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Dimethyl sulfide (DMS) is the largest source of natural sulfur in the atmosphere and undergoes oxidation reactions resulting in gas‐to‐particle conversion to form sulfate aerosol. Climate models typically use independent chemical schemes to simulate these processes, however, the sensitivity of sulfate aerosol to the schemes used by CMIP6 models has not been evaluated. Current climate models offer oversimplified DMS oxidation pathways, adding to the ambiguity surrounding the global sulfur burden. Here, we implemented seven DMS and sulfate chemistry schemes, six of which are from CMIP6 models, in an atmosphere‐only Earth system model. A large spread in aerosol optical depth (AOD) is simulated (0.077), almost twice the magnitude of the pre‐industrial to present‐day increase in AOD. Differences are largely driven by the inclusion of the nighttime DMS oxidation reaction with NO3, and in the number of aqueous phase sulfate reactions. Our analysis identifies the importance of DMS‐sulfate chemistry for simulating aerosols. We suggest that optimizing DMS/sulfur chemistry schemes is crucial for the accurate simulation of sulfate aerosols. Plain Language Summary: Dimethyl sulfide (DMS) is a sulfur‐bearing gas predominantly emitted from marine biological activity. DMS is the largest natural contributor to the global sulfur cycle, but its contribution is highly uncertain. Representing the complex chemical conversion of DMS to form natural sulfur atmospheric particles accurately in Earth System Models is difficult. Complex atmospheric chemistry is expensive to implement, therefore simplistic approaches to represent the chemistry are used. Here we examine the variability between different chemistry schemes. To achieve this, we employ a state‐of‐the‐art Earth System Model to compare seven simulations with differing sulfur‐related chemical reactions. We show that sulfate chemistry contributes to large uncertainties in aerosol and cloud formation. This work underscores the need to improve sulfur chemistry to improve the accuracy of cloud and aerosol projections in a warming world. Key Points: The simulated spread in aerosol optical depth and cloud droplet number concentration is more than twice as large as the change from pre‐industrial to present‐daySimulations with similar Dimethyl sulfide burdens have very different sulfate burdens driven by the different sulfate mechanisms/oxidation pathwaysConstraining the chemistry of atmospheric sulfur is critical to constrain aerosol‐cloud interactions [ABSTRACT FROM AUTHOR]

The biogeochemical formation of dimethyl sulfide (DMS) from the Southern Ocean is complex, dynamic, and driven by physical, chemical, and biological processes. Such processes, produced by marine biogenic activity, are the dominant source of sulfate aerosol over the Southern Ocean. Using an atmosphere-only configuration of the United Kingdom Earth System Model (UKESM1-AMIP), we performed eight 10-year simulations for the recent past (2009–2018) during austral summer. We tested the sensitivity of atmospheric DMS to four oceanic DMS datasets and three DMS transfer velocity parameterizations. One oceanic DMS dataset was developed here from satellite chlorophyll a. We find that the choice of oceanic DMS dataset has a larger influence on atmospheric DMS than the choice of DMS transfer velocity. Simulations with linear transfer velocity parameterizations show a more accurate representation of atmospheric DMS concentration than those using quadratic relationships. This work highlights that the oceanic DMS and DMS transfer velocity parameterizations currently used in climate models are poorly constrained for the Southern Ocean region. Simulations using oceanic DMS derived from satellite chlorophyll a data, and when combined with a recently developed linear transfer velocity parameterization for DMS, show better spatial variability than the UKESM1 configuration. We also demonstrate that capturing large-scale spatial variability can be more important than large-scale interannual variability. We recommend that models use a DMS transfer velocity parameterization that was developed specifically for DMS and improvements to oceanic DMS spatial variability. Such improvements may provide a more accurate process-based representation of oceanic and atmospheric DMS, and therefore sulfate aerosol, in the Southern Ocean region. [ABSTRACT FROM AUTHOR]

The biogeochemical behaviour of the Southern Ocean is complex and dynamic. The processes that affect this behaviour are highly dependent on physical, chemical, and biological constraints, which are poorly constrained in Earth System Models. We assess how emissions of dimethyl sulfide (DMS), a precursor of sulfate aerosol, change over the Southern Ocean when the chlorophyll-a distribution, which influences oceanic DMS production, is altered. Using a nudged configuration of the atmosphere-only United Kingdom Earth System Model, UKESM1-AMIP, we performed nine 10-year simulations using forcings representative of the period 2009–2018. Four different seawater DMS data sets are tested as input for these simulations. Three different DMS sea-to-air flux parameterizations are also explored. Our goal is to evaluate the changes in oceanic DMS, sea-to-air fluxes of DMS, and atmospheric DMS through these different simulations during austral summer. The mean spread across all the simulations with different oceanic DMS datasets, but the same sea-to-air flux parameterizations, is 112 % (3.3 to 6.9 TgS Yr−1). The mean spread in simulations using the same oceanic DMS dataset, but differing sea-to-air flux parameterisations is 50–60 % (2.9 to 4.7 TgS Yr−1). The choice of DMS emission parameterisation has a larger influence on atmospheric DMS than the choice of oceanic DMS source. We also find that linear relationships between wind and DMS flux generally compare better to observations than quadratic relationships. Simulations that implement a quadratic emission rate show on average 35 % higher DMS mixing ratios than the linear emission rates. Simulations using seawater DMS derived from satellite chlorophyll-a data in combination with a recently-developed flux parameterisation for DMS show the closest agreement with atmospheric DMS observations and are recommended to be included in future simulations. This work recommends for Earth System Models to include a sea-to-air parameterization that is appropriate for DMS, and for oceanic DMS datasets to include inter-annual variability based on observed marine biogenic activity. Such improvements will provide a more accurate process-based representation of oceanic and atmospheric DMS, and therefore sulfate aerosol, in the Southern Ocean region. [ABSTRACT FROM AUTHOR]

