Abstract
In the present study, a conventional mixing line analysis is applied to the Indian post monsoon boundary layer, characterized by shallow clouds. Characteristics of a ‘double mixing line’ are investigated with airborne observations and large eddy simulations (LES). The unique aspect of the study is the use of cloud microphysical information together with the traditional mixing line analysis incorporating moist-adiabatic conserved parameters such as equivalent potential temperature (θE) and total water mixing ratio (qT). The LES results showed that the double mixing line structure strengthened in cloudy regions, compared to the cloud-free regions. The increasing cloud condensation nuclei (CCN) concentration has impacted the double mixing line structure of the cloud-free environment by reducing the θE. This increase in CCN also reduced the environmental mixing line through cooling and moistening by the evaporation of droplets near the cloud base. The joint probability density function of cloud base turbulence fields of water vapour and cloud droplet number concentration showed indications of the moistening through downward moving air parcels.
Similar content being viewed by others
References
Bera S and Prabha T V 2019 Parameterization of entrainment rate and mass flux in continental cumulus clouds: Inference from large eddy simulation; J. Geophys. Res. Atmos. 124 13,127–13,139.
Bera S, Prabha T V and Grabowski W W 2016 Observations of monsoon convective cloud microphysics over India and role of entrainment-mixing; J. Geophys. Res. Atmos. 121 9767–9788.
Betts A 1973 Non-precipitating cumulus convection and its parameterization; Q. J. Roy. Meteorol. Soc. 99 178–196.
Betts A 1985 Mixing line analysis of clouds and cloudy boundary layers; J. Atmos. Sci. 42 2751–2763.
Betts A 1986 A new convective adjustment scheme. Part I: Observational and theoretical Basis; Q. J. Roy. Meteorol. Soc. 112 677–691.
Betts A K and Albrecht B A 1987 Conserved variable analysis of boundary layer thermodynamic structure over the tropical oceans; J. Atmos. Sci. 44 83–99.
Blyth A M and Raymond D J 1988 Comparisons between observations of entrainment in Montana cumuli and results from a simple model; J. Atmos. Sci. 45 1965–1969.
Blyth A M, Cooper W A and Jensen J B 1988 A study of the source of entrained air in Montana cumuli; J. Atmos. Sci. 45 3944–3964.
Böing S J, Harm J J, Witek A N and Pier Siebesma A 2014 On the deceiving aspects of mixing diagrams of deep cumulus convection; J. Atmos. Sci. 71 56–68.
Derbyshire S H, Beau I, Bechtold P, Grandpeix J-Y, Piriou J-M, Redelsperger J-L and Soares P M M 2004 Sensitivity of moist convection to environmental humidity; Q. J. Roy. Meteorol. Soc. 130 3055–3079.
Grabowski W W and Pawlowska H 1993 Entrainment and mixing in clouds: The Paluch mixing diagram revisited; J. Appl. Meteorol. 32 1767–1773.
Heus T, Van Dijk G, Jonker H J J and Van den Akker H E A 2008 Mixing in shallow cumulus clouds studied by Lagrangian particle tracking; J. Atmos. Sci. 65 2581–2597.
Jiang H, Xue H, Teller A, Feingold G and Levin Z 2006 Aerosol effects on the lifetime of shallow cumulus; Geophys. Res. Lett. 33 1–4.
Johansson C, Barbara H, Bōsenberg J, Linné H and Smedman A-S 2005 Double-layer structure in the boundary layer over the Baltic sea; Bound. Layer Meteorol. 114 389–412.
Jonker H J J, Heus T and Sullivan P P 2008 A refined view of vertical transport by cumulus convection; Geophys. Res. Lett. 35 1–5.
Kain J S and Fritsch J M 1990 A one-dimensional entraining/detraining plume model and its application in convective parameterization; J. Atmos. Sci. 47 2784–2802.
