Abstract
Regional climate models can be used to examine how past weather events might unfold under different climate conditions by simulating analogue versions of those events with modified thermodynamic conditions (i.e., warming signals). Here, we apply this approach by dynamically downscaling a 40-year sequence of past weather from 1980–2019 driven by atmospheric re-analysis, and then repeating this 40-year sequence a total of 8 times using a range of time-evolving thermodynamic warming signals that follow 4 80-year future warming trajectories from 2020–2099. Warming signals follow two emission scenarios (SSP585 and SSP245) and are derived from two groups of global climate models based on whether they exhibit relatively high or low climate sensitivity. The resulting dataset, which contains 25 hourly and over 200 3-hourly variables at 12 km spatial resolution, can be used to examine a plausible range of future climate conditions in direct reference to previously observed weather and enables a systematic exploration of the ways in which thermodynamic change influences the characteristics of historical extreme events.
| Original language | English |
|---|---|
| Article number | 664 |
| Journal | Scientific Data |
| Volume | 10 |
| Issue number | 1 |
| DOIs | |
| State | Published - Dec 2023 |
Funding
The authors would like to thank Claudia Tebaldi and Ruby Leung of Pacific Northwest National Laboratory for helpful comments on this work. They would also like to thank Stefan Rahimi of the University of CA, Los Angeles for advice on configuring the WRF model. This data was developed collaboratively between the Integrated Multisector, Multiscale Modeling (IM3) and HyperFACETS projects, both of which are supported by the U.S. Department of Energy, Office of Science, as part of research in MultiSector Dynamics; HyperFACETS is also supported by the Regional and Global Model Analysis, Earth and Environmental System Modeling Program. A portion of this research used the computing resources of the National Energy Research Scientific Computing Center (NERSC), a U.S. Department of Energy Office of Science User Facility located at Lawrence Berkeley National Laboratory, operated under Contract No. DE-AC02-05CH11231. The CPC Unified Gauge-Based Analysis of Daily Precipitation over CONUS data is provided by the NOAA PSL, Boulder, Colorado, USA, from their website at https://psl.noaa.gov. Notice: DR is an employee of UT-Battelle, LLC, under contract DEAC05-00OR22725 with the US Department of Energy (DOE). Accordingly, the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (https://www.energy.gov/downloads/doe-public-access-plan). The authors would like to thank Claudia Tebaldi and Ruby Leung of Pacific Northwest National Laboratory for helpful comments on this work. They would also like to thank Stefan Rahimi of the University of CA, Los Angeles for advice on configuring the WRF model. This data was developed collaboratively between the Integrated Multisector, Multiscale Modeling (IM3) and HyperFACETS projects, both of which are supported by the U.S. Department of Energy, Office of Science, as part of research in MultiSector Dynamics; HyperFACETS is also supported by the Regional and Global Model Analysis, Earth and Environmental System Modeling Program. A portion of this research used the computing resources of the National Energy Research Scientific Computing Center (NERSC), a U.S. Department of Energy Office of Science User Facility located at Lawrence Berkeley National Laboratory, operated under Contract No. DE-AC02-05CH11231. The CPC Unified Gauge-Based Analysis of Daily Precipitation over CONUS data is provided by the NOAA PSL, Boulder, Colorado, USA, from their website at https://psl.noaa.gov . Notice: DR is an employee of UT-Battelle, LLC, under contract DEAC05-00OR22725 with the US Department of Energy (DOE). Accordingly, the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan ( https://www.energy.gov/downloads/doe-public-access-plan ).
| Funders | Funder number |
|---|---|
| DOE Public Access Plan | |
| NOAA PSL | |
| U.S. Department of Energy | |
| Office of Science | |
| Lawrence Berkeley National Laboratory | DE-AC02-05CH11231 |
| UT-Battelle | DEAC05-00OR22725 |