This document provides an overview of the history and scientific basis of cloud seeding. It discusses the conceptual model of cloud seeding, including that seeding material must be transported to clouds containing supercooled liquid water. Past research is summarized, including studies of seeding materials, transport and dispersion modeling, measurements of supercooled liquid water, and measurements showing microphysical and precipitation responses to seeding. Current research projects aiming to further validate the effects of cloud seeding are also mentioned. Hydrologic modeling techniques used to assess the impact of cloud seeding on streamflow are briefly outlined.

1. History and Scientific Basis of Cloud Seeding
Forum on Cloud Seeding in the Humboldt River
Basin to Increase Snowpack
Reno, Nevada
22 October 2012
Arlen W. Huggins
Desert Research Institute
Reno, Nevada, USA

2.  Brief history of cloud seeding
 Cloud seeding conceptual model
 Validation of the conceptual model
 Past and current research
 Trace chemical evaluation techniques
 Hydrologic modeling to assess impact on
streamflow
 Environmental issues
 Summary

3. Wintertime Seeding Conceptual Model
• Seeding material must be reliably produced
• Seeding material must be successfully transported to
clouds over the intended target
• Clouds must contain supercooled liquid water (SLW)
• Dispersion of seeding material
• Significant cloud volume must be affected by ice
nuclei, so
• Significant numbers of ice crystals can be formed
• Seeding material must reach the temperature needed for
ice crystal formation
• Depends on seeding material
• Ice crystals must reside in cloud long enough for growth
and fallout over the target area

4. Conceptual Diagram of Orographic Cloud Seeding
Ground-based seeding with silver iodide
-10C
-5C

5. Past Research
• Ice nucleating properties of various substances
• Transport and dispersion of seeding material
– Mapping plumes with aircraft or mobile ground platforms
– Plume dispersion models
• Supercooled liquid water measurements
– Aircraft sensors, mountain top icing sensors, microwave
radiometers
• Seeding-induced (microphysical) changes to clouds
– In cloud aircraft measurements
– Mobile ground-based measurements
– Ground-based remote sensing measurements
– Inference from trace chemical analysis of snowfall
• Seeding-induced changes to precipitation/snowfall
– Randomized experiments
– Detailed case studies with high-resolution precipitation
measurements (gauges or laser imaging probes)

6. Ice-forming Activity of Seeding Materials
Note with AgI
that a very small
mass is needed
to produce a very
large number of
ice nucleating
particles

7. Weather station
Plume of ice controls dispenser
crystals
Seeding materials & delivery methods

8. Availability of supercooled liquid water
 Seeding potential relies on an excess of SLW
 Studies over many mountainous areas have shown
 SLW is present at some stage on nearly every winter storm
 SLW exhibits considerable temporal and spatial variability
 SLW is found mainly over the windward slope and can extend
upwind
 Maximum SLW exists from below mountain crest to ~1km above
 SLW temperature
 Depends a lot on barrier height and geographic location
 Rocky Mountains: SLW base -2 to -10 C SLW top -10 to -15 C
 Sierra Nevada: SLW base often > 0 C SLW top -12 C or higher
 Seasonal SLW flux can be 50 – 100% of seasonal snowfall
 Suggests significant cloud seeding potential

10. SLW over a mountain barrier

11. Ag and In
Concentrations
Radiometer LW
Icing Sensor Counts
Precipitation
Temperature
Assessing conditions for seeding

12. Transport and Dispersion of Seeding Material
 Verification of T and D is Critical
 Documented in several research studies of 1970s, 1980s and 1990s
 Key element in success of randomized Bridger Range experiment
 Consistently successful T&D from high altitude generators
 Generators positioned part way up the windward slope
 Methods of verification
 Aircraft or ground-based detection of tracer gases
 Aircraft or ground-based ice nucleus counters
 Dispersion models for feasibility assessments (with verification)
 Trace chemical analysis of snowfall from the target

13. T and D Examples:
Measurements
Aircraft
from mobile Detection
platforms
Wasatch Plateau
AgI seeding from
a single site
Tracer gas and
ice nuclei
measurements Ground
Detection
Plume dimension
similar to results in
other areas

14. T and D
Examples:
Measurements
from a fixed site
Seeding plume verified with
Ice nuclei measurements
(NCAR counter)
SLW also verified
(Microwave radiometer)

15. Measurements of
microphysical
effects from
seeding:
Use of fixed
instrument
sites, aircraft
instruments, and
mobile ground-based
platforms

16. DRI Particle Dispersion Model Results
Two DRI ground
Generator sites
Part of
Dual-tracer
Ice Crystal
Enhancement
Experiment

17. Cloud Microphysical Responses to Seeding
 Verification of the initiation, growth and fallout of ice crystals
 Strong evidence from ground-based seeding experiments in Bridger Range
(MT), Grand Mesa (CO) and Wasatch Plateau (UT)
 Significant IC enhancement (>5x background) found in seeding plumes
 Best evidence found in cloud regions colder than -9 C with cloud tops
warmer than -20 C.
 Method of verification
 Aircraft or ground-based particle imaging probes
 Aircraft detection required flying within 300 m of mountain peaks
 Ground-base instruments at fixed location, or mobile

18. Microphysical
seeding effect
examples
Wasatch Plateau
AgI seeding from
a single site
Aircraft data show
aerosol and ice
crystal seeding
plumes
6 km or 16.7 min downwind
of seeding site

19. Microphysical
seeding effect
examples
Wasatch Plateau
AgI seeding from
a single site
Aircraft data show
aerosol and ice
crystal seeding
plumes
15 km or 41.7 min downwind
of seeding site

20. Microphysical seeding effect examples:
Time after
seeding
An aircraft case study
10 min
19 min
22 min
30 min
39 min

21. Seeding Effects in Precipitation
 Last link in the “chain” and hardest to verify
 Physical evidence from ground-based seeding experiments on the
Grand Mesa (CO) and Wasatch Plateau (UT)
 Statistical evidence from randomized experiments in Bridger
Range and northern Sierra Nevada – supporting physical evidence
 One randomized propane experiment in UT with significant
results – 1-hour seeded periods had ~20% more precipitation than
unseeded periods
 Methods of verification
 Ground-based particle imaging probes
 Precipitation gauges
 Radar occasionally useful
 Statistical assessments of target area precipitation

22. Radar detection of a
seeding plume
from Wasatch Plateau
case that documented
aerosol and ice crystal
plumes

23. Precipitation from
gauges inside and
outside seeding
plume
Vertical dashed lines
enclose the time
period of the
seeding effect at
each gauge site

24. Some of the Best Evidence
of Precipitation Increases
 Physical evidence from case studies
 Wasatch Plateau (UT) experiments (1990s, 2004)
 Ground releases of silver iodide and liquid propane
 Precipitation rate increases of a few hundredths to > 1
mm/hour
 Grand Mesa (CO) 1990s
 Ground and aircraft releases of silver iodide
 Precipitation rates in seeded periods >> than unseeded periods
 Statistical results with supporting physical evidence
 Bridger Range randomized experiment (1970s)
 Double ratio analysis showed 15% increase in the target
 Increases in target were much greater in cold storms
 Increases of 15% found within a few km of the source
 Lake Almanor randomized experiment (1960s)
 Statistically significant increase found with cold storm category
 Supported by later trace chemical evaluations

25. Current Research Projects
• Australian Snowy Mountain Project
– Funded by Australian government and
conducted by Snowy Hydro (power company)
– 5-year study with randomized seeding of a
single target
– Published results showed a statistically
significant 14% increase in target precipitation
for “seeded” events
– Statistical results strongly supported by trace
chemical assessment
• U. of Wyoming airborne radar study
– Radar signal increase noted during seeding
periods
– Radar signal increase corresponds to a
significant precipitation rate increase

26. Hydrologic Modeling
to Assess the Impact
of Cloud Seeding
HRU Setup for Walker
River
HRUs outlined in red
were given a 10% seeding
impact

27. Seeded Year Month Precip ET Storage P-Runoff
(inches) (inches) (inches) (inches)
Hydrologic 2003
2003
10
11
1.029
2.451
0.447
0.459
1.421
3.128
0.470
0.285
Modeling: 2003
2004
12
1
9.512
1.626
0.342
0.396
11.397
12.047
0.900
0.580
Simulation of 2004 2 11.132 0.386 22.432 0.361
2004 3 4.048 1.009 23.910 1.561
Seeding 2004 4 1.732 2.427 18.362 4.853
2004 5 0.000 2.765 11.537 4.060
Effects* *************************************************************************
Total 31.530 8.231 11.537 13.070
Not seeded Year Month Precip ET Storage P-Runoff
*Estimated at (inches) (inches) (inches) (inches)
10% for 2003 10 0.932 0.397 1.262 0.402
selected HRU’s 2003 11 2.274 0.463 2.829 0.244
2003 12 8.64 0.348 10.353 0.768
2004 1 1.471 0.401 10.896 0.526
2004 2 10.124 0.388 20.293 0.339
2004 3 3.653 1.02 21.381 1.545
2004 4 1.558 2.386 16.073 4.481
2004 5 0 2.672 9.835 3.566
*************************************************************************
Total 28.652 8.075 9.835 11.871
Difference 2.878 0.156 1.702 1.199
% Difference 10.0 1.9 17.3 10.1

28. Use of trace chemistry in evaluating cloud seeding
projects
 The element silver in silver iodide has a very low background
concentration in natural snowfall (~4 PPT).
 Analyzing target area precipitation for evidence of Ag above
background is one means of evaluating targeting
effectiveness.
 In a randomized seeding project using a target and control
design trace chemistry can be used to verify that the control
area is unaffected by seeding.
 Can be used to address environmental concerns regarding Ag
in snow, soil, water supplies, etc.
 Non-ice nucleating particles used in combination with AgI can
be used to differentiate between nucleation and scavenging
processes in target area snowfall.

29. Trace chemical response to seeding during an Australian experiment
Ag is part of the ice nucleant (AgI)
In is an non-ice nucleating tracer
A ratio of Ag to In that
exceeds one indicates ice
nucleation by AgI is
contributing to the snowfall

30. Summary Points on Wintertime Cloud Seeding
Research
 All the links in the chain of the conceptual model have been
verified in physical case studies
 Ice crystal and precipitation enhancement have been
verified through physical observations
 Precipitation enhancement has been documented by
statistical methods in several projects where results were
also validated by physical measurements
 New modeling (atmospheric and hydrologic) and radar
methods being used to evaluate cloud seeding projects
 Trace chemical techniques used to validate targeting and
the process of ice nucleation by seeding