In recent years, attention was paid to the detection and monitoring of volcanic ash clouds as their impact on the air traffic control system was unprecedented. Volcanic clouds are dangerous for the aviation as they can cause damage of the aircraft systems and engines not only close to active volcanoes but also at large distance from the eruption.
The intensity of the extreme convective events is supposed to increase worldwide due to the climate change and they can also cause large damages and affect air safety.

The recent Anak Krakatau, Raikoke and Ulawun eruptions highlighted the issue on different techniques to distinguish volcanic ash clouds from convective clouds, and the unsolved problem to understand if the cloud top is tropospheric or stratospheric.

The “extreme clouds” detection and estimation of their physical parameters is a highly multidisciplinary and challenging topic since the same techniques and instruments can be used for meteorology, volcanic monitoring, atmospheric physics and climate purposes. There is an urgent need to develop new techniques and instruments for monitoring, detecting and modeling “extreme clouds” to develop early warning systems and to support users, decision makers and policy makers.

This session solicits the latest studies from the spectrum of:
- Volcanic and Convective Clouds (CVC) remote sensing, detection, monitoring, modeling, forecasting and nowcasting
- understanding of CVC structure, including overshooting and ice clouds
- understanding the impact of CVC on climate changes and air safety
- proposal of new products or services focused on the end-users prospective (air traffic management and air safety)
- discussion on the recent Anak Krakatau, Raikoke and Ulawun eruptions

By considering studies over this range of topics we aim to identify new methods, detail current challenges, understand common techniques/methods and identify common discussions within the communities of atmospheric physicists, meteorologists, modelers, air traffic managers, pilots sensors engineers and engines manufacturers.

We particularly welcome and encourage contributions connecting different fields such as:
- forecasting tools to support air traffic management improving the limits of the present science and new products/tools providing better services to the end-users,
- extreme clouds remote sensing with novel techniques and new sensors,
- novel techniques to detect overshooting and their impact on climate.

Co-organized by GMPV9/NH1
Convener: Riccardo Biondi | Co-conveners: Elisa Carboni, Stefano Corradini, Isabelle TaylorECSECS
| Attendance Mon, 04 May, 08:30–10:15 (CEST)

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Download all presentations (43MB)

Chat time: Monday, 4 May 2020, 08:30–10:15

Chairperson: Stefano Corradini
D3354 |
Elżbieta Lasota, Riccardo Biondi, Florian Ladstädter, and Andrea K. Steiner

Recent studies have shown an increase of stratospheric aerosol optical depth in the last 20 years despite the absence of large volcanic eruptions in the same period, contributing to supporting the hypothesis that several minor eruptions could impact the atmospheric variability as a large one. November 2010 was a relatively active volcanic period in the tropical belt, three eruptions with Volcanic Explosivity Index higher than 3 occurred in a time span of about 3 weeks: Merapi, Tengger Caldera and Tungurahua. Merapi was the largest eruption of the three, directly overshooting the stratosphere and injecting a large amount of sulfur dioxide. In this study, we analyse the impact of this series of eruptions on the temperature derived from radio occultation observations in upper troposphere lower stratosphere at the local, regional and global scale. The impact of the Quasi‐Biennial Oscillation, El Niño–Southern Oscillation, and linear trend on temperature is estimated and removed from temperature time series using multiple linear regression. Signatures of volcanic eruptions in temperature are analysed using post fit residuals. The results show significant warming in the lower stratosphere between 10°S and 0° for a period of 7 months after the eruptions with a maximum anomaly amplitude of about 1.4 K at 18 km altitude. Whilst the maximum warming in Merapi’s vicinity occurred 4 months after the eruption and reached the magnitude of almost 4 K.

How to cite: Lasota, E., Biondi, R., Ladstädter, F., and Steiner, A. K.: Impact of November 2010 volcanic activity on the UTLS temperatures , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-458, https://doi.org/10.5194/egusphere-egu2020-458, 2020.

D3355 |
Pierre-Yves Tournigand, Valeria Cigala, Mohammed Hammouti, Fred Prata, Hugues Brenot, Lieven Clarisse, Andrea K. Steiner, Gottfried Kirchengast, and Riccardo Biondi

Explosive volcanic eruptions can generate ash and SO2 clouds rising to the stratosphere and dispersing on a global scale. Such volcanic features are at the origin of many hazards including aircraft engine damages, ash fallouts, acid rains, short-term climate changes and health threats. It is thus crucial to monitor volcanic clouds altitude and dispersion over time in order to prevent these hazards. In the past decades, satellite monitoring techniques have proven to be efficient at detecting volcanic aerosols in the atmosphere. In particular the detection of SO2 (e.g. IASI, AIRS, GOME-2) spatial and temporal dispersion and altitude (e.g. CALIOP). However, satellite data are scattered amongst the different institutes and agencies acquiring and processing them, and their retrieval is time-consuming.

