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Perturbations to the global climate system changed from net cooling to net heating during the first month after the 2022 Hunga Tonga-Hunga Ha-apai eruption, according to radiative forcing estimates based on satellite, ground-based, in situ and radiosonde observations.

ABSTRACT: The purpose of this study was to evaluate the effect of 6 different feeding systems (based on corn silage as the main ingredient) on the chemical composition of milk and to highlight the potential of untargeted metabolomics to find discriminant marker compounds of different nutritional strategies. Interestingly, the multivariate statistical analysis discriminated milk samples mainly according to the high-moisture ear corn (HMC) included in the diet formulation. Overall, the most discriminant compounds, identified as a function of the HMC, belonged to AA (10 compounds), peptides (71 compounds), pyrimidines (38 compounds), purines (15 compounds), and pyridines (14 compounds). The discriminant milk metabolites were found to significantly explain the metabolic pathways of pyrimidines and vitamin B6. Interestingly, pathway analyses revealed that the inclusion of HMC in the diet formulation strongly affected the pyrimidine metabolism in milk, determining a significant up-accumulation of pyrimidine degradation products, such as 3-ureidopropionic acid, 3-ureidoisobutyric acid, and 3-aminoisobutyric acid. Also, some pyrimidine intermediates (such as l-aspartic acid, N-carbamoyl-l-aspartic acid, and orotic acid) were found to possess a high discrimination degree. Additionally, our findings suggested that the inclusion of alfalfa silage in the diet formulation was potentially correlated with the vitamin B6 metabolism in milk, being 4-pyridoxic acid (a pyridoxal phosphate degradation product) the most significant and up-accumulated compound. Taken together, the accumulation trends of different marker compounds revealed that both pyrimidine intermediates and degradation products are potential marker compounds of HMC-based diets, likely involving a complex metabolism of microbial nitrogen based on total splanchnic fluxes from the rumen to mammary gland in dairy cows. Also, our findings highlight the potential of untargeted metabolomics in both foodomics and foodomics-based studies involving dairy products.

We use a combination of spaceborne instruments to study the unprecedented stratospheric plume after the Tonga eruption of 15 January 2022. The aerosol plume was initially formed of two clouds at 30 and 28 km, mostly composed of submicron-sized sulfate particles, without ash, which is washed out within the first day following the eruption. The large amount of injected water vapour led to a fast conversion of SO2 to sulfate aerosols and induced a descent of the plume to 24–26 km over the first 3 weeks by radiative cooling. Whereas SO2 returned to background levels by the end of January, volcanic sulfates and water still persisted after 6 months, mainly confined between 35∘ S and 20∘ N until June due to the zonal symmetry of the summer stratospheric circulation at 22–26 km. Sulfate particles, undergoing hygroscopic growth and coagulation, sediment and gradually separate from the moisture anomaly entrained in the ascending branch Brewer–Dobson circulation. Sulfate aerosol optical depths derived from the IASI (Infrared Atmospheric Sounding Interferometer) infrared sounder show that during the first 2 months, the aerosol plume was not simply diluted and dispersed passively but rather organized in concentrated patches. Space-borne lidar winds suggest that those structures, generated by shear-induced instabilities, are associated with vorticity anomalies that may have enhanced the duration and impact of the plume.

Excessive numerical diffusion is one of the major limitations in the representation of long-range transport by chemistry transport models. In the present study, we focus on excessive diffusion in the vertical direction, which has been shown to be a major issue, and we explore three possible ways of addressing this problem: increasing the vertical resolution, using an advection scheme with anti-diffusive properties and more accurately representing the vertical wind. This study was carried out using the CHIMERE chemistry transport model for the 18 March 2012 eruption of Mount Etna, which released about 3 kt of sulfur dioxide into the atmosphere in a plume that was observed by satellite instruments (the Infrared Atmospheric Sounding Interferometer instrument, IASI, and the Ozone Monitoring Instrument, OMI) for several days. The change from the classical Van Leer (1977) scheme to the Després and Lagoutière (1999) anti-diffusive scheme in the vertical direction was shown to provide the largest improvement to model outputs in terms of preserving the thin plume emitted by the volcano. To a lesser extent, the improved representation of the vertical wind field was also shown to reduce plume dispersion. Both of these changes helped to reduce vertical diffusion in the model as much as a brute-force approach (increasing vertical resolution).

