A correct and reliable forecast of volcanic plume dispersion is vital for aviation safety. This can only be achieved by representing all responsible physical and chemical processes (sources, sinks, and interactions) in the forecast models. The representation of the sources has been enhanced over the last decade, while the sinks and interactions have received less attention. In particular, aerosol dynamic processes and aerosol–radiation interaction are neglected so far. Here we address this gap by further developing the ICON-ART (ICOsahedral Nonhydrostatic – Aerosols and Reactive Trace gases) global modeling system to account for these processes. We use this extended model for the simulation of volcanic aerosol dispersion after the Raikoke eruption in June 2019. Additionally, we validate the simulation results with measurements from AHI (Advanced Himawari Imager), CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization), and OMPS-LP (Ozone Mapping and Profiling Suite-Limb Profiler). Our results show that around 50 % of very fine volcanic ash mass (particles with diameter d<30 µm) is removed due to particle growth and aging. Furthermore, the maximum volcanic cloud top height rises more than 6 km over the course of 4 d after the eruption due to aerosol–radiation interaction. This is the first direct evidence that shows how cumulative effects of aerosol dynamics and aerosol–radiation interaction lead to a more precise forecast of very fine ash lifetime in volcanic clouds.

In June 2019, the Raikoke volcano, Kuril Islands, emitted 0.4–1.8×10⁹ kg of very fine ash and 1–2×10⁹ kg of SO₂ up to 14 km into the atmosphere. The eruption was characterized by several eruption phases of different duration and height summing up to a total eruption length of about 5.5 h. Resolving such complex eruption dynamics is required for precise volcanic plume dispersion forecasts. To address this issue, we coupled the atmospheric model system ICON-ART (ICOsahedral Nonhydrostatic with the Aerosols and Reactive Trace gases module) with the 1D plume model FPlume to calculate the eruption source parameters (ESPs) online. The main inputs are the plume heights for the different eruption phases that are geometrically derived from satellite data. An empirical relationship is used to derive the amount of very fine ash (particles <32 µm), which is relevant for long-range transport in the atmosphere. On the first day after the onset of the eruption, the modeled ash loading agrees very well with the ash loading estimated from AHI (Advanced Himawari Imager) observations due to the resolution of the eruption phases and the online treatment of the ESPs. In later hours, aerosol dynamical processes (nucleation, condensation, and coagulation) explain the loss of ash in the atmosphere in agreement with the observations. However, a direct comparison is partly hampered by water and ice clouds overlapping the ash cloud in the observations. We compared 6-hourly means of model and AHI data with respect to the structure, amplitude, and location (SAL method) to further validate the simulated dispersion of SO₂ and ash. In the beginning, the structure and amplitude values for SO₂ differed largely because the dense ash cloud leads to an underestimation of the SO₂ amount in the satellite data. On the second and third day, the SAL values are close to zero for all parameters (except for the structure value of ash), indicating a very good agreement of the model and observations. Furthermore, we found a separation of the ash and SO₂ plume after 1 d due to particle sedimentation, chemistry, and aerosol–radiation interaction. The results confirm that coupling the atmospheric model system and plume model enables detailed treatment of the plume dynamics (phases and ESPs) and leads to significant improvement of the ash and SO₂ dispersion forecast. This approach can benefit the operational forecast of ash and SO₂ especially in the case of complex and noncontinuous volcanic eruptions like that of Raikoke in 2019.

Volcanic aerosols change the atmospheric composition and thereby affect weather and climate. Aerosol dynamic processes such as nucleation, condensation, and coagulation modify the shape, size, and mass of aerosol particles, which influence their atmospheric lifetime and radiative properties. Nevertheless, most models omit these processes for ash particles. In this work, we explore the ash aerosol aging and sulfate production during the first 4 days following the 2021 La Soufrière (St. Vincent) eruption with the ICON‐ART model (ICOsahedral Nonhydrostatic model with Aerosol and Reactive Trace gases). Online coupling of ICON‐ART with a one‐dimensional volcanic plume model calculates volcanic emission, which makes it possible to resolve the different eruption phases of the noncontinuous La Soufrière eruption. We compared our simulated aerosol distribution and composition with observations from the Cloud‐Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument, the Multiangle Imaging SpectroRadiometer (MISR) Research Aerosol (RA) Algorithm, and the Barbados Cloud Observatory (BCO). We show that online coupling is essential to adequately model the emissions and plume development close to the volcano. The modeled aerosol aging is in very good agreement with observations from MISR near the emission source and with CALIOP at larger distances. Furthermore, particle aging occurs faster in the troposphere than in the stratosphere due to the availability of water vapor and OH, but a layer of coated ash appears at the plume top due to faster oxidation of SO ₂ and lofting by aerosol‐radiation interaction. This paper gives the first direct comparison of aerosol aging in volcanic eruption plumes between simulations and observations.

