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Wyoming Weather Modification Pilot Program (WWMPP)

Executive Summary

The Wyoming Weather Modification Pilot Program (WWMPP) was a comprehensive study conducted from 2005 to 2014 to assess the feasibility of increasing Wyoming's water supplies through winter orographic cloud seeding. This executive summary provides an in-depth overview of the project's design, implementation, and key findings.

1. Introduction and Background

1.1 Project Overview

  • Duration: 2005-2014
  • Funding: Wyoming Water Development Commission (WWDC)
  • Primary Goal: Determine the viability of cloud seeding for augmenting water supplies in Wyoming

1.2 Target Areas

The WWMPP established cloud-seeding research programs in three Wyoming mountain ranges:

  1. Medicine Bow Range
  2. Sierra Madre Range
  3. Wind River Range

1.3 Orographic Cloud Seeding Concept

Orographic cloud seeding is designed to enhance precipitation in winter storms with inefficient precipitation processes due to a lack of natural ice nuclei.

Key points:

  • Uses ground-based generators to produce silver iodide plumes

  • Plumes are transported by ambient winds into orographic clouds

  • Aims to increase precipitation by creating additional ice crystals

1.4 Project Structure

  • Operations: Weather Modification, Inc. (WMI)
  • Evaluation: National Center for Atmospheric Research (NCAR)
  • Additional Contributors:
  • University of Wyoming
  • Desert Research Institute
  • Heritage Environmental Consultants
  • University of Alabama
  • University of Nevada Las Vegas
  • University of Tennessee

1.5 Oversight and Collaboration

  • Technical Advisory Team (TAT) established
  • Local stakeholders engaged throughout the project

2. Design of the WWMPP

2.1 Primary Evaluation Method

The main evaluation tool was a Randomized Statistical Experiment (RSE) focusing on the Medicine Bow and Sierra Madre Ranges.

2.2 Additional Evaluation Components

  1. Permits for siting seeding generators and instruments
  2. Numerical modeling studies
  3. Physical measurements of silver iodide
  4. Verification of silver iodide targeting
  5. Climatological context of seeding opportunities
  6. Hydrological modeling of cloud-seeding impacts
  7. Environmental monitoring of silver
  8. Studies of extra-area effects

2.3 RSE Design

  • Duration: Six winter seasons (2008-2014)
  • Design Process: Iterative, involving peer reviews and facility adjustments
  • Experiment Type: Crossover design
  • One range randomly selected for seeding
  • Other range served as "control"

2.4 Seeding Criteria

  1. Temperature < -8°C (+17°F) near mountain top
  2. Favorable wind direction for silver iodide transport
  3. Presence of supercooled liquid water

2.5 Facilities and Equipment

Equipment Purpose
Atmospheric sounding unit Measure vertical profile of atmosphere
Microwave radiometers Detect supercooled liquid water
Ground-based seeding generators Produce silver iodide for seeding
High-resolution snow gauges Measure precipitation in target and control areas
High-resolution weather forecast model Predict atmospheric conditions

2.6 Experimental Design Details

  • Case Duration: 4 hours
  • Response Variable: 4-hour precipitation accumulation
  • Test Statistic: Root regression ratio (RRR)
  • Estimated Cases Needed: 65-70 per year for 5-6 years

2.7 Permitting and Approvals

  • Federal: U.S. Forest Service (USFS) special use permit
  • State: Wyoming Office of State Lands and Investments
  • Private: Landowner permissions
  • Additional: Wyoming State Engineer's Office, NOAA

3. Physical, Statistical, and Modeling Analyses

3.1 Physical Studies

3.1.1 Trace Chemical Analysis

  • Purpose: Determine silver incorporation from cloud seeding
  • Finding: Variable results, but generally lower than Australian studies

3.1.2 Ground-based Measurements

  • Instrument: Acoustic ice nucleus counter (AINC)
  • Duration: First three project years (2008-2011)
  • Key Finding: Confirmed silver iodide reaching intended target

3.1.3 Aircraft Studies

  • Conducted by: University of Wyoming
  • Initial Results: Up to 25% increase in precipitation for 7 lightly precipitating storms
  • Follow-up Studies: Less pronounced effects, highlighting need for larger sample sizes