We present version 3 (V3) of the Cloud_cci Along-Track Scanning Radiometer (ATSR) and Advanced ATSR (AATSR) data set. The data set was created for the European Space Agency (ESA) Cloud_cci (Climate Change Initiative) programme. The cloud properties were retrieved from the second ATSR (ATSR-2) on board the second European Remote Sensing Satellite (ERS-2) spanning 1995–2003 and the AATSR on board Envisat, which spanned 2002–2012. The data are comprised of a comprehensive set of cloud properties: cloud top height, temperature, pressure, spectral albedo, cloud effective emissivity, effective radius, and optical thickness, alongside derived liquid and ice water path. Each retrieval is provided with its associated uncertainty. The cloud property retrievals are accompanied by high-resolution top- and bottom-of-atmosphere shortwave and longwave fluxes that have been derived from the retrieved cloud properties using a radiative transfer model. The fluxes were generated for all-sky and clear-sky conditions. V3 differs from the previous version 2 (V2) through development of the retrieval algorithm and attention to the consistency between the ATSR-2 and AATSR instruments. The cloud properties show improved accuracy in validation and better consistency between the two instruments, as demonstrated by a comparison of cloud mask and cloud height with co-located CALIPSO data. The cloud masking has improved significantly, particularly in its ability to detect clear pixels. The Kuiper Skill score has increased from 0.49 to 0.66. The cloud top height accuracy is relatively unchanged. The AATSR liquid water path was compared with the Multisensor Advanced Climatology of Liquid Water Path (MAC-LWP) in regions of stratocumulus cloud and shown to have very good agreement and improved consistency between ATSR-2 and AATSR instruments. The correlation with MAC-LWP increased from 0.4 to over 0.8 for these cloud regions. The flux products are compared with NASA Clouds and the Earth's Radiant Energy System (CERES) data, showing good agreement within the uncertainty. The new data set is well suited to a wide range of climate applications, such as comparison with climate models, investigation of trends in cloud properties, understanding aerosol–cloud interactions, and providing contextual information for co-located ATSR-2/AATSR surface temperature and aerosol products. The following new digital identifier has been issued for the Cloud_cci ATSR-2/AATSRv3 data set: https://doi.org/10.5676/DWD/ESA_Cloud_cci/ATSR2-AATSR/V003 (Poulsen et al., 2019).

We developed an optimal-estimation algorithm to simultaneously retrieve, for the first time, coexisting volcanic gaseous SO2 and sulfate aerosols (SA) from ground-based Fourier transform infrared (FTIR) observations. These effluents, both linked to magmatic degassing process and subsequent atmospheric evolution processes, have overlapping spectral signatures leading to mutual potential interferences when retrieving one species without considering the other. We show that significant overestimations may be introduced in SO2 retrievals if the radiative impact of coexistent SA is not accounted for, which may have impacted existing SO2 long-term series, e.g. from satellite platforms. The method was applied to proximal observations at Masaya volcano, where SO2 and SA concentrations, and SA acidity, were retrieved. A gas-to-particle sulfur partitioning of 400 and a strong SA acidity (sulfuric acid concentration: 65 %) were found, consistent with past in situ observations at this volcano. This method is easily exportable to other volcanoes to monitor magma extraction processes and the atmospheric sulfur cycle in the case of ash-free plumes.

