Chayan Roychoudhury

I am currently a Ph.D. candidate in Atmospheric Sciences at the University of Arizona, under the guidance of Dr. Avelino Arellano. Check out the group at MAAC Lab for the research I am a part of at the University of Arizona.

The research I have conducted to this date has focused on atmospheric composition, aerosol transport, and their interactions with the Earth system. I have also collaborated closely with institutions like NCAR on the integration of climate models and machine learning for the investigation of nonlinear dynamics within aerosol-meteorological interactions and their impact on snow hydrology at the cryosphere-atmosphere interface. I have also contributed to research in tropospheric ozone sensitivity to its chemical and meteorological precursors using modeling and remote sensing products over the desert southwest in the US.

In addition, I am assisting in the development of an Environmental Disturbance Index (EnDI) with NASA's HiMAT2 team to create a vulnerability atlas of indices from air quality to temperature extremes over High Mountain Asia. A couple of my collaborations include working with Dr. Debanjana Das and Dr. Husile Bai regarding atmospheric teleconnections, tropical cyclones, and the Asian monsoon.

Before my PhD, I did my MSc in Atmospheric Sciences from the University of Calcutta in 2019 at Bose Institute under the supervision of Dr. Sanat Kumar Das. My research journey started with observational data analysis as well as measurement techniques by participating in two campaigns near the Bay of Bengal.

My specific research interests span atmospheric chemistry modeling, data assimilation, and Earth system predictability. I am particularly interested in understanding how different Earth system components interact at the interface, an example being the synergistic impacts of atmospheric composition and meteorology on surface processes, such as aerosol deposition on glaciers over the Third Pole. I am excited to push forward the integration of machine learning techniques with atmospheric models in addressing pertinent Earth system predictability challenges.

Feel free to explore my CV or reach out to me for more details.