Key Laboratory of Meteorological Disaster, Ministry of Education
(KLME), Joint International Research Laboratory of Climate and Environment
Change (ILCEC), and Collaborative Innovation Center on Forecast and Evaluation of
Meteorological Disasters (CIC-FEMD), Nanjing University of Information
Science and Technology, Nanjing, China
Key Laboratory of Meteorological Disaster, Ministry of Education
(KLME), Joint International Research Laboratory of Climate and Environment
Change (ILCEC), and Collaborative Innovation Center on Forecast and Evaluation of
Meteorological Disasters (CIC-FEMD), Nanjing University of Information
Science and Technology, Nanjing, China
Li Qi
Key Laboratory of Meteorological Disaster, Ministry of Education
(KLME), Joint International Research Laboratory of Climate and Environment
Change (ILCEC), and Collaborative Innovation Center on Forecast and Evaluation of
Meteorological Disasters (CIC-FEMD), Nanjing University of Information
Science and Technology, Nanjing, China
Qiaohua Zhao
Key Laboratory of Meteorological Disaster, Ministry of Education
(KLME), Joint International Research Laboratory of Climate and Environment
Change (ILCEC), and Collaborative Innovation Center on Forecast and Evaluation of
Meteorological Disasters (CIC-FEMD), Nanjing University of Information
Science and Technology, Nanjing, China
Jinhai He
Key Laboratory of Meteorological Disaster, Ministry of Education
(KLME), Joint International Research Laboratory of Climate and Environment
Change (ILCEC), and Collaborative Innovation Center on Forecast and Evaluation of
Meteorological Disasters (CIC-FEMD), Nanjing University of Information
Science and Technology, Nanjing, China
Julian X. L. Wang
Air Resources Laboratory, National Oceanic and Atmospheric
Administration, College Park, MD, USA
Viewed
Total article views: 3,904 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
Supplement
BibTeX
EndNote
2,905
896
103
3,904
441
106
136
HTML: 2,905
PDF: 896
XML: 103
Total: 3,904
Supplement: 441
BibTeX: 106
EndNote: 136
Views and downloads (calculated since 06 Nov 2018)
Cumulative views and downloads
(calculated since 06 Nov 2018)
Total article views: 3,020 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
Supplement
BibTeX
EndNote
2,269
654
97
3,020
254
101
125
HTML: 2,269
PDF: 654
XML: 97
Total: 3,020
Supplement: 254
BibTeX: 101
EndNote: 125
Views and downloads (calculated since 06 Feb 2019)
Cumulative views and downloads
(calculated since 06 Feb 2019)
Total article views: 884 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
Supplement
BibTeX
EndNote
636
242
6
884
187
5
11
HTML: 636
PDF: 242
XML: 6
Total: 884
Supplement: 187
BibTeX: 5
EndNote: 11
Views and downloads (calculated since 06 Nov 2018)
Cumulative views and downloads
(calculated since 06 Nov 2018)
Viewed (geographical distribution)
Total article views: 3,904 (including HTML, PDF, and XML)
Thereof 3,747 with geography defined
and 157 with unknown origin.
Total article views: 3,020 (including HTML, PDF, and XML)
Thereof 2,948 with geography defined
and 72 with unknown origin.
Total article views: 884 (including HTML, PDF, and XML)
Thereof 799 with geography defined
and 85 with unknown origin.
Less attention has been paid to haze weather during the autumn season. Here, we unravel the mechanism of how SST anomalies over the subtropical North Atlantic and western North Pacific drive the interannual variability of the autumnal haze days in the Beijing–Tianjin–Hebei region. The two pathways of SST anomaly forcings can result in an anticyclonic (cyclonic) anomaly over Northeast Asia, leading to a lower-level southerly (northerly) anomaly and in turn more (fewer) haze days in this region.
Less attention has been paid to haze weather during the autumn season. Here, we unravel the...