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Introduction This chapter synthesizes the scientific literature on the detection and attribution of observed changes in natural and human systems in response to observed recent climate change. For policy makers and the public, detection and attribution of observed impacts will be a key element to determine the necessity and degree of mitigation and adaptation efforts. For most natural and essentially all human systems, climate is only one of many drivers that cause change-other factors such as technological innovation, social and demographic changes, and environmental degradation frequently play an important role as well. Careful accounting of the importance of these and other confounding factors is therefore an important part of the analysis. At any given location, observed recent climate change has happened as a result of a combination of natural, longer term fluctuations and anthropogenic alteration of forcings. To inform about the sensitivity of natural and human systems to ongoing climate change, the chapter assesses the degree to which detected changes in such systems can be attributed to all aspects of recent climate change. For the development of adaptation policies, it is less important whether the observed changes have been caused by anthropogenic climate change or by natural climate fluctuations. Where possible, the relative importance of anthropogenic drivers of climate change is assessed as well. 18.1.1. Scope and Goals of the Chapter Previous assessments, notably in the IPCC Fourth Assessment Report (AR4; Rosenzweig et al., 2007), indicated that numerous physical and biological systems are affected by recent climate change. Owing to a limited number of published studies, human systems received comparatively little attention in these assessments, with the exception of the food system, which is a coupled human-natural system. This knowledge base is growing rapidly, for all types of impacted systems, but the disequilibrium remains (see also Section 1.1.1, Figure 1-1). The great majority of published studies attribute local to regional changes in affected systems to local to regional climate change.

Attribution has become a recurring issue in discussions about Loss and Damage (L&D;). In this highly-politicised context, attribution is often associated with responsibility and blame; and linked to debates about liability and compensation. The aim of attribution science, however, is not to establish responsibility, but to further scientific understanding of causal links between elements of the Earth System and society. This research into causality could inform the management of climate-related risks through improved understanding of drivers of relevant hazards, or, more widely, vulnerability and exposure; with potential benefits regardless of political positions on L&D.; Experience shows that it is nevertheless difficult to have open discussions about the science in the policy sphere. This is not only a missed opportunity, but also problematic in that it could inhibit understanding of scientific results and uncertainties, potentially leading to policy planning which does not have sufficient scientific evidence to support it. In this chapter, we first explore this dilemma for science-policy dialogue, summarising several years of research into stakeholder perspectives of attribution in the context of L&D.; We then aim to provide clarity about the scientific research available, through an overview of research which might contribute evidence about the causal connections between anthropogenic climate change and losses and damages, including climate science, but also other fields which examine other drivers of hazard, exposure, and vulnerability. Finally, we explore potential applications of attribution research, suggesting that an integrated and nuanced approach has potential to inform planning to avert, minimise and address losses and damages. The key messages are In the political context of climate negotiations, questions about whether losses and damages can be attributed to anthropogenic climate change are often linked to issues of responsibility, blame, and liability. Attribution science does not aim to establish responsibility or blame, but rather to investigate drivers of change. Attribution science is advancing rapidly, and has potential to increase understanding of how climate variability and change is influencing slow onset and extreme weather events, and how this interacts with other drivers of risk, including socio-economic drivers, to influence losses and damages. Over time, some uncertainties in the science will be reduced, as the anthropogenic climate change signal becomes stronger, and understanding of climate variability and change develops. However, some uncertainties will not be eliminated. Uncertainty is common in science, and does not prevent useful applications in policy, but might determine which applications are appropriate. It is important to highlight that in attribution studies, the strength of evidence varies substantially between different kinds of slow onset and extreme weather events, and between regions. Policy-makers should not expect the later emergence of conclusive evidence about the influence of climate variability and change on specific incidences of losses and damages; and, in particular, should not expect the strength of evidence to be equal between events, and between countries. Rather than waiting for further confidence in attribution studies, there is potential to start working now to integrate science into policy and practice, to help understand and tackle drivers of losses and damages, informing prevention, recovery, rehabilitation, and transformation.

