Scientist Profile

Ms. Neelam Namadev Malap

Designation
: Scientist B

Phone
: 020-25904345

Fax
: 

Email ID
: neelam[at]tropmet[dot]res[dot]in

Clouds, aerosols and atmospheric boundary layer physics
Degree University Year Stream
PhD Savitribai Phule Pune University, Pune Ongoing Atmospheric Sciences
M. Tech. Savitribai Phule Pune University, Pune 2012 Atmospheric Sciences
M. Sc University of Mumbai, Mumbai 2009 Physics
B. Sc. Ramniranjan Jhunjhunwala College, Mumbai 2007 Physics

 Clouds aerosols interaction

 Entrainment and mixing processes in clouds and atmospheric boundary layer

 Diurnal cycle of convection

Award Name Awarded By Awarded For Year
Best Poster Award TROPMET conference Best Poster Presentation 2016
Year Designation Institute
2023-Present Scientist B Indian Institute of Tropical Meteorology, Pune
2022-2023 Project Scientist II Indian Institute of Tropical Meteorology, Pune
2018-2022 Project Scientist B Indian Institute of Tropical Meteorology, Pune
2016-2017 Project Scientist B Indian Institute of Tropical Meteorology, Pune
2015-2016 Junior Research Fellow India Meteorological Department, Pune
2012-2015 Junior Research Fellow Department of Atmospheric & Space Sciences, Savitribai Phule Pune University, Pune
2009-2010 Assistant Teacher in Physics Bharat Junior College of Science and Commerce, Thane

Research Highlight


Entrainment rates in the cloud zones of continental shallow cumulus

The saturation deficit regions of the clouds are strongly affected by the entrainment and mixing of moist cloudy air with drier environmental air due to ascending and descending moist thermal plumes differing in the buoyancy. Study identifies the different dilution regimes of clouds with the three parameter clustering method and illustrates the larger entrainment rates in the drier environment. The core region is less diluted and exhibits large liquid water content. Both CAIPEEX aircraft observations and large eddy simulation shows an increase in entrainment rate with a decrease in adiabatic fraction and this relationship is very useful for the large-scale modelers.

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