Many Coupled Model Intercomparison Project phase 6 (CMIP6) models have exhibited a substantial cold bias in the global mean surface temperature (GMST) in the latter part of the 20th century. An overly strong negative aerosol forcing has been suggested as a leading contributor to this bias. An updated configuration of UK Earth System Model (UKESM) version 1, UKESM1.1, has been developed with the aim of reducing the historical cold bias in this model. Changes implemented include an improved representation of SO2 dry deposition, along with several other smaller modifications to the aerosol scheme and a retuning of some uncertain parameters of the fully coupled Earth system model. The Diagnostic, Evaluation and Characterization of Klima (DECK) experiments, a six-member historical ensemble and a subset of future scenario simulations are completed. In addition, the total anthropogenic effective radiative forcing (ERF), its components and the effective and transient climate sensitivities are also computed. The UKESM1.1 preindustrial climate is warmer than UKESM1 by up to 0.75 K , and a significant improvement in the historical GMST record is simulated, with the magnitude of the cold bias reduced by over 50 %. The warmer climate increases ocean heat uptake in the Northern Hemisphere oceans and reduces Arctic sea ice, which is in better agreement with observations. Changes to the aerosol and related cloud properties are a driver of the improved GMST simulation despite only a modest reduction in the magnitude of the negative aerosol ERF (which increases by +0.08 Wm-2). The total anthropogenic ERF increases from 1.76 Wm-2 in UKESM1 to 1.84 Wm-2 in UKESM1.1. The effective climate sensitivity (5.27 K) and transient climate response (2.64 K) remain largely unchanged from UKESM1 (5.36 and 2.76 K respectively). [ABSTRACT FROM AUTHOR]

Many CMIP6 models exhibit a substantial cold bias in global mean surface temperature (GMST) in the latter part of the 20th century. An overly strong negative aerosol forcing has been suggested as a leading contributor to this bias. An updated configuration of UKESM1, UKESM1.1, has been developed with the aim of reducing the historical cold bias in this model. Changes implemented include an improved representation of SO2 dry deposition along with several other smaller modifications to the aerosol scheme and a retuning of some uncertain parameters of the fully coupled Earth System Model. The Diagnostic, Evaluation and Characterization of Klima (DECK) experiments, a 6-member historical ensemble and a subset of future scenario simulations are completed. In addition, the total anthropogenic effective radiative forcing (ERF), its components and the effective and transient climate sensitivities are also computed. The UKESM1.1 pre-industrial climate is warmer than UKESM1 by up to 0.75K and a significant improvement in the historical GMST record is simulated with the magnitude of the cold bias reduced by over 50%. The warmer climate increases ocean heat uptake in the northern hemisphere oceans and reduces Arctic sea ice in better agreement with observations. Changes to the aerosol and related cloud properties are the key drivers of the improved GMST simulation despite only a modest change in aerosol ERF (+0.08Wm-2). The total anthropogenic ERF increases from 1.76Wm-2 in UKESM1 to 1.84Wm-2 in UKESM1.1. The effective climate sensitivity (5.27K) and transient climate response (2.64K) remain largely unchanged from UKESM1 (5.36K and 2.76K respectively). [ABSTRACT FROM AUTHOR]

In this study we evaluate simulated surface SO2 and sulphate (SO42−) concentrations from the United Kingdom Earth System Model (UKESM1) against observations from ground based measurement networks in the USA and Europe for the period 1987 to 2014. We find that UKESM1 captures the historical trend for decreasing concentrations of atmospheric SO2 and SO42− in both Europe and the USA over the period 1987 to 2014. However, in the polluted regions of the eastern USA and Europe, UKESM1 over-predicts surface SO2 concentrations by a factor of 3, while under-predicting surface SO42− concentrations by 25–35 %. In the cleaner western USA, the model over-predicts both surface SO2 and SO42− concentrations by a factor of 12 and 1.5 respectively. We find that UKESM1’s bias in surface SO2 and SO42− concentrations is variable according to region and season. We also evaluate UKESM1 against total column SO2 from the Ozone Monitoring Instrument (OMI) using an updated data product. This comparison provides information about the model’s global performance, finding that UKESM1 over predicts total column SO2 over much of the globe, including the large source regions of India, China, the USA and Europe as well as over outflow regions. Finally, we assess the impact of a more realistic treatment of the model’s SO2 dry deposition parameterization. This change increases SO2 dry deposition to the land and ocean surfaces, thus reducing the atmospheric loading of SO2 and SO42− . In comparison with the ground-based and satellite observations, we find that the modified parameterization reduces the model’s over prediction of surface SO2 concentrations and total column SO2. Relative to the ground-based observations the simulated surface SO42− concentrations are also reduced, while the simulated SO2 dry deposition fluxes increase. [ABSTRACT FROM AUTHOR]

