Separating Microphysical Impacts from Dynamic Feedbacks in a Winter Orographic Seeding Case from SNOWIE

To better understand how silver iodide (AgI) aerosol impact wintertime orographic clouds and to improve the model capability to simulate such impacts, the Seeded and Natural Orographic Wintertime clouds: the Idaho Experiment (SNOWIE) field campaign was conducted between January–March 2017 based in Boise, Idaho. The artificial perturbations of natural wintertime orographic clouds induced by airborne AgI seeding led to observable in-situ and remote-sensing signals that were detected in several Intensive Observing Periods (IOPs) during SNOWIE. These IOPs are great cases for testing and improving the numerical models to simulate the impacts of seeding with AgI.

The previous numerical approach to address seeding impacts involves running two simulations, one without and one with seeding activities (Xue et al. 2013). The differences between these two runs should represent the simulated seeding impacts. However, due to microphysics-dynamics interactions and associated numerical error propagation, the precipitation difference pattern is often too noisy to consistently represent the simulated seeding effect.

In this study, we apply a piggybacking modeling methodology that allows clear separation of dynamical and microphysical impacts to simulate one SNOWIE IOP. The simulated seeding effects due to microphysical versus dynamic feedbacks will be presented.