Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, School of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing, China
Zexia Duan
Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, School of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing, China
Shaohui Zhou
Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, School of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing, China
Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, School of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing, China
Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China
China Meteorological Administration Xiong'an Atmospheric Boundary Layer Key Laboratory, Xiong'an New Area, China
Zhiqiu Gao
State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, School of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing, China
Viewed
Total article views: 1,257 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
BibTeX
EndNote
937
266
54
1,257
40
45
HTML: 937
PDF: 266
XML: 54
Total: 1,257
BibTeX: 40
EndNote: 45
Views and downloads (calculated since 19 Dec 2022)
Cumulative views and downloads
(calculated since 19 Dec 2022)
Total article views: 777 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
BibTeX
EndNote
596
144
37
777
34
40
HTML: 596
PDF: 144
XML: 37
Total: 777
BibTeX: 34
EndNote: 40
Views and downloads (calculated since 25 Apr 2023)
Cumulative views and downloads
(calculated since 25 Apr 2023)
Total article views: 480 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
BibTeX
EndNote
341
122
17
480
6
5
HTML: 341
PDF: 122
XML: 17
Total: 480
BibTeX: 6
EndNote: 5
Views and downloads (calculated since 19 Dec 2022)
Cumulative views and downloads
(calculated since 19 Dec 2022)
Viewed (geographical distribution)
Total article views: 1,257 (including HTML, PDF, and XML)
Thereof 1,237 with geography defined
and 20 with unknown origin.
Total article views: 777 (including HTML, PDF, and XML)
Thereof 756 with geography defined
and 21 with unknown origin.
Total article views: 480 (including HTML, PDF, and XML)
Thereof 481 with geography defined
and -1 with unknown origin.
In this paper, we used a random forest model to fill the observation gaps of the fluxes measured during 2015–2019. We found that the net radiation was the most important input variable. And we justified the reliability of the model. Further, it was revealed that the model performed better after relative humidity was removed from the input. Lastly, we compared the results of the model with those of three other machine learning models, and we found that the model outperformed all of them.
In this paper, we used a random forest model to fill the observation gaps of the fluxes measured...