Climate Risk Summary
Camp Swift, TX Risk Profile
The primary drivers of climate-related financial risk in Camp Swift, TX are Inland Flooding, Tornado, and Cold Wave. This area also faces an unusually high intensity for Heat Wave, Hail, Winter Weather, and Wildfire compared to national averages. Based on recent federal data, homeowners in this market face an estimated average annual insurance premium of $1,756.
Based on FEMA EAL and hazard intensity.
Metrics indicate a balanced risk-to-premium environment with standard renewal rates.
Primary Risks
Inland Flooding
Expected Annual Loss for Camp Swift
Very High compared to US average
Tornado
Expected Annual Loss for Camp Swift
Very High compared to US average
Cold Wave
Expected Annual Loss for Camp Swift
Relatively High compared to US average
Spatial Analysis
Flood Plain Analysis
Significant Flood Exposure in Camp Swift
FEMA Flood Maps for Camp Swift identify the "100-year" and "500-year" floodplains (1% and 0.2% annual chance), but modern climate risk analysis suggests that nearly 25% of flood insurance claims originate from properties outside of these designated high-risk zones.
Insurance Market Stability
Avg. Annual Premium
Estimated baseline property insurance cost prior to localized disaster surcharges.
Non-Renewal Rate
The percentage of homeowner policies canceled by insurers, a key indicator of market retreat.
Insurer Loss Ratio
For every $1 collected in premium, insurers are paying out $0.26 in claims.
Financial Risk Inventory
Recommended Mitigation Strategies
Recommended investments to protect your property value and reduce insurance liability based on your local risk profile.
Inland Flooding Mitigation
Install a smart sump pump with battery backup and extend downspouts 10ft from foundation.
Tornado Mitigation
Reinforce garage doors and consider a FEMA-approved safe room or storm cellar.
Cold Wave Mitigation
General property maintenance and insurance review recommended.
Heat Wave Mitigation
Ensure attic insulation is R-49+ and consider a dual-fuel backup generator for AC.
Hail Mitigation
Replace roof with Class 4 impact-resistant shingles to significantly lower insurance premiums.
Strong Wind Mitigation
Trim large trees back from the roofline and reinforce roof-to-wall connectors (hurricane straps).
Lightning Mitigation
General property maintenance and insurance review recommended.
Winter Weather Mitigation
General property maintenance and insurance review recommended.
Hurricane Mitigation
Install permanent hurricane shutters or upgrade to impact-resistant windows.
Wildfire Mitigation
Create a 5ft 'non-combustible' zone around your home using gravel or pavers instead of mulch.
Ice Storm Mitigation
Install a 10kWh backup battery system to keep pipes from freezing during grid failure.
Landslide Mitigation
Professional slope stabilization and foundation drainage inspection is highly recommended.
Sources and Methodology
Spatial Climate Risk Modeling
The Expected Annual Loss (EAL) and hazard risk scores are derived from the FEMA NRI zip code dataset using a population-weighted spatial join. Because Zip Codes and Census Tracts do not share perfectly aligned boundaries, we utilize US Census Block Group population centroids to identify where residents actually live.
Financial & Insurance Metrics
The pysical resilence score is calculated by synthesizing Expected Annual Loss (EAL) against the total building replacement value within a jurisdiction. This creates a "Loss Ratio" that measures physical resilience. We supplement this with ZIP-code level data from the U.S. Treasury's Federal Insurance Office (FIO), monitoring trends in premium growth, loss ratios, and policy non-renewals to identify emerging "Insurance Deserts."
Primary Data Sources
- FEMA National Flood Hazard LayerHigh-resolution vector data for 100-year and 500-year flood zones.
- U.S. Department of the TreasuryFIO ZIP-code level insurance data (2018–2022 Historical Set).
- FEMA National Risk IndexBaseline hazard frequency and economic loss data (v1.20.0).
- U.S. Census BureauTIGER/Line 2025 Shapefiles & Decennial Population Statistics.