ALBERT

Description: Anthropogenic aerosols are a key driver of changes in summer monsoon precipitation in the Northern Hemisphere during the 20th century. Here we apply detection and attribution methods to investigate causes of change in the West African and South Asian monsoons separately and identify the aerosol source regions that are most important for explaining the observed changes during 1920–2005. Historical simulations with the GFDL-CM3 model are used to derive fingerprints of aerosol forcing from different regions. For West Africa, remote aerosol emissions from North America and Europe (NAEU) are essential in order to detect the anthropogenic signal in observed monsoon precipitation changes. The changes are significantly underestimated in the model, however. While natural (volcanic) forcing seems to also play a role, the dominant contribution is found to come from aerosol-induced changes in the interhemispheric temperature gradient and associated meridional shifts of the Intertropical Convergence Zone. For South Asia, in contrast, changes in observed monsoon precipitation cannot be explained without local emissions. Here the findings show a weakening of the monsoon circulation, driven by the increase of remote NAEU aerosol emissions until 1975, and since then by the increase in local emissions offsetting the decrease of NAEU emissions. The results show that the aerosol forcing from individual emission regions is strong enough to be detected over internal variability. They also underscore the importance of the spatial pattern of global-aerosol emissions, which is likely to continue to change throughout the expected near-future decline in global emissions. ©2018. The Authors.

Description: The extent and mechanisms of the Atlantic response to the historical (1850–1975) increase of sulphate aerosol emissions from North America and Europe as simulated in eight-member ensemble experiments with the coupled Community Earth System Model (CESM1)-Community Atmosphere Model version 5.3 are contrasted. The results show that aerosols from either source cause a long-term cooling of North Atlantic sea surface temperatures, with the patterns a combination of atmospheric aerosol effects and an aerosol-induced strengthening of the Atlantic Meridional Overturning Circulation. The response to North American emissions is larger since prevailing winds cause wider aerosol spread over the Atlantic, collocated with climatological cloud cover. The Intertropical Convergence Zone shifts southward affecting tropical precipitation globally. The simulated (multi)decadal components of sea surface temperature and Atlantic Meridional Overturning Circulation variability are furthermore primarily externally forced. The analysis provides novel insights into the mechanisms of aerosol impact on the Atlantic. It suggests that projected further emission reductions will lead to opposite changes. ©2018. American Geophysical Union. All Rights Reserved.

Description: 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.

Description: 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.

Description: 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.

Description: Changes in anthropogenic aerosol emissions have strongly contributed to global and regional trends in temperature, precipitation, and other climate characteristics and have been one of the dominant drivers of decadal trends in Asian and African precipitation. These and other influences on regional climate from changes in aerosol emissions are expected to continue and potentially strengthen in the coming decades. However, a combination of large uncertainties in emission pathways, radiative forcing, and the dynamical response to forcing makes anthropogenic aerosol a key factor in the spread of near-term climate projections, particularly on regional scales, and therefore an important one to constrain. For example, in terms of future emission pathways, the uncertainty in future global aerosol and precursor gas emissions by 2050 is as large as the total increase in emissions since 1850. In terms of aerosol effective radiative forcing, which remains the largest source of uncertainty in future climate change projections, CMIP6 models span a factor of 5, from −0.3 to −1.5 W m−2. Both of these sources of uncertainty are exacerbated on regional scales. The Regional Aerosol Model Intercomparison Project (RAMIP) will deliver experiments designed to quantify the role of regional aerosol emissions changes in near-term projections. This is unlike any prior MIP, where the focus has been on changes in global emissions and/or very idealised aerosol experiments. Perturbing regional emissions makes RAMIP novel from a scientific standpoint and links the intended analyses more directly to mitigation and adaptation policy issues. From a science perspective, there is limited information on how realistic regional aerosol emissions impact local as well as remote climate conditions. Here, RAMIP will enable an evaluation of the full range of potential influences of realistic and regionally varied aerosol emission changes on near-future climate. From the policy perspective, RAMIP addresses the burning question of how local and remote decisions affecting emissions of aerosols influence climate change in any given region. Here, RAMIP will provide the information needed to make direct links between regional climate policies and regional climate change. RAMIP experiments are designed to explore sensitivities to aerosol type and location and provide improved constraints on uncertainties driven by aerosol radiative forcing and the dynamical response to aerosol changes. The core experiments will assess the effects of differences in future global and regional (Africa and the Middle East, East Asia, North America and Europe, and South Asia) aerosol emission trajectories through 2051, while optional experiments will test the nonlinear effects of varying emission locations and aerosol types along this future trajectory. All experiments are based on the shared socioeconomic pathways and are intended to be performed with 6th Climate Model Intercomparison Project (CMIP6) generation models, initialised from the CMIP6 historical experiments, to facilitate comparisons with existing projections. Requested outputs will enable the analysis of the role of aerosol in near-future changes in, for example, temperature and precipitation means and extremes, storms, and air quality.

Description: 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 0.3813 and normalised root-mean square error 25%. 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.