paper
2023
Observations & remote sensing
New model or method
Classical ML (trees, GP, linear, kernels)Institute of Atmospheric Physics, Chinese Academy of Sciences Journal
2023-07-14
018
Jul 2023
Kecheng Peng, Jinyuan Xin, Xiaoqian Zhu et al.
Atmospheric Research
Institute of Atmospheric Physics, Chinese Academy of Sciences
Machine learning model estimates urban Beijing planetary boundary layer height from ERA5 predictors.
Machine learning model to accurately estimate the planetary boundary layer height of Beijing urban area with ERA5 data
In one sentence. Machine learning model estimates urban Beijing planetary boundary layer height from ERA5 predictors.
Labels
- Topic
- Observations & remote sensing
- Type
- New model or method
- Method
- Classical ML (trees, GP, linear, kernels)
- Domain
- Local / station
- Data
- ERA5 / reanalysis
- Status
- Research
- Identifiers
- DOI:10.1016/j.atmosres.2023.106925 OpenAlex:W4384297306
- Added
- 2026-10-22
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