14:30 〜 14:45
[AAS11-15] 気象雷モデルとオフライン化学輸送モデルを用いた雷起源の窒素酸化物に関する数値実験
キーワード：雷起源のNOx、化学輸送モデル
The production ratio of the lightning-induced nitrogen (LNOx) was investigated using a meteorological model (Nishizawa et al., 2015; Sato et al., 2015) coupled with a bulk lightning model (Sato et al., 2019, 2022) and an offline chemical transport model (Kajino et al., 2019). For investigating it, we have implemented the emission of LNOx into the model. The emission of the LNOx is implemented as the emission of nitrogen mono-oxide (NO) based on literature (Rakov & Uman, 2003).
Using the model, numerical simulations were conducted targeting on August 22th of 2017, when the lightning-induced nitrogen was measured at summit of Mount Fuji (Wada et al., 2019). The results of the numerical simulations indicate that the reactive nitrogen (NOy) measured around 12 UTC on 22 August of 2017 was well reproduced by the model. In contrast, the NOy was not reproduced if the lightning induced nitrogen is not considered in the model. These results indicate that NOy measured around 12 UTC on 22 August was originated from the lightning that occurred around Wakasa Bay around 09 UTC of the same day. The sensitivity of the production ratio of LNO was also investigated by sweeping production ratio of the LNOx.
Reference
Kajino, M., Deushi, M., Sekiyama, T. T., Oshima, N., Yumimoto, K., Tanaka, T. Y., et al. (2019). NHM-Chem, the Japan meteorological agency’s regional meteorology – chemistry model: Model evaluations toward the consistent predictions of the chemical, physical, and optical properties of aerosols. Journal of the Meteorological Society of Japan, 97(2), 337–374. https://doi.org/10.2151/JMSJ.2019-020
Nishizawa, S., Yashiro, H., Sato, Y., Miyamoto, Y., & Tomita, H. (2015). Influence of grid aspect ratio on planetary boundary layer turbulence in large-eddy simulations. Geoscientific Model Development, 8(10), 3393–3419. https://doi.org/10.5194/gmd-8-3393-2015
Rakov, V. A., & Uman, M. A. (2003). Lightning: Physics and Effects. Cambridge University Press.
Sato, Y., Nishizawa, S., Yashiro, H., Miyamoto, Y., Kajikawa, Y., & Tomita, H. (2015). Impacts of cloud microphysics on trade wind cumulus: which cloud microphysics processes contribute to the diversity in a large eddy simulation? Progress in Earth and Planetary Science, 2(1), 23. https://doi.org/10.1186/s40645-015-0053-6
Sato, Y., Miyamoto, Y., & Tomita, H. (2019). Large dependency of charge distribution in a tropical cyclone inner core upon aerosol number concentration. Progress in Earth and Planetary Science, 6(1), 62. https://doi.org/10.1186/s40645-019-0309-7
Sato, Y., Hayashi, S., & Hashimoto, A. (2022). Difference in the lightning frequency between the July 2018 heavy rainfall event over central Japan and the 2017 northern Kyushu heavy rainfall event in Japan. Atmospheric Science Letters, 23(1). https://doi.org/10.1002/asl.1067
Wada, R., Sadanaga, Y., Kato, S., Katsumi, N., Okochi, H., Iwamoto, Y., et al. (2019). Ground-based observation of lightning-induced nitrogen oxides at a mountaintop in free troposphere. Journal of Atmospheric Chemistry, 76(2), 133–150. https://doi.org/10.1007/s10874-019-09391-4
Using the model, numerical simulations were conducted targeting on August 22th of 2017, when the lightning-induced nitrogen was measured at summit of Mount Fuji (Wada et al., 2019). The results of the numerical simulations indicate that the reactive nitrogen (NOy) measured around 12 UTC on 22 August of 2017 was well reproduced by the model. In contrast, the NOy was not reproduced if the lightning induced nitrogen is not considered in the model. These results indicate that NOy measured around 12 UTC on 22 August was originated from the lightning that occurred around Wakasa Bay around 09 UTC of the same day. The sensitivity of the production ratio of LNO was also investigated by sweeping production ratio of the LNOx.
Reference
Kajino, M., Deushi, M., Sekiyama, T. T., Oshima, N., Yumimoto, K., Tanaka, T. Y., et al. (2019). NHM-Chem, the Japan meteorological agency’s regional meteorology – chemistry model: Model evaluations toward the consistent predictions of the chemical, physical, and optical properties of aerosols. Journal of the Meteorological Society of Japan, 97(2), 337–374. https://doi.org/10.2151/JMSJ.2019-020
Nishizawa, S., Yashiro, H., Sato, Y., Miyamoto, Y., & Tomita, H. (2015). Influence of grid aspect ratio on planetary boundary layer turbulence in large-eddy simulations. Geoscientific Model Development, 8(10), 3393–3419. https://doi.org/10.5194/gmd-8-3393-2015
Rakov, V. A., & Uman, M. A. (2003). Lightning: Physics and Effects. Cambridge University Press.
Sato, Y., Nishizawa, S., Yashiro, H., Miyamoto, Y., Kajikawa, Y., & Tomita, H. (2015). Impacts of cloud microphysics on trade wind cumulus: which cloud microphysics processes contribute to the diversity in a large eddy simulation? Progress in Earth and Planetary Science, 2(1), 23. https://doi.org/10.1186/s40645-015-0053-6
Sato, Y., Miyamoto, Y., & Tomita, H. (2019). Large dependency of charge distribution in a tropical cyclone inner core upon aerosol number concentration. Progress in Earth and Planetary Science, 6(1), 62. https://doi.org/10.1186/s40645-019-0309-7
Sato, Y., Hayashi, S., & Hashimoto, A. (2022). Difference in the lightning frequency between the July 2018 heavy rainfall event over central Japan and the 2017 northern Kyushu heavy rainfall event in Japan. Atmospheric Science Letters, 23(1). https://doi.org/10.1002/asl.1067
Wada, R., Sadanaga, Y., Kato, S., Katsumi, N., Okochi, H., Iwamoto, Y., et al. (2019). Ground-based observation of lightning-induced nitrogen oxides at a mountaintop in free troposphere. Journal of Atmospheric Chemistry, 76(2), 133–150. https://doi.org/10.1007/s10874-019-09391-4