Skip to main content
Log in

Understanding Dynamical Properties of Cumulus Clouds Over the Bay of Bengal

  • Published:
Pure and Applied Geophysics Aims and scope Submit manuscript

Abstract

An idealized large eddy simulation (LES) has been performed to understand the dynamics of cumulus clouds over the Bay of Bengal using the Weather Research and Forecasting (WRF) model. Cumulus clouds play a key role in the atmospheric convection process. However, despite their importance, they are not well represented in global climate models (GCMs). Moreover, cumulus clouds involve a transition from shallow to deep clouds (or congestus clouds), and GCMs are unable to capture this phenomenon. The development of cumulus clouds is very pronounced over the Bay of Bengal region, and its dynamics has not yet been fully explored. In the present study, a gradual transition phenomenon of shallow cumulus to deep cumulus (congestus) at the development stage and understanding the evolution of clouds and flux transport is investigated. Different cloud parameters at shallow and deep cumulus congestus stages are examined. It is observed that the shallow clouds have a higher magnitude of entrainment than that of deep clouds, and the rate of decrease in entrainment with height is also higher for the shallow clouds. Moreover, the detrainment rate is higher in the case of shallow cumulus clouds as well. This means that as the clouds have transitioned from shallow cumulus to deep congestus clouds, both entrainment and detrainment rates decrease. This important finding will be quite useful in developing future parameterizations for cumulus clouds. A negative correlation between the entrainment rate and cloud core vertical velocity is observed which is supported by previous studies.

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

Similar content being viewed by others

Data availability

Data can be made available on request.

References

  • Arakawa, A., & Schubert, W. H. (1974). Interaction of a cumulus cloud ensemble with the large-scale environment part I. Journal of the Atmospheric Sciences, 31(3), 674–701.

    Article  Google Scholar 

  • Bera, S. (2021). Droplet spectral dispersion by lateral mixing process in continental deep cumulus clouds. Journal of Atmospheric and Solar Terrestrial Physics, 214, 105550. https://doi.org/10.1016/j.jastp.2021.105550

    Article  Google Scholar 

  • Bera, S., & Prabha, T. V. (2019). Parameterization of entrainment rate and mass flux in continental cumulus clouds: Inference from large eddy simulation. Journal of Geophysical Research Atmospheres, 124(23), 13127–13139.

    Article  Google Scholar 

  • Betts, A. K. (1975). Parametric interpretation of trade-wind cumulus budget studies. Journal of Atmospheric Sciences, 32(10), 1934–1945.

    Article  Google Scholar 

  • Bhat, G. S., Gadgil, S., Kumar, P. H., Kalsi, S. R., Madhusoodanan, P., Murty, V. S. N., Rao, C. P., Babu, V. R., Rao, L. V. G., Rao, R. R., & Ravichandran, M. (2001). BOBMEX: The Bay of Bengal monsoon experiment. Bulletin of the American Meteorological Society, 82(10), 2217–2244.

    Article  Google Scholar 

  • Böing, S. J., Jonker, H. J., Siebesma, A. P., & Grabowski, W. W. (2012). Influence of the subcloud layer on the development of a deep convective ensemble. Journal of the Atmospheric Sciences, 69(9), 2682–2698.

    Article  Google Scholar 

  • Dawe, J. T., & Austin, P. H. (2013). Direct entrainment and detrainment rate distributions of individual shallow cumulus clouds in an LES. Atmospheric Chemistry and Physics, 13(15), 7795–7811.

    Article  Google Scholar 

  • De Rooy, W. C., Bechtold, P., Fröhlich, K., Hohenegger, C., Jonker, H., Mironov, D., Pier Siebesma, A., Teixeira, J., & Yano, J. I. (2013). Entrainment and detrainment in cumulus convection: An overview. Quarterly Journal of the Royal Meteorological Society, 139(670), 1–19.

    Article  Google Scholar 

  • Derbyshire, S. H., Beau, I., Bechtold, P., Grandpeix, J. Y., Piriou, J. M., Redelsperger, J. L., & Soares, P. M. M. (2004). Sensitivity of moist convection to environmental humidity. Quarterly Journal of the Royal Meteorological Society A Journal of the Atmospheric Sciences, Applied Meteorology and Physical Oceanography, 130(604), 3055–3079.

    Google Scholar 

  • Fiedler, S., Crueger, T., D’Agostino, R., Peters, K., Becker, T., Leutwyler, D., Paccini, L., Burdanowitz, J., Buehler, S. A., Cortes, A. U., & Dauhut, T. (2020). Simulated tropical precipitation assessed across three major phases of the coupled model intercomparison project (CMIP). Monthly Weather Review, 148(9), 3653–3680.

    Article  Google Scholar 

  • Gregory, D., Kershaw, R., & Inness, P. M. (1997). Parametrization of momentum transport by convection. II: Tests in single-column and general circulation models. Quarterly Journal of the Royal Meteorological Society, 123(541), 1153–1183.

    Article  Google Scholar 

  • Hawkins, E., & Sutton, R. (2011). The potential to narrow uncertainty in projections of regional precipitation change. Climate Dynamics, 37(1), 407–418.

    Article  Google Scholar 

  • Hohenegger, C., & Stevens, B. (2013). Preconditioning deep convection with cumulus congestus. Journal of the Atmospheric Sciences, 70(2), 448–464.

    Article  Google Scholar 

  • Johnson, R. H., Rickenbach, T. M., Rutledge, S. A., Ciesielski, P. E., & Schubert, W. H. (1999). Trimodal characteristics of tropical convection. Journal of Climate, 12(8), 2397–2418.

    Article  Google Scholar 

  • Khairoutdinov, M. F., Krueger, S. K., Moeng, C. H., Bogenschutz, P. A., & Randall, D. A. (2009). Large-eddy simulation of maritime deep tropical convection. Journal of Advances in Modeling Earth Systems, 1, 4.

    Google Scholar 

  • Khairoutdinov, M., & Randall, D. (2006). High-resolution simulation of shallow-to-deep convection transition over land. Journal of the Atmospheric Sciences, 63(12), 3421–3436.

    Article  Google Scholar 

  • Kirshbaum, D. J. (2011). Cloud-resolving simulations of deep convection over a heated mountain. Journal of the Atmospheric Sciences, 68(2), 361–378.

    Article  Google Scholar 

  • Kuang, Z., & Bretherton, C. S. (2006). A mass-flux scheme view of a high-resolution simulation of a transition from shallow to deep cumulus convection. Journal of the Atmospheric Sciences, 63(7), 1895–1909.

    Article  Google Scholar 

  • Lim, K. S. S., & Hong, S. Y. (2010). Development of an effective double-moment cloud microphysics scheme with prognostic cloud condensation nuclei (CCN) for weather and climate models. Monthly Weather Review, 138(5), 1587–1612.

    Article  Google Scholar 

  • Lu, C., Liu, Y., Zhang, G. J., Wu, X., Endo, S., Cao, L., & Guo, X. (2016). Improving parameterization of entrainment rate for shallow convection with aircraft measurements and large-eddy simulation. Journal of the Atmospheric Sciences, 73(2), 761–773.

    Article  Google Scholar 

  • Masunaga, H., L’Ecuyer, T. S., & Kummerow, C. D. (2005). Variability in the characteristics of precipitation systems in the tropical Pacific. Part I: Spatial structure. Journal of Climate, 18(6), 823–840.

    Article  Google Scholar 

  • Murata, A., & Ueno, M. (2005). The vertical profile of entrainment rate simulated by a cloud-resolving model and application to a cumulus parameterization. Journal of the Meteorological Society of Japan, 83(5), 745–770.

    Google Scholar 

  • Neggers, R. A. J., Siebesma, A. P., & Jonker, H. J. J. (2002). A multiparcel model for shallow cumulus convection. Journal of the Atmospheric Sciences, 59(10), 1655–1668.

    Article  Google Scholar 

  • Ooyama, K. (1971). A theory on parameterization of cumulus convection. Journal of the Meteorological Society of Japan Series II, 49, 744–756.

    Article  Google Scholar 

  • Rieck, M., Hohenegger, C., & van Heerwaarden, C. C. (2014). The influence of land surface heterogeneities on cloud size development. Monthly Weather Review, 142(10), 3830–3846.

    Article  Google Scholar 

  • Riehl, H., & Malkus, J. (1961). Some aspects of hurricane Daisy, 1958. Tellus, 13(2), 181–213.

    Article  Google Scholar 

  • Schiro, K. A., & Neelin, J. D. (2019). Deep convective organization, moisture vertical structure, and convective transition using deep-inflow mixing. Journal of the Atmospheric Sciences, 76(4), 965–987.

