Środowiskowe Seminarium Fizyki Atmosfery

To test the feasibility of inverse modeling of cloud-aerosol interactions a set of synthetic tests (measurements generated by the model) were performed in which we coupled an adiabatic cloud parcel model to a Markov chain Monte Carlo (MCMC) algorithm. It is demonstrated that MCMC simulation can be used to efficiently find the correct optimal values of meteorological and aerosol physiochemical parameters for a specified droplet size distribution and determine the global sensitivity of these parameters. For an updraft velocity of 0.3 m s^-1 , a shift towards an increase in the relative importance of chemistry compared to the accumulation mode number concentration is shown to exist somewhere between marine (~75 cm^-3 ) and rural continental (~450 cm^-3 ) aerosol regimes.The inverse modelling framework was subsequently extended to real world observations. Examination of in-situ measurements from the Marine Stratus/Stratocumulus Experiment (MASE II) revealed that for air masses with higher number concentrations of accumulation mode (Dp = 60-120 nm) particles (~450 cm^-3 ), an accurate simulation of the measured droplet size distribution requires an accurate representation of the particle chemistry. The chemistry is relatively more important than the accumulation mode particle number concentration, and similar in importance to the particle mean radius. This result is somewhat at odds with current theory that suggests chemistry can be ignored in all except for the most polluted environments. Under anthropogenic influence, we must consider particle chemistry also in marine environments that may be deemed relatively clean.The MCMC algorithm can successfully reproduce the observed marine stratocumulus droplet size distributions. However, optimizing towards the broadness of the measured droplet size distribution resulted in a discrepancy between the updraft velocity, and mean radius/geometric standard deviation of the accumulation mode. This suggests that we are missing a dynamical process in the adiabatic cloud parcel model.