Overview of the CRRI methodology, data processing, and supporting reference pages
This section explains how AlphaGeo builds the Climate Risk and Resilience Index (CRRI).
It covers the scoring framework, adaptation logic, climate data pipeline, source data, and how CRRI differs from hazard-only products.
CRRI combines two views of climate risk:
Physical Risk — the baseline hazard signal
Resilience-Adjusted Risk — the likely real-world impact after adaptation and resilience factors are applied
The methodology pages in this section explain how AlphaGeo:
converts hazard intensity into risk signals
applies a triple-layer adaptation workflow
incorporates asset-level remediation measures
processes climate and geospatial data onto a common scoring grid
curates the source data behind the model
Start here for the core CRRI framework.
This page explains how AlphaGeo moves from physical hazard to resilience-adjusted risk using local adaptation capacity, societal resilience, and asset-level remediation inputs.
Use this page to understand the asset-level layer of the model.
It explains how building features and mitigation measures reduce risk by hazard, how the scoring logic works, and how residual risk is capped.
Use this page to understand the data pipeline.
It documents climate model inputs, spatial resolution, H3 processing, per-hazard source layers, and key limitations of the current framework.
Use this page to review the underlying datasets.
It summarizes the core risk and resilience sources, coverage, update cadence, and selected references used across the CRRI framework.
Use this page to see how CRRI differs from other providers.
It explains the role of resilience-adjusted risk, the Global Adaptation Layer, and AlphaGeo's broader analytics stack.
If you are new to CRRI, read the pages in this order:
For the product overview, see Climate Risk and Resilience Index.
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