CMIP6-based Dynamically Downscaled Hydroclimate Projection over the Conterminous US

Ashfaq, Moetasim; Rastogi, Deeksha; Kao, Shih-Chieh

doi:10.13139/OLCF/3000752

Title: CMIP6-based Dynamically Downscaled Hydroclimate Projection over the Conterminous US

Dataset
Other Related Research

Abstract

This dataset presents a suite of downscaled hydro-climate projections over the conterminous United States (CONUS) based on multiple selected Global Climate Models (GCMs) from the Coupled Models Intercomparison Project phase 6 (CMIP6). The CMIP6 GCMs are downscaled dynamically using Regional Climate Model version 4 (RegCM4). Each ensemble member covers the 1980-2019 baseline and 2020-2059 near-future periods under the high-end (SSP585) emission scenario. This dataset is formulated to support the SECURE Water Act Section 9505 Assessment for the US Department of Energy (DOE) Water Power Technologies Office (WPTO). For further details on this dataset, please refer to Kao et al. (2022) and Rastogi et al. (2022).

Authors:

Ashfaq, Moetasim; Rastogi, Deeksha; Kao, Shih-Chieh

Oak Ridge National Laboratory

Publication Date:: Mon Nov 10 04:00:00 UTC 2025

DOE Contract Number:: AC05-00OR22725

Research Org.:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Org.:: US Department of Energy (DOE) Water Power Technologies Office (WPTO)

Subject:: 13 HYDRO ENERGY; 54 ENVIRONMENTAL SCIENCES; 58 GEOSCIENCES; 97 MATHEMATICS AND COMPUTING; CMIP6; CONUS; Downscaling; Hydroclimate Projections; RegCM; atmospheric science

OSTI Identifier:: 3000752

DOI:: https://doi.org/10.13139/OLCF/3000752

Citation Formats


                    Ashfaq, Moetasim, Rastogi, Deeksha, and Kao, Shih-Chieh. CMIP6-based Dynamically Downscaled Hydroclimate Projection over the Conterminous US.  United States: N. p., 2025. 
        Web.  doi:10.13139/OLCF/3000752.

Copy to clipboard


                    Ashfaq, Moetasim, Rastogi, Deeksha, & Kao, Shih-Chieh. CMIP6-based Dynamically Downscaled Hydroclimate Projection over the Conterminous US.  United States.  doi:https://doi.org/10.13139/OLCF/3000752

Copy to clipboard


                    Ashfaq, Moetasim, Rastogi, Deeksha, and Kao, Shih-Chieh. 2025.  
"CMIP6-based Dynamically Downscaled Hydroclimate Projection over the Conterminous US".  United States.  doi:https://doi.org/10.13139/OLCF/3000752.  https://www.osti.gov/servlets/purl/3000752. Pub date:Mon Nov 10 04:00:00 UTC 2025

Copy to clipboard


                    
@article{osti_3000752,

  title        = {CMIP6-based Dynamically Downscaled Hydroclimate Projection over the Conterminous US},

  author       = {Ashfaq, Moetasim and Rastogi, Deeksha and Kao, Shih-Chieh},

  abstractNote = {This dataset presents a suite of downscaled hydro-climate projections over the conterminous United States (CONUS) based on multiple selected Global Climate Models (GCMs) from the Coupled Models Intercomparison Project phase 6 (CMIP6). The CMIP6 GCMs are downscaled dynamically using Regional Climate Model version 4 (RegCM4). Each ensemble member covers the 1980-2019 baseline and 2020-2059 near-future periods under the high-end (SSP585) emission scenario. This dataset is formulated to support the SECURE Water Act Section 9505 Assessment for the US Department of Energy (DOE) Water Power Technologies Office (WPTO). For further details on this dataset, please refer to Kao et al. (2022) and Rastogi et al. (2022).},

  doi          = {10.13139/OLCF/3000752},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Mon Nov 10 04:00:00 UTC 2025},

  month        = {Mon Nov 10 04:00:00 UTC 2025}

}

Copy to clipboard

Dataset:

View Dataset

DOI: https://doi.org/10.13139/OLCF/3000752

Save / Share:

Export Metadata

Save to My Library

Similar records in DOE Data Explorer and OSTI.GOV collections:

CMIP6-based Dynamically Downscaled Hydroclimate Projection over the Conterminous US

