Analysis of thermal infrared satellite measurements of umbrella clouds generated by volcanic eruptions suggests that asymptotic gravity current models of the temporal (t) radial (r) spreading (r ~tf, f < 1) of the umbrella-shaped intrusion do not adequately explain the observations. Umbrella clouds from 13 volcanic eruptions are studied using satellite data that have spatial resolutions of ~4–25 km2 and temporal resolutions of 1–60 minutes. The umbrella cloud morphology is evaluated using digital image processing tools in a Lagrangian frame of reference. At the onset of neutral buoyancy, the radial spreading is better explained by a stronger dependence on time of r ~ t, rather than t2/3, t3/4, or t2/9. This flow regime exists on the order of minutes and has not been observed previously in satellite data. This may be of significance as it provides a means to rapidly (within the first 2–3 observations) determine the volumetric eruption rate. A hyperbolic tangent model, r ~ tanh(t) is presented that matches the entire radial spreading time history and has a conserved torus-shaped volume in which the intrusion depth is proportional to sech(t). This model also predicts the observed radial velocities. The data and the model estimates of the volumetric flow rate for the 15 January 2022 Hunga eruption are found to be 3.6–5 × 1011 m3s−1, the largest ever measured.

Understanding the relationship between the mass eruption rate (MER) and volcanic column height is essential for both real-time volcanic hazard management and reconstruction of past explosive eruptions. Using 134 eruptive events from the new Independent Volcanic Eruption Source Parameter Archive (IVESPA, v1.0), we constrain bespoke empirical MER-height relationships for four measures of column height: spreading level, sulfur dioxide height, and two measures of top height, from direct observations and as reconstructed from deposits. These relationships show significant differences, and we discuss implications for their applications in ash dispersion forecasting and modelling volcanic climate impacts. The roles of atmospheric stratification, wind, and humidity remain challenging to detect across the wide range of eruptive conditions spanned in IVESPA, ultimately resulting in empirical relationships outperforming analytical scaling relationships and the Geneva 1-dimensional (1D) volcanic plume model accounting for atmospheric conditions. However, when excluding the IVESPA events with the highest uncertainties, the 1D model progressively outperforms the empirical MER-height relationship. Our findings highlight persisting challenges in constraining the MER-height relation and reinforce the need for improved eruption source parameter databases documenting uncertainties, as well as improved physics-based models.

The April 2021 explosive eruption of La Soufrière, St Vincent, produced plumes of ash and SO2 which were observed with multiple satellite instruments. In this project these were studied with the Advanced Baseline Imager (ABI) on the Geostationary Operational Environmental Satellite (GOES) and the Infrared Atmospheric Sounding Interferometer (IASI) onboard the three MetOp satellites.The high temporal resolution of the ABI instrument (1-10 minutes) was used to identify the approximate start and end times of each eruptive event during the 14-day eruption. There were a minimum of 35 explosive events which have been divided into four phases. The first was an initial explosive event, which was followed by a sustained event lasting over nine hours. The eruption then entered a pulsatory phase which consisted of 25 explosive events in a 65.3 hour period. Finally, there was a waning sequence of events. Over the final two phases, the duration of each event and the repose time between them was shown to increase.The IASI instrument has sensitivity to sulfur dioxide (SO2) which can be exploited to flag pixels containing SO2 and then to quantify the amount and height. Using IASI data, the SO2 plume was tracked as it was transported around the globe between –45 and 45° N. The retrievals showed a complex structure to the plume which may reflect the multiple explosive events that occurred. Most of the SO2 was shown to be in the upper troposphere and lower stratosphere. A peak SO2 mass loading of 0.31 ± 0.09 Tg occurred on 13 April a few days after the eruption began. The total mass values were converted into fluxes, with the highest fluxes occurring in the first few days of the eruption. In total it is estimated that the eruption emitted 0.63 ± 0.5 Tg of SO2.A number of similarities between the 1979 and 2021 eruptions of La Soufrière were observed in this study. These include the sequence of events with both eruptions including a pulsatory phase and the plume heights. These similarities highlight the value of these studies for better understanding eruptive events.

