Journal article
Assessing Climate Change Impacts on Wind Energy Resources over China Based on CMIP6 Multimodel Ensemble
Abstract
Assessing how wind energy potential will change in the context of global warming is fundamental to local energy development and planning. Twenty-two CMIP6 GCM outputs under three emission scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5) are fed into the convolutional neural networks based on efficient channel attention (ECA-Net) to generate wind energy density projections. This study demonstrates that the ECA-Net model can accurately capture the …
Authors
Zhao X; Huang G; Lu C; Li Y; Tian C
Journal
Environmental Science & Technology Letters, Vol. 11, No. 2, pp. 95–100
Publisher
American Chemical Society (ACS)
Publication Date
February 13, 2024
DOI
10.1021/acs.estlett.3c00829
ISSN
2328-8930