Is the choice of statistical paradigm critical in extreme event attribution studies?

This is the final version of the article. Available from Springer Verlag via the DOI in this record.The science of event attribution meets a mounting demand for reliable and timely information about the links between climate change and individual extreme events. Studies have estimated the contribution of human-induced climate change to the magnitude of an event as well as its likelihood, and many types of event have been investigated including heatwaves, floods, and droughts. Despite this progress, such approaches have been criticised for being unreliable and for being overly conservative. We argue that such criticisms are misplaced. Rather, a false dichotomy has arisen between “conventional” approaches and new alternative framings. We have three points to make about the choice of statistical paradigm for event attribution studies. First, different approaches to event attribution may choose to occupy different places on the conditioning spectrum. Providing this choice of conditioning is communicated clearly, the value of such choices depends ultimately on their utility to the user concerned. Second, event attribution is an estimation problem for which either frequentist or Bayesian paradigms can be used. Third, for hypothesis testing, the choice of null hypothesis is context specific. Thus, the null hypothesis of human influence is not inherently a preferable alternative to the usual null hypothesis of no human influence.PAS is supported by the Joint UK DECCBEIS/Defra Met Office Hadley Centre Climate Programme (GA01101). DJK is supported by the ARC Centre of Excellence for Climate System Science (grant CE 110001028)

Uncertainties in the attribution of greenhouse gas warming and implications for climate prediction

This is the final version. Available from the American Geophysical Union via the DOI in this record. Using optimal detection techniques with climate model simulations, most of the observed increase of near-surface temperatures over the second half of the twentieth century is attributed to anthropogenic influences. However, the partitioning of the anthropogenic influence to individual factors, such as greenhouse gases and aerosols, is much less robust. Differences in how forcing factors are applied, in their radiative influence and in models’ climate sensitivities, substantially influence the response patterns. We find that standard optimal detection methodologies cannot fully reconcile this response diversity. By selecting a set of experiments to enable the diagnosing of greenhouse gases and the combined influence of other anthropogenic and natural factors, we find robust detections of well-mixed greenhouse gases across a large ensemble of models. Of the observed warming over the twentieth century of 0.65 K/century we find, using a multimodel mean not incorporating pattern uncertainty, a well-mixed greenhouse gas warming of 0.87 to 1.22 K/century. This is partially offset by cooling from other anthropogenic and natural influences of-0.54 to-0.22 K/century. Although better constrained than recent studies, the attributable trends across climate models are still wide, with implications for observational constrained estimates of transient climate response. Some of the uncertainties could be reduced in future by having more model data to better quantify the simulated estimates of the signals and natural variability, by designing model experiments more effectively and better quantification of the climate model radiative influences. Most importantly, how model pattern uncertainties are incorporated into the optimal detection methodology should be improved.Joint UK DECC/Defra Met Office Hadley Centre Climate Programm

Different ways of framing event attribution questions: The example of warm and wet winters in the United Kingdom similar to 2015/16

This is the final version. Available from the American Meteorological Society via the DOI in this recordAttribution analyses of extreme events estimate changes in the likelihood of their occurrence due to human climatic influences by comparing simulations with and without anthropogenic forcings. Classes of events are commonly considered that only share one or more key characteristics with the observed event. Here we test the sensitivity of attribution assessments to such event definition differences, using the warm and wet winter of 2015/16 in the United Kingdom as a case study. A large number of simulations from coupled models and an atmospheric model are employed. In the most basic case, warm and wet events are defined relative to climatological temperature and rainfall thresholds. Several other classes of events are investigated that, in addition to threshold exceedance, also account for the effect of observed sea surface temperature (SST) anomalies, the circulation flow, or modes of variability present during the reference event. Human influence is estimated to increase the likelihood of warm winters in the United Kingdom by a factor of 3 or more for events occurring under any atmospheric and oceanic conditions, but also for events with a similar circulation or oceanic state to 2015/16. The likelihood of wet winters is found to increase by at least a factor of 1.5 in the general case, but results from the atmospheric model, conditioned on observed SST anomalies, are more uncertain, indicating that decreases in the likelihood are also possible. The robustness of attribution assessments based on atmospheric models is highly dependent on the representation of SSTs without the effect of human influence.Joint BEIS/Defra Met Office Hadley Centre Climate Programm

The increasing likelihood of temperatures above 30 to 40 °C in the United Kingdom

