.1029/2009GL038026

    Article  Google Scholar 

  • Rajeevan M, Bhate MJ, 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:L18707. doi:10.1029/2008GL035143

    Article  Google Scholar 

  • IMD Report (2013) A preliminary report on heavy rainfall over Uttarakhand during 16–18 June 2013. Accessed 20 Mar 2014

  • Senroy S, Balling RC Jr (2004) Trends in extreme daily precipitation indices in India. Int J Climatol 24:457–466

    Article  Google Scholar 

  • Susmitha J, Sahai AK, Sharmila S, Abhilash S, Borah N, Chattopadhyay R, Pillai PA, Rajeevan M, Kumar A (2014) North Indian heavy rainfall event during June 2013: diagnostics and extended range prediction. Clim Dyn 44:2049–2065

    Google Scholar 

  • Tao W-K, Anderson D, Chern J, Estin J, Hou A, Houser P, Kakar R, Lang S, Lau W, Peters-Lidard C, Li X, Matsui T, Shen B-W, Shi J-J, Zeng X (2009) Goddard multi-scale modeling systems with unified physics. Ann Geophys 27:3055–3064

    Article  Google Scholar 

  • Zhang Z, Krishnamurti TN (2000) Adaptive observations for hurricane prediction. Meterol Atmos Phys 74:19–35

    Article  Google Scholar 

Download references


This work is supported from three research grants to Florida State University, Ministry of Earth Sciences, Government of India MM/SERP/FSU-USA/2013/INT-8/002, NSF Grant Number AGS-1047282, and NASA Grant No. NNX13AQ40G.

Author information

Authors and Affiliations


Corresponding author

Correspondence to T. N. Krishnamurti.

Rights and permissions

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Krishnamurti, T.N., Kumar, V., Simon, A. et al. March of buoyancy elements during extreme rainfall over India. Clim Dyn 48, 1931–1951 (2017).

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: