Articles | Volume 16, issue 23
https://doi.org/10.5194/acp-16-14843-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/acp-16-14843-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Seasonal prediction of winter haze days in the north central North China Plain
Zhicong Yin
CORRESPONDING AUTHOR
Key Laboratory of Meteorological Disaster, Ministry of Education/Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of
Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing, China
Nansen-Zhu International Research Centre, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
Huijun Wang
Key Laboratory of Meteorological Disaster, Ministry of Education/Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of
Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing, China
Nansen-Zhu International Research Centre, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
Climate Change Research Center, Chinese Academy of Sciences, Beijing, China
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Latest update: 23 Nov 2024
Short summary
Recently, the winter haze pollution over the north central North China Plain has become severe. By treating the year-to-year increment as the predictand, two new statistical schemes were established using the multiple linear regression and the generalized additive model approaches. After cross validation, both of these models could capture the interannual and interdecadal trends and the extremums successfully. Independent tests for 2014 and 2015 also confirmed the good predictive skill.
Recently, the winter haze pollution over the north central North China Plain has become severe....
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