Policy Impact Analysis - 117/HR/8400

Bill Overview

Title: WING Act of 2022

Description: This bill directs the National Weather Service to establish a research, development, test, and evaluation program to ensure that weather radar detection and prediction capabilities continue to perform with physical obstructions in their line of sight.

Sponsors: Rep. Feenstra, Randy [R-IA-4]

Target Audience

Population: Individuals worldwide affected by weather forecasting

Estimated Size: 335000000

Reasoning

Simulated Interviews

Insurance Adjuster (New York, NY)

Age: 45 | Gender: female

Wellbeing Before Policy: 7

Duration of Impact: 10.0 years

Commonness: 15/20

Statement of Opinion:

  • Better weather predictions will make my job easier and commute more reliable.
  • I expect fewer disputes over weather-related claims.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 7 7
Year 2 7 7
Year 3 8 7
Year 5 8 7
Year 10 8 7
Year 20 8 7

Farmer (Miami, FL)

Age: 30 | Gender: male

Wellbeing Before Policy: 6

Duration of Impact: 10.0 years

Commonness: 5/20

Statement of Opinion:

  • This policy could mean earlier warnings and better prep to save my crops.
  • Maybe less anxiety around hurricane season.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 7 6
Year 2 8 6
Year 3 8 6
Year 5 9 6
Year 10 9 6
Year 20 9 6

Truck Driver (Kansas City, MO)

Age: 52 | Gender: male

Wellbeing Before Policy: 6

Duration of Impact: 10.0 years

Commonness: 10/20

Statement of Opinion:

  • Improved weather tracking can make my job safer and my routes more efficient.
  • Not having to worry as much about sudden weather changes is a relief.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 7 6
Year 2 8 5
Year 3 9 5
Year 5 9 5
Year 10 9 5
Year 20 9 5

Retired (San Francisco, CA)

Age: 62 | Gender: female

Wellbeing Before Policy: 8

Duration of Impact: 5.0 years

Commonness: 12/20

Statement of Opinion:

  • I'm not sure I'd notice much difference, but if it helps my neighborhood stay safe during storms, that's good.
  • I value any improvements for emergency preparedness.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 8 8
Year 2 8 8
Year 3 8 7
Year 5 8 7
Year 10 8 7
Year 20 7 6

Meteorologist (Houston, TX)

Age: 25 | Gender: female

Wellbeing Before Policy: 9

Duration of Impact: 20.0 years

Commonness: 8/20

Statement of Opinion:

  • This policy is exciting as it directly impacts my work.
  • We could deliver more precise forecasts to our audience.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 9 9
Year 2 9 9
Year 3 10 9
Year 5 10 9
Year 10 10 9
Year 20 10 9

Software Engineer (Los Angeles, CA)

Age: 36 | Gender: male

Wellbeing Before Policy: 7

Duration of Impact: 10.0 years

Commonness: 18/20

Statement of Opinion:

  • I doubt I'll see any major changes, but clearer forecasts would be nice.
  • It might help with planning trips better.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 7 7
Year 2 7 7
Year 3 7 7
Year 5 7 7
Year 10 7 7
Year 20 6 5

Emergency Services Coordinator (Chicago, IL)

Age: 29 | Gender: other

Wellbeing Before Policy: 6

Duration of Impact: 15.0 years

Commonness: 8/20

Statement of Opinion:

  • Better weather tech means we can prepare better and potentially save lives.
  • This would make a real difference in emergency response planning.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 7 6
Year 2 8 6
Year 3 8 6
Year 5 9 6
Year 10 9 6
Year 20 8 6

Construction Manager (Seattle, WA)

Age: 41 | Gender: male

Wellbeing Before Policy: 5

Duration of Impact: 10.0 years

Commonness: 9/20

Statement of Opinion:

  • Anything that helps us plan construction projects around rain patterns is a big help.
  • I'm hopeful this means fewer delays and surprises.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 6 5
Year 2 7 5
Year 3 7 5
Year 5 8 5
Year 10 8 5
Year 20 8 5

School Principal (New Orleans, LA)

Age: 55 | Gender: female

Wellbeing Before Policy: 5

Duration of Impact: 5.0 years

Commonness: 11/20

Statement of Opinion:

  • Improved predictions would help us plan and reduce unnecessary closures.
  • Safety is top priority, but better data helps in making close calls.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 6 5
Year 2 7 5
Year 3 7 5
Year 5 7 5
Year 10 7 5
Year 20 7 5

Small Business Owner (Denver, CO)

Age: 47 | Gender: female

Wellbeing Before Policy: 8

Duration of Impact: 20.0 years

Commonness: 6/20

Statement of Opinion:

  • We rely on accurate forecasts for safety and profits.
  • Better radar helps us plan our season and manage snow more effectively.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 9 8
Year 2 9 8
Year 3 9 8
Year 5 10 8
Year 10 10 8
Year 20 10 8

Cost Estimates

Year 1: $150000000 (Low: $120000000, High: $180000000)

Year 2: $160000000 (Low: $130000000, High: $190000000)

Year 3: $170000000 (Low: $140000000, High: $200000000)

Year 5: $180000000 (Low: $150000000, High: $210000000)

Year 10: $0 (Low: $0, High: $0)

Year 100: $0 (Low: $0, High: $0)

Key Considerations