1Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration/Collaborative Innovation Centre on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing, China
2Institute of Urban Meteorology, China Meteorological Administration (CMA), Beijing 100089, China
3Collaborative Innovation Centre for Western Ecological Safety, Lanzhou University, Lanzhou 730000, China
4Nanjing Joint Institute for Atmospheric Sciences, Nanjing 211112, China
5Key Laboratory of Transportation Meteorology, CMA, Nanjing 210009, China
6College of Safety Science and Engineering, Nanjing Technology University, Nanjing 210009, China
1Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration/Collaborative Innovation Centre on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing, China
2Institute of Urban Meteorology, China Meteorological Administration (CMA), Beijing 100089, China
3Collaborative Innovation Centre for Western Ecological Safety, Lanzhou University, Lanzhou 730000, China
4Nanjing Joint Institute for Atmospheric Sciences, Nanjing 211112, China
5Key Laboratory of Transportation Meteorology, CMA, Nanjing 210009, China
6College of Safety Science and Engineering, Nanjing Technology University, Nanjing 210009, China
Received: 13 Dec 2022 – Discussion started: 24 Jan 2023
Abstract. Abstract. Aerosol–fog interactions (AFIs) play pivotal roles in the fog cycle. However, few studies have focused on the differences in AFIs between two successive radiation fog events and the underlying mechanisms. To fill this knowledge gap, our study simulates two successive radiation fog events in the Yangtze River Delta, China, using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). Our simulations indicate that AFIs in the first fog (Fog1) promote AFIs in the second one (Fog2), resulting in higher number concentration, smaller droplet size, larger fog optical depth, wider fog distribution, and longer fog lifetime in Fog2 than in Fog1. This phenomenon is defined as the self-enhanced AFIs, which are related to the following physical factors. The first one is conducive meteorological conditions between the two fog events, including low temperature, high humidity and high stability. The second one is the feedbacks between microphysics and radiative cooling. A higher fog droplet number concentration increases the liquid water path and fog optical depth, thereby enhancing the long-wave radiative cooling and condensation near the fog top. The third one is the feedbacks between macrophysics, radiation, and turbulence. A higher fog top presents stronger long-wave radiative cooling near the fog top than near the fog base, which weakens temperature inversion and strengthens turbulence, ultimately increasing the fog-top height and fog area. In summary, AFIs postpone the dissipation of Fog1 due to these two feedbacks and generate more conducive meteorological conditions before Fog2 than before Fog1. These more conducive conditions promote the earlier formation of Fog2, further enhancing the two feedbacks and strengthening the AFIs. Our findings are critical for studying AFIs and shed new light on aerosol–cloud interactions.
Fog is an important meteorological phenomenon affecting visibility. Aerosols play critical roles in the fog life cycle. In this study, the self-enhanced aerosol–fog interactions (AFIs) are proposed in two successive radiation fog events (Fog1 and Fog2), defined as a phenomenon that AFIs in Fog1 enhance AFIs in Fog2. The AFIs delay Fog1 dissipation, leading to more conducive meteorological conditions and stronger AFIs in Fog2.
Fog is an important meteorological phenomenon affecting visibility. Aerosols play critical roles...