Abstract
The interplay between energy, climate, and weather is becoming more complex as our changing climate continues to affect the weather we experience which in turn drives changes in the ever increasing share of renewable energy generation and energy demand. Energy system analyses commonly rely on meteorological inputs to estimate renewable energy generation and energy demand; however, these inputs rarely represent the estimated impacts of future climate change. Climate models and publicly available climate change datasets can be used for this purpose, but the selection of inputs from the myriad of available models and datasets is a nuanced and often subjective process. There is no single perfect climate model or dataset for all applications. In this repository, we include software and the corresponding assessments of various global climate models (GCMs) from the Coupled Model Intercomparison Project (CMIP6), evaluating their skills with respect to the historical climate and comparing of their future projections of climate change. We focus on variables that directly affect the energy system including the representation of extreme values that can drive grid resilience events. The objective of this repository is not to recommend the best climate model and dataset for a given analysis, but instead to provide a
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- Developers:
-
Buster, Grant [1] ; Benton, Brandon [1] ; Podgorny, Slater [1]
- National Renewable Energy Laboratory (NREL), Golden, CO (United States)
- Release Date:
- 2024-02-28
- Project Type:
- Open Source, Publicly Available Repository
- Software Type:
- Scientific
- Programming Languages:
-
Python
Jupyter Notebook
- Licenses:
-
BSD 3-clause "New" or "Revised" License
- Sponsoring Org.:
-
USDOE Office of Energy Efficiency and Renewable Energy (EERE)Primary Award/Contract Number:AC36-08GO28308USDOE Office of Cybersecurity, Energy Security, and Emergency Response (CESER)Primary Award/Contract Number:AC36-08GO28308USDOE Office of Electricity (OE)Primary Award/Contract Number:AC36-08GO28308USDOE Office of Fossil Energy and Carbon Management (FECM)Primary Award/Contract Number:AC36-08GO28308
- Code ID:
- 123457
- Site Accession Number:
- NREL SWR-24-37
- Research Org.:
- National Renewable Energy Laboratory (NREL), Golden, CO (United States)
- Country of Origin:
- United States
Citation Formats
Buster, Grant, Benton, Brandon, and Podgorny, Slater.
gcm_eval (Global Climate Model Evaluation) [SWR-24-37].
Computer Software.
https://github.com/NREL/gcm_eval.
USDOE Office of Energy Efficiency and Renewable Energy (EERE), USDOE Office of Cybersecurity, Energy Security, and Emergency Response (CESER), USDOE Office of Electricity (OE), USDOE Office of Fossil Energy and Carbon Management (FECM).
28 Feb. 2024.
Web.
doi:10.11578/dc.20240305.1.
Buster, Grant, Benton, Brandon, & Podgorny, Slater.
(2024, February 28).
gcm_eval (Global Climate Model Evaluation) [SWR-24-37].
[Computer software].
https://github.com/NREL/gcm_eval.
https://doi.org/10.11578/dc.20240305.1.
Buster, Grant, Benton, Brandon, and Podgorny, Slater.
"gcm_eval (Global Climate Model Evaluation) [SWR-24-37]." Computer software.
February 28, 2024.
https://github.com/NREL/gcm_eval.
https://doi.org/10.11578/dc.20240305.1.
@misc{
doecode_123457,
title = {gcm_eval (Global Climate Model Evaluation) [SWR-24-37]},
author = {Buster, Grant and Benton, Brandon and Podgorny, Slater},
abstractNote = {The interplay between energy, climate, and weather is becoming more complex as our changing climate continues to affect the weather we experience which in turn drives changes in the ever increasing share of renewable energy generation and energy demand. Energy system analyses commonly rely on meteorological inputs to estimate renewable energy generation and energy demand; however, these inputs rarely represent the estimated impacts of future climate change. Climate models and publicly available climate change datasets can be used for this purpose, but the selection of inputs from the myriad of available models and datasets is a nuanced and often subjective process. There is no single perfect climate model or dataset for all applications. In this repository, we include software and the corresponding assessments of various global climate models (GCMs) from the Coupled Model Intercomparison Project (CMIP6), evaluating their skills with respect to the historical climate and comparing of their future projections of climate change. We focus on variables that directly affect the energy system including the representation of extreme values that can drive grid resilience events. The objective of this repository is not to recommend the best climate model and dataset for a given analysis, but instead to provide a reference to facilitate the selection of climate models and datasets in subsequent work.},
doi = {10.11578/dc.20240305.1},
url = {https://doi.org/10.11578/dc.20240305.1},
howpublished = {[Computer Software] \url{https://doi.org/10.11578/dc.20240305.1}},
year = {2024},
month = {feb}
}