Bridging evidence gaps in attributing loss and damage, and measures to minimize impacts

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Introduction

Climate change has increasingly caused significant economic and non-economic losses, particularly in low-income and climate-vulnerable countries. The urgency of these impacts has heightened international policy dialogues, leading to the establishment of the Warsaw International Mechanism (WIM) for Loss and Damage at COP19 in 2013. The WIM aims to address loss and damage associated with impacts of climate change in developing countries that are particularly vulnerable to the adverse effects of climate change. Building on this framework, COP27 saw the creation of the Loss and Damage Fund, which aims to provide financial assistance to vulnerable countries. Initial pledges of $770.6 million at COP28 were a positive step but fell short of addressing the projected costs, which may exceed $1 trillion annually by 2050.

This paper highlights the challenges of attributing losses to climate change, particularly in data-scarce developing countries, and explores strategies to enhance attribution science, build resilience, and operationalize the Loss and Damage Fund for inclusive and effective solutions.

Attribution science for loss and damage

Attribution of climate change is defined as “the process of evaluating the relative contributions of multiple causal factors to a change or event with an assignment of statistical confidence.”

Probabilistic event attribution (PEA) is the most frequently used attribution method. PEA allows a quantitative assessment of the extent to which human-induced climate change is affecting local weather events. The methodology provides an opportunity and potential to ensure quantified accountability for loss and damage. The Storyline approach is an alternative method, defined as a “physically self-consistent unfolding of past events, or of plausible future events or pathways”. This approach involves considering main driving factors of change and assessing their roles in a conditional manner.

Attribution science has advanced our understanding of the causal chains within the climate system to establish the relationship between nature and humans’ contributions to increasing concentration of atmospheric greenhouse gases. This understanding extends to both slow- and sudden-onset climate change, and their devastating impacts on natural and human systems.

Climate change attribution also enabled shaping risk assessment discussions on Loss and Damage. Relating meteorological changes to the consequent loss and damage had been the focus of the Loss and Damage negotiation. Following robust developments in attribution methods, loss and damage discussions focus on impacts that are caused by only anthropogenic climate change.

The scope of attribution science has broadened to include the assessment of anthropogenic influence in observed climate hazard impacts, a field that is gaining traction. A growing body of impact attribution research is examining impacts in economic and non-economic areas, depending on the feasibility of allocating monetary values to losses and damages of climate change. Although attribution science has significantly evolved in recent decades, it has not kept pace with the increasing demand to attribute losses and damages in the regions that are already experiencing devastating impacts of climate change, particularly in the Global South.

Challenges in addressing losses and damages in developing countries

Attributing long-term and sudden-onset changes in the climate requires reliable observational data that are lacking in most of the developing countries. When available, data are often incomplete, spatially scarce, and have insufficient temporal coverage, which hampers reliably evaluating model simulations for attributing loss and damage. Despite progress toward operationalizing climate modelling that is more suited to the evolving needs of society, developing countries encounter obstacles in accessing and utilizing high-resolution, convective-permitting climate models.

Scientific attribution studies also require reliable climate models and databases. Their limited availability has resulted in a geographic bias in the distribution of climate hazard attribution studies, with a notable dearth in developing countries. Decisions on Loss and Damage require bridging the data and technological gap to foster the development of the necessary dataset and models for attribution.

To date, the available data and advancements in loss and damage attribution in developing countries do not show the exact magnitude of direct impacts of climate change on different sectors. However, impact assessment studies have clearly indicated that agrifood systems are amongst those most heavily affected by climate change and variability. For this reason, we use the agrifood sector as an example to highlight sector-specific losses and damages as well as strategies to avoid or minimize such losses and damages.

