Methodology: Resilience-adjusted Risk with Triple-layer Adaptation Offset

AlphaGeo's resilience-adjusted risk framework calculates both a physical risk and resilience-adjusted risk score based on a triple-layer adaptation workflow

Access Free Trial

Book a Demo

Overview

Physical hazard models show where climate risks intensify but do not capture how local adaptation changes mitigate damage on the ground. AlphaGeo’s Climate Risk and Resilience Index (CRRI) closes that gap with a novel "resilience-adjusted risk" framework that integrates high-resolution geospatial data on adaptation into climate risk models, resulting in a Resilience-Adjusted Risk assessment for any location worldwide.

This framework produces two complementary outputs:

1. Physical Risk Impact — the unmitigated baseline based on hazard intensity alone

2. Resilience-Adjusted Risk Impact — the likely real-world impact after resilience factors are applied

Toggling between Physical Risk and resilience-adjusted risk reveals how local resilience changes likely impact at the same location.

Why resilience-adjusted risk matters

Traditional climate risk assessments focus on physical hazards such as heat stress, drought, flooding, and wildfire. That baseline is essential, but incomplete.

Two locations can face similar hazard intensity and still experience different outcomes. Flood barriers, drainage, building quality, emergency response capacity, and broader societal resilience all shape likely damage. CRRI captures those differences directly.

How CRRI calculates impact

CRRI follows a four-step framework:

1. Measure hazard intensity for each hazard category at a given location, time horizon, and scenario.

2. Convert intensity into damage using a hazard-specific damage function.

3. Apply three layers of hazard-specific adaptation offsets, based on:

   1. Local adaptation capacity: Local or community-level infrastructural adaptations (e.g., flood defenses, drainage systems), using our proprietary Global Adaptation Layer dataset.

   2. Societal resilience: Ability of a community to absorb and recover from shocks, based on factors such as fiscal capacity and demographic vulnerability.

   3. Asset-level remediations: Presence of asset or building-level mitigation measures, captured through the Remediation Checklist.

AlphaGeo's Risk and Resilience Index offsets the Hazard Score (physical risk only) with a "Triple-Layer Adaptation Workflow": 1. Adaptation Capacty; 2. Societal Resilience; 3. Asset-level Remediations (via the Remediation Checklist).

1. Local adaptation capacity offset

We begin by modelling the mitigating impact of local adaptation capacity on risk. Local adaptation capacity is modelled using our multi-hazard Global Adaptation Layer dataset, which identifies, quantifies, and scores the presence of hazard-specific adaptation features globally.

For each hazard category, CRRI maps hazard intensity (I) to Mean Damage Ratio (MDR).

Mean Damage Ratio (MDR) estimates expected damage at a given hazard intensity.

As hazard intensity changes across time horizons and emissions scenarios, MDR changes as well. This creates a consistent baseline for comparing physical risk over time and across locations.

We then introduce the relevant local adaptation measures to reduce the intensity of the hazard. The higher the degree of adaptation locally, the higher the offset to the intensity of the hazard. As a result, a location with high local adaptation capacity will experience larger offsets to the intensity of the hazard, reducing its MDR proportionally according to the damage function. CRRI then adjusts hazard intensity using local adaptation measures that reduce likely damage.

Examples of local adaptation measures include:

• flood barriers and drainage capacity reducing flood damage

• stronger building materials reducing wind damage

• local water storage and control reducing drought and flood impacts

This process is applied across all hazard categories in the CRRI.

2. Societal resilience adjustment

Climate resilience is not only physical. It also reflects the strength of local institutions, services, and communities.

After hazard-specific adaptation offsets are applied, CRRI applies an additional societal resilience offset across hazard categories. Locations with stronger societal resilience indicators, such as stronger governance or higher human development, are better positioned to absorb shocks and recover faster.

3. Asset-level remediation offset

This step applies when client-provided data is available through the Remediation Checklist.

The Remediation Checklist captures the mitigation measures in place at the asset or building level. When the checklist is filled (even partially), an additional asset-level adaptation offset is then applied to the Resilience-Adjusted Risk Score.

If no asset-level data is available via the Remediation Checklist, this asset-level adjustment is not applied. In that case, the Resilience-adjusted Risk Score only reflects local adaptation capacity and societal resilience.

For more detail on how asset-level adaptation is quantified and applied, see Remediation Checklist: Quantifying Asset-level Adaptation.

Extract of the Remediation Checklist

Outputs: Physical and Resilience-Adjusted Risk

This framework produces two sets of results.

Physical Risk Impact

This is the baseline view, reflecting expected impact from hazard intensity alone.

Resilience-Adjusted Risk Impact

This view reflects the likely climate hazard impact after accounting for local adaptation capacity, societal resilience, and asset-level remediations.

The Resilience-adjusted Risk score reflects adapted risk, where hazard intensity is offset by (1) local adaptations; (2) societal resilience; and (3) asset-level remediations.

Together, these outputs help users distinguish between where hazards are most threatening and where adaptation is sufficient to offset them.

The Climate Risk and Resilience Index's feature matrix. Risk, adaptation, and resilience features are provided by AlphaGeo, while asset-level remediations are an optional, user-reported input.

The underlying adaptation and resilience inputs continue to expand as more data becomes available. This improves coverage, granularity, and the explanatory power of the framework over time.