Application of total-lightning data assimilation in a mesoscale convective system based on the WRF model
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Abstract
A total lightning data assimilation method was proposed and applied in a mesoscale
convective system (MCS) simulation with the Weather Research and Forecasting (WRF)
model. On the bases of analyses of several thunderstorm processes over northern China,
empirical formulas between total lightning flash rate and ice-phase particle (graupel, ice, and
snow) mixing ratio were constructed based on the well-known relationship between the
occurrence of lightning activity and the content of ice-phase particles. The constructed
nudging functions were added into the WSM6 microphysical scheme of WRF to adjust the
mixing ratio of ice-phase particles within a temperature layer from 0 °C to −20 °C isotherms,
and consequently the convective precipitation. The method was examined in a MCS with high
lightning flash rate and heavy precipitation occurred over two megacities of Beijing and
Tianjin, northern China. The representation of convection was significantly improved 1 h after
the lightning data assimilation, and even during the assimilation period. The precipitation
center, amount and coverage were all much closer to the observation in the sensitivity run
with lightning data assimilation than in the control run without lightning data assimilation.
The results showed promising improvements on the convection and precipitation and
demonstrated rationality and effectiveness of the proposed assimilation technique. The results
also showed that active lightning regions have a strong capability of adjusting convection
and precipitation, suggesting that the assimilation method can be used for improving the
short-term precipitation forecasting of MCS with high, even moderate lightning flash rate.
Abstract
A total lightning data assimilation method was proposed and applied in a mesoscale
convective system (MCS) simulation with the Weather Research and Forecasting (WRF)
model. On the bases of analyses of several thunderstorm processes over northern China,
empirical formulas between total lightning flash rate and ice-phase particle (graupel, ice, and
snow) mixing ratio were constructed based on the well-known relationship between the
occurrence of lightning activity and the content of ice-phase particles. The constructed
nudging functions were added into the WSM6 microphysical scheme of WRF to adjust the
mixing ratio of ice-phase particles within a temperature layer from 0 °C to −20 °C isotherms,
and consequently the convective precipitation. The method was examined in a MCS with high
lightning flash rate and heavy precipitation occurred over two megacities of Beijing and
Tianjin, northern China. The representation of convection was significantly improved 1 h after
the lightning data assimilation, and even during the assimilation period. The precipitation
center, amount and coverage were all much closer to the observation in the sensitivity run
with lightning data assimilation than in the control run without lightning data assimilation.
The results showed promising improvements on the convection and precipitation and
demonstrated rationality and effectiveness of the proposed assimilation technique. The results
also showed that active lightning regions have a strong capability of adjusting convection
and precipitation, suggesting that the assimilation method can be used for improving the
short-term precipitation forecasting of MCS with high, even moderate lightning flash rate.
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