The Arctic is experiencing heightened precipitation, affected by aerosols impacting rainfall and snowfall. However, sparse aerosol observations in the central Arctic cryosphere contribute to uncertainties in simulating aerosol-precipitation two-way interaction. This study examines aerosol-precipitation co-variation in various climate models during the Arctic spring and summer seasons from 2003 to 2011, leveraging satellite-based aerosol data and various CMIP6 climate models. Findings reveal significant spatio-temporal biases between models and observations. Snowfall dominance occurs in models where total AOD surpasses the observation by 121% (57–186%, confidence interval), intensifying simulated snowfall by two times compared to rainfall during summer. Consequently, climate models tend to underestimate central Arctic rainfall to the total precipitation ratio, suggesting a positive bias towards snowfall dominance. This highlights the importance of constraining total AOD and associated aerosol schemes in climate models using satellite measurements, which potentially could lead to a substantial reduction in snowfall contribution to the total precipitation ratio in the central Arctic, contrary to current multi-model simulations across various spatiotemporal scales.

Atmospheric aerosols have pronounced effects on climate at both regional and global scales, but the magnitude of these effects is subject to considerable uncertainties. A major contributor to these uncertainties is an incomplete understanding of the vertical structure of aerosol, largely due to observational limitations. Spaceborne lidars can directly observe the vertical distribution of aerosols globally and are increasingly used in atmospheric aerosol remote sensing. As the first spaceborne high-spectral-resolution lidar (HSRL), the Atmospheric LAser Doppler INstrument (ALADIN) on board the Aeolus satellite was operational from 2018 to 2023. ALADIN data can be used to estimate aerosol extinction and co-polar backscatter coefficients separately without an assumption of the lidar ratio. This study assesses the performance of ALADIN's aerosol retrieval capabilities by comparing them with Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) measurements. A statistical analysis of retrievals from both instruments during the June 2020 Saharan dust event indicates consistency between the observed backscatter and extinction coefficients. During this extreme dust event, CALIOP-derived aerosol optical depth (AOD) exhibited large discrepancies with Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua measurements. Using collocated ALADIN observations to revise the dust lidar ratio to 63.5 sr, AODs retrieved from CALIOP are increased by 46 %, improving the comparison with MODIS data. The combination of measurements from ALADIN and CALIOP can enhance the tracking of aerosols' vertical transport. This study demonstrates the potential for spaceborne HSRL to retrieve aerosol optical properties. It highlights the benefits of spaceborne HSRL in directly obtaining the lidar ratio, significantly reducing uncertainties in extinction retrievals.

Volcanic ash clouds are carefully monitored as they present a significant hazard to humans and aircraft. The primary tool for forecasting the transport of ash from a volcano is dispersion modeling. These models make a number of assumptions about the size, sphericity and density of the ash particles. Few studies have measured the density of ash particles or explored the impact that the assumption of ash density might have on the settling dynamics of ash particles. In this paper, the raw apparent density of 23 samples taken from 15 volcanoes are measured with gas pycnometry, and a negative linear relationship is found between the density and the silica content. For the basaltic ash samples, densities were measured for different particle sizes, showing that the density is approximately constant for particles smaller than 100 μm, beyond which it decreases with size. While this supports the current dispersion model used by the London Volcanic Ash Advisory Centre (VAAC), where the density is held at a constant (2.3 g cm), inputting the measured densities into a numerical simulation of settling velocity reveals a primary effect from the silica content changing this constant. The VAAC density overestimates ash removal times by up to 18%. These density variations, including those varying with size beyond 100 μm, also impact short-range particle-size distribution measurements and satellite retrievals of ash.

