Bill Overview
Title: PRECIP Act
Description: This bill directs the National Oceanic and Atmospheric Administration (NOAA) to take actions regarding precipitation estimation. NOAA shall, no less than every 10 years, update probable maximum precipitation estimates for the United States. NOAA must include specified information in the updates and must make publicly available certain probable maximum precipitation studies developed by NOAA. NOAA must seek to enter an agreement with the National Academies of Science, Engineering, and Medicine to conduct a study on the state of practice and research needs for precipitation estimation, including probable maximum precipitation estimation. NOAA, in consideration of the study's recommendations, shall consult with relevant partners on the development of a plan to update probable maximum precipitation estimates. NOAA shall develop a national guidance document regarding probable maximum precipitation estimates that (1) provides best practices for federal and state regulatory agencies, private meteorological consultants, and other users that perform probable maximum precipitation studies; (2) considers the recommendations provided in the National Academies study; (3) facilitates review of probable maximum precipitation studies by regulatory agencies; and (4) provides confidence in regional and site-specific probable maximum precipitation estimates.
Sponsors: Sen. Booker, Cory A. [D-NJ]
Target Audience
Population: People globally relying on accurate precipitation data for safety, infrastructure planning, and climate adaptation
Estimated Size: 330000000
- The PRECIP Act primarily affects agencies and organizations involved in meteorology, specifically in the domain of precipitation estimation.
- NOAA has a central role in updating precipitation estimates, which influence a wide range of sectors including agriculture, construction, disaster preparedness, and environmental management.
- The updates to precipitation data are critical for understanding and mitigating the impacts of climate change, which affects all individuals globally.
- Accurate precipitation data is crucial for infrastructure planning and risk assessment, impacting urban planners, civil engineers, and insurance industries.
- By improving precipitation estimates, the bill indirectly impacts individuals residing in regions prone to flooding, drought, and other weather-related disruptions.
- As the guidance is intended for entities using precipitation data, such as state and federal agencies, this may influence policy making and funding allocations, thus having broader socio-economic impacts.
Reasoning
- The PRECIP Act primarily impacts sectors dependent on accurate precipitation data, like agriculture and infrastructure. However, individual awareness of such a policy might be limited.
- Key decision-makers and professionals such as city planners, engineers, and government officials will be directly influenced by improved data quality, potentially changing workflows and policy planning.
- There could be long-term indirect benefits for people living in flood-prone areas as improved data aids in better regional planning and emergency preparedness.
- Some professionals may see immediate improvements, others may not see direct impacts until data integration in future projects.
- The overall wellbeing impact on individuals is varied, with more noticeable effects in regions more frequently impacted by extreme weather.
- The policy does not directly allocate funds to particular communities or projects but enhances data quality, influencing decisions that affect millions.
Simulated Interviews
Climate Data Analyst (Miami, Florida)
Age: 34 | Gender: female
Wellbeing Before Policy: 7
Duration of Impact: 15.0 years
Commonness: 10/20
Statement of Opinion:
- This policy will significantly enhance our state's ability to prepare for flood risks.
- Accurate and regularly updated data are crucial for making informed decisions.
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 | 8 | 7 |
| Year 10 | 9 | 7 |
| Year 20 | 9 | 6 |
Civil Engineering Student (Houston, Texas)
Age: 22 | Gender: male
Wellbeing Before Policy: 6
Duration of Impact: 7.0 years
Commonness: 15/20
Statement of Opinion:
- The updated rainfall data will be vital for future-proof infrastructure design.
- It’s encouraging to see government update such a critical aspect of data.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 6 | 6 |
| Year 2 | 7 | 6 |
| Year 3 | 8 | 6 |
| Year 5 | 8 | 6 |
| Year 10 | 9 | 6 |
| Year 20 | 9 | 6 |
Insurance Risk Manager (Los Angeles, California)
Age: 45 | Gender: female
Wellbeing Before Policy: 5
Duration of Impact: 20.0 years
Commonness: 12/20
Statement of Opinion:
- More accurate precipitation data will allow for better risk assessments and pricing strategies.
