Getting started

Getting started#

This guide helps you get started with accessing and using Open Climate Risk fire risk data for the continental United States.

What is Open Climate Risk?#

Open Climate Risk is CarbonPlan’s platform for analyzing building-level wildfire risk across CONUS. It includes:

  • Building-level fire risk for 156 million structures

  • Wind-adjusted fire spread modeling that accounts for directional fire propagation

  • Multiple output formats: Interactive web maps, downloadable datasets, and cloud-native data access

  • Present and future scenarios: Current conditions (circa 2011) and future projections (circa 2047)

Quick access options#

Option 1: explore the web tool#

The fastest way to explore Open Climate Risk data is through our interactive web map. The web tool allows you to:

  • Search for specific addresses or locations

  • View building-level risk scores on a 0-10 scale

  • Explore state, county, census tract, and census block aggregations

Option 2: access production data#

If you want to analyze Open Climate Risk data programmatically, you can access our production datasets directly from cloud storage using Python.

Accessing production data#

Open Climate Risk output data is stored in Icechunk, a versioned, cloud-native data format that works seamlessly with Xarray and Zarr.

Prerequisites#

You’ll need Python with a few packages installed:

python -m pip install xarray icechunk dask

Load the dataset#

Here’s a minimal example to load Open Climate Risk wind-adjusted fire risk data:

import icechunk
import xarray as xr

# Connect to production Icechunk repository
version = 'v1.1.0'  # Check GitHub releases for latest version
storage = icechunk.s3_storage(
    bucket='us-west-2.opendata.source.coop',
    prefix=f'carbonplan/carbonplan-ocr/output/fire-risk/tensor/production/{version}/ocr.icechunk',
    region='us-west-2',
    anonymous=True,
)

repo = icechunk.Repository.open(storage)
session = repo.readonly_session('main')

# Open the dataset
ds = xr.open_dataset(session.store, engine='zarr', chunks={})
ds

This gives you access to:

  • Raster datasets: 30m resolution risk surfaces

  • Risk scores (RPS): Risk to Potential Structures values

  • Spatial coverage: Full CONUS extent

  • Multiple variables: Burn probability, conditional risk, wind-adjusted metrics

Understanding the data#

The dataset contains several key variables:

  • rps: Risk to Potential Structures (expected net value change per year)

  • bp: Burn Probability (annual likelihood of burning)

  • crps: Conditional Risk to Potential Structures (damage if fire occurs)

  • Risk scores are for a “generic” or “potential” structure at each location

Important limitation

Risk scores represent a hypothetical structure and do NOT account for building-specific factors like construction materials, retrofits, or defensible space management.

Next steps#

For data users#

  • Working with data: Detailed guide on loading and analyzing Open Climate Risk datasets

  • Data schema: Complete reference of available variables and metadata

  • Access data: Direct download links and bulk access options

For researchers & analysts#

For developers#

Support#

Available data versions#

Check our GitHub releases page for:

  • Latest data version numbers

  • Release notes and changelogs

  • Known issues and fixes

  • Data format changes

Ready to dive deeper? Check out the Working with data notebook for hands-on examples.