Climate adaptation indicators and metrics: State of local policy practice

Abstract

Recent systematic reviews show that, overall, and across governance levels and sectors, climate change adaptation monitoring and evaluation (M&E) systems are rarely programmed and implemented. As a result, there is a generalized lack of knowledge and practice regarding the definition and use of adaptation indicators and metrics from which to effectively learn. This paper focuses on understanding the emergent state of practice regarding adaptation indicators and metrics at the local level: what indicators and metrics are used? What aspects of the adaptation process are they measuring? How will they be monitored, evaluated, and reported? Out of a sample of the largest 136 coastal cities worldwide, only 59 cities have adaptation-related plans and only 11 (Athens, Auckland, Barcelona, Glasgow, Lima, Montreal, Nagoya, New York City, Portland, Tokyo, and Vancouver) list indicators and metrics. Sourced from these documents, we compile and code a total of 1971 indicators, of which 1841 focus fully or partially on adaptation-related aspects. We study the level of detail (objective, indicator, metric), type (target, input, output, outcome, or impact), scale, dimension, units of measurement, target, and proposed monitoring timeframe, among other aspects. Data shows that current adaptation measurement frameworks are tied to the degree to which each city integrates and addresses adaptation in its policies. A majority of adaptation indicators and metrics measure outputs, i.e. implementation aspects. Outcome indicators are generally connected to users or beneficiaries of adaptation measures and impact indicators are mostly related to health (e.g. hospitalizations). Targets and monitoring timeframes, as well as data sources, are rarely defined. We connect this to a lack of definition of local adaptation goals and a poor understanding of how specific adaptation actions lead to vulnerability reductions and resilience increases. Based on the identified gaps, we propose a metric development guiding framework to stimulate discussion around effective and feasible approaches to measure adaptation progress based on improved adaptation decision-making. We argue, that our results should fuel a critical revision of current adaptation planning practices that might ultimately facilitate processes of learning, experimentation and innovation in this embryonic field. © 2022