Extreme biomass burning (BB) events, such as those seen during the 2019–2020 Australian bushfire season, are becoming more frequent and intense with climate change. Ground-based observations of these events can provide useful information on the macro- and micro-physical properties of the plumes, but these observations are sparse, especially in regions which are at risk of intense bushfire events. Satellite observations of extreme BB events provide a unique perspective, with the newest generation of geostationary imagers, such as the Advanced Himawari Imager (AHI), observing entire continents at moderate spatial and high temporal resolution. However, current passive satellite retrieval methods struggle to capture the high values of aerosol optical thickness (AOT) seen during these BB events. Accurate retrievals are necessary for global and regional studies of shortwave radiation, air quality modelling and numerical weather prediction. To address these issues, the Optimal Retrieval of Aerosol and Cloud (ORAC) algorithm has used AHI data to measure extreme BB plumes from the 2019–2020 Australian bushfire season. The sensitivity of the retrieval to the assumed optical properties of BB plumes is explored by comparing retrieved AOT with AErosol RObotic NETwork (AERONET) level-1.5 data over the AERONET site at Tumbarumba, New South Wales, between 1 December 2019 at 00:00 UTC and 3 January 2020 at 00:00 UTC. The study shows that for AOT values > 2, the sensitivity to the assumed optical properties is substantial. The ORAC retrievals and AERONET data are compared against the Japan Aerospace Exploration Agency (JAXA) Aerosol Retrieval Product (ARP), Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue over land, MODIS MAIAC, Sentinel-3 SYN and VIIRS Deep Blue products. The comparison shows the ORAC retrieval significantly improves coverage of optically thick plumes relative to the JAXA ARP, with approximately twice as many pixels retrieved and peak retrieved AOT values 1.4 times higher than the JAXA ARP. The ORAC retrievals have accuracy scores of 0.742–0.744 compared to the values of 0.718–0.833 for the polar-orbiting satellite products, despite successfully retrieving approximately 28 times as many pixels over the study period as the most successful polar-orbiting satellite product. The AHI and MODIS satellite products are compared for three case studies covering a range of BB plumes over Australia. The results show good agreement between all products for plumes with AOT values ≤ 2. For extreme BB plumes, the ORAC retrieval finds values of AOT > 15, significantly higher than those seen in events classified as extreme by previous studies, although with high uncertainty. A combination of hard limits in the retrieval algorithms and misclassification of BB plumes as cloud prevents the JAXA and MODIS products from returning AOT values significantly greater than 5.

Abstract Rapid and simple estimation of the mass eruption rate (MER) from column height is essential for real‐time volcanic hazard management and reconstruction of past explosive eruptions. Using 134 eruptive events from the new Independent Volcanic Eruption Source Parameter Archive (IVESPA, v1.0), we explore empirical MER‐height relationships for four measures of column height: spreading level, sulfur dioxide height, and top height from direct observations and as reconstructed from deposits. These relationships show significant differences and highlight limitations of empirical models currently used in operational and research applications. The roles of atmospheric stratification, wind, and humidity remain challenging to detect across the wide range of eruptive conditions spanned in IVESPA, ultimately resulting in empirical relationships outperforming analytical models that account for atmospheric conditions. This finding highlights challenges in constraining the MER‐height relation using heterogeneous observations and empirical models, which reinforces the need for improved eruption source parameter data sets and physics‐based models.

Volcanic ash clouds are carefully monitored as they present a significant hazard to humans and aircraft. The primary tool for forecasting the transport of ash from a volcano is dispersion modelling. These models make a number of assumptions about the size, sphericity and density of the ash particles. Few studies have measured the density of ash particles or explored the impact that the assumption of ash density might have on the output of a dispersion model. In this paper, the raw apparent density of 23 samples taken from 15 volcanoes are measured with gas pycnometry, and a negative linear relationship is found between the density and the silica content. For the basaltic ash samples, densities were measured for different particle sizes, showing that the density is approximately constant for particles smaller than 100 μm. There is a deviation in density of up to 25% from the operational model currently used by the London Volcanic Ash Advisory Centre (VAAC); by inputting the measured density-size relationship into a numerical simulation, up to 18% difference in ash fallout time was found, with the VAAC model overestimating ash removal times.

Atmospheric aerosols and their interaction with clouds are the largest uncertainty in the human forcing of the climate system. Anthropogenic emissions have increased aerosol concentrations, increasing the concentration of cloud droplets and leading to reductions in droplet size and increases in cloud reflectivity (a negative radiative forcing). Central to this climate impact is the susceptibility of cloud droplet number to aerosol. This susceptibility varies widely with the method and data used to estimate it and within global climate models, explaining much of the variation in estimates of the radiative forcing from aerosol-cloud interactions (RFaci). Better constraints on the susceptibility have been a key target for recent observation-based constraints on the aerosol forcing. Previous work has shown that the aerosol burden of the clean, pre-industrial atmosphere has been demonstrated as a key uncertainty for the aerosol forcing. Here we show that the behaviour of clouds under these clean conditions is of equal importance for understanding the spread in radiative forcing estimates between models and observations. This means that the uncertainty in the aerosol impact on clouds is, counterintuitively, driven by situations with little aerosol. Removing these clean conditions from observational estimates of the susceptibility produces a close agreement between different model and observational estimates of the cloud response to aerosol, but does not provide a strong constraint on the RFaci. If we are to produce tighter constraints on the radiative forcing from aerosol-cloud interactions, better constraints on the behaviour of cloud in keen conditions are vital.

