Abstract. Lightning serves as the dominant source of nitrogen oxides (NOx=NO+NO2) in the upper troposphere (UT), with a strong impact on ozone chemistry and the hydroxyl radical production. However, the production efficiency (PE) of lightning nitrogen oxides (LNOx) is still quite uncertain (32–1100 mol NO per flash). Satellite measurements are a powerful tool to estimate LNOx directly compared to conventional platforms. To apply satellite data in both clean and polluted regions, a new algorithm for calculating LNOx has been developed that uses the Berkeley High-Resolution (BEHR) v3.0B NO2 retrieval algorithm and the Weather Research and Forecasting model coupled with chemistry (WRF-Chem). LNOx PE over the continental US is estimated using the NO2 product of the Ozone Monitoring Instrument (OMI) data and the Earth Networks Total Lightning Network (ENTLN) data. Focusing on the summer season during 2014, we find that the lightning NO2 (LNO2) PE is 32±15 mol NO2 per flash and 6±3 mol NO2 per stroke while LNOx PE is 90±50 mol NOx per flash and 17±10 mol NOx per stroke. Results reveal that our method reduces the sensitivity to the background NO2 and includes much of the below-cloud LNO2. As the LNOx parameterization varies in studies, the sensitivity of our calculations to the setting of the amount of lightning NO (LNO) is evaluated. Careful consideration of the ratio of LNO2 to NO2 is also needed, given its large influence on the estimation of LNO2 PE.

Abstract. Lightning serves as the dominant source of nitrogen oxides (NOx = NO + NO2) in the upper troposphere (UT), with strong impact on ozone chemistry and the hydroxyl radical production. However, the production efficiency (PE) of lightning nitrogen oxides (LNOx) is still quite uncertain (32–1100 mol NO per flash). Satellites measurements are a powerful tool to estimate LNOx directly as compared to conventional platforms. To apply satellite data in both clean and polluted regions, a new algorithm for calculating LNOx has been developed based on the program of new Berkeley High Resolution (BEHR) v3.0B NO2 product and the Weather Research and Forecasting-Chemistry (WRF-Chem) model. LNOx PE over the continental US is estimated using the NO2 product of the Ozone Monitoring Instrument (OMI) satellite and the Earth Networks Total Lightning Network (ENTLN) data. Focusing on the summer season during 2014, we find that the lightning NO2 (LNO2) PE is 44 ± 16 mol NO2 flash-1 and 8 ± 3 mol NO2 stroke-1 while LNOx PE is 120 ± 52 mol NOx flash-1 and 22 ± 9 mol NOx stroke-1. Results reveal that former methods are more sensitive to background NO2 and neglect much of the below-cloud LNO2. As the LNOx parameterization varies in studies, the sensitivity of our calculations to the setting of the amount of lightning NO (LNO) is evaluated. Careful consideration of the ratio of LNO2 to NO2 is also needed, given its large influence on the estimation of LNO2 PE.

The spatiotemporal statistical characteristics of warm-season deep convective systems, particularly deep convective systems initiation (DCSI), over China and its vicinity are investigated using Himawari-8 geostationary satellite measurements collected during April-September from 2016 to 2020. Based on a satellite brightness temperature multiple-threshold convection identification and tracking method, a total of 47593 deep convective systems with lifetimes of at least 3 h were identified in the region. There are three outstanding local maxima in the region, located in the southwestern, central and eastern Tibetan Plateau and Yunnan-Guizhou Plateau, followed by a region of high convective activities in South China. Most convective systems are developed over the Tibetan Plateau, predominantly eastward-moving, while those developed in Yunnan-Guizhou Plateau and South China mostly move westward and southwestward. The DSCI occurrences become extremely active after the onset of the summer monsoon and tend to reach a maximum in July and August, with a diurnal peak at 11–13 LST in response to the enhanced solar heating and monsoon flows. Several DCSI hotspots are identified in the regions of inland mountains, tropical islands and coastal mountains during daytime, but in basins, plains and coastal areas during nighttime. DCSI over land and oceans exhibits significantly different sub-seasonal and diurnal variations. Oceanic DCSI has an ambiguous diurnal variation, although its sub-seasonal variation is similar to that over land. It is demonstrated that the high spatiotemporal resolution satellite dataset provides rich information for understanding the convective systems over China and vicinity, particularly the complex terrain and oceans where radar observations are sparse or none, which will help to improve the convective systems and initiation nowcasting.