Supporting Data for the GFDL Variable-Resolution Global Chemistry-Climate Model for Research at the Nexus of US Climate and Air Quality Extremes
收藏DataCite Commons2024-01-05 更新2024-07-13 收录
下载链接：
https://datacommons.princeton.edu/discovery/doi/10.34770/azw8-7g66
下载链接
链接失效反馈官方服务：
资源简介：
The data were produced by the GFDL Variable-Resolution Global
Chemistry-Climate Model (AM4VR) running in AMIP (Atmospheric Model
Intercomparison Project) mode, driven by observed sea surface temperature
(SST) and sea ice distributions, historical anthropogenic emissions, land
use and atmospheric radiative forcing agents over 1988-2020. Please refer
to Lin et al. (JAMES, 2023) for the details of the experiment design.
Meiyun Lin, Larry W. Horowitz, Ming Zhao, Lucas Harris, Paul Ginoux, John
Dunne, Sergey Malyshev, Elena Shevliakova, Hamza Ahsan, Steve Garner,
Fabien Paulot, Arman Pouyaei, Steven J. Smith, Yuanyu Xie, Niki Zadeh,
Linjiong Zhou. The GFDL Variable-Resolution Global Chemistry-Climate Model
for Research at the Nexus of US Climate and Air Quality Extremes. Journal
of Advances in Modeling Earth Systems,
https://doi.org/10.1029/2023MS003984
提供机构：
Princeton University
创建时间：
2023-12-04
