Measurements in convective clouds show that actual droplet size distributions are much broader than those predicted by the classical deterministic theory of condensational growth. Stochastic condensation models attempt to describe the additional processes acting in real clouds that would explain the occurrence of broader droplet spectra.
In this talk I review the Khvorostyanov-Curry Eulerian model of stochastic condensation and contrast it with Lagrangian stochastic approaches. While in Eulerian models a large ensemble of droplets is uniformly subject to fluctuating supersaturation, Lagrangian models allow each droplet to experience a different fluctuation history, thus providing a natural statistical sampling of the droplet spectra.