Dataset Ashfaq, Moetasim ; Rastogi, Deeksha ; Kao, Shih-Chieh

This dataset presents a suite of downscaled hydro-climate projections over the conterminous United States (CONUS) based on multiple selected Global Climate Models (GCMs) from the Coupled Models Intercomparison Project phase 6 (CMIP6). The CMIP6 GCMs are downscaled dynamically using RegCM4. Each ensemble member covers the 1980-2019 baseline and 2020-2059 near-future periods under the high-end (SSP585) emission scenario. This dataset is formulated to support the SECURE Water Act Section 9505 Assessment for the US Department of Energy (DOE) Water Power Technologies Office (WPTO). For further details on this dataset, please refer to Kao et al. (2022) and Rastogi et al. (2022).
CMIP6-based Multi-model Hydroclimate Projection over the Conterminous US

Dataset Kao, Shih-Chieh ; Ashfaq, Moetasim ; Rastogi, Deeksha ; ...

We present a suite of high-resolution downscaled hydro-climate projections over the conterminous United States (CONUS) based on a six-member General Climate Model (GCM) ensemble from the Coupled Models Intercomparison Project phase 6 (CMIP6). The CMIP6 GCMs are downscaled using two different downscaling approaches (statistical-based DBCCA & dynamical-based RegCM) based on two meteorological reference observations (Daymet & Livneh), and then fed to two calibrated hydrologic models (VIC & PRMS) to simulate projected future hydrologic responses. Each ensemble member covers 1980–2019 in the historic period and 2020–2059 in the near-term future period under the high-end (SSP585) emission scenario. Major variables such asmore »« less
CMIP6-based Multi-model Hydroclimate Projection over the Conterminous US, Version 1.1

Dataset Kao, Shih-Chieh ; Ashfaq, Moetasim ; Rastogi, Deeksha ; ...

This dataset presents a suite of high-resolution downscaled hydro-climate projections over the conterminous United States (CONUS) based on multiple selected Global Climate Models (GCMs) from the Coupled Models Intercomparison Project phase 6 (CMIP6). The CMIP6 GCMs are downscaled using either statistical (DBCCA) or dynamical (RegCM) downscaling approaches based on two meteorological reference datasets (Daymet and Livneh). Subsequently, the downscaled precipitation, temperature, and wind speed are employed to drive two calibrated hydrologic models (VIC and PRMS), enabling the simulation of projected future hydrologic responses across the CONUS. Each ensemble member covers the 1980-2019 baseline and 2020-2059 near-future periods under the high-endmore »« less
CMIP6-based Multi-model Streamflow Projections over the Conterminous US

Dataset Kao, Shih-Chieh ; Ghimire, Ganesh R. ; Gangrade, Sudershan

This dataset presents an ensemble of streamflow projections based on the hydroclimate projections dataset supporting the SECURE Water Act Section 9505 Assessment for the US Department of Energy (DOE) Water Power Technologies Office (WPTO). The six-member General Climate Model (GCM) ensemble from the Coupled Models Intercomparison Project phase 6 (CMIP6) downscaled using statistical (i.e., DBCCA) and dynamical (i.e., RegCM) and bias-corrected using two meteorological reference observations (Daymet & Livneh) are driven through two calibrated hydrologic models (VIC & PRMS) to simulate projected future hydrologic responses. This leads to the production of an ensemble of hydroclimate projections, including total runoff (surfacemore »« less
CMIP6-based Multi-model Streamflow Projections over the Conterminous US, Version 1.1

Dataset Kao, Shih-Chieh ; Ghimire, Ganesh R. ; Gangrade, Sudershan

This dataset presents an ensemble of streamflow projections covering the conterminous United States (CONUS), developed to support the SECURE Water Act Section 9505 Assessment for the US Department of Energy (DOE) Water Power Technologies Office (WPTO). Multiple Coupled Models Intercomparison Project phase 6 (CMIP6) Global Climate Models (GCMs) were downscaled using either statistical (DBCCA) or dynamical (RegCM) downscaling methods, based on two meteorological reference datasets (Daymet and Livneh). Subsequently, the downscaled precipitation, temperature, and wind speed data were used to drive two calibrated hydrologic models (VIC and PRMS), with total runoff routed through the Routing Application for Parallel computatIon ofmore »« less

Similar Records