Losses and damages within the agrifood sector: The agrifood sector is particularly vulnerable to extreme weather events like droughts and floods, which have resulted in significant losses, thus leaving millions of people under stress, crisis, emergency, and famine every year. In the past 30 years, 3.8 trillion USD worth of crops and livestock production have been lost due to climate-related events, equivalent to 5% of the annual global agricultural gross domestic product). The agrifood sector employs about 50% of workers in developing countries, including 500 million smallholder farmers who produce one third of the world’s food yet are among the world’s most climate-vulnerable. Consequently, the agrifood sector’s dual role as a contributor to and a victim of climate change necessitates prioritized consideration within the Loss and Damage agenda.

With different levels of confidence, IPCC’s Sixth Assessment Report (AR6) indicated that anthropogenic climate change has contributed to increasing adverse impacts on water availability and food production resulting in losses in crop production, livestock health and fisheries, with implications on human health and wellbeing. Studies conducted on the yields of major cereal crops (wheat, maize, and barley) showed that climate change-induced warming caused losses of 5 billion USD per year, during 1981 and 2002. Moore et al. find a 5.7% annual reduction in global calorie production from maize, wheat, and rice since 1960, attributed to anthropogenic climate change. According to Ortiz-Bobea et al., anthropogenic climate change is responsible for about 21% decline in global agricultural total factor productivity (TFP) since 1961. This reduction is even more pronounced in the tropics, including regions like Africa, Latin America, and the Caribbean, where the slowdown in TFP growth ranges between approximately 26–34%.

Strategies toward addressing loss and damage

This section explores how strategies for addressing loss and damage can be effectively integrated with ongoing adaptation efforts for both planning and post-event recovery, using examples from the agrifood sector.

Enhancing data availability through climate services: Robust climate services are required to improve data availability, enabling evidence-based decision-making to address climate-related losses and damages. Investments in observational data collection, digitization, and access, combined with capacity building and fostering collaboration among stakeholders, are essential to advancing these services. Digital platforms, such as agro-advisory and early-warning systems, have demonstrated their utility in countries like Angola and Malawi. The integration of local meteorological data with global tools enhances the quality of climate information, while remote sensing and reanalysis techniques bridge data gaps in resource-limited regions. These advancements are critical to informing and supporting policies and actions for mitigating climate impacts.

Enhancing climate resilience: Enhancing resilience involves strengthening the capacity of social, economic, and environmental systems to adapt and transform in response to climate hazards. There is a need for transformative adaptation, which integrates systemic changes in practices and structures with a focus on inclusivity and equity. By incorporating innovative tools, digital solutions, and community-specific strategies, resilience-building measures can reduce vulnerabilities and avert maladaptation. Incremental approaches to adaptation, such as crop diversification and sustainable agricultural practices, complement transformative efforts by addressing immediate risks and reinforcing long-term resilience in vulnerable sectors like agrifood systems.

Reducing climate risk: Decision-support models leveraging climate projections guide adaptive practices like crop diversification and land-use planning. Early-warning systems and integrated early-action services preemptively mitigate the impacts of extreme weather events by ensuring timely responses. Addressing the climate-conflict nexus is crucial, as resource scarcity exacerbated by climate change can fuel social and political unrest. Financial tools like climate risk insurance and satellite-assisted compensation mechanisms empower smallholder farmers to recover from climate-induced shocks, creating a comprehensive framework for reducing risks across economic and social dimensions.

Conclusion

There is a need to increase investments in gathering, storing, and processing data to facilitate loss and damage attributions, especially in the Global South. Improving data sharing platforms and establishing new ones, capacity building, and delivering demand-driven and policy-relevant climate information at national and regional levels can be used as strategies to accelerate data availability. Synergies and cross-border collaborations are necessary for data sharing, and for experience and knowledge exchange. Existing cooperations between developing and developed countries could be leveraged to build synergies for timely data sharing. It is also necessary for policy makers and for data and technology owners to improve laws and policies so that they can support data and technology sharing.

Citation

Engdaw MM, Mayanja B, Rose S, Loboguerrero AM, Ghosh A (2024) Bridging evidence gaps in attributing loss and damage, and measures to minimize impacts. PLOS Clim 3(8): https://doi.org/10.1371/journal.pclm.0000477