Ash clouds are a geographically far-reaching hazard associated with volcanic eruptions. To minimise the risk that these pose to aircraft and to limit disruption to the aviation industry, it is important to closely monitor the emission and atmospheric dispersion of these plumes. The altitude of the plume is an important consideration and is an essential input into many models of ash cloud propagation. CO2 slicing is an established technique for obtaining the top height of aqueous clouds, and previous studies have demonstrated that there is potential for this method to be used for volcanic ash. In this study, the CO2 slicing technique has been adapted for volcanic ash and applied to spectra obtained from the Infrared Atmospheric Sounding Interferometer (IASI). Simulated ash spectra are first used to select the most appropriate channels and then demonstrate that the technique has merit for determining the altitude of the ash. These results indicate a strong match between the true heights and CO2 slicing output with a root mean square error (RMSE) of less than 800 m. Following this, the technique was applied to spectra obtained with IASI during the Eyjafjallajökull and Grímsvötn eruptions in 2010 and 2011 respectively, both of which emitted ash clouds into the troposphere, and which have been extensively studied with satellite imagery. The CO2 slicing results were compared against those from an optimal estimation scheme, also developed for IASI, and a satellite-borne lidar is used for validation. The CO2 slicing heights returned an RMSE value of 2.2 km when compared against the lidar. This is lower than the RMSE for the optimal estimation scheme (2.8 km). The CO2 slicing technique is a relatively fast tool and the results suggest that this method could be used to get a first approximation of the ash cloud height, potentially for use for hazard mitigation, or as an input for other retrieval techniques or models of ash cloud propagation.

The 6-month-long 2014–2015 Holuhraun eruption was the largest in Iceland for 200 years, emitting huge quantities of sulfur dioxide (SO2) into the troposphere, at times overwhelming European anthropogenic emissions. Weather, terrain and latitude made continuous ground-based or UV satellite sensor measurements challenging. Infrared Atmospheric Sounding Interferometer (IASI) data are used to derive the first time series of daily SO2 mass present in the atmosphere and its vertical distribution over the entire eruption period. A new optimal estimation scheme is used to calculate daily SO2 fluxes and average e-folding time every 12 h. For the 6 months studied, the SO2 flux was observed to be up to 200 kt day−1 and the minimum total SO2 erupted mass was 4.4±0.8 Tg. The average SO2 e-folding time was 2.4±0.6 days. Where comparisons are possible, these results broadly agree with ground-based near-source measurements, independent remote-sensing data and values obtained from model simulations from a previous paper. The results highlight the importance of using high-resolution time series data to accurately estimate volcanic SO2 emissions. The SO2 mass missed due to thermal contrast is estimated to be of the order of 3 % of the total emission when compared to measurements by the Ozone Monitoring Instrument. A statistical correction for cloud based on the AVHRR cloud-CCI data set suggested that the SO2 mass missed due to cloud cover could be significant, up to a factor of 2 for the plume within the first kilometre from the vent. Applying this correction results in a total erupted mass of 6.7±0.4 Tg and little change in average e-folding time. The data set derived can be used for comparisons to other ground- and satellite-based measurements and to petrological estimates of the SO2 flux. It could also be used to initialise climate model simulations, helping to better quantify the environmental and climatic impacts of future Icelandic fissure eruptions and simulations of past large-scale flood lava eruptions.

This study focuses on two new aspects of inverse modelling of volcanic emissions. First, we derive an observation operator for satellite retrievals of plume height, and second, we solve the inverse problem using an algorithm based on the 4D-Var data assimilation method. The approach is first tested in a twin experiment with simulated observations and further evaluated by assimilating IASI SO2 plume height and total column retrievals in a source term inversion for the 2010 eruption of Eyjafjallajökull. The inversion resulted in temporal and vertical reconstruction of the SO2 emissions during 1–20 May 2010 with formal vertical and temporal resolutions of 500 m and 12 h.The plume height observation operator is based on simultaneous assimilation of the plume height and total column retrievals. The plume height is taken to represent the vertical centre of mass, which is transformed into the first moment of mass (centre of mass times total mass). This makes the observation operator linear and simple to implement. The necessary modifications to the observation error covariance matrix are derived.Regularization by truncated iteration is investigated as a simple and efficient regularization method for the 4D-Var-based inversion. In the twin experiments, the truncated iteration was found to perform similarly to the commonly used Tikhonov regularization, which in turn is equivalent to a Gaussian a priori source term. However, the truncated iteration allows the level of regularization to be determined a posteriori without repeating the inversion.In the twin experiments, assimilating the plume height retrievals resulted in a 5–20 % improvement in root mean squared error but simultaneously introduced a 10–20 % low bias on the total emission depending on assumed emission profile. The results are consistent with those obtained with real data. For Eyjafjallajökull, comparisons with observations showed that assimilating the plume height retrievals reduced the overestimation of injection height during individual periods of 1–3 days, but for most of the simulated 20 days, the injection height was constrained by meteorological conditions, and assimilation of the plume height retrievals had only small impact. The a posteriori source term for Eyjafjallajökull consisted of 0.29 Tg (with total column and plume height retrievals) or 0.33 Tg (with total column retrievals only) erupted SO2 of which 95 % was injected below 11 or 12 km, respectively.

