Opinion: Inferring process from snapshots of cloud systems

Abstract. The cloudy atmospheric boundary layer is a complex, open, dynamical system that is difficult to fully characterize through observations. Aircraft measurements provide cloud dynamical, thermodynamical, and microphysical properties along a flightpath, at high spatial/temporal resolution (order 10 m/0.1 s). These data are essentially contiguous “snapshots” in time of the state of the cloud and its environment. Polar-orbiting satellite-based remote sensing yields snapshots of retrieved cloud and aerosol properties once or twice a day at spatial scales on the order of 250 m, but these are usually averaged to scales of ≈20–100 km to reduce data variability. Neither approach tracks a parcel of air in time, a view that would yield more direct insights into the evolving system. Nevertheless, our long experience with aircraft and satellite-based remote sensing has taught us much about atmospheric processes, suggesting that one can gain insights into processes from these snapshots. Using mostly previously published work we present examples of collections of observation snapshots that reveal various degrees of process-level understanding. We couch the discussion in terms of the concepts of space-time exchange, ergodicity, and process vs. observation timescales. It is our hope that this paper will encourage the atmospheric sciences community to explore the value of these concepts more deeply.