Mardani, Morteza https://orcid.org/0009-0006-1763-6832
Brenowitz, Noah
Cohen, Yair
Pathak, Jaideep
Chen, Chieh-Yu https://orcid.org/0009-0006-9104-2303
Liu, Cheng-Chin https://orcid.org/0009-0003-4112-072X
Vahdat, Arash
Nabian, Mohammad Amin
Ge, Tao
Subramaniam, Akshay
Kashinath, Karthik
Kautz, Jan
Pritchard, Mike
Article History
Received: 22 December 2023
Accepted: 16 January 2025
First Online: 24 February 2025
Competing interests
: The authors declare no financial or non-financial competing interests related to this work. The method described in this study has been filed as a patent application titled “Generating High Resolution Data from Low Resolution Data”. The inventors of the patent are M. Mardani, N. Brenowitz, Y. Cohen, J. Pathak, C-Y. Chen, A. Vahdat, K. Kashinath, J. Kautz, and M. Pritchard. Beyond this, the authors have no additional competing interests to disclose.
: We affirm that this research was conducted in accordance with all relevant ethical guidelines and standards. Our team represents a diverse and cross-disciplinary collaboration between NVIDIA and the Central Weather Administration (CWA) of Taiwan. Within NVIDIA, the project brought together expertise from multiple teams, including the Learning and Perception Group the Climate Simulation Research Group at NVIDIA Research, along with Developer Technology, and Modulus teams. This inclusive approach fostered a collaborative environment that values diverse disciplines and perspectives. Our collective effort aims to improve the prediction of extreme weather events, contributing to the well-being and safety of communities worldwide. We are committed to transparency and have made all code and data publicly available to support reproducibility and further research in this critical field.