This is the final version. Available on open access from Nature Research via the DOI in this recordData availability: The HadUK-Grid temperature data and station temperature data from the Met Office Integrated Data Archive System (MIDAS) that support the findings of this study are available from the CEDA Archive, http://archive.ceda.ac.uk. The CMIP5 simulated temperature data that support the findings of this study are available from the Earth System Grid Federation (ESGF) Archive, https://esgf.llnl.gov/.Code availability: IDL code used for the analysis is available upon request.As European heatwaves become more severe, summers in the United Kingdom (UK) are also getting warmer. The UK record temperature of 38.7 °C set in Cambridge in July 2019 prompts the question of whether exceeding 40 °C is now within reach. Here, we show how human influence is increasing the likelihood of exceeding 30, 35 and 40 °C locally. We utilise observations to relate local to UK mean extremes and apply the resulting relationships to climate model data in a risk-based attribution methodology. We find that temperatures above 35 °C are becoming increasingly common in the southeast, while by 2100 many areas in the north are likely to exceed 30 °C at least once per decade. Summers which see days above 40 °C somewhere in the UK have a return time of 100-300 years at present, but, without mitigating greenhouse gas emissions, this can decrease to 3.5 years by 2100.Met Office Hadley Centre Climate Programm

The effect of human land use change in the Hadley Centre attribution system

This is the final version. Available on open access from Wiley via the DOI in this recordAtmospheric Science Letters published by John Wiley & Sons Ltd on behalf of the Royal Meteorological Society. We have investigated the effects of land use on past climate change by means of a new 15-member ensemble of the HadGEM3-A-N216 model, usually used for event attribution studies. This ensemble runs from 1960 to 2013, and includes natural external climate forcings with the addition of human land use changes. It supports previously-existing ensembles, either with only natural forcings, or with all forcings (both anthropogenic and natural, including land use changes), in determining the contribution to the change in risk of extreme events made by land use change. We found a significant difference in near-surface air temperature trends over land, attributable to the effects of human land use. The main part of the signal derives from a relative cooling in Arctic regions which closely matches that of deforestation. This cooling appears to spread by polar amplification. A similar pattern of change is seen in latent heat flux trend, but significant rainfall change is almost entirely absent.Department for Business, Energy and Industrial Strategy, Met Office Hadley Centre Climate ProgrammeDepartment for Environment, Food and Rural AffairsEuropean CommissionUK‐China Research & Innovation Partnership Fund, Newton Fun

Human Influence on Seasonal Precipitation in Europe

This is the final version. Available on open access from the American Meteorological Society via the DOI in this recordData availability statement. CRU TS4.03 gridded precipitation data are available from the CEDA archive (https://archive.ceda.ac.uk/). Data from different experiments with the CMIP6 models used in the study can be downloaded from nodes of the ESGF (https://esgf.llnl.gov/).The response of precipitation to global warming is manifest in the strengthening of the hydrological cycle but can be complex on regional scales. Fingerprinting analyses have so far detected the effect of human influence on regional changes of precipitation extremes. Here we examine changes in seasonal precipitation in Europe since the beginning of the twentieth century and use an ensemble of new climate models to assess the role of different climatic forcings, both natural and anthropogenic. We find that human influence gives rise to a characteristic pattern of contrasting trends, with drier seasons in the Mediterranean basin and wetter over the rest of the continent. The trends are stronger in winter and weaker in summer, when drying is more spatially widespread. The anthropogenic signal is dominated by the response to greenhouse gas emissions, but is also weakened, to some extent, by the opposite effect of anthropogenic aerosols. Using a formal fingerprinting attribution methodology, we show here for the first time that the effects of the total anthropogenic forcing, and also of its greenhouse gas component, can be detected in observed changes of winter precipitation. Greenhouse gas emissions are also found to drive an increase in precipitation variability in all seasons. Moreover, the models suggest that human influence alters characteristics of seasonal extremes, with the frequency of high precipitation extremes increasing everywhere except the Mediterranean basin, where low precipitation extremes become more common. Regional attribution information contributes to the scientific basis that can help European citizens build their climate resilience.Met Office Hadley Centre Climate Programm

