Collaborative Innovation Centre 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, 210044, China
Collaborative Innovation Centre 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, 210044, China
Jiaqin Mi
Collaborative Innovation Centre 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, 210044, China
Xueyan Bi
Institute of Tropical and Marine Meteorology, China Meteorological
Administration, Guangzhou, 510080, China
You Zhao
Collaborative Innovation Centre 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, 210044, China
Zehao Huang
Collaborative Innovation Centre 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, 210044, China
Chao Liu
Collaborative Innovation Centre 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, 210044, China
Lian Zong
Collaborative Innovation Centre 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, 210044, China
Wanju Li
Institute of Tropical and Marine Meteorology, China Meteorological
Administration, Guangzhou, 510080, China
Viewed
Total article views: 6,581 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
Supplement
BibTeX
EndNote
5,431
1,021
129
6,581
351
111
149
HTML: 5,431
PDF: 1,021
XML: 129
Total: 6,581
Supplement: 351
BibTeX: 111
EndNote: 149
Views and downloads (calculated since 20 Jul 2021)
Cumulative views and downloads
(calculated since 20 Jul 2021)
Total article views: 5,768 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
Supplement
BibTeX
EndNote
4,898
761
109
5,768
204
101
141
HTML: 4,898
PDF: 761
XML: 109
Total: 5,768
Supplement: 204
BibTeX: 101
EndNote: 141
Views and downloads (calculated since 05 Nov 2021)
Cumulative views and downloads
(calculated since 05 Nov 2021)
Total article views: 813 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
Supplement
BibTeX
EndNote
533
260
20
813
147
10
8
HTML: 533
PDF: 260
XML: 20
Total: 813
Supplement: 147
BibTeX: 10
EndNote: 8
Views and downloads (calculated since 20 Jul 2021)
Cumulative views and downloads
(calculated since 20 Jul 2021)
Viewed (geographical distribution)
Total article views: 6,581 (including HTML, PDF, and XML)
Thereof 6,469 with geography defined
and 112 with unknown origin.
Total article views: 5,768 (including HTML, PDF, and XML)
Thereof 5,674 with geography defined
and 94 with unknown origin.
Total article views: 813 (including HTML, PDF, and XML)
Thereof 795 with geography defined
and 18 with unknown origin.
A random forest (RF) model framework for Fengyun-4A (FY-4A) daytime and nighttime quantitative precipitation estimation (QPE) is established using FY-4A multi-band spectral information, cloud parameters, high-density precipitation observations and physical quantities from reanalysis data. The RF model of FY-4A QPE has a high accuracy in estimating precipitation at the heavy-rain level or below, which has advantages for quantitative estimation of summer precipitation over East Asia in future.
A random forest (RF) model framework for Fengyun-4A (FY-4A) daytime and nighttime quantitative...
