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The ASCII 2012 campaign: overview and early results AgI Seeding Cloud Impact Investigation

The ASCII 2012 campaign: overview and early results AgI Seeding Cloud Impact Investigation. funded by NSF AGS-1058426. University of Wyoming NCAR University of Colorado University of Illinois Ningbo University. Bart Geerts presented by: Xia Chu

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The ASCII 2012 campaign: overview and early results AgI Seeding Cloud Impact Investigation

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  1. The ASCII 2012 campaign: overview and early resultsAgI Seeding Cloud Impact Investigation funded by NSF AGS-1058426 University of Wyoming NCAR University of Colorado University of Illinois Ningbo University Bart Geerts presented by: Xia Chu contributions by: KatjaFriedrich, Terry Deshler, David Kristovich, Joshua Wurman, Larry Oolman, Samuel Haimov, Qun Miao, Dan Breed, Roy Rasmussen, LulinXue, Binod Pokharel, Yang Yang, Bruce Boe AMS Planned and Inadvertent Weather Modification Conference, 9 Jan 2013

  2. ASCII’s core goal to gain insight into how glaciogenic seeding alters cloud microphysical processes in orographic clouds, using • new instrumentsboth airborne and ground-based • LES modeling with resolved microphysics

  3. ASCII target mountains 2008, 09, 13 target 2012 target

  4. ASCII seeding source: the 2007-14 Wyoming Weather Mod Pilot Project, a dual-mountain randomized project, evaluated by NCAR (Rasmussen, Breed) Medicine Bow Range Sierra Madre

  5. ASCII 2012 experimental design

  6. Battle Pass (elevation 3000 m)

  7. Battle Pass instruments dual-polarization x-band Doppler radar (DOW7)

  8. Battle Pass instruments passive microwave radiometer MRR profiling Ka-band radar Parsiveldisdrometer snow size distribution (>1 mm) and terminal velocity profiles of reflectivity and hydrometeor vertical velocity water vapor, temp profile, liquid water path

  9. Battle Pass instruments Vaisala wxt520 (T, p, q, wind) Yankee Hotplate snow rate snow photography, sampling for chemical analysis ceilometer • mountain • mountain • mountain • valley

  10. Battle Pass instruments SPEC Cloud Particle Imager imaging of particles >20 micron

  11. UW King Air remote sensors • WCR (3 mm, W-band) • three antennas • pulse width 250 ns, sampled at 15 m • max range 6 km • minimum detectable signal (@ 1 km): ~-30 dBZ • reflectivity is dominated by ice crystals • WCL: • down-looking only • backscatter power • depolarization ratio Wyoming Cloud Radar Wyoming Cloud Lidar

  12. leg 1: control leg AgI generators on the ground legs 2-5: treated legs 2009 02 18 flight sequence non-simultaneous comparison NOSEED, then SEED identical flight pattern Medicine Bow Range

  13. 2009 02 18 1726 UTC Medicine Bow Range Wyoming cloud base temperature -9°C cloud top temperature -26°C much liquid water in cloud

  14. case study: 18 Feb 2009 2012 02 21 2010 UTC Sierra Madre cloud base temp -8.4°C much liquid water in cloud (LWP ~0.22 mm) Bridger Peak Battle Pass

  15. leg 4 reflectivity (dBZ) black line = radar blind zone (flight level) pass 1 NOSEED Med Bow Range airflow into the page 40 km 40 km pass 2 NOSEED case study: 18 Feb 2009 pass 3 SEED pass 4 SEED

  16. 18 Feb 2009: [seed – noseed] CFADtreated legs think of blue as a positive SEED effect null hypothesis: this is natural variability seed (2 passes) noseed (2 passes) Positive seeding effect confined to the boundary layer (~lowest 1 km)

  17. 18 Feb 2009: [seed – noseed] CFADcontrol leg seed (2 passes) noseed (2 passes) “Natural” storm intensity actually decreased during SEED period

  18. SEED effect: all cases, all treated legs (source: Bruce Boe) Sierra Madre 2012 9 cases Medicine Bow 2008-09 7 cases height AGL (km)

  19. ground-based profiling radars MRR2

  20. ground-based profiling radars Sierra Madre 2012: 11 cases treated: downstream MRR control: upstream MRR AgI generators

  21. case study: 18 Feb 2009: WRF LES (Xue) terrain map

  22. case study: 18 Feb 2009: WRF LES (Xue) sounding comparison

  23. case study: 18 Feb 2009: WRF LES (Xue) CFAD comparison

  24. Conclusions • Ground-based glaciogenic seeding of orographic clouds may significantly increase reflectivity in the boundary layer, and thus snowfall on the ground. • Profiling radar evidence is based on 3 types of comparisons: • non-simultaneous: treated flight legs (change within the BL) • nearly-simultaneous: control flight legs (upwind of generator) • simultaneous: ground-based radars • 100 m Large Eddy Simulation over mountain range shows strong, but very shallow seeding effect. • Net impact of AgI seeding over a season is typically much smaller, because many poor cases are included. Suitable conditions for seeding appear to be quite rare.

  25. specific ASCII objectives B. related to AgIseeding: model validation to evaluate WRF_Large Eddy Simulations with point seeding module work by LulinXue, Roy Rasmussen

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