Aerosol effects on cloud properties are notoriously difficult to disentangle from variations driven by meteorological factors. Here, a machine learning model is trained on reanalysis data and satellite retrievals to predict cloud microphysical properties, as a way to illustrate the relative importance of meteorology and aerosol, respectively, on cloud properties. It is found that cloud droplet effective radius can be predicted with some skill from only meteorological information, including estimated air mass origin and cloud top height. For ten geographical regions the mean coefficient of determination is 0.41 and normalised root-mean square error 24%. The machine learning model thereby performs better than a reference linear regression model, and a model predicting the climatological mean. A gradient boosting regression performs on par with a neural network regression model. Adding aerosol information as input to the model improves its skill somewhat, but the difference is small and the direction of the influence of changing aerosol burden on cloud droplet effective radius is not consistent across regions, and thereby also not always consistent with what is expected from cloud brightening.

Anthropogenic aerosol emissions are expected to change rapidly over the coming decades, driving strong, spatially complex trends in temperature, hydroclimate, and extreme events both near and far from emission sources. Under-resourced, highly populated regions often bear the brunt of aerosols' climate and air quality effects, amplifying risk through heightened exposure and vulnerability. However, many policy-facing evaluations of near-term climate risk, including those in the latest Intergovernmental Panel on Climate Change assessment report, underrepresent aerosols' complex and regionally diverse climate effects, reducing them to a globally averaged offset to greenhouse gas warming. We argue that this constitutes a major missing element in society's ability to prepare for future climate change. We outline a pathway towards progress and call for greater interaction between the aerosol research, impact modeling, scenario development, and risk assessment communities.

Philosophers argue that many choices in science are influenced by values or have value-implications, ranging from the preference for some research method’s qualities to ethical estimation of the consequences of error. Based on the argument that awareness of values in the scientific process is a necessary first step to both avoid bias and attune science best to the needs of society, an analysis of the role of values in the physical climate science production process is provided. Model-based assessment of climate sensitivity is taken as an illustrative example; climate sensitivity is useful here because of its key role in climate science and relevance for policy, by having been the subject of several assessments over the past decades including a recent shift in assessment method, and because it enables insights that apply to numerous other aspects of climate science. It is found that value-judgements are relevant at every step of the model-based assessment process, with a differentiated role of non-epistemic values across the steps, impacting the assessment in various ways. Scrutiny of current philosophical norms for value-management highlights the need for those norms to be re-worked for broader applicability to climate science. Recent development in climate science turning away from direct use of models for climate sensitivity assessment also gives the opportunity to start investigating the role of values in alternative assessment methods, highlighting similarities and differences in terms of the role of values that encourage further study. 

There is much debate on how social values should influence scientific research. However, the question of practical applicability of philosophers’ normative proposals has received less attention. Here, we test the attainability of Matthew J. Brown’s (2020) Moral Imagination ideal (MI ideal), which aims to help scientists to make warranted value-judgements through reflecting on goals, options, values, and stakeholders of research. Here, the tools of the MI ideal are applied to a climate modelling setting, where researchers are developing aerosol-cloud interaction (ACI) parametrizations in an Earth System Model with the broader goal of improving climate sensitivity estimation. After the identification of minor obstacles to applying the MI ideal, we propose two ways to increase its applicability. First, its tools should be accompanied with more concrete guidance for identifying how social values enter more technical decisions in scientific research. Second, since research projects can have multiple goals, examining the alignment between broader societal aims of research and more technical goals should be part of the tools of the MI ideal.

There is a large range of future aerosol emissions scenarios explored in the Shared Socioeconomic Pathways (SSPs), with plausible pathways spanning a range of possibilities from large global reductions in emissions by 2050 to moderate global increases over the same period. Diversity in emissions across the pathways is particularly large over Asia. Rapid reductions in anthropogenic aerosol and precursor emissions between the present day and the 2050s lead to enhanced increases in global and Asian summer monsoon precipitation relative to scenarios with weak air quality policies. However, the effects of aerosol reductions do not persist to the end of the 21st century for precipitation, when instead the response to greenhouse gases dominates differences across the SSPs. The relative magnitude and spatial distribution of aerosol changes are particularly important for South Asian summer monsoon precipitation changes. Precipitation increases here are initially suppressed in SSPs 2-4.5, 3-7.0, and 5-8.5 relative to SSP1-1.9 when the impact of remote emission decreases is counteracted by continued increases in South Asian emissions.

