Deep Learning-Based Ensemble Forecasts and Predictability Assessments for Surface Ozone Pollution

Zhang，Aoxing1,2; Fu，Tzung May3; Feng，Xu4; Guo，Jianfeng5; Liu，Chanfang5; Chen，Jiongkai1,2; Mo，Jiajia1,2; Zhang，Xiao6; Wang，Xiaolin7; Wu，Wenlu1,2; Hou，Yue1,2; Yang，Honglong8; Lu，Chao8; Zhang，Aoxing9,10; Fu，Tzung May11; Feng，Xu12; Guo，Jianfeng13; Liu，Chanfang13; Chen，Jiongkai9,10; Mo，Jiajia9,10; Zhang，Xiao14; Wang，Xiaolin15; Wu，Wenlu9,10; Hou，Yue9,10; Yang，Honglong16; Lu，Chao16

2023-04-28

10.1029/2022GL102611

Geophysical Research Letters   影响因子和分区

0094-8276

1944-8007

CNN Deep Learning Ensemble Forecast Predictability Surface Ozone

SCI ; EI

英语

NI论文

第一

Guangdong Basic and Applied Basic Research Foundation[

Geology

Geosciences, Multidisciplinary

WOS:000973047200001

AMER GEOPHYSICAL UNION

20232014081595

Air Quality ; Convolution ; Convolutional Neural Networks ; Environmental Management ; Ozone ; Weather Forecasting

Meteorology:443 ; Air Pollution Control:451.2 ; Environmental Engineering, General:454.1 ; Environmental Impact And Protection:454.2 ; Ergonomics And Human Factors Engineering:461.4 ; Information Theory And Signal Processing:716.1 ; Chemical Products Generally:804

GEOSCIENCES

2-s2.0-85158953286

Scopus

正式出版

1.Shenzhen Key Laboratory of Precision Measurement and Early Warning Technology for Urban Environmental Health Risks,School of Environmental Science and Engineering,Southern University of Science and Technology,Shenzhen,China
2.Guangdong Provincial Observation and Research Station for Coastal Atmosphere and Climate of the Greater Bay Area,School of Environmental Science and Engineering,Southern University of Science and Technology,Shenzhen,China
3.National Center for Applied Mathematics,Shenzhen (NCAMS),Shenzhen,China
4.John A. Paulson School of Engineering and Applied Sciences,Harvard University,Cambridge,United States
5.Shenzhen Ecology and Environment Monitoring Centre of Guangdong Province,Shenzhen,China
6.Department of Computer Science and Technology,Tsinghua University,Beijing,China
7.Department of Atmospheric and Oceanic Sciences,School of Physics,Peking University,Beijing,China
8.Shenzhen National Climate Observatory,Shenzhen,China
9.Shenzhen Key Laboratory of Precision Measurement and Early Warning Technology for Urban Environmental Health Risks,School of Environmental Science and Engineering,Southern University of Science and Technology,Shenzhen,China
10.Guangdong Provincial Observation and Research Station for Coastal Atmosphere and Climate of the Greater Bay Area,School of Environmental Science and Engineering,Southern University of Science and Technology,Shenzhen,China
11.National Center for Applied Mathematics,Shenzhen (NCAMS),Shenzhen,China
12.John A. Paulson School of Engineering and Applied Sciences,Harvard University,Cambridge,United States
13.Shenzhen Ecology and Environment Monitoring Centre of Guangdong Province,Shenzhen,China
14.Department of Computer Science and Technology,Tsinghua University,Beijing,China
15.Department of Atmospheric and Oceanic Sciences,School of Physics,Peking University,Beijing,China
16.Shenzhen National Climate Observatory,Shenzhen,China

Zhang，Aoxing,Fu，Tzung May,Feng，Xu,et al. Deep Learning-Based Ensemble Forecasts and Predictability Assessments for Surface Ozone Pollution[J]. Geophysical Research Letters,2023,50(8).

Zhang，Aoxing.,Fu，Tzung May.,Feng，Xu.,Guo，Jianfeng.,Liu，Chanfang.,...&Lu，Chao.(2023).Deep Learning-Based Ensemble Forecasts and Predictability Assessments for Surface Ozone Pollution.Geophysical Research Letters,50(8).

Zhang，Aoxing,et al."Deep Learning-Based Ensemble Forecasts and Predictability Assessments for Surface Ozone Pollution".Geophysical Research Letters 50.8(2023).