On 15 January 2022, the Hunga Tonga–Hunga Ha’apai (HTHH) eruption injected 146 MtH2O and 0.42 MtSO2 into the stratosphere. This large water vapour perturbation means that HTHH will probably increase the net radiative forcing, unusual for a large volcanic eruption, increasing the chance of the global surface temperature anomaly temporarily exceeding 1.5 °C over the coming decade. Here we estimate the radiative response to the HTHH eruption and derive the increased risk that the global mean surface temperature anomaly shortly exceeds 1.5 °C following the eruption. We show that HTHH has a tangible impact of the chance of imminent 1.5 °C exceedance (increasing the chance of at least one of the next 5 years exceeding 1.5 °C by 7%), but the level of climate policy ambition, particularly the mitigation of short-lived climate pollutants, dominates the 1.5 °C exceedance outlook over decadal timescales. The Hunga Tonga–Hunga Ha’apai eruption in January 2022 injected large amounts of water vapour into the atmosphere. Here, the authors show that this can cause additional warming over the next years, which increases the likelihood of exceeding 1.5 °C warming over a short time period.

Abstract. Atmospheric aerosols and their impact on cloud properties remain the largest uncertainty in the human forcing of the climate system. By increasing the concentration of cloud droplets (Nd), aerosols reduce droplet size and increase the reflectivity of clouds (a negative radiative forcing). Central to this climate impact is the susceptibility of cloud droplet number to aerosol (β), the diversity of which explains much of the variation in the radiative forcing from aerosol–cloud interactions (RFaci) in global climate models. This has made measuring β a key target for developing observational constraints of the aerosol forcing. While the aerosol burden of the clean, pre-industrial atmosphere has been demonstrated as a key uncertainty for the aerosol forcing, here we show that the behaviour of clouds under these clean conditions is of equal importance for understanding the spread in radiative forcing estimates between models and observations. This means that the uncertainty in the aerosol impact on clouds is, counterintuitively, driven by situations with little aerosol. Discarding clean conditions produces a close agreement between different model and observational estimates of the cloud response to aerosol but does not provide a strong constraint on the RFaci. This makes constraining aerosol behaviour in clean conditions an important goal for future observational studies.

Field-portable Open Path Fourier Transform Infrared (OP-FTIR) spectrometers can be used to remotely measure the composition of volcanic plumes using absorption spectroscopy, providing invaluable data on total gas emissions. Quantifying the temporal evolution of gas compositions during an eruption helps develop models of volcanic processes and aids in eruption forecasting. Absorption measurements require a viewing geometry which aligns infrared source, plume, and instrument, which can be challenging. Here, we present a fast retrieval algorithm to estimate quantities of gas, ash and sulphate aerosols from thermal emission OP-FTIR measurements, and the results from two pilot campaigns on Stromboli volcano in Italy in 2019 and 2021. We validate the method by comparing time series of SO2 slant column densities retrieved using our method with those obtained from a conventional UV spectrometer, demonstrating that the two methods generally agree to within a factor of 2. The algorithm correctly identifies ash-rich plumes and gas bursts associated with explosions and quantifies the mass column densities and particle sizes of ash and sulphate aerosols (SA) in the plume. We compare the ash sizes retrieved using our method with the particle size distribution (PSD) of an ash sample collected during the period of measurements in 2019 by flying a Remotely Piloted Aircraft System into the path of a drifting ash plume and find that both modes of the bimodal PSD (a fine fraction with diameter around 5–10 μm and a coarse fraction around 65 μm) are identified within our datasets at different times. We measure a decrease in the retrieved ash particle size with distance downwind, consistent with settling of larger particles, which we also observed visually. We measure a decrease in the SO2/SA ratio as the plume travels downwind, coupled with an increase in measured SA particle size (range 2–6 μm), suggesting rapid hygroscopic particle growth and/or SO2 oxidation. We propose that infrared emission spectroscopy can be used to examine physical and chemical changes during plume transport and opens the possibility of remote night-time monitoring of volcanic plume emissions. These ground-based analyses may also aid the refinement of satellite-based aerosol retrievals.