Detectable anthropogenic influence on changes in summer precipitation in China

This is the final version. Available from the American Meteorological Society via the DOI in this recordIn China, summer precipitation contributes a major part of the total precipitation amount in a year and has major impacts on society and human life. Whether any changes in summer precipitation are affected by external forcing on the climate system is an important issue. In this study, an optimal fingerprinting method was used to compare the observed changes of total, heavy, moderate, and light precipitation in summer derived from newly homogenized observation data with the simulations from multiple climate models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5). The results demonstrate that the anthropogenic forcing signal can be detected and separated from the natural forcing signal in the observed increase of seasonal accumulated precipitation amount for heavy precipitation in summer in China and eastern China (EC). The simulated changes in heavy precipitation are generally consistent with observed change in China but are underestimated in EC. When the changes in precipitation of different intensities are considered simultaneously, the human influence on simultaneous changes in moderate and light precipitation can be detected in China and EC in summer. Changes attributable to anthropogenic forcing explain most of the observed regional changes for all categories of summer precipitation, and natural forcing contributes little. In the future, with increasing anthropogenic influence, the attribution-constrained projection suggests that heavy precipitation in summer will increasemore than that from the model raw outputs. Society may therefore face a higher risk of heavy precipitation in the future.National Key R&D Program of ChinaNational Natural Science Foundation of ChinaUK‐China Research & Innovation Partnership Fund, Newton FundMet Office Hadley Centre Climate Programm

Using a game to engage stakeholders in extreme event attribution science

The impacts of weather and climate-related disasters are increasing, and climate change can exacerbate many disasters. Effectively communicating climate risk and integrating science into policy requires scientists and stakeholders to work together. But dialogue between scientists and policymakers can be challenging given the inherently multidimensional nature of the issues at stake when managing climate risks. Building on the growing use of serious games to create dialogue between stakeholders, we present a new game for policymakers called Climate Attribution Under Loss and Damage: Risking, Observing,co-Negotiating (CAULDRON). CAULDRON aims to communicate understanding of the science attributing extreme events to climate change in a memorable and compelling way, and create space for dialogue around policy decisions addressing changing risks and loss and damage from climate change. We describe the process of developing CAULDRON, and draw on observations of players and their feedback to demonstrate its potential to facilitate the interpretation of probabilistic climate information and the understanding of its relevance to informing policy. Scientists looking to engage with stakeholders can learn valuable lessons in adopting similar innovative approaches. The suitability of games depends on the policy context but, if used appropriately, experiential learning can drive co-produced understanding and meaningful dialogue

Detectable Anthropogenic Shift toward Heavy Precipitation over Eastern China

Changes in precipitation characteristics directly affect society through their impacts on drought and floods, hydro-dams, and urban drainage systems. Global warming increases the water holding capacity of the atmosphere and thus the risk of heavy precipitation. Here, daily precipitation records from over 700 Chinese stations from 1956 to 2005 are analyzed. The results show a significant shift from light to heavy precipitation over eastern China. An optimal fingerprinting analysis of simulations from 11 climate models driven by different combinations of historical anthropogenic (greenhouse gases, aerosols, land use, and ozone) and natural (volcanic and solar) forcings indicates that anthropogenic forcing on climate, including increases in greenhouse gases (GHGs), has had a detectable contribution to the observed shift toward heavy precipitation. Some evidence is found that anthropogenic aerosols (AAs) partially offset the effect of the GHG forcing, resulting in a weaker shift toward heavy precipitation in simulations that include the AA forcing than in simulations with only the GHG forcing. In addition to the thermodynamic mechanism, strengthened water vapor transport from the adjacent oceans and by midlatitude westerlies, resulting mainly from GHG-induced warming, also favors heavy precipitation over eastern China. Further GHG-induced warming is predicted to lead to an increasing shift toward heavy precipitation, leading to increased urban flooding and posing a significant challenge for mega-cities in China in the coming decades. Future reductions in AA emissions resulting from air pollution controls could exacerbate this tendency toward heavier precipitation

Characterising loss and damage from climate change

Policy-makers are creating mechanisms to help developing countries cope with loss and damage from climate change, but the negotiations are largely neglecting scientific questions about what the impacts of climate change actually are. Mitigation efforts have failed to prevent the continued increase of anthropogenic greenhouse gas (GHG) emissions. Adaptation is now unlikely to be sufficient to prevent negative impacts from current and future climate change1. In this context, vulnerable nations argue that existing frameworks to promote mitigation and adaptation are inadequate, and have called for a third international mechanism to deal with residual climate change impacts, or “loss and damage”2. In 2013, the United Nations Framework Convention on Climate Change (UNFCCC) responded to these calls and established the Warsaw International Mechanism (WIM) to address loss and damage from the impacts of climate change in developing countries3. An interim Executive Committee of party representatives has been set up, and is currently drafting a two-year workplan comprising meetings, reports, and expert groups; and aiming to enhance knowledge and understanding of loss and damage, strengthen dialogue among stakeholders, and promote enhanced action and support. Issues identified as priorities for the WIM thus far include: how to deal with non-economic losses, such as loss of life, livelihood, and cultural heritage; and linkages between loss and damage and patterns of migration and displacement2. In all this, one fundamental issue still demands our attention: which losses and damages are relevant to the WIM? What counts as loss and damage from climate change