To understand whether high temperatures and temperature extremes are important for climate change adaptation in Scotland, we place the 2018 heatwave in the context of past, present, and future climate, and provide a rapid but comprehensive impact analysis. The observed hottest day (d), 5 d, and 30 d period of 2018 and the 5 d period with the warmest nights had return periods of 5-15 years for 1950-2018. The warmest night and the maximum 30 d average nighttime temperature were more unusual with return periods of >30 years. Anthropogenic climate change since 1850 has made all these high-temperature extremes more likely. Higher risk ratios are found for experiments from the CMIP6-generation global climate model HadGEM3-GA6 compared to those from the very-large ensemble system weather@home. Between them, the best estimates of the risk ratios for daytime extremes range between 1.2-2.4, 1.2-2.3, and 1.4-4.0 for the 1, 5, and 30 d averages. For the corresponding nighttime extremes, the values are higher and the ranges wider (1.5- >50, 1.5-5.5, and 1.6- >50). The short-period nighttime extremes were more likely in 2018 than in 2017, suggesting a contribution from year-to-year climate variability to the risk enhancement of extreme temperatures due to anthropogenic effects. Climate projections suggest further substantial increases in the likelihood of 2018 temperatures between now and 2050, and that towards the end of the century every summer might be as hot as 2018. Major negative impacts occurred, especially on rural sectors, while transport and water infrastructure alleviated most impacts by implementing costly special measures. Overall, Scotland could cope with the impacts of the 2018 heatwave. However, given the likelihood increase of high-temperature extremes, uncertainty about consequences of even higher temperatures and/or repeated heatwaves, and substantial costs of preventing negative impacts, we conclude that despite its cool climate, high-temperature extremes are important to consider for climate change adaptation in Scotland.

Substantial warming occurred across North America, Europe and the Arctic over the early twentieth century(1), including an increase in global drought(2), that was partially forced by rising greenhouse gases (GHGs)(3). The period included the 1930s Dust Bowl drought(4-7) across North America's Great Plains that caused widespread crop failures(4,8), large dust storms(9) and considerable out-migration(10). This coincided with the central United States experiencing its hottest summers of the twentieth century(11,12) in 1934 and 1936, with over 40 heatwave days and maximum temperatures surpassing 44 degrees C at some locations(13,14). Here we use a large-ensemble regional modelling framework to show that GHG increases caused slightly enhanced heatwave activity over the eastern United States during 1934 and 1936. Instead of asking how a present-day heatwave would behave in a world without climate warming, we ask how these 1930s heatwaves would behave with present-day GHGs. Heatwave activity in similarly rare events would be much larger under today's atmospheric GHG forcing and the return period of a 1-in-100-year heatwave summer (as observed in 1936) would be reduced to about 1-in-40 years. A key driver of the increasing heatwave activity and intensity is reduced evaporative cooling and increased sensible heating during dry springs and summers. The United States experienced two of its hottest recorded summers in 1934 and 1936, amplified by drier soils associated with the Dust Bowl drought. A large regional climate model ensemble estimates present-day GHGs would cause similarly extreme, 1-in-100-year heatwaves to occur about every 40 years.

The effects of increased North American sulphate aerosol emissions on the climate of Mexico and the United States (U.S.) during 1950-1975 are investigated by using two sets of transient coupled experiments with the Community Earth System Model, one with historically evolving emissions, and a second one where North American SO2 emissions are kept at their pre-industrial levels. The 1950-1975 increase in North American sulphate aerosols is found to have regional and remote impact. Over central U.S. and northern Mexico, the strengthening and westward expansion of the North Atlantic Subtropical High and subsequent intensification of the low-level easterlies, along with local aerosol interactions with radiation and clouds, cause a cooling trend and enhance precipitation. The interaction between the enhanced moisture transport across the Gulf of Mexico and the elevated topography of central Mexico favours positive rainfall on the Atlantic side while suppressing it on the Pacific side. These continental anomalies are embedded in a hemispheric-wide upper-tropospheric teleconnection pattern over the mid-latitudes, extending from the Pacific to the Atlantic basin. Details of the underlying mechanisms-in particular the prominent role of dynamical adjustments-are provided. With SO2 emissions considerably reduced in the U.S., and the expectation of a continued global decline throughout the 21st century, this study sheds light upon possible ongoing and future regional climate responses to changes in anthropogenic forcing.

Anthropogenic climate change calls for rapid and enormous cuts in emissions of CO2 and other greenhouse gases to mitigate future impacts. Even with these, however, many changes will continue to occur over the next 20-30 years adding to those already observed. Adaptation is crucial and urgent, but identifying strategies is complex and requires dialogue and cooperation among stakeholders, especially for infrastructure that exhibits interdependent risks in that failure in one type may impact others. A serious game was codeveloped with infrastructure operators to communicate climate projections and climate hazards to them; identify potential interdependencies, cascading impacts, cumulative effects, and vulnerability hot spots; and engage them to improve cooperation and enable a shared understanding of cross-cutting climate risks and interdependencies. In the game, players provide present-day infrastructure services in the Inverclyde district, Scotland, as they experience a plausible decade of 2050s weather characterized by a sequence of hazard events. This sequence was extracted from climate model projections to ensure scientific plausibility. The infrastructure operators were responsible for drinking water and gas supplies, road and rail transport, wastewater treatment, and civil infrastructure. When playing the game the participating U.K. infrastructure providers felt that although there were challenges, they could cope with 2050s climate change. None of the projected hazard events were anticipated to cause catastrophic impact cascades on infrastructure. The game was positively received, and the study suggests it is a useful tool to both communicate climate hazards and explore potential interdependent risks by bringing together stakeholders' individual expertise in an engaging way.