Tappan, NY (10983) Flooding & Climate Risk Profile

The primary drivers of climate-related financial risk in Tappan, NY (10983) are Inland Flooding, Hurricane, and Earthquake. Based on recent federal data, homeowners in this market face an estimated average annual insurance premium of $1,588, with a local policy non-renewal rate of 0.3%.

Understanding the Dollars

Expected Annual Loss (EAL) is a statistical average of property damage for this entire zip code over a standard year across all properties.

  • / It represents the "average cost" rather than a guaranteed yearly bill.
  • / It can be used to compare the relative risk from different hazards and across different neighborhoods.

Zip Code Risk Map

Flood Plain Analysis

Localized Flood Dynamics in 10983

FEMA Flood Maps for 10983 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.

Use the map above to better understand risk by looking at both the FEMA flood plain maps and FEMA Risk Inventory maps by census tract. Standard FEMA maps may not account for 'flash flooding' from intense rain events.
FEMA Designation vs. Reality
Relatively Low
Relative Vulnerability
$844,898
Annualized Property Exposure

Primary Risks

Inland Flooding

$844,898

Expected Annual Loss for Zip Code 10983

41.2Score

Relatively Low compared to US average

Hurricane

$87,022

Expected Annual Loss for Zip Code 10983

69.0Score

Relatively Low compared to US average

Earthquake

$83,384

Expected Annual Loss for Zip Code 10983

60.9Score

Relatively Low compared to US average

Insurance Market Stability

Avg. Annual Premium (2022)

$1,588
Latest Market Rate

Year-over-Year Change

+1.9%
20212022

Market Retreat (Non-Renewals)

0.28%

Higher rates indicate insurers are actively reducing exposure to ZIP 10983 due to climate-linked risk.

Underwriting Stress (Loss Ratio)

55.0%

A ratio over 70% suggests insurers are paying out nearly all premiums as claims, forcing future price hikes.

Historical Market Trends

Toggle series below to compare costs vs. market stress indicators

Historical Trends & Forecasting

Compare premium costs against underlying risk factors.

Financial Risk Inventory

MAJOR DRIVER
Inland Flooding
$844,898
Score: 41.2
MAJOR DRIVER
Hurricane
$87,022
Score: 69.0
MAJOR DRIVER
Earthquake
$83,384
Score: 60.9
Cold Wave
$75,270
Score: 46.7
Strong Wind
$54,771
Score: 68.3
Tornado
$54,660
Score: 38.1
Heat Wave
$43,638
Score: 36.6
Lightning
$19,418
Score: 49.7
Winter Weather
$9,417
Score: 68.5
Ice Storm
$5,943
Score: 41.4
Coastal Flooding
$1,240
Score: 18.0
Hail
$704
Score: 11.7
Wildfire
$61
Score: 29.2
Landslide
$4
Score: 37.8

Recommended Mitigation Strategies

Recommended investments to protect your property value and reduce insurance liability based on your local risk profile.

💧Medium Investment

Inland Flooding Mitigation

Install a smart sump pump with battery backup and extend downspouts 10ft from foundation.

Risk Score: 41.2
🌀High Investment

Hurricane Mitigation

Install permanent hurricane shutters or upgrade to impact-resistant windows.

Risk Score: 69.0
🏠Low Investment

Earthquake Mitigation

General property maintenance and insurance review recommended.

Risk Score: 60.9

Methodology and Sources

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

Nearby Locations