Supplementary tables and MATLAB scripts associated with the manuscript "New insights into the relationship between mass eruption rate and volcanic column height based on the IVESPA dataset".

Due to the remote location of many volcanoes, there is substantial uncertainty about the timing, amount and vertical distribution of volcanic ash released when they erupt. One approach to determine these properties is to combine prior estimates with satellite retrievals and simulations from atmospheric dispersion models to create posterior emission estimates, constrained by both the observations and the prior estimates, using a technique known as source inversion. However, the results are dependent not only on the accuracy of the prior assumptions, the atmospheric dispersion model and the observations used, but also on the accuracy of the meteorological data used in the dispersion simulations. In this study, we advance the source inversion approach by using an ensemble of meteorological data from the Met Office Global and Regional Ensemble Prediction System to represent the uncertainty in the meteorological data and apply it to the 2019 eruption of Raikoke. Retrievals from the Himawari-8 satellite are combined with NAME dispersion model simulations to create posterior emission estimates. The use of ensemble meteorology provides confidence in the posterior emission estimates and associated dispersion simulations that are used to produce ash forecasts. Prior mean estimates of fine volcanic ash emissions for the Raikoke eruption based on plume height observations are more than 15 times higher than any of the mean posterior ensemble estimates. In addition, the posterior estimates have a different vertical distribution, with 27 %–44 % of ash being emitted into the stratosphere compared to 8 % in the mean prior estimate. This has consequences for the long-range transport of ash, as deposition to the surface from this region of the atmosphere happens over long timescales. The posterior ensemble spread represents uncertainty in the inversion estimate of the ash emissions. For the first 48 h following the eruption, the prior ash column loadings lie outside an estimate of the error associated with a set of independent satellite retrievals, whereas the posterior ensemble column loadings do not. Applying a risk-based methodology to an ensemble of dispersion simulations using the posterior emissions shows that the area deemed to be of the highest risk to aviation, based on the fraction of ensemble members exceeding predefined ash concentration thresholds, is reduced by 49 %. This is compared to estimates using an ensemble of dispersion simulations using the prior emissions with ensemble meteorology. If source inversion had been used following the eruption of Raikoke, it would have had the potential to significantly reduce disruptions to aviation operations. The posterior inversion emission estimates are also sensitive to uncertainty in other eruption source parameters and internal dispersion model parameters. Extending the ensemble inversion methodology to account for uncertainty in these parameters would give a more complete picture of the emission uncertainty, further increasing confidence in these estimates.

Sulfuric acid is shown to form a core-shell particle on a micron-sized, optically-trapped spherical silica bead. The refractive indices of the silica and sulfuric acid, along with the shell thickness and bead radius were determined by reproducing Mie scattered optical white light as a function of wavelength in Mie spectroscopy. Micron-sized silica aerosols (silica beads were used as a proxy for atmospheric silica minerals) were levitated in a mist of sulfuric acid particles; continuous collection of Mie spectra throughout the collision of sulfuric acid aerosols with the optically trapped silica aerosol demonstrated that the resulting aerosol particle had a core-shell morphology. Contrastingly, the collision of aqueous sulfuric acid aerosols with optically trapped polystyrene aerosol resulted in a partially coated system. The light scattering from the optically levitated aerosols was successfully modelled to determine the diameter of the core aerosol (±0.003 μm), the shell thickness (±0.0003 μm) and the refractive index (±0.007). The experiment demonstrated that the presence of a thin film rapidly changed the light scattering of the original aerosol. When a 1.964 μm diameter silica aerosol was covered with a film of sulfuric acid 0.287 μm thick, the wavelength dependent Mie peak positions resembled sulfuric acid. Thus mineral aerosol advected into the stratosphere would likely be coated with sulfuric acid, with a core-shell morphology, and its light scattering properties would be effectively indistinguishable from a homogenous sulfuric acid aerosol if the film thickness was greater than a few 100 s of nm for UV-visible wavelengths.

