Articles | Volume 13, issue 4
https://doi.org/10.5194/amt-13-1709-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-13-1709-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
07 Apr 2020
Research article |
| 07 Apr 2020
| 07 Apr 2020
Estimates of lightning NOx production based on high-resolution OMI NO2 retrievals over the continental US
Xin Zhang
Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration,
Nanjing University of Information Science and Technology (NUIST), Nanjing 210044, China
Department of Atmospheric Physics, Nanjing University of Information Science and Technology (NUIST), Nanjing 210044, China
Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration,
Nanjing University of Information Science and Technology (NUIST), Nanjing 210044, China
Department of Atmospheric Physics, Nanjing University of Information Science and Technology (NUIST), Nanjing 210044, China
Ronald van der A
Department of Atmospheric Physics, Nanjing University of Information Science and Technology (NUIST), Nanjing 210044, China
Royal Netherlands Meteorological Institute (KNMI), Department of Satellite Observations, De Bilt, the Netherlands
Jeff L. Lapierre
Earth Networks, Germantown, Maryland, USA
Qian Chen
Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration,
Nanjing University of Information Science and Technology (NUIST), Nanjing 210044, China
Department of Atmospheric Physics, Nanjing University of Information Science and Technology (NUIST), Nanjing 210044, China
Xiang Kuang
Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration,
Nanjing University of Information Science and Technology (NUIST), Nanjing 210044, China
Department of Atmospheric Physics, Nanjing University of Information Science and Technology (NUIST), Nanjing 210044, China
Shuqi Yan
Department of Atmospheric Physics, Nanjing University of Information Science and Technology (NUIST), Nanjing 210044, China
Jinghua Chen
Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration,
Nanjing University of Information Science and Technology (NUIST), Nanjing 210044, China
Department of Atmospheric Physics, Nanjing University of Information Science and Technology (NUIST), Nanjing 210044, China
Chuan He
Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration,
Nanjing University of Information Science and Technology (NUIST), Nanjing 210044, China
Department of Atmospheric Physics, Nanjing University of Information Science and Technology (NUIST), Nanjing 210044, China
Rulin Shi
Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration,
Nanjing University of Information Science and Technology (NUIST), Nanjing 210044, China
Department of Atmospheric Physics, Nanjing University of Information Science and Technology (NUIST), Nanjing 210044, China
Model code and software
BEHR-LNOx v1.0 X. Zhang and J. Laughner https://doi.org/10.5281/zenodo.3553426
Short summary
Lightning NOx has a strong impact on ozone and the hydroxyl radical production. However, the production efficiency of lightning NOx is still quite uncertain. This work develops the algorithm of estimating lightning NOx for both clean and polluted regions and evaluates the sensitivity of estimates to the model setting of lightning NO. Results reveal that our method reduces the sensitivity to the background NO2 and includes much of the below-cloud LNO2.
Lightning NOx has a strong impact on ozone and the hydroxyl radical production. However, the...
