Large-eddy simulations of the impact of ground-based glaciogenic seeding on shallow orographic convection: A case study

Xia Chu, Bart Geerts, Lulin Xue, Roy Rasmussen

Research output: Contribution to journalArticlepeer-review

18 Scopus citations

Abstract

This study uses the WRF large-eddy simulation model at 100-m resolution to examine the impact of ground-based glaciogenic seeding on shallow (~2 km deep), cold-based convection producing light snow showers over the Sierra Madre in southern Wyoming on 13 February 2012, as part of the AgI Seeding Cloud Impact Investigation (ASCII). Detailed observations confirm that simulation faithfully captures the orographic flow, convection, and natural snow production, especially on the upwind side. A comparison between treated and control simulations indicates that glaciogenic seeding effectively converts cloud water in convective updrafts to ice and snow in this case, resulting in increased surface precipitation. This comparison further shows that seeding enhances liquid water depletion by vapor deposition, and enhances buoyancy, updraft strength, and cloud-top height. This suggests that the dynamic seeding concept applies, notwithstanding the clouds' low natural supercooled liquid water content. But the simulated cloud-top-height changes are benign (typically <100 m). This, combined with the fact that most natural and enhanced snow growth occurs in a temperature range in which the Bergeron diffusional growth process is effective, suggests that the modeled snowfall enhancement is largely due to static (microphysical) processes rather than dynamic ones.

Original languageEnglish
Pages (from-to)69-84
Number of pages16
JournalJournal of Applied Meteorology and Climatology
Volume56
Issue number1
DOIs
StatePublished - 2017

Keywords

  • Cloud microphysics
  • Cloud resolving models
  • Large eddy simulations
  • Radars/Radar observations

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