The turbulent future brings a breath of fresh air.

Ventilation of health hazardous aerosol pollution within the planetary boundary layer (PBL) - the lowest layer of the atmosphere - is dependent upon turbulent mixing, which again is closely linked to the height of the PBL. Here we show that emissions of both CO2 and absorbing aerosols such as black carbon influence the number of severe air pollution episodes through impacts on turbulence and PBL height. While absorbing aerosols cause increased boundary layer stability and reduced turbulence through atmospheric heating, CO2 has the opposite effect over land through surface warming. In future scenarios with increasing CO2 concentrations and reduced aerosol emissions, we find that around 10% of the world's population currently living in regions with high pollution levels are likely to experience a particularly strong increase in turbulence and PBL height, and thus a reduction in intense pollution events. Our results highlight how these boundary layer processes provide an added positive impact of black carbon mitigation to human health.

Scientific data from precipitation driver response model intercomparison project.

This data descriptor reports the main scientific values from General Circulation Models (GCMs) in the Precipitation Driver and Response Model Intercomparison Project (PDRMIP). The purpose of the GCM simulations has been to enhance the scientific understanding of how changes in greenhouse gases, aerosols, and incoming solar radiation perturb the Earth's radiation balance and its climate response in terms of changes in temperature and precipitation. Here we provide global and annual mean results for a large set of coupled atmospheric-ocean GCM simulations and a description of how to easily extract files from the dataset. The simulations consist of single idealized perturbations to the climate system and have been shown to achieve important insight in complex climate simulations. We therefore expect this data set to be valuable and highly used to understand simulations from complex GCMs and Earth System Models for various phases of the Coupled Model Intercomparison Project.

Aerosol Absorption: Progress Towards Global and Regional Constraints.

PURPOSE OF REVIEW: Some aerosols absorb solar radiation, altering cloud properties, atmospheric stability and circulation dynamics, and the water cycle. Here we review recent progress towards global and regional constraints on aerosol absorption from observations and modeling, considering physical properties and combined approaches crucial for understanding the total (natural and anthropogenic) influences of aerosols on the climate. RECENT FINDINGS: We emphasize developments in black carbon absorption alteration due to coating and ageing, brown carbon characterization, dust composition, absorbing aerosol above cloud, source modeling and size distributions, and validation of high-resolution modeling against a range of observations. SUMMARY: Both observations and modeling of total aerosol absorption, absorbing aerosol optical depths and single scattering albedo, as well as the vertical distribution of atmospheric absorption, still suffer from uncertainties and unknowns significant for climate applications. We offer a roadmap of developments needed to bring the field substantially forward.

PDRMIP: A Precipitation Driver and Response Model Intercomparison Project, Protocol and preliminary results.

As the global temperature increases with changing climate, precipitation rates and patterns are affected through a wide range of physical mechanisms. The globally averaged intensity of extreme precipitation also changes more rapidly than the globally averaged precipitation rate. While some aspects of the regional variation in precipitation predicted by climate models appear robust, there is still a large degree of inter-model differences unaccounted for. Individual drivers of climate change initially alter the energy budget of the atmosphere leading to distinct rapid adjustments involving changes in precipitation. Differences in how these rapid adjustment processes manifest themselves within models are likely to explain a large fraction of the present model spread and needs better quantifications to improve precipitation predictions. Here, we introduce the Precipitation Driver and Response Model Intercomparison Project (PDRMIP), where a set of idealized experiments designed to understand the role of different climate forcing mechanisms were performed by a large set of climate models. PDRMIP focuses on understanding how precipitation changes relating to rapid adjustments and slower responses to climate forcings are represented across models. Initial results show that rapid adjustments account for large regional differences in hydrological sensitivity across multiple drivers. The PDRMIP results are expected to dramatically improve our understanding of the causes of the present diversity in future climate projections.