A new optimal estimation algorithm for the retrieval of volcanic ash properties has been developed for use with the Infrared Atmospheric Sounding Interferometer (IASI). The retrieval method uses the wave number range 680–1200 cm−1, which contains window channels, the CO2 ν2 band (used for the height retrieval), and the O3 ν3 band.Assuming a single infinitely (geometrically) thin ash plume and combining this with the output from the radiative transfer model RTTOV, the retrieval algorithm produces the most probable values for the ash optical depth (AOD), particle effective radius, plume top height, and effective radiating temperature. A comprehensive uncertainty budget is obtained for each pixel. Improvements to the algorithm through the use of different measurement error covariance matrices are explored, comparing the results from a sensitivity study of the retrieval process using covariance matrices trained on either clear-sky or cloudy scenes. The result showed that, due to the smaller variance contained within it, the clear-sky covariance matrix is preferable. However, if the retrieval fails to pass the quality control tests, the cloudy covariance matrix is implemented.The retrieval algorithm is applied to scenes from the Eyjafjallajökull eruption in 2010, and the retrieved parameters are compared to ancillary data sources. The ash optical depth gives a root mean square error (RMSE) difference of 0.46 when compared to retrievals from the MODerate-resolution Imaging Spectroradiometer (MODIS) instrument for all pixels and an improved RMSE of 0.2 for low optical depths (AOD

The vulnerability of the European airspace to volcanic eruptions was brought to the attention of the public and the scientific community by the 2010 eruptions of the Icelandic volcano Eyjafjallajökull. As a consequence of this event, ash concentration thresholds replaced the “zero tolerance to ash” rule, drastically changing the requirements on satellite ash retrievals. In response to that, the ESA funded several projects aiming at creating an optimal end-to-end system for volcanic ash plume monitoring and prediction. Two of them, namely the SACS-2 and SMASH projects, developed and improved dedicated satellite-derived ash plume and sulfur dioxide level assessments. The validation of volcanic ash levels and height extracted from the GOME-2 and IASI instruments on board the MetOp-A satellite is presented in this work. EARLINET lidar measurements are compared to different satellite retrievals for two eruptive episodes in April and May 2010. Comparisons were also made between satellite retrievals and aircraft lidar data obtained with the UK's BAe-146-301 Atmospheric Research Aircraft (managed by the Facility for Airborne Atmospheric Measurements, FAAM) over the United Kingdom and the surrounding regions. The validation results are promising for most satellite products and are within the estimated uncertainties of each of the comparative data sets, but more collocation scenes would be desirable to perform a comprehensive statistical analysis. The satellite estimates and the validation data sets are better correlated for high ash optical depth values, with correlation coefficients greater than 0.8. The IASI retrievals show a better agreement concerning the ash optical depth and ash layer height when compared with the ground-based and airborne lidar data.

Sulfur dioxide (SO2) is an important atmospheric constituent that plays a crucial role in many atmospheric processes. Volcanic eruptions are a significant source of atmospheric SO2 and its effects and lifetime depend on the SO2 injection altitude. The Infrared Atmospheric Sounding Interferometer (IASI) on the METOP satellite can be used to study volcanic emission of SO2 using high-spectral resolution measurements from 1000 to 1200 and from 1300 to 1410 cm−1 (the 7.3 and 8.7 µm SO2 bands) returning both SO2 amount and altitude data. The scheme described in Carboni et al. (2012) has been applied to measure volcanic SO2 amount and altitude for 14 explosive eruptions from 2008 to 2012. The work includes a comparison with the following independent measurements: (i) the SO2 column amounts from the 2010 Eyjafjallajökull plumes have been compared with Brewer ground measurements over Europe; (ii) the SO2 plumes heights, for the 2010 Eyjafjallajökull and 2011 Grimsvötn eruptions, have been compared with CALIPSO backscatter profiles. The results of the comparisons show that IASI SO2 measurements are not affected by underlying cloud and are consistent (within the retrieved errors) with the other measurements. The series of analysed eruptions (2008 to 2012) show that the biggest emitter of volcanic SO2 was Nabro, followed by Kasatochi and Grímsvötn. Our observations also show a tendency for volcanic SO2 to reach the level of the tropopause during many of the moderately explosive eruptions observed. For the eruptions observed, this tendency was independent of the maximum amount of SO2 (e.g. 0.2 Tg for Dalafilla compared with 1.6 Tg for Nabro) and of the volcanic explosive index (between 3 and 5).

