A Statistical Framework for Evaluating Rain Microphysics in Model Simulations and Disdrometer Observations

Statistical analyses of a large disdrometer data set and a diverse set of model simulations for convection using the Regional Atmospheric Modeling System were conducted, with the mutual goal of providing insights into precipitation formation and microphysical processes. We demonstrate that a two-moment bulk microphysical model successfully captures the dominant observed modes of variability in rainfall related to rainfall intensity and raindrop size distributions. The model reproduced the general distribution of observed precipitation groups (PGs) derived from Principal Component Analysis. The multi-variable analysis also uncovered some shortcomings in the model as well as limitations of the disdrometer data. The model solutions were constrained in their predicted drop size distributions (DSDs) due to the fixed DSD parameters assumed in a two-moment microphysics scheme. A case study from the Mid-latitude Continental Clouds and Convection Experiment field project demonstrated how model results can be used to contextualize the disdrometer observations which are limited in sample size, spatial coherence, and detection of small drops and low drop concentrations. The case study also showed that the spatial patterns of the statistically derived PGs revealed by the model are consistent with the hypothesized microphysical processes that determine surface rain DSDs. This work demonstrates how leveraging the strengths of observations and models together can improve our understanding and representation of rain microphysical processes. Understanding precipitation processes is key to the Earth's water cycle and regional and climate modeling efforts. Herein we demonstrate how multi-parameter statistical analyses can be used to evaluate model representations of precipitation variability, and how the model can subsequently provide information about types of processes resulting in precipitation at the surface. Statistical analysis of disdrometer data and cloud resolving model simulations reveal the same primary modes of rain drop size distribution variabilityThe statistical analysis reveals six precipitation groups which are studied from the model for links to processesThe statistical framework is applied to a case study from Mid-latitude Continental Clouds and Convection Experiment demonstrating the mutual benefit of this analysis technique

Automated summary

Statistical analyses and model simulations were used to explore precipitation formation and microphysical processes, with the finding that the two-moment bulk microphysical model successfully captures rainfall variability. However, the model shows some limitations and the disdrometer data has its own constraints. A case study demonstrates how the model can provide valuable information to supplement limited disdrometer observations and improve the understanding of rain microphysical processes.