Bill Overview
Title: National Mesonet Authorization Act
Description: This bill provides statutory authority for the National Mesonet Program of the National Weather Service (NWS). The program shall obtain observations from observing platforms in all geographic environments to improve understanding of and forecast capabilities for atmospheric events, with a prioritization on leveraging available commercial, academic, and other nonfederal weather data to enhance coordination across the private, public, and academic sectors of the U.S. weather enterprise. The program must carry out specified activities, including improving environmental observations used by the National Oceanic and Atmospheric Administration (NOAA) and the NWS to support baseline forecasts and warnings that protect the nation's citizens, businesses, military, and government agencies and enable such individuals and entities to operate in safe, efficient, and orderly manners. NOAA shall ensure the program has an active advisory committee of subject matter experts to identify, implement, procure, and track data needed to supplement the program, and recommend improvements, expansions, and acquisitions of available data. The advisory committee shall establish partnerships with one or more institutions of higher education to identify, evaluate, and recommend potential partnerships, regional or subregional consortia, and collaborative methods that would expand the number of participants and volume of data in the program.
Sponsors: Rep. Bice, Stephanie I. [R-OK-5]
Target Audience
Population: global population benefiting from improved weather forecasts
Estimated Size: 331000000
- The National Mesonet Program is designed to enhance weather observation and forecasting capabilities, which are essential for various sectors including government, military, businesses, and individuals.
- Increased and improved weather data collection and analysis can provide benefits such as better emergency preparedness, efficient resource allocation, and economic savings.
- The program prioritizes coordination across private, public, and academic sectors, implying broad systemic impacts even beyond individual benefits.
- Accurate weather forecasts and warnings impact everyone, as they influence safety decisions, daily planning, and disaster response preparedness globally.
Reasoning
- The National Mesonet Program is designed to improve weather data collection through various platforms, which enhances NOAA's forecasting capabilities. This is crucial for mitigating weather-related risks, especially in sectors like agriculture, transportation, and disaster management.
- Key beneficiaries include farmers who rely on weather data for crop planning, transport companies that need accurate data for logistics, and local governments preparing for natural disasters.
- The policy also affects individuals indirectly by potentially improving daily life aspects such as commute safety and energy usage planning.
- Given budget constraints, the policy primarily aims at enhancing existing systems and using partnerships effectively to expand its impact without exceeding costs.
- While broadly beneficial, the policy's direct impact can vary across individuals depending on their reliance or vulnerability to weather conditions.
Simulated Interviews
farmer (Oklahoma)
Age: 45 | Gender: female
Wellbeing Before Policy: 6
Duration of Impact: 15.0 years
Commonness: 8/20
Statement of Opinion:
- More accurate weather forecasts will help me plan the planting and harvesting better, hopefully reducing loss from unexpected weather changes.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 7 | 6 |
| Year 2 | 7 | 6 |
| Year 3 | 7 | 6 |
| Year 5 | 8 | 6 |
| Year 10 | 8 | 5 |
| Year 20 | 9 | 5 |
city planner (New York)
Age: 60 | Gender: male
Wellbeing Before Policy: 7
Duration of Impact: 20.0 years
Commonness: 6/20
Statement of Opinion:
- Improved weather data will greatly assist in making disaster preparations more reliable, reducing risks to the city during storms.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 8 | 7 |
| Year 2 | 8 | 7 |
| Year 3 | 9 | 7 |
| Year 5 | 9 | 6 |
| Year 10 | 9 | 5 |