The impact of volcanic emissions, especially from passive degassing and minor explosions, is a source of uncertainty in estimations of aerosol indirect effects. Observations of the impact of volcanic aerosol on clouds contribute to our understanding of both present-day atmospheric properties and of the pre-industrial baseline necessary to assess aerosol radiative forcing. We present systematic measurements over several years at multiple active and inactive volcanic islands in regions of low present-day aerosol burden. The time-averaged indirect aerosol effects within 200 km downwind of island volcanoes are observed using Moderate Resolution Imaging Spectroradiometer (MODIS, 2002–2013) and Advanced Along-Track Scanning Radiometer (AATSR, 2002–2008) data. Retrievals of aerosol and cloud properties at Kīlauea (Hawai'i), Yasur (Vanuatu) and Piton de la Fournaise (la Réunion) are rotated about the volcanic vent to be parallel to wind direction, so that upwind and downwind retrievals can be compared. The emissions from all three volcanoes – including those from passive degassing, Strombolian activity and minor explosions – lead to measurably increased aerosol optical depth downwind of the active vent. Average cloud droplet effective radius is lower downwind of the volcano in all cases, with the peak difference ranging from 2–8 μm at the different volcanoes in different seasons. Estimations of the difference in Top of Atmosphere upward Short Wave flux upwind and downwind of the active volcanoes from NASA's Clouds and the Earth's Radiant Energy System (CERES) suggest a downwind elevation of between 10 and 45 Wm−2 at distances of 150–400 km from the volcano, with much greater local (< 80 km) effects. Comparison of these observations with cloud properties at isolated islands without degassing or erupting volcanoes suggests that these patterns are not purely orographic in origin. Our observations of unpolluted, isolated marine settings may capture processes similar to those in the pre-industrial marine atmosphere.

A new optimal estimation algorithm for the retrieval of sulphur dioxide (SO2) has been developed for the Infrared Atmospheric Sounding Interferometer (IASI) using the channels between 1000–1200 and 1300–1410 cm−1. These regions include the two SO2 absorption bands centred at about 8.7 and 7.3 μm (the ν1 and ν3 bands respectively). The retrieval assumes a Gaussian SO2 profile and returns the SO2 column amount in Dobson units and the altitude of the plume in millibars (mb). Forward modelled spectra (against which the measurements are compared) are based on the Radiative Transfer for TOVS (RTTOV) code. In our implementation RTTOV uses atmospheric profiles from European Centre for Medium-Range Weather Forecasts (ECMWF) meteorological data. The retrieval includes a comprehensive error budget for every pixel derived from an error covariance matrix that is based on the SO2-free climatology of the differences between the IASI and forward modelled spectra. The IASI forward model includes the ability to simulate a cloud or ash layer in the atmosphere. This feature is used to illustrate that: (1) the SO2 retrieval is not affected by underlying cloud but is affected if the SO2 is within or below a cloud layer; (2) it is possible to discern if ash (or other atmospheric constituents not considered in the error covariance matrix) affects the retrieval using quality control based on the fit of the measured spectrum by the forward modelled spectrum. In this work, the algorithm is applied to follow the behaviour of SO2 plumes from the Eyjafjallajökull eruption during April and May 2010. From 14 April to 4 May (during Phase I and II of the eruption) the total amount of SO2 present in the atmosphere, estimated by IASI measurements, is generally below 0.02 Tg. During the last part of the eruption (Phase III) the values are an order of magnitude higher, with a maximum of 0.18 Tg measured on the afternoon of 7 May.