In this study, we are building a whole new database gathering SO2 volcanic cloud altitude and dispersion data of 12 VEI 4 volcanic eruptions from 2008 to 2019. The spatial and temporal dispersion is retrieved from AIRS, IASI and GOME-2 sensors, as well as from collocated backscatter data of CALIOP sensor. Cloud altitude estimations are retrieved based on IASI, CALIOP and Global Navigation Satellite System (GNSS) radio occultation (RO) data when available. Besides, GNSS RO atmospheric profiles collocated with the other sensors at 12h temporal window and 0.2° spatial window, will be included. For the first time a dataset gathering several of the primary sensors used to monitor volcanic clouds and new ones will be freely available. Such new tool provides direct access to volcanic clouds data, and enables to perform original analysis and comparisons between different techniques. Applications for this dataset will impact many fields of volcanology and atmospheric physics, including but not restricted to volcanic clouds dispersal numerical modelling and volcanic aerosol impact on the atmosphere and climate. In fact, the collocation with GNSS RO will allow the study of the atmospheric structure with high vertical resolution.

How to cite: Tournigand, P.-Y., Cigala, V., Hammouti, M., Prata, F., Brenot, H., Clarisse, L., Steiner, A. K., Kirchengast, G., and Biondi, R.: SO2 volcanic clouds detected from space: a new database, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-671, https://doi.org/10.5194/egusphere-egu2020-671, 2020.

D3356 |
Oscar S. Sandvik, Bengt G. Martinsson, Johan Friberg, and Moa Sporre

After major volcanic eruptions, sulphur dioxide (SO2) can be released in large quantities to the stratosphere. The sulphur dioxide is later oxidised into sulphate aerosol which reflect incoming sunlight and cools the surface temperatures around the globe. The duration length is highly dependent on the altitude of the SO2 cloud and its geographical location. Today, infrared sensors on-board satellites can give an estimate of the SO2 cloud top height and lidar instruments can give height profiles in their narrow field-of-view. Both these classes of instrument lack the capability to fully map the vertical distribution of the SO2 clouds. We propose a scheme to create a SO2 dataset with high vertical resolution. The scheme consists of distributing SO2 column densities from ultra-violet and infrared satellite instruments into SO2 profiles using scattering data from the CALIOP lidar on-board the CALIPSO satellite. The CALIOP lidar has a vertical resolution of up to 60 m in the region of interest. Since CALIOP only collect data along narrow fields-of-view, this initially gives us the SO2 dataset only where CALIOP has collected data. To make the most of this information we run the FLEXPART trajectory model. If air parcels that were initially in CALIOP’s field-of-view and later in another part of the SO2 cloud, then the output from FLEXPART gives us this information. Thus, from CALIOP we shift the vertical information in time to other parts of the SO2 cloud using the trajectory model.

How to cite: Sandvik, O. S., Martinsson, B. G., Friberg, J., and Sporre, M.: Creating a 4D SO2 dataset with high vertical resolution by connecting volcanic cloud observations through trajectory modelling, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2847, https://doi.org/10.5194/egusphere-egu2020-2847, 2020.

D3357 |
Frances Beckett, Claire Witham, Susan Leadbetter, Ric Crocker, Helen Webster, Matthew Hort, Andrew Jones, Benjamin Devenish, and David Thomson

It has been 10 years since the ash cloud from the eruption of Eyjafjallajökull caused chaos to air traffic across Europe. Although disruptive, the longevity of the event afforded the scientific community the opportunity to observe and extensively study the transport and dispersion of a volcanic ash cloud. Here we present the development of the NAME atmospheric dispersion model and modifications to its application in the London VAAC forecasting system since 2010, based on the lessons learned.

