no code implementations • 25 May 2023 • Sukhpal Singh Gill, Minxian Xu, Panos Patros, Huaming Wu, Rupinder Kaur, Kamalpreet Kaur, Stephanie Fuller, Manmeet Singh, Priyansh Arora, Ajith Kumar Parlikad, Vlado Stankovski, Ajith Abraham, Soumya K. Ghosh, Hanan Lutfiyya, Salil S. Kanhere, Rami Bahsoon, Omer Rana, Schahram Dustdar, Rizos Sakellariou, Steve Uhlig, Rajkumar Buyya
ChatGPT, an AI-based chatbot, was released to provide coherent and useful replies based on analysis of large volumes of data.
no code implementations • 20 Mar 2023 • Sifatkaur Dhingra, Manmeet Singh, Vaisakh SB, Neetiraj Malviya, Sukhpal Singh Gill
Cognitive psychology delves on understanding perception, attention, memory, language, problem-solving, decision-making, and reasoning.
no code implementations • 18 Aug 2022 • Moumita Bhowmik, Manmeet Singh, Suryachandra Rao, Souvik Paul
Simulation of turbulent flows, especially at the edges of clouds in the atmosphere, is an inherently challenging task.
no code implementations • 18 Aug 2022 • Mriganka Sekhar Biswas, Manmeet Singh
Dynamic atmospheric chemistry models struggle to simulate atmospheric formaldehyde and often overestimate by up to two times relative to satellite observations and reanalysis.
no code implementations • 15 Aug 2022 • Manmeet Singh, Nachiketa Acharya, Sajad Jamshidi, Junfeng Jiao, Zong-Liang Yang, Marc Coudert, Zach Baumer, Dev Niyogi
We show the development of a high-resolution gridded precipitation product (300 m) from a coarse (10 km) satellite-based product (JAXA GsMAP).
no code implementations • 2 Jul 2022 • Bipin Kumar, Kaustubh Atey, Bhupendra Bahadur Singh, Rajib Chattopadhyay, Nachiket Acharya, Manmeet Singh, Ravi S. Nanjundiah, Suryachandra A. Rao
To test the efficacy of different DL approaches, we apply four different methods of downscaling and evaluate their performance.
no code implementations • 23 Jun 2022 • Manmeet Singh, Vaisakh S B, Nachiketa Acharya, Aditya Grover, Suryachandra A Rao, Bipin Kumar, Zong-Liang Yang, Dev Niyogi
We augment the output of the well-known NWP model CFSv2 with deep learning to create a hybrid model that improves short-range global precipitation at 1-, 2-, and 3-day lead times.
no code implementations • 24 May 2022 • Harsh G. Kamath, Manmeet Singh, Lori A. Magruder, Zong-Liang Yang, Dev Niyogi
The building information from GLOBUS can be ingested in Numerical Weather Prediction (NWP) and urban energy-water balance models to study localized phenomena such as the Urban Heat Island (UHI) effect.
no code implementations • 24 Dec 2021 • Manmeet Singh, Bipin Kumar, Rajib Chattopadhyay, K Amarjyothi, Anup K Sutar, Sukanta Roy, Suryachandra A Rao, Ravi S. Nanjundiah
This survey focuses on the current problems in Earth systems science where machine learning algorithms can be applied.
1 code implementation • 28 Jul 2021 • Manmeet Singh, Chirag Dhara, Adarsh Kumar, Sukhpal Singh Gill, Steve Uhlig
Climate change has become one of the biggest global problems increasingly compromising the Earth's habitability.
no code implementations • 20 Jun 2021 • Manmeet Singh, Bipin Kumar, Suryachandra Rao, Sukhpal Singh Gill, Rajib Chattopadhyay, Ravi S Nanjundiah, Dev Niyogi
This study is a proof-of-concept showing that residual learning-based UNET can unravel physical relationships to target precipitation, and those physical constraints can be used in the dynamical operational models towards improved precipitation forecasts.
no code implementations • 23 Nov 2020 • Bipin Kumar, Rajib Chattopadhyay, Manmeet Singh, Niraj Chaudhari, Karthik Kodari, Amit Barve
In this work, we employed three deep learning-based algorithms derived from the super-resolution convolutional neural network (SRCNN) methods, to precipitation data, in particular, IMD and TRMM data to produce 4x-times high-resolution downscaled rainfall data during the summer monsoon season.