This work provides a comparison of satellite retrievals of Saharan desert dust aerosol optical depth (AOD) during a strong dust event through March 2006. In this event, a large dust plume was transported over desert, vegetated, and ocean surfaces. The aim is to identify the differences between current datasets. The satellite instruments considered are AATSR, AIRS, MERIS, MISR, MODIS, OMI, POLDER, and SEVIRI. An interesting aspect is that the different algorithms make use of different instrument characteristics to obtain retrievals over bright surfaces. These include multi-angle approaches (MISR, AATSR), polarisation measurements (POLDER), single-view approaches using solar wavelengths (OMI, MODIS), and the thermal infrared spectral region (SEVIRI, AIRS). Differences between instruments, together with the comparison of different retrieval algorithms applied to measurements from the same instrument, provide a unique insight into the performance and characteristics of the various techniques employed. As well as the intercomparison between different satellite products, the AODs have also been compared to co-located AERONET data. Despite the fact that the agreement between satellite and AERONET AODs is reasonably good for all of the datasets, there are significant differences between them when compared to each other, especially over land. These differences are partially due to differences in the algorithms, such as assumptions about aerosol model and surface properties. However, in this comparison of spatially and temporally averaged data, it is important to note that differences in sampling, related to the actual footprint of each instrument on the heterogeneous aerosol field, cloud identification and the quality control flags of each dataset can be an important issue.

Fast and reliable methods for the detection of atmospheric trace species are needed for near-real-time applications including volcanic hazard avoidance. One common approach using hyperspectral instruments is to measure the difference in brightness temperature between a small number of target sensitive and background channels to determine the presence of the target species. Although fast and robust, current brightness temperature difference methods do not fully exploit the spectral range and resolution of hyperspectral instruments, and the noise associated with the measurements remains high. In this paper, we describe a way to make full use of the spectral information from hyperspectral sounders allowing the presence of the target species to be determined with much better sensitivity in near-real-time if required. The technique is demonstrated using the MetOp Infrared Atmospheric Sounding Interferometer considering two case studies: (a) the detection of sulphur dioxide from the eruption of the Kasatochi volcano in Alaska in August 2008, and (b) the detection of ammonia emissions related to agriculture over Southern Asia in May 2008. The performance of this method is compared against that of existing brightness temperature difference methods. It is found that the sensitivity of the detection of these trace species is improved by up to an order of magnitude.

The Global Retrieval of ATSR Cloud Parameters and Evaluation (GRAPE) project has produced a global data-set of cloud and aerosol properties from the Along Track Scanning Radiometer-2 (ATSR-2) instrument, covering the time period 1995–2001. This paper presents the validation of aerosol optical depths (AODs) over the ocean from this product against AERONET sun-photometer measurements, as well as a comparison to the Advanced Very High Resolution Radiometer (AVHRR) optical depth product produced by the Global Aerosol Climatology Project (GACP). The GRAPE AOD over ocean is found to be in good agreement with AERONET measurements, with a Pearson's correlation coefficient of 0.79 and a best-fit slope of 1.0±0.1, but with a positive bias of 0.08±0.04. Although the GRAPE and GACP datasets show reasonable agreement, there are significant differences. These discrepancies are explored, and suggest that the downward trend in AOD reported by GACP may arise from changes in sampling due to the orbital drift of the AVHRR instruments.

The aerosol component of the Oxford-Rutherford Aerosol and Cloud (ORAC) combined cloud and aerosol retrieval scheme is described and the theoretical performance of the algorithm is analysed. ORAC is an optimal estimation retrieval scheme for deriving cloud and aerosol properties from measurements made by imaging satellite radiometers and, when applied to cloud free radiances, provides estimates of aerosol optical depth at a wavelength of 550 nm, aerosol effective radius and surface reflectance at 550 nm. The aerosol retrieval component of ORAC has several incarnations – this paper addresses the version which operates in conjunction with the cloud retrieval component of ORAC (described by Watts et al., 1998), as applied in producing the Global Retrieval of ATSR Cloud Parameters and Evaluation (GRAPE) data-set. The algorithm is described in detail and its performance examined. This includes a discussion of errors resulting from the formulation of the forward model, sensitivity of the retrieval to the measurements and a priori constraints, and errors resulting from assumptions made about the atmospheric/surface state.