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Climate Models and Methodologies

The data models developed by UrbanFootprint leverage trusted US government sources and authoritative private data providers to build peer-reviewed models and datasets built for actionable, real-world analysis and decision making.

Models presented at the 2023 American Geophysical Union Conference
Tropical Cyclone Wind Risk
Tropical Cyclone Wind Risk

The UrbanFootprint Tropical Cyclone Wind Risk model estimates the rate of 1-min wind speed exceedance events per year on a 0.1 degree grid nationwide.

NonCyclonic Wind
Noncyclonic Wind Risk

The UrbanFootprint Noncyclonic Wind Risk model estimates probabilities of exceedance at various wind speeds for CONUS on an H3 zoom level 5 grid.

Tornado Wind
Tornado Wind

The UrbanFootprint Tornado Wind Risk model generates probabilities of exceedance for CONUS on an H3 zoom level 4 grid.

Coastal Flood Risk
Coastal Flood Risk

The UrbanFootprint Coastal Flood Risk model estimates flood depth at the parcel geography for CONUS.

Earthquake Risk
Earthquake Risk

The UrbanFootprint Earthquake Risk model produces a single seismic hazard map for CONUS that accounts for variability in Vs30 on an H3 zoom level 9 grid.

Meet our climate team

The UrbanFootprint climate team brings interdisciplinary expertise from data science, geospatial engineering, and urban planning to holistic modeling and methodologies.

Erik Larson, PhD

Data Science Manager

Moorea Brega, PhD

VP of Data Science and Engineering

Dhruvi Kothari, MS

Data Scientist

René Sorina, MS

Senior Data Scientist

Madeline Jones, MS

Senior Geospatial Data Engineer