Coupling of CCN and INP in Cloud Systems Is Important to Climate: Uncertainties and Implications

Uncertainties in microphysical processes are currently a leading barrier to establishing the response of both convective and cold stratiform cloud systems to variations in CCN and INP populations. In the case of deep convection with stratiform outflow, which is common and widespread particularly over the tropics, observationally driven studies are increasingly concluding that ice multiplication is far more efficient than expected. Such active ice multiplication achieves far greater ice crystal number concentrations than can be explained by available INP, as well as more rapid glaciation of updrafts, reduced precipitation efficiency, and greater ice water content in convective outflow that is more widespread and longer-lived. The typical use of diagnostic INP in modeling studies, attributable at least in part to a lack of understanding of environmental INP properties, partially masks the inadequacy of ice multiplication schemes because neglecting INP consumption artificially enhances ice formation. Observationally driven studies are increasingly seeking to establish whether various multiplication mechanism candidates not commonly included in models can explain the amounts of ice observed; thus far such studies often report conflicting results and are broadly limited by robust and repeatable results from laboratory chambers, which have been challenged to reproduce many aspects of the natural environment. Evidence from convective as well as mixed-phase stratiform cloud systems continues to indicate that the presence of precipitation-sized drops is commonly associated with rapid ice multiplication. Cloud system responses to CCN and INP variations in nature should therefore be coupled at least insofar as reducing CCN increases the number of precipitation-sized drops. A minimum primary INP activation rate would also be expected, and other coupling mechanisms could be of consequence depending on the active processes. Owing to the radiative effects of widespread convective and mixed-phase cloud systems, the climate modeling community would benefit from focusing clearly on research priorities that can rapidly advance understanding. Such priorities would need to include a sustained commitment to (i) laboratory studies of ice multiplication processes with repeatable results, (ii) observationally driven studies that can elucidate microphysical processes, and (iii) use of prognostic CCN and INP schemes in modeling studies that are well constrained by observations.