Ice-phase cloud microphysics scheme implementation in open-source Julia library

Clouds are major sources of uncertainty in global circulation models (GCMs). Since GCMs use 10-100km length scales, clouds are too small to be resolved and require computationally efficient methods of parameterization. Traditionally, tracking different artificial ice categories has led to model biases, but the predicted particle properties (P3) scheme offers the alternative of tracking a single category by evolving properties such as rime and liquid fraction.

Implemented in CloudMicrophysics.jl, an open-source Julia library developed by the Climate Modeling Alliance (CliMA), the P3 scheme solves two nonlinear systems involving critical property-determining sizes and the parameters of the particle size distribution. Tests in a 1D framework produced stable sedimentation and melting simulations, and a portion of the microphysical process rates have been implemented. Results indicate that the scheme is attuned to complex ice processes. Upon completion of the process rates, testing the scheme against observations in increasingly complex models will allow for further evaluation.