The role of data quality for supporting climate Adaptation and Resilience Frameworks – policy paper published in Sustainability Journal

Bridging data gaps, so plans may be targeted, context-specific, and impactful – so better serve people at the frontlines of climate change

Interviews with experienced practitioners highlighted a shortfall of suitably representative data of reliable quality is limiting effective implementation of adaptation and resilience projects, particularly at local levels and in developing nations. What’s more, as reported today/this week in the paper ‘Examining Adaptation and Resilience Frameworks: Data quality’s role in supporting climate efforts’ published in Sustainability Journal, no common approach or tool is available to help these experts streamline the process of designing, monitoring, and evaluating such plans.

The experts interviewed for the paper cited a lack of measurement indicators that might otherwise help assess the effectiveness of adaptation and resilience strategies, particularly in terms of data availability and data quality. However, rather than back development of new indicator frameworks in relative isolation, these experts would prefer more coordinated approaches that address local contexts and practical guidance for measuring progress toward adaptation and resilience goals.

The research paper was produced by the as part of to help understand how metrological principles can be brought into policy domains, specifically looking at current policies, frameworks, and indicators for climate adaptation and resilience. Qualitative data were collected via semi-structured interviews between April and August 2022 with thirteen civil servants and stakeholders engaged in planning and implementation for climate change adaptation and resilience. These structured interviews were designed to form a picture of the practical experience of developing and implementing adaptation and resilience policies/practices and indicators, and the role of data availability and quality supporting climate adaptation and resilience efforts.

Interviewees represented academia (3), research centres (4), and governmental or intergovernmental organisations (6). The respondents were based across the world and their research activities ranged in scale from localised, such as for London, through to regional and continental scales, including Europe, South America, and Asia, to a global level.

While concepts of ‘adaptation’ and ‘resilience’ are linked to headline news about climate change, each has distinct meanings and implications.

According to IPCC AR6 WGII adaptation is defined as, ‘in human systems, the process of adjustment to actual or expected climate and its effects, to moderate harm or exploit beneficial opportunities. In natural systems, the process of adjustment to actual climate and its effects; human intervention may facilitate adjustment to expected climate and its effects whereas resilience is ‘the capacity of social, economic and environmental systems to cope with a hazardous event or trend or disturbance, responding or reorganising in ways that maintain their essential function, identity, and structure while also maintaining the capacity for adaptation, learning, and transformation’.

In addition, resilience is commonly used under a ‘wide spectrum of meaning which overlaps with concepts of vulnerability, adaptive capacity and, thus, risk, and resilience as a strategy overlap with risk management, adaptation, and transformation. Implemented adaptation is often organised around resilience as bouncing back and returning to a previous state after a disturbance’.

Scant information on levels of implementation and how to monitor and evaluate

The UNFCCC emphasises that governments of developing countries should create comprehensive and integrated adaptation plans aligned with their development priorities. More than 70 countries have adopted such policies, but limited information on the level of implementation and monitoring, and evaluation of these plans is on offer.  

It’s therefore unsurprising that developing effective climate change adaptation plans, recommendations for designing adaptation, and resilience indicators, were reported as particularly challenging. 

One “impressive” example cited by one respondent – a project aiming to turn an ‘exploratory research approach into a solid methodology’ — is the Global Human Settlement Layer project of the European Commission’s Joint Research Centre.

This project provides spatially detailed information on population and settlements, using data reflecting scientific-technological developments such use of free/open data including Earth Observation and volunteered geographic information at global scales; artificial intelligence and machine learning, and collaborative data sharing.

Local adaptation strategies: anticipating ripple effects of disruptions

The paper found that Local-level adaptation is a critical component of a comprehensive response to climate change, and different regions, communities, and sectors should develop adaptation strategies based on their specific local climate risks. However, one researcher notes, “We are we’re quite a way behind in terms of even gathering new information, my priority is for people to begin measuring the same thing so that you can measure something consistently. At the moment we haven’t really got into the quality of measurement, how you measure things, whatever else I think that’s important and hopefully that will come. I think the priority is still to get something in terms of a consistent approach to this. So, it’s quite early in the process in that sense, which is not good.”

The same respondent reported a scarcity of quality data, especially at the local level. “This undermines our capacity to understand the specific needs and vulnerabilities of communities on the frontlines of climate impacts. It is crucial to bridge this data gap to ensure that adaptation efforts are targeted, context-specific, and impactful.”

A challenge to providing solutions on the ground is inherent complexity. For example, in London, the biggest issues are reported as heat, drought, and flooding. Each risk has numerous sub-classifications: there are at least five different types of flooding, that could affect different local communities differently.

Data challenges

Other challenges were reported around choices of data for measuring adaptation and resilience indicators. Concerns were raised about a lack of data at the local level, limited technical capacity for data processing and access, and the need for quality assurance.

One recent study Exploring Switzerland’s Land Cover Change Dynamics highlighted another barrier to identifying underlying drivers of changes to land cover and understanding the rate of change: spatial resolution and temporal update frequency of Switzerland’s national Land Cover dataset.

Another project relates to the UN Sustainable Development Goal 15 on reversing land degradation, suggested the value of that indicator was twice as high as officially reported to the United Nations.

“[…] because I really have the feeling that they are taking decisions, but not on the […] best knowledge available. That’s why I think communicating uncertainty properly is even more difficult when more results are compared, and error associated with the model is linked to the data and algorithms used.” (R 4)

Recommendations and proposed project model

The study found that the majority of respondents’ concerns related to the planning phase of interventions rather than implementation or even the Monitoring, Reporting, and Verification (MRV) stages. The study concludes with recommendations on how to design indicators, covering planning, monitoring the effectiveness of adaptation actions, and measuring adaptive capacity. Developing indicators would support improved monitoring and reporting of adaptation and resilience efforts at the local and national levels, by enabling consistent and comparable data.

A project model for climate change adaptation and resilience is also proposed, that could support the development of policies, plans and strategies, and indicators at the local level — that identifies important steps for adaptation and resilience projects in planning, implementation, and MRV.