Work

Machine learning model to accurately estimate the planetary boundary layer height of Beijing urban area with ERA5 data

Year: 2023

Type: article

Source: Atmospheric Research

DOI: 10.1016/j.atmosres.2023.106925

Authors: Kecheng Peng, Jinyuan Xin, Xiaoqian Zhu, Xiaoyuan Wang, Xiaoqun Cao, Yongjing Ma, Xinbing Ren, Dandan Zhao, Junji Cao, Zifa Wang

Institutions: National University of Defense Technology, Chinese Academy of Sciences, Institute of Atmospheric Physics, State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, University of Chinese Academy of Sciences, Zhejiang Environmental Monitoring Center

Language: English

Topic: Meteorological Phenomena and Simulations

Subfield: Atmospheric Science

Field: Earth and Planetary Sciences

Domain: Physical Sciences

SDGs: Climate action, Sustainable cities and communities

Open Access status: closed

OpenAlex ID: W4384297306

FWCI: 2.543

Cites: 63

Cited by: 23

Related to: 10