Abstract. 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.

Abstract. 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.

Abstract. 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 modelling 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 days 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.

Abstract. 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.

&lt;p&gt;&lt;span&gt;The Raikoke volcano emitted about &lt;/span&gt;&lt;span&gt;0.4-1.8 x 10&amp;#8313; kg &lt;/span&gt;&lt;span&gt;of ash and &lt;/span&gt;&lt;span&gt;1-2 x 10&amp;#8313; kg&lt;/span&gt;&lt;span&gt; of SO&lt;/span&gt;&lt;sub&gt;&lt;span&gt;2 &lt;/span&gt;&lt;/sub&gt;&lt;span&gt;up to 15 km into the atmosphere. However, the eruption was characterized by several puffs of different &lt;/span&gt;&lt;span&gt;time periods&lt;/span&gt;&lt;span&gt; and eruption heights. &lt;/span&gt;&lt;span&gt;Here, we&lt;/span&gt;&lt;span&gt; use the ICON-ART model in a model setup in which we resolve the phases of the Raikoke eruption. &lt;/span&gt;&lt;span&gt;W&lt;/span&gt;&lt;span&gt;e&lt;/span&gt;&lt;span&gt; calculated the eruption source parameters &lt;/span&gt;&lt;span&gt;(ESPs) online &lt;/span&gt;&lt;span&gt;by coupling &lt;/span&gt;&lt;span&gt;ICON-ART&lt;/span&gt;&lt;span&gt; to the 1-D plume model FPlume. &lt;/span&gt;&lt;span&gt;The input heights for the different eruption phases needed for FPlume are geometrically derived from GEOS-17 satellite data. An empirical relationship &lt;/span&gt;&lt;span&gt;is used to derive&lt;/span&gt;&lt;span&gt; the amount of very fine ash (particles &lt;32&amp;#181;m) which is relevant for long range transport in the atmosphere. &lt;/span&gt;In the first hours during and after the eruption, the modeled ash loading agrees very well with the observed ash loading from Himawari-8 due to the resolution of the eruption phase and the online calculation 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. In case of SO&lt;sub&gt;2&lt;/sub&gt;, we compared 6-hourly means of model and Himawari data with respect to the structure, amplitude, and location (SAL-method). In the beginning, the structure and amplitude values differed largely because the dense ash cloud directly after the eruption leads to an underestimation of the SO&lt;sub&gt;2&lt;/sub&gt; amount in the satellite data. On the second and third day, the SAL values are close to zero for all parameters indicating a good agreement of model and observations. We argue that representing the plume phases and ESPs in ICON-ART by FPlume enhances ash and SO&lt;sub&gt;2&lt;/sub&gt; predictability in the first days after the eruption, especially in case of non-continuous volcanic eruptions like the Raikoke eruption 2019.&lt;/p&gt;