Kulkarni J R, Maheskumar R S, Morwal S B, Padma Kumari B, Konwar M, Deshpande C G, Joshi R R, Bhalwankar R V, Pandithurai G, Safai P D, Narkhedkar S G, Dani K K, Nath A, Nair Sathy, Sapre V V, Puranik P V, Kandalgaonkar S S, Mujumdar V R, Khaladkar R M, Vijayakumar R, Prabha T V and Goswami B N 2012 The Cloud Aerosol Interaction and Precipitation Enhancement Experiment (CAIPEEX): Overview and preliminary results; Curr. Sci. 102(3) 413–425.
Lim Kyo-Sun Sunny and Hong Song-You 2010 Development of an effective double-moment cloud microphysics scheme with prognostic cloud condensation nuclei (CCN) for weather and climate models; Mon. Wea. Rev. 138 1587–1612.
Moeng C H, Dudhia J, Klemp J B and Sullivan P P 2007 Examining two-way grid nesting for large eddy simulation of the PBL using the WRF model; Mon. Wea. Rev. 135 2295–2311.
Morwal S B 2005 Atmospheric boundary layer during ARMEX-2002 at stationary positions – comparative study; Mausam 56 221–232.
Murthy B S and Parasnis S S 2002 Observations of double mixing line structures in the convective boundary layer during the summer monsoon season; Pure Appl. Geophys. 159 1345–1357.
Paluch I R 1979 The entrainment mechanism in Colorado cumuli; J. Atmos. Sci. 36 2467–2478.
Paluch I R and Lenschow D H 1991 Stratiform cloud formation in the marine boundary layer; J. Atmos. Sci. 48 2141–2158.
Prabha T V, Patade S, Pandithurai G, Khain A, Axisa D, Pradeep Kumar P, Maheshkumar R S, Kulkarni J R and Goswami B N 2012 Spectral width of pre-monsoon and monsoon clouds over Indo-Gangetic valley; J. Geophys. Res. 117 D20205.
Raymond D J and Blyth A M 1986 A stochastic mixing model for nonprecipitating cumulus Clouds; J. Atmos. Sci. 43 2708–2718.
Siebesma A P and Cuijpers J W M 1994 Evaluation of parametric assumptions for shallow cumulus convection; J. Atmos. Sci. 52 650–666.
Subrahamanyam and Radhika 2003 Structural characteristics of marine atmospheric boundary layer and its associated dynamics over the central Arabian sea during INDOEX, IFP-99 campaign; Curr. Sci. 85 1334–1340.
Wang Y and Bart G 2011 Observations of detrainment signatures from non-precipitating orographic cumulus clouds; Atmos. Res. 99 302–324.
Zhao M and Austin P H 2005 Life cycle of numerically simulated shallow cumulus clouds. Part I: Transport; J. Atmos. Sci. 62 1269–1290.
Acknowledgements
The Indian Institute of Tropical Meteorology (IITM) and the CAIPEEX experiment is fully funded by the Ministry of Earth Sciences (MoES), Government of India, New Delhi. We acknowledge the contribution of several of our colleagues in their dedicated help with data and the CAIPEEX experiment. The simulations are carried out by the High-Performance Computing System (HPCS) of IITM, Pune. Giovanni website https://giovanni.gsfc.nasa.gov is acknowledged for the MERRA data and the image (figure 2).
Author information
Authors and Affiliations
Contributions
Neelam Malap and T V Prabha: Conceptualization, large eddy simulation, data analysis and writing manuscript. S Bera: Data analysis and editing manuscript. Bipin Kumar and A Karipot: Editing manuscript.
Corresponding author
Additional information
Communicated by P A Francis
Appendix
Appendix
Rights and permissions
About this article
Cite this article
Malap, N., Prabha, T.V., Bera, S. et al. Impact of CCN on mixing line structure over the peninsular Indian region. J Earth Syst Sci 131, 241 (2022). https://doi.org/10.1007/s12040-022-01994-y
Received:
Revised:
Accepted:
Published:
DOI: https://doi.org/10.1007/s12040-022-01994-y