Suhas Ettammal
Associate Professor
Earth and Climate Science
Earth Science
+91-20-25908411
suhas@iiserpune.ac.in
Suhas Ettammal obtained his PhD in Atmospheric and Space Sciences in 2011 from Indian Institute of Tropical Meteorology, Pune. He was a postdoctoral Research scholar at Scripps Institution of Oceanography, University of California San Diego from 2012 to 2014 and jointly at Jet Propulsion Laboratory and California Institute of Technology from 2014 to 2016 before joining IISER Pune in 2016.
Research
Organized Tropical Convective Systems
Convective cloud clusters of different spatial-temporal scales are fundamental features of the tropical atmosphere. Equatorial waves are assumed to play a critical role in organizing the clouds into synoptic and planetary scales. Suhas' main research interest lies in understanding the physical processes by which the equatorial waves organize the convective cloud systems. We use ground and satellite based observations and hierarchy of models for investigating the wave responses in the atmosphere. He also work towards improving convective parameterization schemes in climate models using satellite observations, as the representation of organized convective systems such as the Madden-Julian Oscillation, monsoon, tropical depressions etc. are still a challenge for most of the climate models.
Selected Publications
E. Suhas, J.M. Neena, X. Jiang (2020), Exploring the Factors Influencing the Strength and Variability of Convectively Coupled Mixed Rossby–Gravity Waves, Journal of Climate, 33, 9705-9719.
Meera, M., Suhas, E. and Sandeep, S (2019). Downstream and In Situ: Two Perspectives on the Initiation of Monsoon Low-Pressure Systems Over the Bay of Bengal. Geophysical Research Letters, https://doi.org/10.1029/2019GL084555.
Suhas, E. and Zhang, G. J. (2015). Evaluating convective parameterization closures using cloud resolving simulation of tropical deep convection, Journal of Geophysical Research-Atmosphere, 120, 1260-1277.
Suhas, E. and Zhang, G. J. (2014). Evaluation of Convective Parameterization Schemes Using Observations. Journal of Climate, 27, 7647-7666.