| Year 20 | 10 | 5 |
software developer (California)
Age: 29 | Gender: female
Wellbeing Before Policy: 8
Duration of Impact: 5.0 years
Commonness: 12/20
Statement of Opinion:
- I don't directly notice the weather data changes, but if it helps in making travel safer, I'm all for it.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 8 | 8 |
| Year 2 | 8 | 8 |
| Year 3 | 8 | 8 |
| Year 5 | 8 | 8 |
| Year 10 | 8 | 8 |
| Year 20 | 8 | 8 |
transport dispatcher (Florida)
Age: 52 | Gender: male
Wellbeing Before Policy: 5
Duration of Impact: 10.0 years
Commonness: 7/20
Statement of Opinion:
- Accurate weather forecasts are crucial for planning trucking routes and avoiding delays caused by hazardous weather. This policy could potentially save on costs.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 6 | 5 |
| Year 2 | 6 | 5 |
| Year 3 | 7 | 5 |
| Year 5 | 7 | 4 |
| Year 10 | 7 | 4 |
| Year 20 | 7 | 4 |
research scientist (Illinois)
Age: 33 | Gender: other
Wellbeing Before Policy: 7
Duration of Impact: 15.0 years
Commonness: 6/20
Statement of Opinion:
- The program could significantly contribute to research data accuracy and granularity, aiding more effective studies and findings.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 8 | 7 |
| Year 2 | 9 | 7 |
| Year 3 | 9 | 7 |
| Year 5 | 9 | 7 |
| Year 10 | 9 | 7 |
| Year 20 | 9 | 7 |
retired (Texas)
Age: 64 | Gender: female
Wellbeing Before Policy: 6
Duration of Impact: 20.0 years
Commonness: 9/20
Statement of Opinion:
- Better weather forecasts would help us prepare for hurricanes more effectively, hopefully reducing stress and damage.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 6 | 6 |
| Year 2 | 7 | 6 |
| Year 3 | 7 | 6 |
| Year 5 | 8 | 6 |
| Year 10 | 8 | 5 |
| Year 20 | 9 | 5 |
graduate student (Ohio)
Age: 25 | Gender: male
Wellbeing Before Policy: 7
Duration of Impact: 10.0 years
Commonness: 10/20
Statement of Opinion:
- This policy gives more access to data for my studies and research, potentially opening doors to more opportunities and collaborations.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 8 | 7 |
| Year 2 | 8 | 7 |
| Year 3 | 8 | 7 |
| Year 5 | 9 | 7 |
| Year 10 | 9 | 7 |
| Year 20 | 9 | 7 |
school teacher (Minnesota)
Age: 37 | Gender: female
Wellbeing Before Policy: 6
Duration of Impact: 8.0 years
Commonness: 11/20
Statement of Opinion:
- I can incorporate more accurate and up-to-date weather data into my curricula, making lessons more engaging and relevant for students.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 6 | 6 |
| Year 2 | 6 | 6 |
| Year 3 | 7 | 6 |
| Year 5 | 7 | 6 |
| Year 10 | 7 | 6 |
| Year 20 | 7 | 6 |
emergency first responder (Washington)
Age: 42 | Gender: male
Wellbeing Before Policy: 5
Duration of Impact: 20.0 years
Commonness: 7/20
Statement of Opinion:
- Improving forecast reliability means better preparation and response, directly impacting the effectiveness of my job in saving lives.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 6 | 5 |
| Year 2 | 7 | 5 |
| Year 3 | 8 | 5 |
| Year 5 | 8 | 5 |
| Year 10 | 8 | 5 |
| Year 20 | 8 | 5 |
solar energy consultant (Nevada)
Age: 50 | Gender: female
Wellbeing Before Policy: 7
Duration of Impact: 15.0 years
Commonness: 5/20
Statement of Opinion:
- More precise weather data can help optimize solar energy systems for clients, increasing their output efficiency.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 7 | 7 |
| Year 2 | 8 | 7 |
| Year 3 | 8 | 7 |
| Year 5 | 8 | 7 |
| Year 10 | 9 | 7 |
| Year 20 | 9 | 7 |
Cost Estimates
Year 1: $85000000 (Low: $75000000, High: $95000000)
Year 2: $87000000 (Low: $76000000, High: $96000000)
Year 3: $89000000 (Low: $77000000, High: $97000000)
Year 5: $92000000 (Low: $79000000, High: $99000000)
Year 10: $98000000 (Low: $82000000, High: $102000000)
Year 100: $150000000 (Low: $100000000, High: $200000000)
Key Considerations
- The program relies on the successful integration of commercial and academic data.
- The cost estimates need to account for potential technological innovations that might alter operational expenses.
- Long-term commitments may be necessary to ensure technological and infrastructural effectiveness.