Strong constraints on aerosol-cloud interactions from volcanic eruptions.

Aerosols have a potentially large effect on climate, particularly through their interactions with clouds, but the magnitude of this effect is highly uncertain. Large volcanic eruptions produce sulfur dioxide, which in turn produces aerosols; these eruptions thus represent a natural experiment through which to quantify aerosol-cloud interactions. Here we show that the massive 2014-2015 fissure eruption in Holuhraun, Iceland, reduced the size of liquid cloud droplets-consistent with expectations-but had no discernible effect on other cloud properties. The reduction in droplet size led to cloud brightening and global-mean radiative forcing of around -0.2 watts per square metre for September to October 2014. Changes in cloud amount or cloud liquid water path, however, were undetectable, indicating that these indirect effects, and cloud systems in general, are well buffered against aerosol changes. This result will reduce uncertainties in future climate projections, because we are now able to reject results from climate models with an excessive liquid-water-path response

Description and evaluation of aerosol in UKESM1 and HadGEM3-GC3.1 CMIP6 historical simulations

We document and evaluate the aerosol schemes as implemented in the physical and Earth system models, HadGEM3-GC3.1 (GC3.1) and UKESM1, which are contributing to the 6th Coupled Model Intercomparison Project (CMIP6). The simulation of aerosols in the present-day period of the historical ensemble of these models is evaluated against a range of observations. Updates to the aerosol microphysics scheme are documented as well as differences in the aerosol representation between the physical and Earth system configurations. The additional Earth-system interactions included in UKESM1 leads to differences in the emissions of natural aerosol sources such as dimethyl sulfide, mineral dust and organic aerosol and subsequent evolution of these species in the model. UKESM1 also includes a stratospheric-tropospheric chemistry scheme which is fully coupled to the aerosol scheme, while GC3.1 employs a simplified aerosol chemistry mechanism driven by prescribed monthly climatologies of the relevant oxidants. Overall, the simulated speciated aerosol mass concentrations compare reasonably well with observations. Both models capture the negative trend in sulfate aerosol concentrations over Europe and the eastern United States of America (US) although the models tend to underestimate the sulfate concentrations in both regions. Interactive emissions of biogenic volatile organic compounds in UKESM1 lead to an improved agreement of organic aerosol over the US. Simulated dust burdens are similar in both models despite a 2-fold difference in dust emissions. Aerosol optical depth is biased low in dust source and outflow regions but performs well in other regions compared to a number of satellite and ground-based retrievals of aerosol optical depth. Simulated aerosol number concentrations are generally within a factor of 2 of the observations with both models tending to overestimate number concentrations over remote ocean regions, apart from at high latitudes, and underestimate over Northern Hemisphere continents. Finally, a new primary marine organic aerosol source is implemented in UKESM1 for the first time. The impact of this new aerosol source is evaluated. Over the pristine Southern Ocean, it is found to improve the seasonal cycle of organic aerosol mass and cloud droplet number concentrations relative to GC3.1 although underestimations in cloud droplet number concentrations remain. This paper provides a useful characterization of the aerosol climatology in both models facilitating the understanding of the numerous aerosol-climate interaction studies that will be conducted as part of CMIP6 and beyond

UKESM1: description and evaluation of the UK Earth System Model

We document the development of the first version of the United Kingdom Earth System Model UKESM1. The model represents a major advance on its predecessor HadGEM2‐ES, with enhancements to all component models and new feedback mechanisms. These include: a new core physical model with a well‐resolved stratosphere; terrestrial biogeochemistry with coupled carbon and nitrogen cycles and enhanced land management; tropospheric‐stratospheric chemistry allowing the holistic simulation of radiative forcing from ozone, methane and nitrous oxide; two‐moment, five‐species, modal aerosol; and ocean biogeochemistry with two‐way coupling to the carbon cycle and atmospheric aerosols. The complexity of coupling between the ocean, land and atmosphere physical climate and biogeochemical cycles in UKESM1 is unprecedented for an Earth system model. We describe in detail the process by which the coupled model was developed and tuned to achieve acceptable performance in key physical and Earth system quantities, and discuss the challenges involved in mitigating biases in a model with complex connections between its components. Overall the model performs well, with a stable pre‐industrial state, and good agreement with observations in the latter period of its historical simulations. However, global mean surface temperature exhibits stronger‐than‐observed cooling from 1950 to 1970, followed by rapid warming from 1980 to 2014. Metrics from idealised simulations show a high climate sensitivity relative to previous generations of models: equilibrium climate sensitivity (ECS) is 5.4 K, transient climate response (TCR) ranges from 2.68 K to 2.85 K, and transient climate response to cumulative emissions (TCRE) is 2.49 K/TtC to 2.66 K/TtC

Dynamical simulation of Indian summer monsoon circulation, rainfall and its interannual variability using a high resolution atmospheric general circulation model

This paper discusses the simulations of Indian summer monsoon (ISM) using a high-resolution National Center for Environmental Prediction (NCEP) T170/L42 model for a 20-year period (1985–2004) with observed Sea Surface Temperature (SSTs) as boundary conditions and using five initial conditions in the first week of May. Good agreement is found between the observed and simulated climatologies. Interannual variability (IAV) of the ISM rainfall as simulated in individual ensemble members and as provided by ensemble average shows that the two series are found to agree well; however, the simulation of the actual observed year-to-year variability is poor. The model simulations do not show much skill in the simulation of drought and excess monsoon seasons. One aspect which has emerged from the study is that where dynamical seasonal prediction has specific base for the large areal and temporal averages, the technique is not to be stretched for application on short areal scale such as that of a cluster of a few grid point. Monsoon onset over Kerala (MOK) coast of India and advance from Kerala coast to northwest India is discussed based on ensemble average and individual ensemble member basis. It is suggested that the model is capable of realistically simulating these processes, particularly if ensemble average is used, as the intermember spread in the ensemble members is large. In short, the high-resolution model appears to provide better climatology and its magnitude of IAV, which compares favourably with observations, although year-to-year matching of the observed and simulated seasonal/monthly rainfall totals for India as a whole is not good. Copyright © 2010 Royal Meteorological Societ

A GIS based methodology for gridding of large-scale emission inventories: application to carbon-monoxide emissions over Indian region

Chemical simulations in most of the atmospheric chemistry models require surface emissions in a specific form (gridded), which are often not available. Simple interpolation of broader level emissions to obtain gridded data may lead to erroneous results. An attempt has been made in this paper to develop a geographical information system (GIS) based methodology for distributing the emissions from a broader level inventory to finely gridded emission values, considering local micro-level details and activity data. Given the importance of Carbon Monoxide emissions in ozone pollution chemistry over India, an emission inventory for CO from various sources for India has been used to demonstrate the GIS-based gridding methodology. The total CO emissions over India for 2001, which are estimated to be around 69.0 Tg year-1, have been downscaled source-wise (distinguishing between rural and urban bio-fuel, vehicular traffic, coal and biomass burning) from state-level (28 points) to district level (~500 points) before mapping through a GIS utility and finally gridded to a 1° ×1° resolution with a data loss of only about 13%. The final results provide detailed information with emission "hot spots" and the relative contribution of various sources. This article focuses on usage of the GIS based statistical methodology for gridding the inventory and the results obtained thereof are discussed

A GIS based methodology for gridding of large-scale emission inventories: Application to carbon-monoxide emissions over Indian region

Chemical simulations in most of the atmospheric chemistry models require surface emissions in a specific form (gridded), which are often not available. Simple interpolation of broader level emissions to obtain gridded data may lead to erroneous results. An attempt has been made in this paper to develop a geographical information system (GIS) based methodology for distributing the emissions from a broader level inventory to finely gridded emission values, considering local micro-level details and activity data. Given the importance of Carbon Monoxide emissions in ozone pollution chemistry over India, an emission inventory for CO from various sources for India has been used to demonstrate the GIS-based gridding methodology. The total CO emissions over India for 2001, which are estimated to be around 69.0 Tg year(-1). have been downscaled source-wise (distinguishing between rural and urban bio-fuel, vehicular traffic, coal and biomass burning) from state-level (28 points) to district level (similar to 500 points) before mapping through a GIS utility and finally gridded to a 1 degrees x 1 degrees resolution with a data loss of only about 13%. The final results provide detailed information with emission "hot spots" and the relative contribution of various sources. This article focuses on usage of the GIS based statistical methodology for gridding the inventory and the results obtained thereof are discussed

Quantifying the impact of current and future concentrations of air pollutants on respiratory disease risk in England

Abstract Background Estimating the long-term health impact of air pollution in a spatio-temporal ecological study requires representative concentrations of air pollutants to be constructed for each geographical unit and time period. Averaging concentrations in space and time is commonly carried out, but little is known about how robust the estimated health effects are to different aggregation functions. A second under researched question is what impact air pollution is likely to have in the future. Methods We conducted a study for England between 2007 and 2011, investigating the relationship between respiratory hospital admissions and different pollutants: nitrogen dioxide (NO2); ozone (O3); particulate matter, the latter including particles with an aerodynamic diameter less than 2.5 micrometers (PM2.5), and less than 10 micrometers (PM10); and sulphur dioxide (SO2). Bayesian Poisson regression models accounting for localised spatio-temporal autocorrelation were used to estimate the relative risks (RRs) of pollution on disease risk, and for each pollutant four representative concentrations were constructed using combinations of spatial and temporal averages and maximums. The estimated RRs were then used to make projections of the numbers of likely respiratory hospital admissions in the 2050s attributable to air pollution, based on emission projections from a number of Representative Concentration Pathways (RCP). Results NO2 exhibited the largest association with respiratory hospital admissions out of the pollutants considered, with estimated increased risks of between 0.9 and 1.6% for a one standard deviation increase in concentrations. In the future the projected numbers of respiratory hospital admissions attributable to NO2 in the 2050s are lower than present day rates under 3 Representative Concentration Pathways (RCPs): 2.6, 6.0, and 8.5, which is due to projected reductions in future NO2 emissions and concentrations. Conclusions NO2 concentrations exhibit consistent substantial present-day health effects regardless of how a representative concentration is constructed in space and time. Thus as concentrations are predicted to remain above limits set by European Union Legislation until the 2030s in parts of urban England, it will remain a substantial health risk for some time

Additional file 2 of Quantifying the impact of current and future concentrations of air pollutants on respiratory disease risk in England

Study data. This is a .zip file containing the data used in the study. The file also contains a read-me document summarising the content of the file. (ZIP 5070 kb