Volcanic eruptions eject large amounts of ash and trace gases such as sulfur dioxide (SO2) into the atmosphere. A significant difficulty in mitigating the impact of volcanic SO2 clouds on air traffic safety is that these gas emissions can be rapidly transported over long distances. The use of space-borne instruments enables the global monitoring of volcanic SO2 emissions in an economical and risk-free manner. Within the European Space Agency (ESA) Sentinel-5p+ Innovation project, the S5P SO2 layer height (S5P+I: SO2LH) activities led to the improvements of the retrieval algorithm and generation of the corresponding near real-time S5P SO2 LH products. These are currently operationally provided, in near real-time, by the German Aerospace Center (DLR) within the framework of the Innovative Products for Analyses of Atmospheric Composition (INPULS) project. The main aim of this paper is to present its extensive verification, accomplished within the S5P+I: SO2LH project, over major recent volcanic eruptions, against collocated space-borne measurements from the IASI/Metop and CALIOP/CALIPSO instruments as well as assess its impact on the forecasts provided by the Copernicus Atmospheric Monitoring Service (CAMS). The mean difference between S5P and IASI observations for the Raikoke 2019, the Nishinoshima 2020 and the La Soufrière-St Vincent 2021 eruptive periods is ∼ 0.5 ± 3 km, while for the Taal 2020 eruption, a larger difference was found, between 3 ± 3 km and 4 ± 3 km. The comparison of the daily mean SO2 LH further demonstrates the capabilities of this near real-time product, with slopes between 0.8 and 1 and correlation coefficients ranging between 0.6 and 0.8. Comparisons between the S5P SO2 LH and the CALIOP/CALIPSO ash plumes revealed an expected bias at −2.5 ± 2 km, considering that the injected SO2 and ash plume locations do not always coincide over an eruption. Furthermore, the CAMS assimilation of the S5P SO2 LH product led to much improved model output against the non-assimilated IASI LH, with a mean difference of 1.5 ± 2 km, compared to the original CAMS analysis, and improved the geographical spread of the Raikoke volcanic plume following the eruptive days.

After the eruption of volcanoes around the world, monitoring of the dispersion of ash in the atmosphere is an important task for satellite remote sensing since ash represents a threat to air traffic. In this work we present a novel method, tailored for Eyjafjallajökull ash but applicable to other eruptions as well, that uses thermal observations of the SEVIRI imager aboard the geostationary Meteosat Second Generation satellite to detect ash clouds and determine their mass column concentration and top height during the day and night. This approach requires the compilation of an extensive data set of synthetic SEVIRI observations to train an artificial neural network. This is done by means of the RTSIM tool that combines atmospheric, surface and ash properties and runs automatically a large number of radiative transfer calculations for the entire SEVIRI disk. The resulting algorithm is called “VADUGS” (Volcanic Ash Detection Using Geostationary Satellites) and has been evaluated against independent radiative transfer simulations. VADUGS detects ash-contaminated pixels with a probability of detection of 0.84 and a false-alarm rate of 0.05. Ash column concentrations are provided by VADUGS with correlations up to 0.5, a scatter up to 0.6 g m−2 for concentrations smaller than 2.0 g m−2 and small overestimations in the range 5 %–50 % for moderate viewing angles 35–65∘, but up to 300 % for satellite viewing zenith angles close to 90 or 0∘. Ash top heights are mainly underestimated, with the smallest underestimation of −9 % for viewing zenith angles between 40 and 50∘. Absolute errors are smaller than 70 % and with high correlation coefficients of up to 0.7 for ash clouds with high mass column concentrations. A comparison with spaceborne lidar observations by CALIPSO/CALIOP confirms these results: For six overpasses over the ash cloud from the Puyehue-Cordón Caulle volcano in June 2011, VADUGS shows similar features as the corresponding lidar data, with a correlation coefficient of 0.49 and an overestimation of ash column concentration by 55 %, although still in the range of uncertainty of CALIOP. A comparison with another ash algorithm shows that both retrievals provide plausible detection results, with VADUGS being able to detect ash further away from the Eyjafjallajökull volcano, but sometimes missing the thick ash clouds close to the vent. VADUGS is run operationally at the German Weather Service and this application is also presented.

