Access data

Access data#

There are a few different ways to access Open Climate Risk data, in addition to exploration via the map tool. This page outlines the different versions and formats of data available for download.

License Agreement

Open Climate Risk data are made available under the licenses listed below. By accessing the data, you agree to adhere to the license terms.

Terms

By viewing Open Climate Risk data, you agree to the TERMS OF DATA ACCESS.

Download options#

Option

Description

Formats

Access

License

Data sources

Raster (tensor) data

Full gridded dataset spanning CONUS

Icechunk (Zarr-based)

Source Coop

CC BY 4.0

K Riley et al. (2025), J Scott et al. (2024), R Rasmussen et al. (2023)

Vector (polygon) data

Full buildings dataset spanning CONUS

GeoParquet

Source Coop

ODbL

Overture Maps Foundation buildings dataset, K Riley et al. (2025), J Scott et al. (2024), R Rasmussen et al. (2023)

Regional statistics

Summary statistics for regions (state, county, census tract, census block) within CONUS

CSV, GeoJSON

Source Coop

ODbL

Census TIGER/Line, Overture Maps Foundation buildings dataset, K Riley et al. (2025), J Scott et al. (2024), R Rasmussen et al. (2023)

Subsetted vector (point) data

Building-level data subsetted to active region (county, census tract, census block)

CSV, GeoJSON

Map tool (see below)

ODbL

Census TIGER/Line, Overture Maps Foundation buildings dataset, K Riley et al. (2025), J Scott et al. (2024), R Rasmussen et al. (2023)

Full dataset downloads#

Schema#

The schemas for each of the full datasets are described on the Data schema page.

Regional statistics downloads#

Note

In rare cases, buildings with centroids situated exactly on regional boundaries may be counted in both region’s statistics.

Links#

CSV

GeoJSON

Statistics by county across CONUS

stats.csv

stats.geojson

Statistics by census tract across CONUS

stats.csv

stats.geojson

Statistics by census block across CONUS

stats.csv

stats.geojson

Statistics by state across CONUS

stats.csv

stats.geojson

Summary statistics across CONUS

stats.csv

stats.geojson

Schema#

Variable

Type

Description

Region identifiers

Identifying information for region–a state, county, census tract, or census block–represented in each row

GEOID

int

Geographic Identifier for region

building_count

int

Total number of buildings in region

Risk values

Risk values from output, input, or comparison datasets

rps_2011_mean

float

Mean annual fire risk (~2011 climate conditions) across all buildings in region

rps_2047_mean

float

Mean annual fire risk (~2047 climate conditions) across all buildings in region

bp_2011_mean

float

Mean burn probability (~2011 climate conditions) across all buildings in region

bp_2047_mean

float

Mean burn probability (~2047 climate conditions) across all buildings in region

crps_scott_mean

float

Mean conditional risk to potential structures (cRPS) from Scott et al. (2024)

bp_2011_riley_mean

float

Mean burn probability (~2011 climate conditions) across all buildings in region from Riley et al. (2025)

bp_2047_riley_mean

float

Mean burn probability (~2047 climate conditions) across all buildings in region from Riley et al. (2025)

rps_2011_median

float

Median annual fire risk (~2011 climate conditions) across all buildings in region

rps_2047_median

float

Median annual fire risk (~2047 climate conditions) across all buildings in region

bp_2011_median

float

Median burn probability (~2011 climate conditions) across all buildings in region

bp_2047_median

float

Median burn probability (~2047 climate conditions) across all buildings in region

crps_scott_median

float

Median conditional risk to potential structures from Scott et al. (2024)

bp_2011_riley_median

float

Median burn probability (~2011 climate conditions) across all buildings in region from Riley et al. (2025)

bp_2047_riley_median

float

Median burn probability (~2047 climate conditions) across all buildings in region from Riley et al. (2025)

Histogram values

Index in array corresponds to integer risk score (e.g., first value reflects number buildings with 0 score, next value reflects number buildings with 1 score, final value reflects number buildings with 10 score, etc.).

risk_score_2011_hist

float[]

Count of buildings with each risk score (~2011 climate conditions)

risk_score_2047_hist

float[]

Count of buildings with each risk score (~2047 climate conditions)

Downloading subsetted data in the map tool#

The map tool can be used to access region-specific, subsetted downloads.

Steps#

  1. Using the map or search bar, navigate to region of interest.

  2. Scroll to the Risk in the region section in the sidebar.

  3. Select your region of interest (continental U.S., state, county, census tract, or census block) and view trends inline.

  4. For subsetted, building-level data (schema below), click CSV ↓ or GeoJSON ↓ to download the applicable file for the selected region.

    If you are instead interested in summary statistics for the region (e.g., to reproduce the histogram), you may click CSV ↓ or GeoJSON ↓ to download those files (also available in the Regional statistics downloads section above).

Schema#

Variable

Type

Description

Building identifiers

GEOID

int

Geographic Identifier representing building (multiple buildings might belong to the same GEOID)

longitude

degrees

(CSV only) Longitude of building centroid

latitude

degrees

(CSV only) Latitude of building centroid

geometry

Point

(GeoJSON only) Building centroid as a GeoJSON Point

Risk values

rps_2011

float

Annual fire risk (~2011 climate conditions)

rps_2047

float

Annual fire risk (~2047 climate conditions)

bp_2011

float

Annual burn probability (~2011 climate conditions)

bp_2047

float

Annual burn probability (~2047 climate conditions)

crps_scott

float

Conditional risk to potential structures (cRPS) from Scott et al. (2024)

bp_2011_riley

float

Annual burn probability (~2011 climate conditions) from Riley et al. (2025)

bp_2047_riley

float

Annual burn probability (~2047 climate conditions) from Riley et al. (2025)