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The 1257 CE eruption of Mount Samalas (Indonesia) is the source of the largest stratospheric injection of volcanic gases in the Common Era. Sulfur dioxide emissions produced sulfate aerosols that cooled Earth's climate with a range of impacts on society. The coemission of halogenated species has also been speculated to have led to wide-scale ozone depletion. Here we present simulations from HadGEM3-ES, a fully coupled Earth system model, with interactive atmospheric chemistry and a microphysical treatment of sulfate aerosol, used to assess the chemical and climate impacts from the injection of sulfur and halogen species into the stratosphere as a result of the Mt. Samalas eruption. While our model simulations support a surface air temperature response to the eruption of the order of -1°C, performing well against multiple reconstructions of surface temperature from tree-ring records, we find little evidence to support significant injections of halogens into the stratosphere. Including modest fractions of the halogen emissions reported from Mt. Samalas leads to significant impacts on the composition of the atmosphere and on surface temperature. As little as 20% of the halogen inventory from Mt. Samalas reaching the stratosphere would result in catastrophic ozone depletion, extending the surface cooling caused by the eruption. However, based on available proxy records of surface temperature changes, our model results support only very minor fractions (1%) of the halogen inventory reaching the stratosphere and suggest that further constraints are needed to fully resolve the issue.

The amount of dioxygen (O2) in the atmosphere may have varied from as little as 10 % to as high as 35 % during the Phanerozoic eon (541 Ma–Present). These changes in the amount of O2 are large enough to have lead to changes in atmospheric mass, which may alter the radiative budget of the atmosphere, leading to this mechanism being invoked to explain discrepancies between climate model simulations and proxy reconstructions of past climates. Here we present the first fully 3D numerical model simulations to investigate the climate impacts of changes in O2 during different climate states using the HadGEM3-AO and HadCM3-BL models. We show that simulations with an increase in O2 content result in increased global mean surface air temperature under conditions of a pre-industrial Holocene climate state, in agreement with idealised 1D and 2D modelling studies. We demonstrate the mechanism behind the warming is complex and involves trade-off between a number of factors. Increasing atmospheric O2 leads to a reduction in incident shortwave radiation at Earth's surface due to Rayleigh scattering, a cooling effect. However, there is a competing warming effect due to an increase in the pressure broadening of greenhouse gas absorption lines and dynamical feedbacks, which alter the meridional heat transport of the ocean, warming polar regions and cooling tropical regions. Case studies from past climates are investigated using HadCM3-BL which show that in the warmest climate states, increasing oxygen may lead to a temperature decrease, as the equilibrium climate sensitivity is lower. For the Maastrichtian (72.1–66.0 Ma), increasing oxygen content leads to a better agreement with proxy reconstructions of surface temperature at that time irrespective of the carbon dioxide content. For the Asselian (298.9–295.0 Ma), increasing oxygen content leads to a warmer global mean surface temperature and reduced carbon storage on land, suggesting that high oxygen content may have been a contributing factor in preventing a Snowball Earth during this period of the early Permian. These climate model simulations reconcile the surface temperature response to oxygen content changes across the hierarchy of model complexity and highlight the broad range of Earth system feedbacks that need to be accounted for when considering the climate response to changes in atmospheric oxygen content.

Here we present results from an evaluation of model simulations from the International Hemispheric Transport of Air Pollution Phase II (HTAPII) and Chemistry Climate Model Initiative (CCMI) model inter-comparison projects against a comprehensive series of ground based, aircraft and satellite observations of ozone mixing ratios made at various locations across India. The study focuses on the recent past (observations from 2008–2013, models from 2008–2010) as this is most pertinent to understanding the health impacts of ozone. To our understanding this is the most comprehensive evaluation of these models' simulations of ozone across the Indian sub-continent to date. This study highlights some significant successes and challenges that the models face in representing the oxidative chemistry of the region. The multi-model range in area weighted surface ozone over the Indian subcontinent is 37.26–56.11 ppb, whilst the population weighted range is 41.38–57.5 ppb. When compared against surface observations from the Modelling Atmospheric Pollution and Networking (MAPAN) network of eight semi-urban monitoring sites spread across India, we find that the models tend to simulate higher ozone than that which is observed. However, observations of NOx and CO tend to be much higher than modelled mixing-ratios, suggesting that the underlying emissions used in the models do not characterise these regions accurately and/or that the resolution of the models is not adequate to simulate the photo-chemical environment about these surface observations. Empirical Orthogonal Function (EOF) analysis is used in order to identify the extent to which the models agree with regards to the spatio-temporal distribution of the tropospheric ozone column, derived using OMI-MLS observations. We show that whilst the models agree with the spatial pattern of the first EOF of observed tropospheric ozone column, most of the models simulate a peak in the first EOF seasonal cycle represented by principle component 1, which is later than the observed peak . This suggest a widespread systematic bias in the timing of emissions or some other unknown seasonal process. In addition to evaluating modelled ozone mixing ratios, we explore modelled emissions of NOx, CO, VOCs, and the ozone response to the emissions. We find a high degree of variation in emissions from non-anthropogenic sources (e.g. lightning NOx and biomass burning CO) between models. Total emissions of NOx and CO over India vary more between different models in the same MIP than the same model used in different MIPs, making it impossible to diagnose whether differences in modelled ozone are due to emissions or model processes. We therefore recommend targeted experiments to pinpoint the exact causes of discrepancies between modelled and observed ozone and ozone precursors for this region. To this end, a higher density of long term monitoring sites measuring not only ozone but also ozone precursors including speciated VOCs, located in more rural regions of the Indian sub-continent, would enable improvements in assessing the biases in models run at the resolution found in HTAPII and CCMI.