TY - JOUR
T1 - Large-eddy simulations of the impact of ground-based glaciogenic seeding on shallow orographic convection
T2 - A case study
AU - Chu, Xia
AU - Geerts, Bart
AU - Xue, Lulin
AU - Rasmussen, Roy
PY - 2017
Y1 - 2017
N2 - 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.
AB - 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.
KW - Cloud microphysics
KW - Cloud resolving models
KW - Large eddy simulations
KW - Radars/Radar observations
UR - https://www.scopus.com/pages/publications/85009433775
U2 - 10.1175/JAMC-D-16-0191.1
DO - 10.1175/JAMC-D-16-0191.1
M3 - Article
AN - SCOPUS:85009433775
SN - 1558-8424
VL - 56
SP - 69
EP - 84
JO - Journal of Applied Meteorology and Climatology
JF - Journal of Applied Meteorology and Climatology
IS - 1
ER -