Our ability to represent both the vertical and horizontal transport of ash in the atmosphere and its removal have been improved through the introduction of new schemes to represent the sedimentation and wet deposition of volcanic ash, and updated schemes to represent deep atmospheric convection and parameterizations for plume spread due to unresolved mesoscale motions. A good simulation of the transport and dispersion of a volcanic ash cloud requires an accurate representation of the source and we have introduced more sophisticated approaches to representing the eruption source parameters, and their uncertainties, used to initialize NAME. Further, atmospheric dispersion models are driven by 3-dimensional meteorological data from Numerical Weather Prediction (NWP) models and the Met Office’s upper air wind field data is now more accurate than it was in 2010. These developments have resulted in a more robust modelling system at the London VAAC, ready to provide forecasts and guidance during the next volcanic ash event affecting their region.

How to cite: Beckett, F., Witham, C., Leadbetter, S., Crocker, R., Webster, H., Hort, M., Jones, A., Devenish, B., and Thomson, D.: Dispersion Modelling at the London VAAC 10 Years after the Eyjafjallajökull Ash Cloud, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4774, https://doi.org/10.5194/egusphere-egu2020-4774, 2020.

D3358 |
Geraint Vaughan, David Wareing, and Hugo Ricketts

On 22 June 2019, the Raikoke volcano in the Kuril Islands erupted, sending a plume of ask and sulphur dioxide into the stratosphere. A Raman lidar system at Capel Dewi, UK (52.4°N, 4.1°W) has been used to measure the extent and optical depth of the stratospheric aerosol layer following the eruption. The lidar was modified to give it much enhanced sensitivity in the elastic channel, allowing measurements up to 25 km, but the Raman channel is only sensitive to the troposphere. Therefore, backscatter ratio profiles were derived by comparison with aerosol-free profiles derived from nearby radiosondes, corrected for aerosol extinction. Small amounts of stratospheric aerosol were measured prior to the arrival of the volcanic cloud, probably from pyroconvection over Canada. Volcanic ash began to arrive as a thin layer at 14 km late on 3 July, extending over the following month to fill the stratosphere below around 19 km. Aerosol optical depths reached around 0.03 by mid-August and continued at this level for the remainder of the year. The location of peak backscatter varied considerably but was generally around 15 km. However, on one notable occasion on August 25, a layer around 300 m thick with peak lidar backscatter ratio around 1.5 was observed as high as 21 km.

How to cite: Vaughan, G., Wareing, D., and Ricketts, H.: Lidar observations of volcanic aerosol over the UK since June 2019, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5653, https://doi.org/10.5194/egusphere-egu2020-5653, 2020.

D3359 |
Lieven Clarisse, Alexandre Deguine, Tim Hultberg, Nicolas Theys, Simon Carn, Karen Fontijn, Luna Decoster, Juliette Hadji-Lazaro, Daniel Hurtmans, Claude Camy-Peyret, Cathy Clerbaux, and Pierre-François Coheur

Hydrogen Chloride (HCl) is an important but still poorly understood magmatic volatile species. Degassed HCl and ratios with other volatiles can be used to monitor, understand and forecast volcanic activity. As the dominant chlorine reservoir species in the stratosphere, and a source of reactive halogens, HCl also plays an important role in the depletion of ozone. The contribution of volcanic HCl to the stratospheric budget is however somewhat debated, but it is generally accepted that scavenging by hydrometeors is a dominant process. Unlike the less soluble SO2, this prevents the majority of volcanically emitted HCl from reaching the stratosphere. Currently HCl measurements have only been reported from limb sounders (MLS and ACE-FTS in particular), but given their viewing geometry, their vertical sensitivity is limited to the upper troposphere/lower stratosphere. In the past ten years, MLS was able to measure traces of HCl in a number of large volcanic plumes such as those originating from Sarychev Peak, Nabro and Calbuco.

Here, we report the first measurements from IASI of HCl in volcanic plumes. We provide unambiguous spectroscopic identification of HCl in the 2670-2760 cm-1 spectral region in several IASI observed spectra. A survey of 12 years of IASI data was carried out, and revealed several large plumes of volcanic HCl. We show two notably large plumes of HCl identified in the eruptions of Calbuco (2015) and Raikoke (2019). For these two eruptions, we show that HCl is detected in the lower altitude plumes emitted towards the end of the eruptions (and not in the main, higher-altitude and SO2-rich plumes).  This finding could be a result of the greater scavenging of HCl relative to SO2 in rapidly rising plumes, but could also be related to particular degassing mechanics of different volatile components in the erupted melt. First quantitative estimates indicate that for the analysed plumes, the HCl/SO2 molar ratios exceed one, which is much higher than the typical ratios measured by MLS (typically below 0.05) and also higher than reported from petrological data or in situ measurements (typically in the range 0.1-0.3).

