Artificial Intelligence-Enhanced CMIP6 Climate Projections Across the Conterminous United States
- Rastogi, Deeksha | Oak Ridge National Laboratory
- Niu, Haoran | Oak Ridge National Laboratory
- Kao, Shih-Chieh | Oak Ridge National Laboratory
Description
Funding resources
DOE contract number
DE-AC05-00OR22725Originating research organization
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)Sponsoring organization
Laboratory Directed Research and Development (LDRD) Program, Oak Ridge National Laboratory; US DOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Water Power Technologies OfficeRelated resources
- IsDerivedFrom (URL): https://aims2.llnl.gov/search/cmip6/
- IsDerivedFrom (DOI): https://doi.org/10.3334/ORNLDAAC/2129
Details
DOI
10.13139/OLCF/2530405Release date
March 27, 2025Dataset
Dataset type
ND Numeric DataSoftware
Any type of NetCDF readersAcknowledgements
Users should acknowledge the OLCF in all publications and presentations that speak to work performed on OLCF resources:
This research used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725.
Category
- 54 ENVIRONMENTAL SCIENCES,
- 58 GEOSCIENCES,
- 13 HYDRO ENERGY,
- 97 MATHEMATICS AND COMPUTING
Keywords
- CMIP6,
- CONUS,
- Downscaling,
- Bias Correction,
- Hydroclimate Projections,
- Hydropower,
- SRCNN,
- SRGAN,
- Artificial Intelligence