Quantifying uncertainty in aggregated climate change risk assessments.

High-level assessments of climate change impacts aggregate multiple perils into a common framework. This requires incorporating multiple dimensions of uncertainty. Here we propose a methodology to transparently assess these uncertainties within the 'Reasons for Concern' framework, using extreme heat as a case study. We quantitatively discriminate multiple dimensions of uncertainty, including future vulnerability and exposure to changing climate hazards. High risks from extreme heat materialise after 1.5-2 °C and very high risks between 2-3.5 °C of warming. Risks emerge earlier if global assessments were based on national risk thresholds, underscoring the need for stringent mitigation to limit future extreme heat risks.

Climate change as a driver of food insecurity in the 2007 Lesotho-South Africa drought.

Climate-induced food production shocks, like droughts, can cause food shortages and price spikes, leading to food insecurity. In 2007, a synchronous crop failure in Lesotho and South Africa-Lesotho's sole trading partner-led to a period of severe food insecurity in Lesotho. Here, we use extreme event attribution to assess the role of climate change in exacerbating this drought, going on to evaluate sensitivity of synchronous crop failures to climate change and its implications for food security in Lesotho. Climate change was found to be a critical driver that led to the 2007 crisis in Lesotho, aggravating an ongoing decline in food production in the country. We show how a fragile agricultural system in combination with a large trade-dependency on a climatically connected trading partner can lead to a nonlinear response to climate change, which is essential information for building a climate-resilient food-supply system now and in the future.

Using Detection And Attribution To Quantify How Climate Change Is Affecting Health.

The question of whether, how, and to what extent climate change is affecting health is central to many climate and health studies. We describe a set of formal methods, termed detection and attribution, used by climatologists to determine whether a climate trend or extreme event has changed and to estimate the extent to which climate change influenced that change. We discuss events where changing weather patterns were attributed to climate change and extend these analyses to include health impacts from heat waves in 2018 and 2019 in Europe and Japan, and we show how such impact attribution could be applied to melting ice roads in the Arctic. Documenting the causal chain from emissions of greenhouse gases to observed human health outcomes is important input into risk assessments that prioritize health system preparedness and response interventions and into financial investments and communication about potential risk to policy makers and to the public.

Ocean and land forcing of the record-breaking Dust Bowl heatwaves across central United States.

The severe drought of the 1930s Dust Bowl decade coincided with record-breaking summer heatwaves that contributed to the socio-economic and ecological disaster over North America's Great Plains. It remains unresolved to what extent these exceptional heatwaves, hotter than in historically forced coupled climate model simulations, were forced by sea surface temperatures (SSTs) and exacerbated through human-induced deterioration of land cover. Here we show, using an atmospheric-only model, that anomalously warm North Atlantic SSTs enhance heatwave activity through an association with drier spring conditions resulting from weaker moisture transport. Model devegetation simulations, that represent the wide-spread exposure of bare soil in the 1930s, suggest human activity fueled stronger and more frequent heatwaves through greater evaporative drying in the warmer months. This study highlights the potential for the amplification of naturally occurring extreme events like droughts by vegetation feedbacks to create more extreme heatwaves in a warmer world.

Ensemble of European regional climate simulations for the winter of 2013 and 2014 from HadAM3P-RM3P.

Large data sets used to study the impact of anthropogenic climate change on the 2013/14 floods in the UK are provided. The data consist of perturbed initial conditions simulations using the Weather@Home regional climate modelling framework. Two different base conditions, Actual, including atmospheric conditions (anthropogenic greenhouse gases and human induced aerosols) as at present and Natural, with these forcings all removed are available. The data set is made up of 13 different ensembles (2 actual and 11 natural) with each having more than 7500 members. The data is available as NetCDF V3 files representing monthly data within the period of interest (1st Dec 2013 to 15th February 2014) for both a specified European region at a 50 km horizontal resolution and globally at N96 resolution. The data is stored within the UK Natural and Environmental Research Council Centre for Environmental Data Analysis repository.

Attribution of extreme weather and climate-related events.

Extreme weather and climate-related events occur in a particular place, by definition, infrequently. It is therefore challenging to detect systematic changes in their occurrence given the relative shortness of observational records. However, there is a clear interest from outside the climate science community in the extent to which recent damaging extreme events can be linked to human-induced climate change or natural climate variability. Event attribution studies seek to determine to what extent anthropogenic climate change has altered the probability or magnitude of particular events. They have shown clear evidence for human influence having increased the probability of many extremely warm seasonal temperatures and reduced the probability of extremely cold seasonal temperatures in many parts of the world. The evidence for human influence on the probability of extreme precipitation events, droughts, and storms is more mixed. Although the science of event attribution has developed rapidly in recent years, geographical coverage of events remains patchy and based on the interests and capabilities of individual research groups. The development of operational event attribution would allow a more timely and methodical production of attribution assessments than currently obtained on an ad hoc basis. For event attribution assessments to be most useful, remaining scientific uncertainties need to be robustly assessed and the results clearly communicated. This requires the continuing development of methodologies to assess the reliability of event attribution results and further work to understand the potential utility of event attribution for stakeholder groups and decision makers. WIREs Clim Change 2016, 7:23-41. doi: 10.1002/wcc.380 For further resources related to this article, please visit the WIREs website.

Attribution of changes in precipitation patterns in African rainforests.

Tropical rainforests in Africa are one of the most under-researched regions in the world, but research in the Amazonian rainforest suggests potential vulnerability to climate change. Using the large ensemble of Atmosphere-only general circulation model (AGCM) simulations within the weather@home project, statistics of precipitation in the dry season of the Congo Basin rainforest are analysed. By validating the model simulation against observations, we could identify a good model performance for the June, July, August (JJA) dry season, but this result does need to be taken with caution as observed data are of poor quality. Additional validation methods have been used to investigate the applicability of probabilistic event attribution analysis from large model ensembles to a tropical region, in this case the Congo Basin. These methods corroborate the confidence in the model, leading us to believe the attribution result to be robust. That is, that there are no significant changes in the risk of low precipitation extremes during this dry season (JJA) precipitation in the Congo Basin. Results for the December, January, February dry season are less clear. The study highlights that attribution analysis has the potential to provide valuable scientific evidence of recent or anticipated climatological changes, especially in regions with sparse observational data and unclear projections of future changes. However, the strong influence of sea surface temperature teleconnection patterns on tropical precipitation provides more challenges in the set up of attribution studies than midlatitude rainfall.