Climate resilience has gained an essential role in research as well as in international policies. An increasing number of cities are adapting to climate change to enhance their climate resilience. Given the complexity of urban systems in combination with the acceleration of climate and social change, it is challenging to measure the success of resilience-rising activities. To manage and accelerate the learning process and the transformation process, monitoring and evaluation of implemented adaptation measures are crucial. Most of the currently used indicator sets are dealing with system-focused changes. However, actor-focused changes are less addressed in holistic indicator sets, even if individual agency assumes an important role in the transformation process. This research was intended to design a framework for individual climate resilience agency and operationalise it in a composite indicator set. The indicator set is implemented in a survey with 14 research projects in Germany. Finally, the indicator set is verified using statistical and empirical validation. The study presents an applicable indicator set, which reveals more in-depth insights into the individual climate resilience agency and changes within adaptation measurements. Further, the set can be applied in both one-time assessments and repetitive measurement. Therefore, the tool can be implemented as a monitoring tool, as well as a formative evaluation tool, in the climate resilience adaptation context.

High uncertainty in the occurrence of extreme events and disasters have made resilience-building an imperative part of society. Resilience assessment is an important tool in this context. Resilience is multidimensional as well as place-, scale- and time-specific, which requires a comprehensive approach for measuring and analysing. In this regard, composite indicators are preferred, and extensive literature is available on resilience indices on all spatial and temporal scales as well as hazard-specific or multi-hazard related indicators. However, transparent, robust, validated and transferable metrics are still missing from the scientific discourse. Hence, the research follows a novel composite index development approach: First, to develop and operationalise climate resilience on the county level in the state of Baden-Wurttemberg, Germany; second, to develop multiple composite indices in order to assess the impact of the construction methodology to increase transparency and decrease uncertainty; third, validating the index by statistical as well as empirical data and machine learning models - which is a novel endeavour so far. The results underscored that the two-step inclusive validation of data-driven statistical analysis in combination with empirical data proved to be essential in developing the index during the selection and aggregation of indicators. The results also highlighted a lower climate resilience of rural regions compared to metropolitan regions despite their better environmental status. Overall, machine learning proved to be essential in understanding and linking indicators and indices to policy, resilience and empirical data. The research contributes to a better understanding of climate resilience as well as to the methodological construction of composite indicators.

In the face of accelerating climate change, urbanization and the need to adapt to these changes, the concept of resilience as an interdisciplinary and positive approach has gained increasing attention over the last decade. However, measuring resilience and monitoring adaptation efforts have received only limited attention from science and practice so far. Thus, this paper aims to provide an indicator set to measure urban climate resilience and monitor adaptation activities. In order to develop this indicator set, a four-step mixed method approach was implemented: (1) based on a literature review, relevant resilience indicators were selected, (2) researchers, consultants and city representatives were then invited to evaluate those indicators in an online survey before the remaining indicator candidates were validated in a workshop (3) and finally reviewed by sector experts (4). This thorough process resulted in 24 indicators distributed over 24 action fields based on secondary data. The participatory approach allowed the research team to take into account the complexity and interdisciplinarity nature of the topic, as well as place- and context-specific parameters. However, it also showed that in order to conduct a holistic assessment of urban climate resilience, a purely quantitative, indicator-based approach is not sufficient, and additional qualitative information is needed.