SNOWIE (Seeded and Natural Orographic Wintertime Clouds: The Idaho Experiment)
Introduction
SNOWIE marked a turning point in cloud seeding technology. Conducted from 2017 to 2021 in Idaho's Payette Mountains, this experiment introduced groundbreaking innovations that addressed longstanding challenges in the field.
Background
- Climate change and population growth have increased water demand in arid regions
- Cloud seeding has been evaluated as a potential technology to increase water supply
- Previous studies relied on statistical comparisons, often with inconclusive results
For decades, cloud seeding suffered from "the attribution problem." Despite 70 years of practice, the industry struggled to definitively prove its effectiveness. This lack of clear evidence led to skepticism and diminished commercial interest.
Innovations
1. High-Resolution Mobile Radar
SNOWIE developed portable, high-resolution radar systems that could be deployed directly in seeding areas, offering unprecedented detail in cloud analysis. These radars allowed researchers to:
- Measure precise cloud conditions before and after seeding
- Detect clear signatures of water-to-ice phase changes
- Attribute rainfall to seeding efforts with remarkable accuracy
2. Perpendicular Flight Path
SNOWIE aircraft flew perpendicular to the crosswind direction, creating a distinctive "zebra pattern" of precipitation. This uniform spacing made it far easier to distinguish seeded rainfall from natural precipitation.
3. Novel Approach to Isolate Seeding-Induced Precipitation
- Identified areas with light or no natural precipitation (<1 mm/h)
- Used radar observations to track spatial and temporal evolution
- Quantified snowfall accumulation using radar data and snow gauge measurements
- Developed relationships between radar reflectivity (Ze) and liquid equivalent snowfall rate (S)
Methods
Data Collection
- Precipitation Gauges: Network deployed in the study area
- Radars: Two ground-based Doppler on Wheels (DOW) radars
- Airborne Observations: Radar and seeding operations
All data are publicly available through the SNOWIE data archive website and the SNOWIE radar data archive.
Results and Discussion
SNOWIE's advancements enabled researchers to measure seeding-induced rainfall with extraordinary precision - within an accuracy of 100,000 gallons. In some cases, a single day's operation produced 100-121 acre-feet of water, equivalent to hundreds of millions of gallons.
January 19, 2017 Event
Seeding Operations
- Two seeding lines passed over multiple gauge sites
- Airborne cloud seeding began at 1619 UTC
Gauge Measurements
- Five Corners: Increase of ~0.1 mm (1.2 mm/h) over 5 minutes
- Banner: Increase of ~0.1 mm over 14 minutes
Total Accumulation
- Best-match estimate: 123,220 m³ (100 acre-feet) over 67 minutes
- Area covered: 2,327 km²
Uncertainty Analysis
| Percentile | Accumulation (m³) |
|---|---|
| 25th | 95,776 |
| 75th | 144,994 |
| 5th | 78,582 |
| 95th | 194,261 |
January 20, 2017 Event
Seeding Operations
- Eight seeding lines observed
- Two lines passed over the Silver Creek gauge site
Gauge Measurements
- Silver Creek: Increase of 0.28 mm over 38 minutes
Total Accumulation
- Best-match estimate: 241,260 m³ (196 acre-feet) over 160 minutes
- Area covered: 1,838 km²
Uncertainty Analysis
| Percentile | Accumulation (m³) |
|---|---|
| 25th | 196,319 |
| 75th | 312,521 |
| 5th | 179,986 |
| 95th | 437,125 |
January 31, 2017 Event
Seeding Operations
- Two seeding lines with enhanced radar reflectivity detected
- Strong vertical wind shear observed
Gauge Measurements
- Silver Creek: Increase of 0.25 mm over 25 minutes
Total Accumulation
- Best-match estimate: 339,540 m³ (275 acre-feet) over 25 minutes
- Area covered: 2,410 km²
Uncertainty Analysis
| Percentile | Accumulation (m³) |
|---|---|
| 25th | 222,051 |
| 75th | 335,863 |
| 5th | 187,004 |
| 95th | 480,420 |
Key Findings and Significance
Quantitative Evidence
- Snow Accumulations:
- Range: 0.05 to 0.28 mm at gauge sites
- Precipitation Rates:
- Range: 0.4 to 1.2 mm/h
- Total Liquid Equivalent Snowfall:
- January 19: 123,220 m³ from 20 minutes of seeding
- January 20: 241,260 m³ from 86 minutes of seeding
- January 31: 339,540 m³ from 24 minutes of seeding
Factors Influencing Seeding Efficacy
- Wind conditions
- Terrain
- Atmospheric variables
Uncertainty in Estimates
- Range: 20% to 47% due to variability in Ze-S relationships
Significance
- Fundamental Step: Provides quantitative evidence of snowfall generated by cloud seeding
- Methodology: Introduces a physically-based approach to isolate seeding-induced precipitation
- Future Applications: Sets the stage for validating numerical models and improving interpretation of precipitation observations
SNOWIE's success was a catalyst. By solving the attribution problem, SNOWIE has potentially opened the door for a renaissance in weather modification.
Historical Context
Prior to SNOWIE, cloud seeding relied on less precise methods: - Planes dispersing agents with limited control - Ground-based "bonfires" spewing chemicals skyward - Rudimentary rain gauges for measurement
These methods often resulted in immeasurable or statistically insignificant increases in precipitation, making it difficult to justify the cost and effort involved.
NOTE
Many of the acre-feet estimations used here are not from the SNOWIE paper directly, but from following research that examined the same events. Friedrich et al., 2020, “Quantifying snowfall from orographic cloud seeding,” PNAS: the first study that actually calculated domain-wide snowfall from SNOWIE seeding.
Future Work
Research Directions
- Quantifying ice and snow production in seeded clouds
- Studying environmental conditions and cloud dynamic/microphysical processes
- Validating numerical models that simulate microphysical impacts of cloud seeding
- Improving interpretation of precipitation observations during cloud seeding operations
- Quantifying AgI seeding effects over target areas at different time scales using ensemble approaches