no code implementations • 13 May 2023 • Subhashis Hazarika, Haruki Hirasawa, Sookyung Kim, Kalai Ramea, Salva R. Cachay, Peetak Mitra, Dipti Hingmire, Hansi Singh, Phil J. Rasch
Clouds have a significant impact on the Earth's climate system.
no code implementations • 28 Apr 2023 • Peetak Mitra, Majid Haghshenas, Niccolo Dal Santo, Conor Daly, David P. Schmidt
High-fidelity computational fluid dynamics (CFD) simulations for design space explorations can be exceedingly expensive due to the cost associated with resolving the finer scales.
1 code implementation • 7 Feb 2023 • Soo Kyung Kim, Kalai Ramea, Salva Rühling Cachay, Haruki Hirasawa, Subhashis Hazarika, Dipti Hingmire, Peetak Mitra, Philip J. Rasch, Hansi A. Singh
Our model, AiBEDO, is capable of capturing the complex, multi-timescale effects of radiation perturbations on global and regional surface climate, allowing for a substantial acceleration of the exploration of the impacts of spatially-heterogenous climate forcers.
no code implementations • 3 Feb 2023 • Haruki Hirasawa, Sookyung Kim, Peetak Mitra, Subhashis Hazarika, Salva Ruhling-Cachay, Dipti Hingmire, Kalai Ramea, Hansi Singh, Philip J. Rasch
Here, we describe an AI model, named AiBEDO, that can be used to rapidly projects climate responses to forcings via a novel application of the Fluctuation-Dissipation Theorem (FDT).
no code implementations • 27 Dec 2022 • Feras A. Batarseh, Priya L. Donti, Ján Drgoňa, Kristen Fletcher, Pierre-Adrien Hanania, Melissa Hatton, Srinivasan Keshav, Bran Knowles, Raphaela Kotsch, Sean McGinnis, Peetak Mitra, Alex Philp, Jim Spohrer, Frank Stein, Meghna Tare, Svitlana Volkov, Gege Wen
These applications have implications in areas ranging as widely as energy, agriculture, and finance.
no code implementations • 11 Nov 2018 • Peetak Mitra
We propose a new deep learning based framework to identify pedestrians, and caution distracted drivers, in an effort to prevent the loss of life and property.