WRF-WxMod®

Cloud-seeding parameterization in WRF

The WRF-WxMod® model (Xue et al. 2013a,b) is a novel capability for evaluating the impacts of cloud seeding on precipitation, designing new or optimizing existing cloud-seeding programs, and/or forecasting cloud-seeding opportunities when run in a real-time forecast mode. WRF-WxMod uses a silver iodide (AgI) cloud-seeding parameterization to simulate the physical effects of AgI nucleation into ice, and growth into snow. Running two simulations of WRF-WxMod--one in which seeding is simulated and a “control simulation” without seeding--and then assessing the difference between the two simulations, provides a controlled way to evaluate the impacts of cloud seeding. For example, the difference in precipitation from the seeded simulation compared against the control simulation, is interpreted as the simulated seeding effect on precipitation.

This method not only provides an estimate of the amount of precipitation change, but also a spatial map of where the changes occurred. The cloud-seeding modeling framework has been used to investigate the microphysical chain of events of glaciogenic seeding and its effect on wintertime orographic clouds under both idealized and realistic conditions (Xue et al. 2013a,b, 2014, 2016, 2017; Geresdi et al. 2017, 2020; Chen et al. 2023, 2025; Harrold et al. 2026). The results indicate that the cloud-seeding parameterization can physically simulate the processes associated with seeding events.

Advanced computer models, like WRF-WxMod, and novel observations of seeding impacts, through field programs like the Seeded and Natural Orographic Wintertime clouds: the Idaho Experiment (SNOWIE, Tessendorf et al. 2019), are providing new opportunities to understand and quantify the effects of cloud seeding and to more efficiently design and operate cloud-seeding programs.