Abstract. Due to the remote location of many volcanoes, there is large uncertainty in the timing, amount and vertical distribution of volcanic ash released when they erupt. One approach to determine these properties is to combine prior estimates with satellite retrievals and simulations from atmospheric dispersion models to create posterior emissions estimates constrained by both the observations and the prior estimates using a technique known as source inversion. However, the results are dependent not only on the accuracy of the prior assumptions, the atmospheric dispersion model and the observations used but also the accuracy of the meteorological data used in the dispersion simulations. In this study we advance the source inversion approach by using an ensemble of meteorological data to represent the uncertainty in the meteorological data and apply it to the 2019 eruption of Raikoke. This provides confidence in the posterior emission estimates and associated dispersion simulations that are used to produce ash forecasts. Prior mean estimates of fine volcanic ash emissions for the Raikoke eruption based on plume height observations are more than 15 times higher than any of the mean posterior ensemble estimates. In addition, the posterior estimates have a different vertical distribution with 27–44 % of ash being emitted into the stratosphere compared to 8 % in the mean prior estimate. This has consequences for the long-range transport of ash as deposition to the surface from this region of the atmosphere happens over long time-scales. The posterior ensemble spread represents uncertainty in the inversion estimate of the ash emissions. For the first 48 hours following the eruption, the prior ash column loadings lie outside an estimate of the error associated with a set of independent satellite retrievals whereas the posterior ensemble column loadings do not. Applying a risk-based methodology to an ensemble of dispersion simulations using the posterior emissions shows that the area deemed to be highest risk to aviation, based on the fraction of ensemble members exceeding predefined ash concentration thresholds, is reduced by 51 % compared to estimates using an ensemble of dispersion simulations using the prior emissions with ensemble meteorology. If source inversion had been used following the eruption of Raikoke it would have had the potential to significantly reduce the disruption to aviation operations. The posterior inversion emission estimates are also sensitive to uncertainty in other eruption source parameters (e.g., the ash density and size distribution) and internal dispersion model parameters (e.g., parameters relating to the turbulence parameterisation). Extending the ensemble inversion methodology to account for uncerainty in these parameters would give a more complete picture of the emission uncertainty, further increasing confidence in these estimates.

Estimates of the anthropogenic effective radiative forcing (ERF) trend have increased by 50% since 2000 (from +0.4 W m(-2) decade(-1) in 2000-09 to +0.6 W m(-2) decade(-1) in 2010-19), the majority of which is driven by changes in the aerosol ERF trend, as a result of aerosol emissions reductions. Here we study the extent to which observations of the climate system agree with these ERF assumptions. We use a large ERF ensemble from the IPCC's Sixth Assessment Report (AR6) to attribute the anthropogenic contributions to global mean surface temperature (GMST), top-of-atmosphere radiative flux, and we use aerosol optical depth observations. The GMST trend has increased from +0.18 degrees C decade(-1) in 2000-09 to +0.35 degrees C decade(-1) in 2010-19, coinciding with the anthropogenic warming trend rising from +0.19 degrees C decade(-1) in 2000-09 to +0.24 degrees C decade(-1) in 2010-19. This, as well as observed trends in top-of-atmosphere radiative fluxes and aerosol optical depths, supports the claim of an aerosol-induced temporary acceleration in the rate of warming. However, all three observation datasets additionally suggest that smaller aerosol ERF trend changes are compatible with observations since 2000, since radiative flux and GMST trends are significantly influenced by internal variability over this period. A zero-trend-change aerosol ERF scenario results in a much smaller anthropogenic warming acceleration since 2000 but is poorly represented in AR6's ERF ensemble. Short-term ERF trends are difficult to verify using observations, so caution is required in predictions or policy judgments that depend on them, such as estimates of current anthropogenic warming trend, and the time remaining to, or the outstanding carbon budget consistent with, 1.5 degrees C warming. Further systematic research focused on quantifying trends and early identification of acceleration or deceleration is required.