- We heavily rely on NOAA's data for underwriting.
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 |
Farmer (Cedar Rapids, Iowa)
Age: 58 | Gender: male
Wellbeing Before Policy: 6
Duration of Impact: 10.0 years
Commonness: 8/20
Statement of Opinion:
- Increased accuracy in rainfall predictions could help my planting schedule and yield unpredictability.
- Policy could indirectly improve economic stability for farmers.
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 | 7 | 6 |
| Year 10 | 8 | 6 |
| Year 20 | 8 | 6 |
Urban Planner (New York City, New York)
Age: 29 | Gender: female
Wellbeing Before Policy: 7
Duration of Impact: 12.0 years
Commonness: 10/20
Statement of Opinion:
- Improvements in precipitation data are vital for sustainable urban development.
- The data could deeply influence our future city planning strategies.
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 |
Construction Project Manager (Phoenix, Arizona)
Age: 40 | Gender: male
Wellbeing Before Policy: 6
Duration of Impact: 10.0 years
Commonness: 11/20
Statement of Opinion:
- Accurate weather data directly affects our project timelines and cost management.
- This policy could improve efficiency and reduce unforeseen weather delays.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 7 | 6 |
| Year 2 | 7 | 6 |
| Year 3 | 8 | 6 |
| Year 5 | 8 | 6 |
| Year 10 | 9 | 6 |
| Year 20 | 9 | 6 |
Environmental Scientist (Seattle, Washington)
Age: 51 | Gender: other
Wellbeing Before Policy: 8
Duration of Impact: 20.0 years
Commonness: 7/20
Statement of Opinion:
- Policies enhancing data accuracy are crucial for climate adaptation strategies.
- Seeing priority towards improved environmental assessments is promising.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 8 | 8 |
| Year 2 | 9 | 8 |
| Year 3 | 9 | 8 |
| Year 5 | 9 | 8 |
| Year 10 | 9 | 8 |
| Year 20 | 9 | 8 |
State Emergency Planner (Boston, Massachusetts)
Age: 37 | Gender: female
Wellbeing Before Policy: 7
Duration of Impact: 12.0 years
Commonness: 9/20
Statement of Opinion:
- Up-to-date precipitation data is vital for emergency preparedness planning.
- This policy helps in making our community more resilient to weather disasters.
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 | 7 |
| Year 10 | 9 | 7 |
| Year 20 | 9 | 7 |
Retired (Denver, Colorado)
Age: 60 | Gender: male
Wellbeing Before Policy: 5
Duration of Impact: 5.0 years
Commonness: 15/20
Statement of Opinion:
- While I am retired, knowing more accurate data is available gives me peace of mind about local weather risks.
- I support policies that prioritize accuracy and safety.
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 | 5 |
| Year 10 | 7 | 5 |
| Year 20 | 7 | 5 |
Software Developer (Birmingham, Alabama)
Age: 28 | Gender: male
Wellbeing Before Policy: 6
Duration of Impact: 10.0 years
Commonness: 14/20
Statement of Opinion:
- This act could potentially open up new technical requirements and project opportunities.
- Better data means more accurate and reliable software services.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 7 | 6 |
| Year 2 | 7 | 6 |
| Year 3 | 8 | 6 |
| Year 5 | 8 | 6 |
| Year 10 | 8 | 6 |
| Year 20 | 8 | 6 |
Cost Estimates
Year 1: $35000000 (Low: $30000000, High: $40000000)
Year 2: $35000000 (Low: $30000000, High: $40000000)
Year 3: $35000000 (Low: $30000000, High: $40000000)
Year 5: $35000000 (Low: $30000000, High: $40000000)
Year 10: $35000000 (Low: $30000000, High: $40000000)
Year 100: $0 (Low: $0, High: $0)
Key Considerations
- The scale and frequency of NOAA's updates significantly influence the annual cost.
- Coordination with the National Academies may require complex contracts and additional operational considerations.
- Long-term savings and GDP benefits depend heavily on the effective implementation and global usability of NOAA's updated data and guidance.