Karagodin, A., E. Rozanov, E., and I. Mironova, On the Possibility of Modeling the IMF By-Weather Coupling through GEC-Related Effects on Cloud Droplet Coalescence Rate, Atmosphere, 13, 881, 2022. doi: 10.3390/ atmos13060881.
The meteorological response to the fluctuation of the interplanetary magnetic field (IMF), known as the Mansurov effect, is well established. It is hypothesized that the IMF By fluctuation can modulate the atmospheric global electric circuit (GEC) over the polar regions and affect surface meteorology. The influence of electric charges on the rate of droplet coalescence in fair-weather clouds is one of several cloud microphysical mechanisms that have been hypothesized to be involved. However, although meteorological effects associated with IMF By have been observed, the role of cloud droplet coalescence in this solar–weather coupling mechanism has not yet been confirmed. In addition, studies demonstrating the solar wind-driven effects are based on observations without using global climate models to support the IMF By-weather linkage. In this study, we investigate the Mansurov effect over the period 1999–2002 using ensemble experiments modeled with the chemistryclimate model (CCM) SOCOLv3 (SOlar Climate Ozone Links, version 3.0). Using observed IMF By, we model its effect on ground-level air pressure and temperature to examine one of the proposed GEC-cloud hypotheses: that surface meteorology response on IMF By fluctuations occurs through the Jz-associated intensification of cloud droplet coalescence rate. The results showed that we cannot explain and confirm the hypothesis that the rate of cloud droplet coalescence is an intermediate link for the IMF By-weather coupling. Anomalies in surface air pressure and temperature from the control run, where IMF By is omitted, do not robustly differ from experiments in which the dependence of cloud droplet coalescence rate on IMF By is included. In addition, the standard deviation of anomalies in surface air pressure and temperature between ensemble members is consistent with the magnitude of the observed effect even in the control run, suggesting that the model has a strong internal variability that prevents the IMF By effect from being properly detected in the model.