Assessing glaciogenic seeding impacts in Australia's Snowy Mountains: an ensemble modeling approach

Abstract

Winter precipitation over Australia's Snowy Mountains provides a crucial water resource in the region. Cloud seeding has been operational to enhance snowfall and water storage. This study presents ensemble simulations to assess cloud seeding impacts across diverse meteorological conditions and evaluate associated model uncertainties. Nine seeding cases from 2016 to 2019 were simulated, with 18 ensemble members varying initialization datasets and model configurations. Two main storm categories were studied (convective vs. stratiform). Results demonstrate that simulated seeding efficacy highly depends on meteorological conditions. Stratiform cases exhibited consistent precipitation enhancement, while convective cases showed reductions and downwind shifts in precipitation. Significantly inter-member variability was also observed. Notably, simulations driven by the Bureau of Meteorology Atmospheric high-resolution Regional Reanalysis for Australia (BARRA) reanalysis dataset show better representation in supercooled liquid water. Aerosol and planetary boundary layer scheme variations also contributed to ensemble spread. The findings demonstrate the value of ensemble modeling for reliable cloud seeding assessment. Key areas are also identified for future investigations in winter cloud seeding.