    Article  Google Scholar 

  • Siebesma, A. P., Bretherton, C. S., Brown, A., Chlond, A., Cuxart, J., Duynkerke, P. G., et al. (2003). A large-eddy simulation intercomparison study of shallow cumulus convection. Journal of the Atmospheric Sciences, 60(10), 1201–1219.

    Article  Google Scholar 

  • Siebesma, A. P., & Cuijpers, J. W. M. (1995). Evaluation of parametric assumptions for shallow cumulus convection. Journal of Atmospheric Sciences, 52(6), 650–666.

    Article  Google Scholar 

  • Stirling, A. J., & Stratton, R. A. (2012). Entrainment processes in the diurnal cycle of deep convection over land. Quarterly Journal of the Royal Meteorological Society, 138(666), 1135–1149.

    Article  Google Scholar 

  • Stull, R. B. (1988). An Introduction to Boundary Layer Meteorology (Vol. 13). Springer.

    Book  Google Scholar 

  • Sukanya, P., & Kalapureddy, M. C. R. (2021). Cloud radar observations of multi-scale variability of cloud vertical structure associated with Indian summer monsoon over a tropical location. Climate Dynamics, 56, 1055–1081. https://doi.org/10.1007/s00382-020-05520-y

    Article  Google Scholar 

  • Tan, Z., Kaul, C. M., Pressel, K. G., Cohen, Y., Schneider, T., & Teixeira, J. (2018). An extended eddy-diffusivity mass-flux scheme for unified representation of subgrid scale turbulence and convection. Journal of Advances in Modeling Earth Systems, 10, 770–800.

    Article  Google Scholar 

  • Tompkins, A. M. (2001). Organization of tropical convection in low vertical wind shears: The role of cold pools. Journal of the Atmospheric Sciences, 58(13), 1650–1672.

    Article  Google Scholar 

  • Wu, X., Deng, L., Song, X., & Zhang, G.-J. (2007). Coupling of convective momentum transport with convective heating in global climate simulations. Journal of the Atmospheric Sciences, 64, 1334–1349.

    Article  Google Scholar 

  • Yang, S., & Smith, E. A. (2006). Mechanisms for diurnal variability of global tropical rainfall observed from TRMM. Journal of Climate, 19(20), 5190–5226.

    Article  Google Scholar 

  • Zhang, G. J., & Mu, M. (2005). Simulation of the Madden–Julian oscillation in the NCAR CCM3 using a revised Zhang–McFarlane convection parameterization scheme. Journal of Climate, 18(19), 4046–4064.

    Article  Google Scholar 

  • Zhang, Y., & Klein, S. A. (2010). Mechanisms affecting the transition from shallow to deep convection over land: Inferences from observations of the diurnal cycle collected at the ARM Southern Great Plains site. Journal of the Atmospheric Sciences, 67(9), 2943–2959.

    Article  Google Scholar 

  • Zhuang, Y., Fu, R., Marengo, J. A., & Wang, H. (2017). Seasonal variation of shallow-to-deep convection transition and its link to the environmental conditions over the Central Amazon. Journal of Geophysical Research Atmospheres, 122(5), 2649–2666.

    Article  Google Scholar 

Download references

Acknowledgements

The authors thank the IIT Delhi HPC facility for computational resources and G.S. Bhat for providing BOBMEX data. The research has been partially funded by the DST Centre of Excellence in Climate Modeling at the Indian Institute of Technology Delhi, New Delhi, India. The Indian Institute of Tropical Meteorology is funded by the Ministry of Earth Sciences, Govt. of India.

Author information

Authors and Affiliations

Authors

Contributions

GD and SB conceptualized the work. GD performed computations, prepared figures and wrote the manuscript. SB helped in preparing the manuscript. AD and SS reviewed the manuscript.

Corresponding author

Correspondence to Anupam Dewan.

Ethics declarations

Conflict of interest

The authors declare that they have no known competing financial interests that could have appeared to influence the work reported in this paper.

Additional information

Publisher's Note

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

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

Dogra, G., Bera, S., Dewan, A. et al. Understanding Dynamical Properties of Cumulus Clouds Over the Bay of Bengal. Pure Appl. Geophys. 180, 2915–2926 (2023). https://doi.org/10.1007/s00024-023-03264-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00024-023-03264-4

Keywords

Navigation