Can we infer microphysical process information from (infrequent) snapshots of data?

Satellite-based radiometers are providing a wealth of remotely sensed retrievals of aerosol and cloud properties but often in the form of snapshots of data that are composited in geophysical variable (GV) maps such as liquid water path, drop concentration, cloud fraction, optical depth, radar reflectivity, etc. Similar GV maps can be constructed from aircraft or surface-remote sensing data. The question arises whether the snapshot GV maps encode information on time-evolving physical processes. For example, does the relationship between variables X and Y in the form of Y(X) represent the influence of X on Y? And if so, how quantitative is the relationship? We will present a number of examples examining this question and reflect on the nature of the underlying processes for cases that do allow us to infer ‘process’ from ‘snapshot’.