We are currently funded by a one year NSF EAGER award to build the “Arbitrary Moment Predictor” Microphysics Scheme.
There are two common classes of microphysics schemes – bin and bulk. Bin schemes explicitly predict the shape of the particle size distribution (PSD), whereas bulk schemes predict 1-3 integral quantities of the PSD. Bin and bulk schemes often lead to disparate predictions of cloud properties. The inherent problem that has not been overcome in the past when comparing simulations using bin or bulk schemes is that the list of differences between the schemes is long, and not all differences are a result of the various approaches that the two scheme types take to representing cloud particle properties. In the proposed work, the research team will circumvent this problem by constructing a bulk microphysics scheme from a bin scheme. Both the bin scheme, and the new “bulk-emulating” scheme (called AMP) will share the same set of assumptions and will use the exact same routines to predict cloud process rates. The only difference will be in how much, and what type of information about the cloud and hydrometeor categories is passed back to the main model at the end of each call to the microphysics routines.
The proposed AMP microphysics scheme is a novel and innovative idea that can lead to new insights in microphysical modeling. For the first time, a highly flexible microphysics scheme will exist that can be easily configured to predict any combination of moments, make use of PDFs other than the gamma PDF, and be structurally identical to a bin scheme in order to facilitate truly fair comparison between the two scheme types. A bulk-emulating scheme will allow for a large number of new research questions to be addressed by the science community. It will be able to reveal the conceptual and numerical limitations of bulk microphysics schemes, and it will allow us to develop guidance for the design of improved bulk microphysics schemes. It will allow us to assess the hypothesis that bulk schemes are inappropriate for simulating aerosol-cloud interactions. It will allow new simulations to be designed that investigate the physical mechanisms by which microphysical processes modulate cloud properties and aerosol-cloud interactions.
Our initial paper describing AMP was published in JAMES in 2019. The focus of the paper was on the impact of predicting different combinations of cloud droplet size distribution moments. We found that for evaporation and collision-coalescence, improvements could be obtained by predicting moments other than the 0th (number concentration) and 3rd (mass mixing ratio).