A Multivariate Approach for Identifying Modeled Liquid Propane Seeding Opportunities

Cloud seeding has long been considered a potential method for enhancing precipitation in water-scarce regions. However, the viability of traditional silver iodide (AgI) cloud seeding is constrained by stringent temperature requirements, limiting its applicability as ground temperatures rise in future climate simulations. This presentation introduces a methodology that leverages CONUS404 model data - a 40-year, 4-km model retrospective simulation - to identify regions and frequency of periods suitable for cloud seeding using liquid propane, addressing the temperature limitations associated with AgI seeding.

The proposed methodology integrates a comprehensive set of atmospheric parameters to assess cloud seeding potential. Criteria such as temperature and liquid water content are first assessed on a large spatial scale to identify regions of interest, then cloud depth, wind patterns, and planetary boundary layer height are additionally employed within these regions to determine favorable conditions for effective seeding. Results of the application of this methodology over Idaho will be presented.

This research contributes to the evolving landscape of cloud seeding techniques, addressing challenges posed by changing climate conditions and describing a robust framework for future analysis of liquid propane-seedable opportunities.