3.2 Modeling Studies

  • Model Used: Weather Research and Forecasting (WRF) with NCAR cloud-seeding module
  • Seasons Simulated: 2009-2010, 2011-2012, 2013-2014
  • Key Results:
  • Simulated seeding effects between 10-15% in both mountain ranges
  • Model performance verified using radiometer, snow gauge, and sounding data

3.3 Statistical Studies

3.3.1 Primary Analysis

  • Total RSE Cases: 154
  • Cases Included in Analysis: 118
  • Primary Result:
  • RRR = 1.03
  • p-value = 0.28
  • Interpretation: 3% increase in precipitation, 28% chance of occurring by chance

3.3.2 Secondary Analyses

  1. Unintended Downwind Effects:
  2. 18 cases with downwind impacts identified

  3. Removing these cases increased RRR to 1.09

  4. Silver Iodide Reaching Target:

  5. 21 cases with confirmed silver iodide at target

  6. Removing these cases increased RRR from 1.03 to 1.04

  7. Generator Hours Stratification:

  8. RRR increased to 1.17 for cases with ≥27 generator hours
  9. Suggests sufficient seeding agent necessary for detectable effect

Note: These secondary analyses, while informative, cannot claim statistical significance due to post-hoc nature.

4. Climatology of Seeding Opportunities

4.1 Methodology

  • Model: 8-year high-resolution regional climate model (2000-2008)
  • Forced by: Re-analysis meteorological data

4.2 Key Findings

  1. Atmospheric conditions met seeding criteria <1/3 of winter time
  2. Precipitation occurred ~50% of the time when conditions met criteria
  3. ~30% of wintertime snowpack would have been seeded under RSE conditions

5. Streamflow Impacts

5.1 Hydrological Modeling

  • Model: Variable Infiltration Capacity (VIC)
  • Study Area: North Brush Creek watershed (Upper North Platte River Basin)
  • Baseline Performance: Within 1% of observed snowmelt-driven streamflow (2001-2008)

5.2 Modeled Impacts

For 5-15% seeding impact on winter precipitation:

  • Streamflow Increase: 95-288 AF/sq-mi over 8 years
  • Seedable Area: ~390 sq-mi (elevation > 9,000 ft)
  • Potential Impact Area: 30-80% of seedable area

5.3 Example Scenario

For 10% seeding effect impacting 60% of the basin:

  • Additional Water Generated: 7,100 AF/year on average
  • Percentage Increase: 1.8% in Wyoming area of North Platte River Basin

6. Cost Analysis

6.1 Operational Cost Estimates

Option Annual Cost Range
Sponsor-owned equipment $375,500 - $526,400
Contractor/leased operation $420,600 - $571,500
Evaluation component Additional $222,700

6.2 Cost per Acre-Foot

For 10% efficiency and 60% basin coverage:

  • Low-cost estimate: ~$53/AF
  • Range: $35-107/AF (5-15% efficiency)

Comparison: Wyoming markets North Platte water at $30-75/AF for temporary uses

7. Environmental Impacts

7.1 Trace Chemistry Analyses

  • Samples: Water and soil from all three ranges
  • Frequency: Following each operational season

7.2 Key Findings

  • Water: Silver concentrations in parts per trillion
  • Soil: Silver concentrations in parts per billion
  • Interpretation: Negligible environmental impact, far below hazardous levels

8. Extra-Area Effects

  • Method: WRF model simulations
  • Key Finding: Net effect outside intended targets small to zero (<0.5%)
  • Caveat: Based on model results, not validated by observations beyond target areas

9. Conclusions

  1. Ample supercooled liquid water existed at conducive temperatures
  2. Cloud seeding appears viable for augmenting water supplies in Medicine Bow and Sierra Madre Ranges
  3. Statistical analysis suggests 3-17% increase for well-seeded storms
  4. ~30% of winter precipitation fell from storms meeting seeding criteria
  5. Modeling studies showed 10-15% positive seeding effects
  6. Potential streamflow increases of 0.4-3.7% in Wyoming's North Platte River Basin
  7. Estimated water cost: $27-$427 per acre-foot
  8. Negligible environmental impacts
  9. Minimal extra-area effects

10. Recommendations

  1. Barrier Identification: Conduct long-term climatological studies
  2. Program Design: Optimize seeding methods and generator placement
  3. Operational Criteria: Utilize real-time data and forecasting
  4. Evaluation: Combine modeling and high-resolution measurements
  5. Program Management: Engage stakeholders and pursue collaborative opportunities