Resilience Scanner · Data Sources

Resilience Scanner aggregates a number of different data sources on cities and their climate hazards and resilience plans.

Climate Hazard Indicators

Climate hazard forecasts are taken from Wong, T. and E. Mackres. 2024. City-Scale Climate Hazards at 1.5°C, 2.0°C, and 3.0°C of Global Warming. (Washington, DC: World Resources Institute). These probabilistic estimates for temperature, precipitation and humidity are generated from down-scaled global climate models. We use the highest value of the three models employed for the 3.0°C warming scenario to represent the most conservative estimates of future climate risks.

City location, population, and development level are also provided by this source.

City Size Classification

Cities in our dataset are classified by population size using a metropolitan classification scheme inspired by United Nations standards for urban development:

Small cities: Population under 1.5 million
Medium cities: Population between 1.5 and 5 million
Large cities: Population of 5 million or more

This classification aligns with international urban classification standards and reflects global patterns of urbanization and metropolitan development. It helps identify how adaptation and resilience solutions vary across different scales of urban areas.

City Resilience Plans

Baseline descripions of adaptation and resilience technology solutions were extracted using a large language model tool (LLM) from our collection of city resilience and climate adaptation plans published by over 100 global cities.

Taxonomies and Classifications

Our solution categorization and subcategorization scheme is adaptated from a collection of leading adaptation and resilience taxonomies:

Our climate hazard taxonomy is based the C40 City Climate Hazard Taxonomy, created by Arup in 2015.

Background Research

Key reference materials informing our analysis include: