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This paper documents the methodology and preliminary results from a perturbed parameter ensemble (PPE) technique, where multiple parameters are varied simultaneously and the parameter values are determined with Latin hypercube sampling. This is done with the Community Atmosphere Model version 6 (CAM6), the atmospheric component of the Community Earth System Model version 2 (CESM2). We apply the PPE method to CESM2–CAM6 to understand climate sensitivity to atmospheric physics parameters. The initial simulations vary 45 parameters in the microphysics, convection, turbulence and aerosol schemes with 263 ensemble members. These atmospheric parameters are typically the most uncertain in many climate models. Control simulations and targeted simulations to understand climate forcing due to aerosols and fast climate feedbacks are analyzed. The use of various emulators is explored in the multi-dimensional space mapping input parameters to output metrics. Parameter impacts on various model outputs, such as radiation, cloud and aerosol properties, are evaluated. Machine learning is also used to probe optimal parameter values against observations. Our findings show that PPE is a valuable tool for climate uncertainty analysis. Furthermore, by varying many parameters simultaneously, we find that many different combinations of parameter values can produce results consistent with observations, and thus careful analysis of tuning is important. The CESM2–CAM6 PPE is publicly available and extensible to other configurations to address questions of other model processes in the atmosphere and other model components (e.g., coupling to the land surface).

Abstract Ships brighten low marine clouds from emissions of sulfur and aerosols, resulting in visible “ship tracks”. In 2020, new shipping regulations mandated an ∼80% reduction in the allowed fuel sulfur content. Recent observations indicate that visible ship tracks have decreased. Model simulations indicate that since 2020 shipping regulations have induced a net radiative forcing of +0.12 Wm−2. Analysis of recent temperature anomalies indicates Northern Hemisphere surface temperature anomalies in 2022–2023 are correlated with observed cloud radiative forcing and the cloud radiative forcing is spatially correlated with the simulated radiative forcing from the 2020 shipping emission changes. Shipping emissions changes could be accelerating global warming. To better constrain these estimates, better access to ship position data and understanding of ship aerosol emissions are needed. Understanding the risks and benefits of emissions reductions and the difficultly in robust attribution highlights the large uncertainty in attributing proposed deliberate climate intervention.

The climate science community aims to improve our understanding of climate change due to anthropogenic influences on atmospheric composition and the Earth's surface. Yet not all climate interactions are fully understood, and uncertainty in climate model results persists, as assessed in the latest Intergovernmental Panel on Climate Change (IPCC) assessment report. We synthesize current challenges and emphasize opportunities for advancing our understanding of the interactions between atmospheric composition, air quality, and climate change, as well as for quantifying model diversity. Our perspective is based on expert views from three multi-model intercomparison projects (MIPs) – the Precipitation Driver Response MIP (PDRMIP), the Aerosol Chemistry MIP (AerChemMIP), and the Radiative Forcing MIP (RFMIP). While there are many shared interests and specializations across the MIPs, they have their own scientific foci and specific approaches. The partial overlap between the MIPs proved useful for advancing the understanding of the perturbation–response paradigm through multi-model ensembles of Earth system models of varying complexity. We discuss the challenges of gaining insights from Earth system models that face computational and process representation limits and provide guidance from our lessons learned. Promising ideas to overcome some long-standing challenges in the near future are kilometer-scale experiments to better simulate circulation-dependent processes where it is possible and machine learning approaches where they are needed, e.g., for faster and better subgrid-scale parameterizations and pattern recognition in big data. New model constraints can arise from augmented observational products that leverage multiple datasets with machine learning approaches. Future MIPs can develop smart experiment protocols that strive towards an optimal trade-off between the resolution, complexity, and number of simulations and their length and, thereby, help to advance the understanding of climate change and its impacts.

For over 6 months, the 2014–2015 effusive eruption at Holuhraun, Iceland, injected considerable amounts of sulfur dioxide (SO2) into the lower troposphere with a daily rate of up to one-third of the global emission rate, causing extensive air pollution across Europe. The large injection of SO2, which oxidises to form sulfate aerosol (SO42-), provides a natural experiment offering an ideal opportunity to scrutinise state-of-the-art general circulation models' (GCMs) representation of aerosol–cloud interactions (ACIs). Here we present Part 1 of a two-part model inter-comparison using the Holuhraun eruption as a framework to analyse ACIs. We use SO2 retrievals from the Infrared Atmospheric Sounding Interferometer (IASI) instrument and ground-based measurements of SO2 and SO42- mass concentrations across Europe, in conjunction with a trajectory analysis using the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model, to assess the spatial and chemical evolution of the volcanic plume as simulated by five GCMs and a chemical transport model (CTM). IASI retrievals of plume altitude and SO2 column load reveal that the volcanic perturbation is largely contained within the lower troposphere. Compared to the satellite observations, the models capture the spatial evolution and vertical variability of the plume reasonably well, although the models often overestimate the plume altitude. HYSPLIT trajectories are used to attribute to Holuhraun emissions 111 instances of elevated sulfurous surface mass concentrations recorded at European Monitoring and Evaluation Programme (EMEP) stations during September and October 2014. Comparisons with the simulated concentrations show that the modelled ratio of SO2 to SO42- during these pollution episodes is often underestimated and overestimated for the young and mature plume, respectively. Models with finer vertical resolutions near the surface are found to better capture these elevated sulfurous ground-level concentrations. Using an exponential function to describe the decay of observed surface mass concentration ratios of SO2 to SO42- with plume age, the in-plume oxidation rate constant is estimated as 0.032 ± 0.002 h−1 (1.30 ± 0.08 d e-folding time), with a near-vent ratio of 25 ± 5 (µg m−3 of SO2 / µg m−3 of SO42-). The majority of the corresponding derived modelled oxidation rate constants are lower than the observed estimate. This suggests that the representation of the oxidation pathway/s in the simulated plumes is too slow. Overall, despite their coarse spatial resolutions, the six models show reasonable skill in capturing the spatial and chemical evolution of the Holuhraun plume. This capable representation of the underlying aerosol perturbation is essential to enable the investigation of the eruption's impact on ACIs in the second part of this study.

Human aerosol emissions change cloud properties by providing additional cloud condensation nuclei. This increases cloud droplet numbers, which in turn affects other cloud properties like liquid-water content and ultimately cloud albedo. These adjustments are poorly constrained, making aerosol effects the most uncertain part of anthropogenic climate forcing. Here we show that cloud droplet number and water content react differently to changing emission amounts in shipping exhausts. We use information about ship positions and modeled emission amounts together with reanalysis winds and satellite retrievals of cloud properties. The analysis reveals that cloud droplet numbers respond linearly to emission amount over a large range (1–10 kg h−1) before the response saturates. Liquid water increases in raining clouds, and the anomalies are constant over the emission ranges observed. There is evidence that this independence of emissions is due to compensating effects under drier and more humid conditions, consistent with suppression of rain by enhanced aerosol. This has implications for our understanding of cloud processes and may improve the way clouds are represented in climate models, in particular by changing parameterizations of liquid-water responses to aerosol.

Aerosol radiative forcing uncertainty affects estimates of climate sensitivity and limits model skill in terms of making climate projections. Efforts to improve the representations of physical processes in climate models, including extensive comparisons with observations, have not significantly constrained the range of possible aerosol forcing values. A far stronger constraint, in particular for the lower (most-negative) bound, can be achieved using global mean energy balance arguments based on observed changes in historical temperature. Here, we show that structural deficiencies in a climate model, revealed as inconsistencies among observationally constrained cloud properties in the model, limit the effectiveness of observational constraint of the uncertain physical processes. We sample the uncertainty in 37 model parameters related to aerosols, clouds, and radiation in a perturbed parameter ensemble of the UK Earth System Model and evaluate 1 million model variants (different parameter settings from Gaussian process emulators) against satellite-derived observations over several cloudy regions. Our analysis of a very large set of model variants exposes model internal inconsistencies that would not be apparent in a small set of model simulations, of an order that may be evaluated during model-tuning efforts. Incorporating observations associated with these inconsistencies weakens any forcing constraint because they require a wider range of parameter values to accommodate conflicting information. We show that, by neglecting variables associated with these inconsistencies, it is possible to reduce the parametric uncertainty in global mean aerosol forcing by more than 50 %, constraining it to a range (around −1.3 to −0.1 W m−2) in close agreement with energy balance constraints. Our estimated aerosol forcing range is the maximum feasible constraint using our structurally imperfect model and the chosen observations. Structural model developments targeted at the identified inconsistencies would enable a larger set of observations to be used for constraint, which would then very likely narrow the uncertainty further and possibly alter the central estimate. Such an approach provides a rigorous pathway to improved model realism and reduced uncertainty that has so far not been achieved through the normal model development approach.

Background: Esophageal cancer [esophagogastric adenocarcinoma (OGA)] shows heterogeneity at the molecular level, leading to lower efficacy rates and highlighting the need for personalized treatment strategies. We have developed a computational model that uses both mechanistic and statistical approaches to integrate a patient’s genomic aberrations, revealing signaling pathway dysregulation and variable drug response. The model output, Therapy Response Index (TRI), has been used to predict therapeutic outcomes in this study. Design: TRI’s ability to predict patient outcomes was retrospectively evaluated in a prospectively collected cohort of patients with operable OGA from the UK Oesophageal Cancer Clinical and Molecular Stratification (OCCAMS) consortium receiving neoadjuvant chemotherapy. Stratified random sampling was used to split the data into training and validation subsets. Multivariate Cox proportional hazard and proportional odds models were used to predict survival and pathological response as a function of TRI and clinical thresholds compared with clinical factors. Results: A total of 270 patients with OGA were selected who had 50× whole genome sequencing carried out on tissue derived from either biopsy or resection. Patients were treated with chemotherapy drugs or regimens according to UK clinical guidelines. The association of TRI with overall survival (OS) was significant above and beyond standard clinical factors (P = 0.0012). A significant association was also observed with disease-free survival (DFS; P = 0.0288). A TRI optimized for tumor regression grade also displayed a significant association (P = 0.0011). Conclusions: TRI was predictive of OS and DFS beyond clinical factors. These positive results suggest the potential utility of personalized biosimulation-informed therapy selection and that further assessment in prospective clinical studies is warranted.

The semi-permanent stratocumulus clouds over the south-eastern Atlantic Ocean (SEA) can act as an “air conditioner” to the regional and global climate system. The interaction of aerosols and clouds becomes important in this region and can lead to negative radiative effects, partially offsetting the positive radiative forcing of greenhouse gases. A key pathway by which aerosols affect cloud properties is by acting as cloud condensation nuclei (CCN). In this paper, we use the United Kingdom Earth System Model (UKESM1) to investigate the sources of CCN (from emissions and atmospheric processes) in the SEA as well as the response of the cloud droplet number concentration (CDNC), the cloud liquid water path (LWP), and radiative forcing to these sources during 2016 and 2017. Overall, free and upper troposphere nucleated aerosols are the dominant source of the boundary layer CCN concentration at 0.2 % supersaturation (CCN0.2 %), contributing an annual average of ∼ 41 % as they subside and entrain into the marine boundary layer, which is consistent with observations highlighting the important role of nucleation in the boundary layer CCN concentration. In terms of emission sources, anthropogenic emissions (from energy, industry, agriculture, etc.) contribute the most to the annual average CCN0.2 % in the marine boundary layer (∼ 26 %), followed by biomass burning (BB, ∼ 17 %). In the cloud layer, BB contributes about 34 % of the annual CCN0.2 %, midway between the contributions from aerosol nucleation (36 %) and anthropogenic sources (31 %). The contribution of aerosols from different sources to the CDNC is consistent with their contribution to CCN0.2 % within the marine boundary layer, with free and upper troposphere aerosol nucleation being the most important source of the CDNC overall. In terms of emission sources, anthropogenic sources are also the largest contributors to the annual average CDNC, closely followed by BB. However, during the BB season, BB and free and upper troposphere aerosol nucleation are equally the most important sources of the CDNC. The contribution of BB to the CDNC is more significant than its increase to CCN0.2 %, mainly because BB aerosols are mostly located directly above the inversion layer in the model; thus, they can increase the in-cloud CDNC by enhancing the supersaturation through the dynamical feedback due to short-wave absorption. An aerosol source that shows an increase in the CDNC also shows an increase in the LWP resulting from a reduction in autoconversion. Due to the absorption effect, BB aerosol can enhance existing temperature inversions and reduce the entrainment of sub-saturated air, leading to a further increase in the LWP. As a result, the contribution of BB to the LWP is second only to aerosol nucleation on annual averages. These findings demonstrate that BB is not the dominant source of CCN within the marine boundary layer from an emission source perspective. However, as most BB aerosols are located directly above the inversion layer, their effect on clouds increases due to their absorption effect (about the same as anthropogenic sources for the CDNC and more than anthropogenic sources for the LWP), highlighting the crucial role of their radiative effect on clouds. The results on the radiative effects of aerosols show that BB aerosol exhibits an overall positive RFari (radiative forcing associated with aerosol–radiation interactions), but its net effective radiative forcing remains negative due to its effect on clouds (mainly due to its absorbing effect). By quantifying aerosol and cloud properties affected by different sources, this paper provides a framework for understanding the effects of aerosol sources on marine stratocumulus clouds and radiation in the SEA.

While carbon dioxide is the main cause for global warming, modeling short-lived climate forcers (SLCFs) such as methane, ozone, and particles in the Arctic allows us to simulate near-term climate and health impacts for a sensitive, pristine region that is warming at 3 times the global rate. Atmospheric modeling is critical for understanding the long-range transport of pollutants to the Arctic, as well as the abundance and distribution of SLCFs throughout the Arctic atmosphere. Modeling is also used as a tool to determine SLCF impacts on climate and health in the present and in future emissions scenarios. In this study, we evaluate 18 state-of-the-art atmospheric and Earth system models by assessing their representation of Arctic and Northern Hemisphere atmospheric SLCF distributions, considering a wide range of different chemical species (methane, tropospheric ozone and its precursors, black carbon, sulfate, organic aerosol, and particulate matter) and multiple observational datasets. Model simulations over 4 years (2008–2009 and 2014–2015) conducted for the 2022 Arctic Monitoring and Assessment Programme (AMAP) SLCF assessment report are thoroughly evaluated against satellite, ground, ship, and aircraft-based observations. The annual means, seasonal cycles, and 3-D distributions of SLCFs were evaluated using several metrics, such as absolute and percent model biases and correlation coefficients. The results show a large range in model performance, with no one particular model or model type performing well for all regions and all SLCF species. The multi-model mean (mmm) was able to represent the general features of SLCFs in the Arctic and had the best overall performance. For the SLCFs with the greatest radiative impact (CH4, O3, BC, and SO42-), the mmm was within ±25 % of the measurements across the Northern Hemisphere. Therefore, we recommend a multi-model ensemble be used for simulating climate and health impacts of SLCFs. Of the SLCFs in our study, model biases were smallest for CH4 and greatest for OA. For most SLCFs, model biases skewed from positive to negative with increasing latitude. Our analysis suggests that vertical mixing, long-range transport, deposition, and wildfires remain highly uncertain processes. These processes need better representation within atmospheric models to improve their simulation of SLCFs in the Arctic environment. As model development proceeds in these areas, we highly recommend that the vertical and 3-D distribution of SLCFs be evaluated, as that information is critical to improving the uncertain processes in models.

Abstract Background AGITG DOCTOR was a randomised phase 2 trial of pre-operative cisplatin, 5 fluorouracil (CF) followed by docetaxel (D) with or without radiotherapy (RT) based on poor early response to CF, detected via PET, for resectable oesophageal adenocarcinoma. This study describes PROs over 2 years. Methods Participants (N = 116) completed the EORTC QLQ-C30 and oesophageal module (QLQ-OES18) before chemotherapy (baseline), before surgery, six and 12 weeks post-surgery and three-monthly until 2 years. We plotted PROs over time and calculated the percentage of participants per treatment group whose post-surgery score was within 10 points (threshold for clinically relevant change) of their baseline score, for each PRO scale. We examined the relationship between Grade 3+ adverse events (AEs) and PROs. This analysis included four groups: CF responders, non-responders randomised to DCF, non-responders randomised to DCF + RT, and “others” who were not randomised. Results Global QOL was clinically similar between groups from 6 weeks post-surgery. All groups had poorer functional and higher symptom scores during active treatment and shortly after surgery, particularly the DCF and DCF + RT groups. DCF + RT reported a clinically significant difference (−13points) in mean overall health/QOL between baseline and pre-surgery. Similar proportions of patients across groups scored +/− 10 points of baseline scores within 2 years for most PRO domains. Instance of grade 3+ AEs were not related to PROs at baseline or 2 years. Conclusions By 2 years, similar proportions of patients scored within 10 points of baseline for most PRO domains, with the exception of pain and insomnia for the DCF + RT group. Non-responders randomised to DCF or DCF + RT experienced additional short-term burden compared to CF responders, reflecting the longer duration of neoadjuvant treatment and additional toxicity. This should be weighed against clinical benefits reported in AGITG DOCTOR. This data will inform communication of the trajectory of treatment options for early CF non-responders. Trial registration Australia New Zealand Clinical Trials Registry (ANZCTR), ACTRN12609000665235 . Registered 31 July 2009.

Aerosol–cloud interactions (ACIs) are considered to be the most uncertain driver of present-day radiative forcing due to human activities. The nonlinearity of cloud-state changes to aerosol perturbations make it challenging to attribute causality in observed relationships of aerosol radiative forcing. Using correlations to infer causality can be challenging when meteorological variability also drives both aerosol and cloud changes independently. Natural and anthropogenic aerosol perturbations from well-defined sources provide “opportunistic experiments” (also known as natural experiments) to investigate ACI in cases where causality may be more confidently inferred. These perturbations cover a wide range of locations and spatiotemporal scales, including point sources such as volcanic eruptions or industrial sources, plumes from biomass burning or forest fires, and tracks from individual ships or shipping corridors. We review the different experimental conditions and conduct a synthesis of the available satellite datasets and field campaigns to place these opportunistic experiments on a common footing, facilitating new insights and a clearer understanding of key uncertainties in aerosol radiative forcing. Cloud albedo perturbations are strongly sensitive to background meteorological conditions. Strong liquid water path increases due to aerosol perturbations are largely ruled out by averaging across experiments. Opportunistic experiments have significantly improved process-level understanding of ACI, but it remains unclear how reliably the relationships found can be scaled to the global level, thus demonstrating a need for deeper investigation in order to improve assessments of aerosol radiative forcing and climate change.

Large computer models are ubiquitous in the Earth sciences. These models often have tens or hundreds of tuneable parameters and can take thousands of core hours to run to completion while generating terabytes of output. It is becoming common practice to develop emulators as fast approximations, or surrogates, of these models in order to explore the relationships between these inputs and outputs, understand uncertainties, and generate large ensembles datasets. While the purpose of these surrogates may differ, their development is often very similar. Here we introduce ESEm: an open-source tool providing a general workflow for emulating and validating a wide variety of models and outputs. It includes efficient routines for sampling these emulators for the purpose of uncertainty quantification and model calibration. It is built on well-established, high-performance libraries to ensure robustness, extensibility and scalability. We demonstrate the flexibility of ESEm through three case studies using ESEm to reduce parametric uncertainty in a general circulation model and explore precipitation sensitivity in a cloud-resolving model and scenario uncertainty in the CMIP6 multi-model ensemble.

We present a joint analysis of the galaxy S04590 at z = 8.496 based on NIRSpec, NIRCam, and NIRISS observations obtained as part of the Early Release Observations program of the James Webb Space Telescope (JWST) and the far-infrared [C ii ] 158 μ m emission line detected by dedicated Atacama Large Millimeter/submillimeter Array (ALMA) observations. We determine the physical properties of S04590 from modeling of the spectral energy distribution (SED) and through the redshifted optical nebular emission lines detected with JWST/NIRSpec. The best-fit SED model reveals a low-mass ( M _⋆ = 10 ^7.2 –10 ^8 M _⊙ ) galaxy with a low oxygen abundance of $12+\mathrm{log}({\rm{O}}/{\rm{H}})={7.16}_{-0.12}^{+0.10}$ derived from the strong nebular and auroral emission lines. Assuming that [C ii ] effectively traces the interstellar medium, we estimate the total gas mass of the galaxy to be M _gas = (8.0 ± 4.0) × 10 ^8 M _⊙ based on the luminosity and spatial extent of [C ii ]. This yields an exceptionally high gas fraction, f _gas = M _gas /( M _gas + M _⋆ ) ≳ 90%, though one still consistent with the range expected for low metallicity. We further derive the metal mass of the galaxy based on the gas mass and gas-phase metallicity, which we find to be consistent with the expected metal production from Type II supernovae. Finally, we make the first constraints on the dust-to-gas (DTG) and dust-to-metal (DTM) ratios of galaxies in the epoch of reionization at z ≳ 6, showing overall low mass ratios of logDTG < −3.8 and logDTM < −0.5, though they are consistent with established scaling relations and in particular with those of the local metal-poor galaxy I Zwicky 18. Our analysis highlights the synergy between ALMA and JWST in characterizing the gas, metal, and stellar content of the first generation of galaxies.

We present James Webb Space Telescope (JWST) and Hubble Space Telescope (HST) observations of the afterglow of GRB 221009A, the brightest gamma-ray burst (GRB) ever observed. This includes the first mid-IR spectra of any GRB, obtained with JWST/Near Infrared Spectrograph (0.6–5.5 micron) and Mid-Infrared Instrument (5–12 micron), 12 days after the burst. Assuming that the intrinsic spectral slope is a single power law, with F _ν ∝ ν ^− ^β , we obtain β ≈ 0.35, modified by substantial dust extinction with A _V = 4.9. This suggests extinction above the notional Galactic value, possibly due to patchy extinction within the Milky Way or dust in the GRB host galaxy. It further implies that the X-ray and optical/IR regimes are not on the same segment of the synchrotron spectrum of the afterglow. If the cooling break lies between the X-ray and optical/IR, then the temporal decay rates would only match a post-jet-break model, with electron index p < 2, and with the jet expanding into a uniform ISM medium. The shape of the JWST spectrum is near-identical in the optical/near-IR to X-SHOOTER spectroscopy obtained at 0.5 days and to later time observations with HST. The lack of spectral evolution suggests that any accompanying supernova (SN) is either substantially fainter or bluer than SN 1998bw, the proto-type GRB-SN. Our HST observations also reveal a disk-like host galaxy, viewed close to edge-on, that further complicates the isolation of any SN component. The host galaxy appears rather typical among long-GRB hosts and suggests that the extreme properties of GRB 221009A are not directly tied to its galaxy-scale environment.

Aerosol-induced absorption of shortwave radiation can modify the climate through local atmospheric heating, which affects lapse rates, precipitation, and cloud formation. Presently, the total amount of aerosol absorption is poorly constrained, and the main absorbing aerosol species (black carbon (BC), organic aerosols (OA), and mineral dust) are diversely quantified in global climate models. As part of the third phase of the Aerosol Comparisons between Observations and Models (AeroCom) intercomparison initiative (AeroCom phase III), we here document the distribution and magnitude of aerosol absorption in current global aerosol models and quantify the sources of intermodel spread, highlighting the difficulties of attributing absorption to different species. In total, 15 models have provided total present-day absorption at 550 nm (using year 2010 emissions), 11 of which have provided absorption per absorbing species. The multi-model global annual mean total absorption aerosol optical depth (AAOD) is 0.0054 (0.0020 to 0.0098; 550 nm), with the range given as the minimum and maximum model values. This is 28 % higher compared to the 0.0042 (0.0021 to 0.0076) multi-model mean in AeroCom phase II (using year 2000 emissions), but the difference is within 1 standard deviation, which, in this study, is 0.0023 (0.0019 in Phase II). Of the summed component AAOD, 60 % (range 36 %–84 %) is estimated to be due to BC, 31 % (12 %–49 %) is due to dust, and 11 % (0 %–24 %) is due to OA; however, the components are not independent in terms of their absorbing efficiency. In models with internal mixtures of absorbing aerosols, a major challenge is the lack of a common and simple method to attribute absorption to the different absorbing species. Therefore, when possible, the models with internally mixed aerosols in the present study have performed simulations using the same method for estimating absorption due to BC, OA, and dust, namely by removing it and comparing runs with and without the absorbing species. We discuss the challenges of attributing absorption to different species; we compare burden, refractive indices, and density; and we contrast models with internal mixing to models with external mixing. The model mean BC mass absorption coefficient (MAC) value is 10.1 (3.1 to 17.7) m2 g−1 (550 nm), and the model mean BC AAOD is 0.0030 (0.0007 to 0.0077). The difference in lifetime (and burden) in the models explains as much of the BC AAOD spread as the difference in BC MAC values. The difference in the spectral dependency between the models is striking. Several models have an absorption Ångstrøm exponent (AAE) close to 1, which likely is too low given current knowledge of spectral aerosol optical properties. Most models do not account for brown carbon and underestimate the spectral dependency for OA.

Changes in global-mean precipitation are strongly constrained by global radiative cooling, while regional rainfall changes are less constrained because energy can be transported. Absorbing and non-absorbing aerosols have different effects on both global-mean and regional precipitation, due to the distinct effects on energetics. This study analyses the precipitation responses to large perturbations in black carbon (BC) and sulfate (SUL) by examining the changes in atmospheric energy budget terms on global and regional scales, in terms of fast (independent of changes in sea surface temperature, SST) and slow responses (mediated by changes in SST). Changes in atmospheric radiative cooling/heating are further decomposed into contributions from clouds, aerosols, and clear–clean sky (without clouds or aerosols). Both cases show a decrease in global-mean precipitation, which is dominated by fast responses in the BC case and slow responses in the SUL case. The geographical patterns are distinct too. The intertropical convergence zone (ITCZ), accompanied by tropical rainfall, shifts northward in the BC case, while it shifts southward in the SUL case. For both cases, energy transport terms from the slow response dominate the changes in tropical rainfall, which are associated with the northward (southward) shift of the Hadley cell in response to the enhanced southward (northward) cross-equatorial energy flux caused by increased BC (SUL) emission. The extra-tropical precipitation decreases in both cases. For the BC case, fast responses to increased atmospheric radiative heating contribute most to the reduced rainfall, in which absorbing aerosols directly heat the mid-troposphere, stabilise the column, and suppress precipitation. Unlike BC, non-absorbing aerosols decrease surface temperatures through slow processes, cool the whole atmospheric column, and reduce specific humidity, which leads to decreased radiative cooling from the clear–clean sky, which is consistent with the reduced rainfall. Examining the changes in large-scale circulation and local thermodynamics qualitatively explains the responses of precipitation to aerosol perturbations, whereas the energetic perspective provides a method to quantify their contributions.

The representations of clouds, aerosols, and cloud–aerosol–radiation impacts remain some of the largest uncertainties in climate change, limiting our ability to accurately reconstruct past climate and predict future climate. The south-east Atlantic is a region where high atmospheric aerosol loadings and semi-permanent stratocumulus clouds are co-located, providing an optimum region for studying the full range of aerosol–radiation and aerosol–cloud interactions and their perturbations of the Earth's radiation budget. While satellite measurements have provided some useful insights into aerosol–radiation and aerosol–cloud interactions over the region, these observations do not have the spatial and temporal resolution, nor the required level of precision to allow for a process-level assessment. Detailed measurements from high spatial and temporal resolution airborne atmospheric measurements in the region are very sparse, limiting their use in assessing the performance of aerosol modelling in numerical weather prediction and climate models. CLARIFY-2017 was a major consortium programme consisting of five principal UK universities with project partners from the UK Met Office and European- and USA-based universities and research centres involved in the complementary ORACLES, LASIC, and AEROCLO-sA projects. The aims of CLARIFY-2017 were fourfold: (1) to improve the representation and reduce uncertainty in model estimates of the direct, semi-direct, and indirect radiative effect of absorbing biomass burning aerosols; (2) to improve our knowledge and representation of the processes determining stratocumulus cloud microphysical and radiative properties and their transition to cumulus regimes; (3) to challenge, validate, and improve satellite retrievals of cloud and aerosol properties and their radiative impacts; (4) to improve the impacts of aerosols in weather and climate numerical models. This paper describes the modelling and measurement strategies central to the CLARIFY-2017 deployment of the FAAM BAe146 instrumented aircraft campaign, summarizes the flight objectives and flight patterns, and highlights some key results from our initial analyses.

The south-eastern Atlantic Ocean (SEA) is semi-permanently covered by one of the most extensive stratocumulus cloud decks on the planet and experiences about one-third of the global biomass burning emissions from the southern Africa savannah region during the fire season. To get a better understanding of the impact of these biomass burning aerosols on clouds and the radiation balance over the SEA, the latest generation of the UK Earth System Model (UKESM1) is employed. Measurements from the CLARIFY and ORACLES flight campaigns are used to evaluate the model, demonstrating that the model has good skill in reproducing the biomass burning plume. To investigate the underlying mechanisms in detail, the effects of biomass burning aerosols on the clouds are decomposed into radiative effects (via absorption and scattering) and microphysical effects (via perturbation of cloud condensation nuclei – CCN – and cloud microphysical processes). July–August means are used to characterize aerosols, clouds, and the radiation balance during the fire season. Results show that around 65 % of CCN at 0.2 % supersaturation in the SEA can be attributed to biomass burning. The absorption effect of biomass burning aerosols is the most significant on clouds and radiation. Near the continent, it increases the supersaturation diagnosed by the activation scheme, while further from the continent it reduces the altitude of the supersaturation. As a result, the cloud droplet number concentration responds with a similar pattern to the absorption effect of biomass burning aerosols. The microphysical effect, however, decreases the supersaturation and increases the cloud droplet concentration over the ocean, although this change is relatively small. The liquid water path is also significantly increased over the SEA (mainly caused by the absorption effect of biomass burning aerosols) when biomass burning aerosols are above the stratocumulus cloud deck. The microphysical pathways lead to a slight increase in the liquid water path over the ocean. These changes in cloud properties indicate the significant role of biomass burning aerosols for clouds in this region. Among the effects of biomass burning aerosols on the radiation balance, the semi-direct radiative effects (rapid adjustments induced by the radiative effects of biomass burning aerosols) have a dominant cooling impact over the SEA, which offset the warming direct radiative effect (radiative forcing from biomass burning aerosol–radiation interactions) and lead to an overall net cooling radiative effect in the SEA. However, the magnitude and the sign of the semi-direct effects are sensitive to the relative location of biomass burning aerosols and clouds, reflecting the critical task of the accurate modelling of the biomass burning plume and clouds in this region.

Abstract Rapid development of an effective vaccine for SARSCoV2 is a global priority. A controlled human infection model (CHIM) would accelerate the efficacy assessment of candidate vaccines. This strategy would require deliberate exposure of volunteers to SARSCoV2 with no currently available treatment and a small but definite risk of serious illness or death. This raises complex questions about the social and ethical acceptability of risk to individuals, given the potential benefit to the wider population, and as such, a study cannot be done without public involvement. We conducted a structured public consultation with 57 individuals aged 20–40 years to understand public attitudes to a CHIM, and pre-requisites for enrolment. The overall response to this strategy was positive, and many would volunteer altruistically. Carefully controlled infection is viewed as safer than natural exposure to wild virus. The prolonged social isolation required for the proposed CHIM is considered an obstacle but not insurmountable, with reasonable compensation and supportive care. Given the significant level of public interest, a CHIM should be done as open science with regular, controlled dissemination of information into the public domain. Importantly, there was a strong view that the final decision whether to conduct a CHIM should be in the hands of qualified and experienced clinician-scientists and the authorities.

Wind turbines possess the technical ability to provide various ancillary services to the electrical grid. Despite this, renewable generators such as wind and solar have traditionally not been allowed to provide significant amounts of ancillary services, in part due to the variable and uncertain nature of their electricity generation. Increasing levels of renewable generation, however, continue to displace existing synchronous generation and thus necessitate new sources of ancillary or system services. This work is part of an ongoing project that seeks to provide empirical evidence and an examination of how ancillary services can be provided from commercially available wind turbines. We focus specifically on providing secondary frequency response (automatic generation control or AGC) and demonstrate that wind turbines have the technical capability to provide this service. The algorithms used are intentionally simple so as to evaluate the capabilities and limitations of the turbine technology. This work presents results from a single, 800 kW, International Electrotechnical Commission (IEC) Type 4 wind turbine. A total of 10 % of rated power is offered on the regulation market. We do not separate up- and downregulation into individual services. Upregulation is offered through a 5 % constant power curtailment. The AGC update interval is 4 s, to mimic real-world conditions. We use performance scoring methods from the Pennsylvania–Jersey–Maryland (PJM) operator and the National Research Council (NRC) of Canada to quantify the wind turbine's response. We use the calculated performance scores, annual site wind data, and 2017 PJM market price data to estimate income from providing secondary frequency regulation. In all cases presented, income from the regulation market is greater than the energy income lost due to curtailment.

Abstract The Hamburg Aerosol Module version 2.3 (HAM2.3) from the ECHAM6.3‐HAM2.3 global atmosphere‐aerosol model is coupled to the recently developed icosahedral nonhydrostatic ICON‐A (icon‐aes‐1.3.00) global atmosphere model to yield the new ICON‐A‐HAM2.3 atmosphere‐aerosol model. The ICON‐A and ECHAM6.3 host models use different dynamical cores, parameterizations of vertical mixing due to sub‐grid scale turbulence, and parameter settings for radiation balance tuning. Here, we study the role of the different host models for simulated aerosol optical thickness (AOT) and evaluate impacts of using HAM2.3 and the ECHAM6‐HAM2.3 two‐moment cloud microphysics scheme on several meteorological variables. Sensitivity runs show that a positive AOT bias over the subtropical oceans is remedied in ICON‐A‐HAM2.3 because of a different default setting of a parameter in the moist convection parameterization of the host models. The global mean AOT is biased low compared to MODIS satellite instrument retrievals in ICON‐A‐HAM2.3 and ECHAM6.3‐HAM2.3, but the bias is larger in ICON‐A‐HAM2.3 because negative AOT biases over the Amazon, the African rain forest, and the northern Indian Ocean are no longer compensated by high biases over the sub‐tropical oceans. ICON‐A‐HAM2.3 shows a moderate improvement with respect to AOT observations at AERONET sites. A multivariable bias score combining biases of several meteorological variables into a single number is larger in ICON‐A‐HAM2.3 compared to standard ICON‐A and standard ECHAM6.3. In the tropics, this multivariable bias is of similar magnitude in ICON‐A‐HAM2.3 and in ECHAM6.3‐HAM2.3. In the extra‐tropics, a smaller multivariable bias is found for ICON‐A‐HAM2.3 than for ECHAM6.3‐HAM2.3.

ABSTRACT (198): Background: The multi-dose regimen is a known barrier to successful human papillomavirus (HPV) vaccination. Emerging evidence suggests that one vaccine dose could protect against HPV. While there are clear advantages to a single dose schedule, beliefs about vaccine dosage in low and middle income countries (LMICs) are poorly understood. We investigated acceptability of dose-reduction among girls, and parents/guardians of girls, randomised to receive one, two or three doses in an HPV vaccine dose-reduction and immunobridging study (DoRIS trial) in Tanzania. Methods: Semi-structured interviews with girls (n = 19), and parents/guardians of girls (n = 18), enrolled in the study and completing their vaccine course. Results: Most participants said they entrusted decisions about the number of HPV vaccine doses to experts. Random allocation to the different dose groups did not feature highly in the decision to participate in the trial. Given a hypothetical choice, girls generally said they would prefer fewer doses in order to avoid the pain of injections. Parental views were mixed, with most wanting whichever dose was most efficacious. Nonetheless, a few parents equated a higher number of doses with greater protection. Conclusion: Vaccine trials and programmes will need to employ careful messaging to explain that one dose offers sufficient protection against HPV should emerging evidence from ongoing dose-reduction clinical trials support this.

We introduce tobac (Tracking and Object-Based Analysis of Clouds), a newly developed framework for tracking and analysing individual clouds in different types of datasets, such as cloud-resolving model simulations and geostationary satellite retrievals. The software has been designed to be used flexibly with any two- or three-dimensional time-varying input. The application of high-level data formats, such as Iris cubes or xarray arrays, for input and output allows for convenient use of metadata in the tracking analysis and visualisation. Comprehensive analysis routines are provided to derive properties like cloud lifetimes or statistics of cloud properties along with tools to visualise the results in a convenient way. The application of tobac is presented in two examples. We first track and analyse scattered deep convective cells based on maximum vertical velocity and the three-dimensional condensate mixing ratio field in cloud-resolving model simulations. We also investigate the performance of the tracking algorithm for different choices of time resolution of the model output. In the second application, we show how the framework can be used to effectively combine information from two different types of datasets by simultaneously tracking convective clouds in model simulations and in geostationary satellite images based on outgoing longwave radiation. The tobac framework provides a flexible new way to include the evolution of the characteristics of individual clouds in a range of important analyses like model intercomparison studies or model assessment based on observational data.

Water vapour in the atmosphere is the source of a major climate feedback mechanism and potential increases in the availability of water vapour could have important consequences for mean and extreme precipitation. Future precipitation changes further depend on how the hydrological cycle responds to different drivers of climate change, such as greenhouse gases and aerosols. Currently, neither the total anthropogenic influence on the hydrological cycle nor that from individual drivers is constrained sufficiently to make solid projections. We investigate how integrated water vapour (IWV) responds to different drivers of climate change. Results from 11 global climate models have been used, based on simulations where CO2, methane, solar irradiance, black carbon (BC), and sulfate have been perturbed separately. While the global-mean IWV is usually assumed to increase by ∼7 % per kelvin of surface temperature change, we find that the feedback response of IWV differs somewhat between drivers. Fast responses, which include the initial radiative effect and rapid adjustments to an external forcing, amplify these differences. The resulting net changes in IWV range from 6.4±0.9 % K−1 for sulfate to 9.8±2 % K−1 for BC. We further calculate the relationship between global changes in IWV and precipitation, which can be characterized by quantifying changes in atmospheric water vapour lifetime. Global climate models simulate a substantial increase in the lifetime, from 8.2±0.5 to 9.9±0.7 d between 1986–2005 and 2081–2100 under a high-emission scenario, and we discuss to what extent the water vapour lifetime provides additional information compared to analysis of IWV and precipitation separately. We conclude that water vapour lifetime changes are an important indicator of changes in precipitation patterns and that BC is particularly efficient in prolonging the mean time, and therefore likely the distance, between evaporation and precipitation.

Despite ongoing efforts, the vertical distribution of aerosols globally is poorly understood. This in turn leads to large uncertainties in the contributions of the direct and indirect aerosol forcing on climate. Using the Global Aerosol Synthesis and Science Project (GASSP) database – the largest synthesised collection of in situ aircraft measurements currently available, with more than 1000 flights from 37 campaigns from around the world – we investigate the vertical structure of submicron aerosols across a wide range of regions and environments. The application of this unique dataset to assess the vertical distributions of number size distribution and cloud condensation nuclei (CCN) in the global aerosol–climate model ECHAM-HAM reveals that the model underestimates accumulation-mode particles in the upper troposphere, especially in remote regions. The processes underlying this discrepancy are explored using different aerosol microphysical schemes and a process sensitivity analysis. These show that the biases are predominantly related to aerosol ageing and removal rather than emissions.

A total of 16 global chemistry transport models and general circulation models have participated in this study; 14 models have been evaluated with regard to their ability to reproduce the near-surface observed number concentration of aerosol particles and cloud condensation nuclei (CCN), as well as derived cloud droplet number concentration (CDNC). Model results for the period 2011–2015 are compared with aerosol measurements (aerosol particle number, CCN and aerosol particle composition in the submicron fraction) from nine surface stations located in Europe and Japan. The evaluation focuses on the ability of models to simulate the average across time state in diverse environments and on the seasonal and short-term variability in the aerosol properties. There is no single model that systematically performs best across all environments represented by the observations. Models tend to underestimate the observed aerosol particle and CCN number concentrations, with average normalized mean bias (NMB) of all models and for all stations, where data are available, of −24 % and −35 % for particles with dry diameters >50 and >120 nm, as well as −36 % and −34 % for CCN at supersaturations of 0.2 % and 1.0 %, respectively. However, they seem to behave differently for particles activating at very low supersaturations ( %) than at higher ones. A total of 15 models have been used to produce ensemble annual median distributions of relevant parameters. The model diversity (defined as the ratio of standard deviation to mean) is up to about 3 for simulated N3 (number concentration of particles with dry diameters larger than 3 nm) and up to about 1 for simulated CCN in the extra-polar regions. A global mean reduction of a factor of about 2 is found in the model diversity for CCN at a supersaturation of 0.2 % (CCN0.2) compared to that for N3, maximizing over regions where new particle formation is important. An additional model has been used to investigate potential causes of model diversity in CCN and bias compared to the observations by performing a perturbed parameter ensemble (PPE) accounting for uncertainties in 26 aerosol-related model input parameters. This PPE suggests that biogenic secondary organic aerosol formation and the hygroscopic properties of the organic material are likely to be the major sources of CCN uncertainty in summer, with dry deposition and cloud processing being dominant in winter. Models capture the relative amplitude of the seasonal variability of the aerosol particle number concentration for all studied particle sizes with available observations (dry diameters larger than 50, 80 and 120 nm). The short-term persistence time (on the order of a few days) of CCN concentrations, which is a measure of aerosol dynamic behavior in the models, is underestimated on average by the models by 40 % during winter and 20 % in summer. In contrast to the large spread in simulated aerosol particle and CCN number concentrations, the CDNC derived from simulated CCN spectra is less diverse and in better agreement with CDNC estimates consistently derived from the observations (average NMB −13 % and −22 % for updraft velocities 0.3 and 0.6 m s−1, respectively). In addition, simulated CDNC is in slightly better agreement with observationally derived values at lower than at higher updraft velocities (index of agreement 0.64 vs. 0.65). The reduced spread of CDNC compared to that of CCN is attributed to the sublinear response of CDNC to aerosol particle number variations and the negative correlation between the sensitivities of CDNC to aerosol particle number concentration (∂Nd/∂Na) and to updraft velocity (∂Nd/∂w). Overall, we find that while CCN is controlled by both aerosol particle number and composition, CDNC is sensitive to CCN at low and moderate CCN concentrations and to the updraft velocity when CCN levels are high. Discrepancies are found in sensitivities ∂Nd/∂Na and ∂Nd/∂w; models may be predisposed to be too “aerosol sensitive” or “aerosol insensitive” in aerosol–cloud–climate interaction studies, even if they may capture average droplet numbers well. This is a subtle but profound finding that only the sensitivities can clearly reveal and may explain inter-model biases on the aerosol indirect effect.

We introduce and evaluate aerosol simulations with the global aerosol–climate model ECHAM6.3–HAM2.3, which is the aerosol component of the fully coupled aerosol–chemistry–climate model ECHAM–HAMMOZ. Both the host atmospheric climate model ECHAM6.3 and the aerosol model HAM2.3 were updated from previous versions. The updated version of the HAM aerosol model contains improved parameterizations of aerosol processes such as cloud activation, as well as updated emission fields for anthropogenic aerosol species and modifications in the online computation of sea salt and mineral dust aerosol emissions. Aerosol results from nudged and free-running simulations for the 10-year period 2003 to 2012 are compared to various measurements of aerosol properties. While there are regional deviations between the model and observations, the model performs well overall in terms of aerosol optical thickness, but may underestimate coarse-mode aerosol concentrations to some extent so that the modeled particles are smaller than indicated by the observations. Sulfate aerosol measurements in the US and Europe are reproduced well by the model, while carbonaceous aerosol species are biased low. Both mineral dust and sea salt aerosol concentrations are improved compared to previous versions of ECHAM–HAM. The evaluation of the simulated aerosol distributions serves as a basis for the suitability of the model for simulating aerosol–climate interactions in a changing climate.

The Community Intercomparison Suite (CIS) is an easy-to-use command-line tool which has been developed to allow the straightforward intercomparison of remote sensing, in situ and model data. While there are a number of tools available for working with climate model data, the large diversity of sources (and formats) of remote sensing and in situ measurements necessitated a novel software solution. Developed by a professional software company, CIS supports a large number of gridded and ungridded data sources "out-of-the-box", including climate model output in NetCDF or the UK Met Office pp file format, CloudSat, CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization), MODIS (MODerate resolution Imaging Spectroradiometer), Cloud and Aerosol CCI (Climate Change Initiative) level 2 satellite data and a number of in situ aircraft and ground station data sets. The open-source architecture also supports user-defined plugins to allow many other sources to be easily added. Many of the key operations required when comparing heterogenous data sets are provided by CIS, including subsetting, aggregating, collocating and plotting the data. Output data are written to CF-compliant NetCDF files to ensure interoperability with other tools and systems. The latest documentation, including a user manual and installation instructions, can be found on our website (http://cistools.net). Here, we describe the need which this tool fulfils, followed by descriptions of its main functionality (as at version 1.4.0) and plugin architecture which make it unique in the field.

Abstract Background Completion of multiple dose vaccine schedules is crucial to ensure a protective immune response, and maximise vaccine cost-effectiveness. While barriers and facilitators to vaccine uptake have recently been reviewed, there is no comprehensive review of factors influencing subsequent adherence or completion, which is key to achieving vaccine effectiveness. This study identifies and summarises the literature on factors affecting completion of multi-dose vaccine schedules by adolescents. Methods Ten online databases and four websites were searched (February 2014). Studies with analysis of factors predicting completion of multi-dose vaccines were included. Study participants within 9–19 years of age were included in the review. The defined outcome was completion of the vaccine series within 1 year among those who received the first dose. Results Overall, 6159 abstracts were screened, and 502 full texts were reviewed. Sixty one studies were eligible for this review. All except two were set in high-income countries. Included studies evaluated human papillomavirus vaccine, hepatitis A, hepatitis B, and varicella vaccines. Reported vaccine completion rates, among those who initiated vaccination, ranged from 27 % to over 90 %. Minority racial or ethnic groups and inadequate health insurance coverage were risk factors for low completion, irrespective of initiation rates. Parental healthcare seeking behaviour was positively associated with completion. Vaccine delivery in schools was associated with higher completion than delivery in the community or health facilities. Gender, prior healthcare use and socio-economic status rarely remained significant risks or protective factors in multivariate analysis. Conclusions Almost all studies investigating factors affecting completion have been carried out in developed countries and investigate a limited range of variables. Increased understanding of barriers to completion in adolescents will be invaluable to future new vaccine introductions and the further development of an adolescent health platform. PROSPERO reg# CRD42014006765.

The fangtooth moray, Enchelycore anatina (Lowe, 1838), native to the eastern Atlantic Ocean but also known from eastern sections of the Mediterranean, is recorded for the first time from Maltese coastal waters in the central Mediterranean. This record is the westernmost one within the Mediterranean and the observed E. anatina individual co-occurred with an individual of Muraena helena Linnaeus, 1758.

Islet cell transplantation as a therapy for type 1 diabetes has been limited by progressive graft loss. Significant immunosuppression including T-cell ablation has been used in an attempt to limit islet rejection. Here, we show that CD3 + lymphocytes depleted of alloreactive T cells selected from a mixed lymphocyte reaction (MLR), where responder BALB/c splenocytes stained with carboxyfluorescein succinimidyl ester (CFSE) were stimulated with irradiated C57BL/6 splenocytes for 5 days, infused into diabetic immunodeficient mice are capable of restoring a broad T-cell repertoire and specifically do not reject islet transplants from the strain (C57BL/6) used in the original depletion. These mice demonstrate reconstitution with CD4 + and CD8 + T cells, the capacity to reject third-party grafts (CBA), and restoration of interferon-γ (IFN-γ) responses to third-party alloantigens. Over time, both forkhead box P3-positive (Foxp3 + ) T regulatory cells (Tregs) and γδ T cells expand, suggesting a role for peripheral tolerance, in addition to the initial depletion of alloreactive T cells, in long-term islet graft survival. Our results suggest that immune restoration with CD3 + lymphocytes where alloreactive T cells are removed can restore cognate immunity without islet allograft loss and recurrence of diabetes.