Climate Risk and Resilience Framework

Climate change poses multifaceted risks to locations around the globe, impacting economies, ecosystems, and communities. Traditionally, climate risk assessments have focused purely on physical risks such as heat stress, drought, flooding, and other natural hazards. While these assessments can illuminate the changes in climate patterns, they overlook the role of human activities and adaptations in the built environment which can significantly influence the actual impact of such patterns in the real world.

To address this gap, we are introducing a new climate risk assessment framework that integrates high-resolution geospatial data on adaptation and resilience into climate risk models, resulting in a Resilience-Adjusted Risk assessment for any location worldwide. This approach recognizes that while physical risks significantly contribute to overall climate risk, the ability of locations, communities, and infrastructure to adapt and stay resilient amid future uncertainties can significantly alter the risk landscape. By doing so, we aim to provide a more nuanced and actionable understanding of location-based climate risks. Whether you are a policymaker, investor, or environmental researcher, the Resilience-Adjusted Risk framework is designed to inform better strategic and investment decisions.

You may explore the differences between the Climate Risk Index and the Resilience-adjusted Risk Index in our interactive app here. To understand key component of the method further, please read on.

Toggling between Physical Risk and RAJ Risk. Both maps reveal different insights that provide a more nuanced and actionable understanding of location-based climate risks.

Risk damage calculations with resilience adjustment

AlphaGeo's Resilience-Adjusted Risk framework utilizes a comprehensive, domain knowledge driven approach that seamlessly incorporates local resilience measures into traditional global risk engineering methodologies. There are currently 6 risk categories (hazard types) in this framework.

Drawing from risk engineering practices, for each risk category, we assign a damage function that maps the intensity (I) of the exposure to the mean damage ratio (MDR). The resultant MDR calculated from the intensity (I) represents the estimated damage on an exposed asset or a location given a certain climate hazard. As intensity of the hazard changes over time under different climate change scenarios for the target location, the MDR of a location changes over time as well. In addition to the SSP emission scenarios, we also support a wider range of scenario-based impact analysis including accelerated climate volatility.

Next, we introduce the relevant adaptation measures to reduce the intensity of the hazard. The higher the local resilience, the higher the offset to the intensity of the hazard. As a result, a location with high resilience can experience large offsets to the intensity of the hazard, reducing its MDR proportionally according to the damage function.

This process of intensity adjustment is applied to all 6 risk categories, with each risk being offset by specific adaptation measures. For example, the presence of flood barriers and a high capacity in local water storage and control can greatly reduce the damage of flooding; the strength of the building material play a significant role in reducing wind damages.

Lastly, climate resilience also includes intangible measures of societal resilience. Physical adaptations to risks and the robustness of the local community to shocks work in tandem to minimize the effect of natural hazards. Therefore, after adjusting for risk-specific adaptation features, we apply an additional offset to all risk categories to account for societal resilience. A location with strong societal resilience indicator, such as a high human development index or high government efficiency, would benefit from additional intensity offset, further reducing the expected MDR.

Overview of impact calculations in the risk-resilience framework. The modular methodology allows the computation of a pure physical risk impact to serve as a baseline to understand how much offset resilience can have on a location.

This method allows flexibility in designating the appropriate offsets for each risk category as each hazard are being offset by different local adaptation measures. It also allows us to create two set of results: one with only Physical Risk Impact, as show in the first equation, serving as a baseline, and one adjusted with resilience, giving the Resilience-adjusted Risk Impact, which allow users to understand how effective the current measures are in offsetting climate risks.

AlphaGeo's methodology integrates local adaptation measures as well as metrics of societal resilience as modifiers to a location's physical climate risk exposure, resulting in a more holistic assessment of the true impact of climate change.

The diagram above summarizes the underlying risk and resilience features for each risk category. The set of local adaptation features and societal resilience features continues to grow over time as more data is collected, enhancing the results overtime.

To understand the methodology behind the localized resilience features, please refer to the article on the Global Climate Adaptation Layer.

Continue next to our methods on benchmarking the impacts into comparative scores for climate reporting and analytics.