The newest and upcoming geostationary passive imagers have thermal infrared channels comparable to those of more established instruments, but their spectral response functions still differ significantly. Therefore, retrievals developed for a certain type of radiometer cannot simply be applied to another imager. Here, a set of spectral band adjustment factors is determined for MSG/SEVIRI, Himawari-8/AHI, and MTG1/FCI from a training dataset based on MetOp/IASI hyperspectral observations. These correction functions allow to turn the observation of one sensor into an analogue observation of another sensor. This way, the same satellite retrieval—that has been usually developed for a specific instrument with a specific spectral response function—can be applied to produce long time series that go beyond one single satellite/satellite series or to cover the entire geostationary ring in a consistent way. It is shown that the mean uncorrected brightness temperature differences between corresponding channels of two imagers can be >1 K, in particular for the channels centered around 13.4 μm in the carbon dioxide absorption band and even when comparing different imager realizations of the same series, such as the four SEVIRI sensors aboard MSG1 to MSG4. The spectral band adjustment factors can remove the bias and even reduce the standard deviation in the brightness temperature difference by more than 80%, with the effect being dependent on the spectral channel and the complexity of the correction function. Further tests include the application of the spectral band adjustment factors in combination with (a) a volcanic ash cloud retrieval to Himawari-8/AHI observations of the Raikoke eruption 2019 and a comparison to an ICON-ART model simulation, and (b) an ice cloud retrieval to simulated MTG1/FCI test data with the outcome compared to the retrieval results using real MSG3/SEVIRI measurements for the same scene.

Novel observations of aerosol and clouds by means of ground-based remote sensing have been performed in Antarctica over the Ekström Ice Shelf on the coast of Dronning Maud Land at Neumayer Station III (70.67°S, 8.27°W) from January to December 2023. The deployment of the OCEANET-Atmosphere remote sensing observatory in the framework of the Continuous Observations of Aerosol-Cloud Interaction (COALA) campaign has brought Aerosol, Clouds and Trace Gases Research Infrastructure (ACTRIS) aerosol and cloud profiling capabilities next to meteorological and air chemistry in situ observations at the Antarctic station. We present an overview of the site, the instrumental setup, and data analysis strategy and introduce 3 scientific highlights from austral fall and winter, namely, 1) observations of a persistent mixed-phase cloud embedded in a plume of marine aerosol. Remote sensing–based retrievals of cloud-relevant aerosol properties and cloud microphysical parameters confirm that the free-tropospheric mixed-phase cloud layer formed in an aerosol-limited environment. 2) Two extraordinary warm air intrusions: one with intense snowfall produced the equivalent of 10% of the yearly snow accumulation and a second one with record-breaking maximum temperatures and heavy icing due to supercooled drizzle. 3) Omnipresent aerosol layers in the stratosphere. Our profiling capabilities could show that 50% of the 500-nm aerosol optical depth of 0.06 was caused by stratospheric aerosol, while the troposphere was usually pristine. As demonstrated by these highlights, the 1-yr COALA observations will serve as a reference dataset for the vertical structure of aerosol and clouds above the region, enabling future observational and modeling studies to advance understanding of atmospheric processes in Antarctica.

In June 2019, the Raikoke volcano, Kuril Islands, emitted 0.4–1.8 × 10⁹ kg of very fine ash and 1–2 × 10⁹ kg of SO₂ up to 14 km into the atmosphere. The eruption was characterized by several phases or puffs of different duration and eruption heights. Resolving such complex eruption dynamics is required for precise volcanic plume dispersion forecasts. To address this issue, we coupled the atmospheric model system ICON-ART (ICOsahedral Nonhydrostatic – Aerosols and Reactive Trace gases) with the 1-D plume model FPlume to calculate the eruption source parameters (ESPs) online. The main inputs are the plume heights for the different eruption phases that are geometrically derived from satellite data. An empirical relationship is used to derive the amount of very fine ash (particles < 32 µm), which is relevant for long range transport in the atmosphere. On the first day after the onset of the eruption, the modeled ash loading agrees very well with the ash loading estimated from AHI (Advanced Himawari Imager) observations due to the resolution of the eruption phases and the online treatment of the ESPs. In later hours, aerosol dynamical processes (nucleation, condensation, coagulation) explain the loss of ash in the atmosphere in agreement with the observations. However, a direct comparison is partly hampered by water and ice clouds overlapping the ash cloud in the observations. We compared 6-hourly means of model and AHI data with respect to the structure, amplitude, and location (SAL-method) to further validate the simulated dispersion of SO₂ and ash. In the beginning, the structure and amplitude values differed largely because the dense ash cloud leads to an underestimation of the SO₂ amount in the satellite data. On the second and third day, the SAL values are close to zero for all parameters indicating a very good agreement of model and observations. Furthermore, we found a separation of the ash and SO₂ plume after one day due to particle sedimentation, chemistry, and aerosol-radiation interaction. The results confirm that coupling the atmospheric model system and plume model enables detailed treatment of the plume dynamics (phases and ESPs) and leads to significant improvement of the ash and SO₂ dispersion forecast. This approach can benefit the operational forecast of ash and SO₂ especially in case of complex and non-continuous volcanic eruptions like the Raikoke 2019.