Quantifying forcings from anthropogenic perturbations to the Earth System (ES) is important for understanding changes in climate since the pre-industrial period. In this paper, we quantify and analyse a wide range of present-day (PD) anthropogenic climate forcings with the UK's Earth System Model (ESM), UKESM1, following the protocols defined by the Radiative Forcing Model Intercomparison Project (RFMIP) and the Aerosol and Chemistry Model Intercomparison Project (AerChemMIP). In particular, by quantifying effective radiative forcings (ERFs) that include rapid adjustments within a full ESM, it enables the role of various climate-chemistry-aerosol-cloud feedbacks to be quantified. Global mean ERFs are 1.83, 0.13, −0.33, and 0.93 W m−2 at the PD (Year 2014) relative to the pre-industrial (PI; Year 1850) for carbon dioxide, nitrous oxide, ozone-depleting substances, and methane, respectively. The PD total greenhouse gas ERF is 2.89 W m−2, larger than the sum of the individual GHG ERFs. UKESM1 has an aerosol forcing of −1.13 W m−2. A relatively strong negative forcing from aerosol-cloud interactions and a small negative instantaneous forcing from aerosol-radiation interactions are partially offset by a substantial forcing from black carbon absorption. Internal mixing and chemical interactions mean that neither the forcing from aerosol-radiation interactions nor aerosol-cloud interactions are linear, making the total aerosol ERF less than the sum of the individual speciated aerosol ERFs. Tropospheric ozone precursors, in addition to exerting a positive forcing due to ozone, lead to oxidant changes which in turn cause an indirect aerosol ERF, altering the sign of the net ERF from nitrogen oxide emissions. Together, aerosol and tropospheric ozone precursors (near-term climate forcers, NTCFs) exert a global mean ERF of −1.12 W m−2, mainly due to changes in the cloud radiative effect. There is also a negative PD ERF from land use (−0.32 W m−2). It is outside the range of previous estimates, and is most likely due to too strong an albedo response. In combination, the net anthropogenic ERF is potentially biased low (1.61 W m−2) relative to other estimates, due to the inclusion of non-linear feedbacks and ES interactions. By including feedbacks between greenhouse gases, stratospheric and tropospheric ozone, aerosols, and clouds, some of which act non-linearly, this work demonstrates the importance of ES interactions when quantifying climate forcing. It also suggests that rapid adjustments need to include chemical as well as physical adjustments to fully account for complex ES interactions. [ABSTRACT FROM AUTHOR]

Here we present a description of the UKCA StratTrop chemical mechanism which is used in the UKESM1 Earth System Model for CMIP6. The StratTrop chemical mechanism is a merger of previously well evaluated tropospheric and stratospheric mechanisms and we provide results from a series of bespoke integrations to assess the overall performance of the model. We find that the StratTrop scheme performs well when compared to a wide array of observations. The analysis we present here focuses on key components of atmospheric composition, namely the performance of the model to simulate ozone in the stratosphere and troposphere and constituents that are important for ozone in these regions. We find that the results obtained from the use of the StratTrop mechanism are sensitive to the host model; simulations with the same chemical mechanism run in an earlier version of the MetUM host model show a range of sensitivity to emissions that the current model does not fall within. Whilst the general model performance is suitable for use in the UKESM1 CMIP6 integrations, we note some shortcomings in the scheme that future targeted studies will address. [ABSTRACT FROM AUTHOR]

Particulates emitted from the ocean's surface such as sea salt and byproducts of marine biogenic activity form atmospheric aerosols. Aerosols are important for climate change because they have offset some of the historical warming caused by greenhouse gases. Aerosols are also significant for human health: they are small enough to be inhaled and contribute to respiratory problems and other illnesses. Marine aerosol is the primary source of natural aerosol present in urban areas of Aotearoa New Zealand and, as part of the natural aerosol background, cannot be managed. Here, we review the production and presence of marine aerosols in New Zealand's air, and the implications for human health and climate change. Because marine aerosol is sensitive to physical changes in climate such as sea surface temperature and winds, production is likely to be affected by climate change. Overall, marine aerosol is unlikely to become a smaller contributor to urban atmospheric aerosol loading in New Zealand towns and cities under future climate change scenarios. Continued assessment of anthropogenic aerosols will be necessary to ensure that air quality targets are met. [ABSTRACT FROM AUTHOR]