A Numerical Evaluation of the Impact of Operational Ground-Based Glaciogenic Cloud Seeding on Precipitation over the Wind River Range, Wyoming

Thomas Mazzetti, Bart Geerts, Lulin Xue

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

This study evaluates an operational glaciogenic cloud-seeding program using ground-based generators of silver iodide (AgI), with a total of 190 seeded storms over 10 cold seasons, using the Weather Research and Forecasting Weather Modification (WRF-WxMod) scheme at 900-m grid spacing. This study examines both the quantitative change in precipitation and the ambient and cloud conditions impacting seeding efficacy. An ensemble approach is used, with differing model boundary conditions, ice nucleation physics, concentrations of cloud condensation nuclei, and boundary layer schemes. This is intended to provide an envelope of uncertainty of natural clouds and seeding impacts. The simulations are validated against radiosonde, snow gauge, and microwave radiometer observations, and the seeding impact is inferred from simulations with/without AgI seeding. The seeding-induced precipitation enhancement (“yield”) varies greatly between storms. A small portion of the cases produces the majority of the yield. Overall, the precipitation in the target area (the Wind River Range in Wyoming) increased by 1.10% ± 0.13% in the 10 years of operational seeding. This rather low fractional increase is related to the frequent seeding at unsuitable times, primarily because of low-level flow blocking. The flow and cloud structure for select cases are examined to provide better insight into the variability of yield. Cases with unblocked surface flow and abundant cloud liquid water tend to be the most productive. The technique presented here can be readily adapted to evaluate the seeding impact of other long-term glaciogenic seeding operations and to improve their operational efficiency.

Original languageEnglish
Pages (from-to)489-510
Number of pages22
JournalJournal of Applied Meteorology and Climatology
Volume62
Issue number4
DOIs
StatePublished - Apr 2023

Keywords

  • Cloud seeding
  • Cloud-resolving models
  • Weather modification

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