the ascii 2012 campaign: overview and early results agi seeding cloud impact investigation bart...
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The ASCII 2012 campaign: overview and early results
AgI Seeding Cloud Impact Investigation
Bart Geertspresented by: Xia Chu
contributions by: Katja Friedrich, Terry Deshler, David Kristovich, Joshua Wurman, Larry Oolman, Samuel Haimov, Qun Miao, Dan
Breed, Roy Rasmussen, Lulin Xue, Binod Pokharel, Yang Yang, Bruce Boe
AMS Planned and Inadvertent Weather Modification Conference, 9 Jan 2013
University of WyomingNCARUniversity of ColoradoUniversity of Illinois Ningbo University
funded by NSF AGS-1058426
ASCII’s core goal
to gain insight into how glaciogenic seeding alters cloud microphysical processes in orographic clouds, using
– new instruments both airborne and ground-based– LES modeling with resolved microphysics
2012 target
ASCII target mountains
2008, 09, 13 target
Sierra Madre
Medicine Bow Range
ASCII seeding source: the 2007-14 Wyoming Weather Mod Pilot Project, a dual-mountain randomized project,
evaluated by NCAR (Rasmussen, Breed)
ASCII 2012experimental design
Battle Pass (elevation 3000 m)
dual-polarization x-band Doppler radar (DOW7)
Battle Pass instruments
Battle Pass instruments
snow size distribution (>1 mm)
and terminal velocity
profiles of reflectivityand hydrometeor vertical velocity
water vapor, temp profile, liquid water
path
passive microwaveradiometer
MRR profiling Ka-band radar
Parsivel disdrometer
Yankee Hotplate
snow rate
Vaisalawxt520
(T, p, q, wind)
snow photography, sampling for
chemical analysis
ceilometer
mountain mountain mountainvalley
Battle Pass instruments
SPEC Cloud Particle Imager
imaging of particles >20 micron
Battle Pass instruments
UW King Air remote sensors
Wyoming Cloud Lidar
• 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
Medicine Bow Rangenon-simultaneous comparison
NOSEED, then SEEDidentical flight pattern
legs
2-5
: tre
ated
legs
NO SEEDING SEEDING
54321 54321 54321 54321
2009 02 18 flight sequence
AgI generatorson the ground
leg
1: c
ontrol
leg
2009 02 18 1726 UTCMedicine Bow Range
Wyomingcloud base temperature -9°Ccloud top temperature -26°Cmuch liquid water in cloud
Battle PassBridger Peak
2012 02 21 2010 UTCSierra Madre
cloud base temp -8.4°Cmuch liquid water in cloud
(LWP ~0.22 mm)
case study: 18 Feb 2009
pass 1NOSEED
pass 2NOSEED
leg 4 reflectivity (dBZ)
40 km
airflow into the
page
Med Bow Range
black line = radar blind zone (flight level)
40 km
pass 3SEED
pass 4SEED
case
study: 1
8 Fe
b 2
00
9
Positive seeding effect confined to the boundary layer (~lowest 1 km)
18 Feb 2009: [seed – noseed] CFADtreated legs
seed (2 passes)noseed (2 passes)
think of blue as a positive SEED effect null hypothesis: this is natural variability
“Natural” storm intensity actually decreased during SEED period
18 Feb 2009: [seed – noseed] CFADcontrol leg
seed (2 passes)noseed (2 passes)
SEED effect: all cases, all treated legs
Sierra Madre 20129 cases
-19
-18
-17
-16
-15
-14
-13
-12
-11
-10
-9 -8 -7 -6 -5 -4 -30
1
2
3
4ASCII Sierra Madre 12Med Bow 08-09
700 mb temperature (°C)
num
ber o
f IO
Ps
(source: Bruce Boe)
Medicine Bow 2008-09 7 cases
heig
ht
AG
L (k
m)
MRR2
ground-based profiling radars
ground-based profiling radars
Sierra Madre 2012: 11 cases
AgI generators
control: upstream MRR treated: downstream MRR
case study: 18 Feb 2009: WRF LES (Xue)
terrain map
case study: 18 Feb 2009: WRF LES (Xue)
sounding comparison
case study: 18 Feb 2009: WRF LES (Xue)
CFAD comparison
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.
specific ASCII objectives
to evaluate WRF_Large Eddy Simulations with point seeding module
B. related to AgI seeding: model validation
work by Lulin Xue, Roy Rasmussen