Attribution has become a recurring issue in discussions about Loss and Damage (L&D). In this highly-politicised context, attribution is often associated with responsibility and blame; and linked to debates about liability and compensation. The aim of attribution science, however, is not to establish responsibility, but to further scientific understanding of causal links between elements of the Earth System and society. This research into causality could inform the management of climate-related risks through improved understanding of drivers of relevant hazards, or, more widely, vulnerability and exposure; with potential benefits regardless of political positions on L&D. Experience shows that it is nevertheless difficult to have open discussions about the science in the policy sphere. This is not only a missed opportunity, but also problematic in that it could inhibit understanding of scientific results and uncertainties, potentially leading to policy planning which does not have sufficient scientific evidence to support it. In this chapter, we first explore this dilemma for science-policy dialogue, summarising several years of research into stakeholder perspectives of attribution in the context of L&D. We then aim to provide clarity about the scientific research available, through an overview of research which might contribute evidence about the causal connections between anthropogenic climate change and losses and damages, including climate science, but also other fields which examine other drivers of hazard, exposure, and vulnerability. Finally, we explore potential applications of attribution research, suggesting that an integrated and nuanced approach has potential to inform planning to avert, minimise and address losses and damages. The key messages are In the political context of climate negotiations, questions about whether losses and damages can be attributed to anthropogenic climate change are often linked to issues of responsibility, blame, and liability. Attribution science does not aim to establish responsibility or blame, but rather to investigate drivers of change. Attribution science is advancing rapidly, and has potential to increase understanding of how climate variability and change is influencing slow onset and extreme weather events, and how this interacts with other drivers of risk, including socio-economic drivers, to influence losses and damages. Over time, some uncertainties in the science will be reduced, as the anthropogenic climate change signal becomes stronger, and understanding of climate variability and change develops. However, some uncertainties will not be eliminated. Uncertainty is common in science, and does not prevent useful applications in policy, but might determine which applications are appropriate. It is important to highlight that in attribution studies, the strength of evidence varies substantially between different kinds of slow onset and extreme weather events, and between regions. Policy-makers should not expect the later emergence of conclusive evidence about the influence of climate variability and change on specific incidences of losses and damages; and, in particular, should not expect the strength of evidence to be equal between events, and between countries. Rather than waiting for further confidence in attribution studies, there is potential to start working now to integrate science into policy and practice, to help understand and tackle drivers of losses and damages, informing prevention, recovery, rehabilitation, and transformation.

The Paris Agreement (2015) under the UNFCCC has anchored loss and damage in a separate article which specifies that understanding and support should be enhanced in areas addressing loss and damage such as early warning, preparedness, insurance and resilience. Irreversible loss is a special category under loss and damage but there is still missing clarity over what irreversible loss actually includes. Many negative impacts of climate change may be handled or mitigated by existing risk management, reduction and absorption approaches. Irreversible loss, however, is thought to be insufficiently addressed by risk management. Therefore, countries potentially or actually affected by irreversible loss are calling for other measures such as compensation, which however is highly contested in international climate policy. In Paris (2015) a decision was adopted that loss and damage as defined in the respective article of the agreement does not involve compensation and liability. Nevertheless, it is likely that some sort of mechanism will eventually need to come into play for irreversible loss due to anthropogenic climate change, which might involve compensation, other forms of non-monetary reparation, or transformation. Furthermore, climate litigation has increasingly been attempted to address negative effects of climate change. In this context, attribution is important to understand the drivers of change, what counts as irreversible loss due to climate change, and, possibly, who or what is responsible. Here we approach this issue by applying a detection and attribution perspective on irreversible loss. We first analyze detected climate change impacts as assessed in the IPCC Fifth Assessment Report. We distinguish between irreversible loss in physical, biological and human systems, and accordingly identify the following candidates of irreversible loss in these systems: loss of glaciers and ice sheets, loss of subsurface ice (permafrost) and related loss of lake systems; loss of land area due to coastal and hillslope erosion and sea level change; loss of plant and animal species, loss of ecosystems and biodiversity; loss of human lives, homelands, and cultural identity. Attribution to anthropogenic climate change is analyzed based on recent progress following from the IPCC AR5. Generally, high confidence in attributing irreversible loss to anthropogenic climate change is found in physical systems and more specifically in cryosphere environments, both in mountain and polar regions. Detected loss in terrestrial ecosystems has typically low confidence in attribution whereas loss in some ocean ecosystems (corals) has high confidence. Impacts in human systems that may be classified as irreversible loss are of low confidence in terms of attribution except for the Arctic where higher confidence for a relation with anthropogenic emissions was found. Our analysis suggests that scientific progress in detection and attribution is now at a level that would likely allow policy, or courts, to define mechanisms, or take decisions, as related to irreversible loss in many cryosphere systems. On the other hand, policy may need to consider that at least in the near future it will be difficult to establish clear tracks between irreversible loss in most human systems and anthropogenic climate change, a domain, which however is at the forefront of discussions. We end our discussion with setting out ideas for further clarification of different categories of irreversible loss, including in human systems, and the role of attribution in any policy or legal mechanism in order to help in the development of just and sensible solutions.

Ice volume estimates are crucial for assessing water reserves stored in glaciers. Due to its large glacier coverage, such estimates are of particular interest for the Himalayan–Karakoram (HK) region. In this study, different existing methodologies are used to estimate the ice reserves: three area–volume relations, one slope-dependent volume estimation method, and two ice-thickness distribution models are applied to a recent, detailed, and complete glacier inventory of the HK region, spanning over the period 2000–2010 and revealing an ice coverage of 40 775 km2. An uncertainty and sensitivity assessment is performed to investigate the influence of the observed glacier area and important model parameters on the resulting total ice volume. Results of the two ice-thickness distribution models are validated with local ice-thickness measurements at six glaciers. The resulting ice volumes for the entire HK region range from 2955 to 4737 km3, depending on the approach. This range is lower than most previous estimates. Results from the ice thickness distribution models and the slope-dependent thickness estimations agree well with measured local ice thicknesses. However, total volume estimates from area-related relations are larger than those from other approaches. The study provides evidence on the significant effect of the selected method on results and underlines the importance of a careful and critical evaluation.