How to cite: Clarisse, L., Deguine, A., Hultberg, T., Theys, N., Carn, S., Fontijn, K., Decoster, L., Hadji-Lazaro, J., Hurtmans, D., Camy-Peyret, C., Clerbaux, C., and Coheur, P.-F.: Measurements of HCl in the volcanic plumes of Calbuco (2015) and Raikoke (2019), EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10651, https://doi.org/10.5194/egusphere-egu2020-10651, 2020.

D3360 |
Sonja Behnke, Harald Edens, Seda Senay, Diana Swanson, Alexa Van Eaton, David Schneider, Masato Iguchi, and Daisuke Miki

Volcanic lightning measurements are gaining momentum in the volcano monitoring community as a tool to identify when an ash producing eruption has occurred. As a volcanic plume develops from an ash-laden jet to a convective plume, the electrical discharges also evolve, ranging from small “vent discharges” (a few meters in length) and near-vent lightning (tens of meters to kilometers in length) to thunderstorm-like plume lightning (tens of kilometers in length). Currently, volcanic lightning monitoring capabilities for volcano observatories are mainly limited to using long-range lightning sensor networks, which do not detect the full gamut of volcanic lightning due to the networks’ detection efficiency and the radio frequency band that they use (very low frequency or low frequency). This biases the sensors towards detecting only the larger volcanic lightning discharges that occur at later stages in plume development, which can result in detection delays of minutes to tens of minutes from the onset of eruption. In addition to the latency, there is no way to know if the lightning picked up by long range networks is from a volcanic or meteorological source without some other additional source measurement. Both the latency and the source ambiguity could be reduced by using lightning sensors at close range that can detect the very small vent discharges associated with volcanic explosions. Vent discharges occur within the gas thrust region in a plume, starting simultaneously with the onset of an eruption and persisting continually for seconds or tens of seconds, depending on the duration of an eruption. They produce a distinctive ‘continual radio frequency’ signal, of which there is no analogous signature in meteorological lightning. Thus, the characteristics of the radio frequency signature of vent discharges could be exploited to innovate a new sensor design that is both low power and transmits information (i.e., a useful derived data product) at rates low enough to be used at remote volcanoes where volcano monitoring is often sparse. To meet this goal, a new experiment at Sakurajima Volcano in Japan is underway to learn more about the physical characteristics and signal characteristics of vent discharges. We use broadband very high frequency sensors to record time series measurements of the vent discharges and other volcanic lightning discharges that occur from explosions of the Minamidake crater of Sakurajima. These measurements reveal new information about vent discharges, such as their duration and spectral features, that can be used to help identify when explosive eruptions are occurring.

How to cite: Behnke, S., Edens, H., Senay, S., Swanson, D., Van Eaton, A., Schneider, D., Iguchi, M., and Miki, D.: Exploiting the characteristics of volcanic lightning for volcano monitoring, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12220, https://doi.org/10.5194/egusphere-egu2020-12220, 2020.

D3361 |
Control of ice and ash particles on electrical discharges in experimental volcanic jets
Corrado Cimarelli, Kimberly Genareau, Sönke Stern, Caron Vossen, and Donald B. Dingwell
D3362 |
Riccardo Biondi, Pierre-Yves Tournigand, Enrico Solazzo, Eugenio Realini, Corrado Cimarelli, and Sebastian Kauczok

Monitoring and predicting extreme atmospheric events, such as deep convective systems, is very challenging especially when they develop locally in a short time range. Despite the great improvement in model parametrization and the use of satellite measurements, there are still large uncertainties on the knowledge of the dynamical processes of deep convective systems at local scale.

We use an innovative approach integrating a dense network of in situ measurements and satellite-based observations/products for the improvement of meteorological nowcasting at airport spatial scale focusing on the Malpensa airport (Italy). We add to the standard atmospheric parameters analysis, the information of integrated water vapour and lightning spatio-temporal behaviour (potential heavy rain precursors) during heavy rain phenomena detected by meteorological radars. The study is based on the anomaly of each atmospheric parameter during a convective event in comparison to its climatology in non-pre-convective environment, so that we are able to detect the variation with respect to the “standard” conditions. The ground based GNSS receivers (allowing the determination of the integrated water vapour trend before and during the storm), together with the lightning detectors, the weather stations (providing the trend of temperature, humidity and wind fields), the radiosondes and the GNSS radio occultations (allowing the estimation of vertical profiles of temperature, pressure and humidity) provide information on the pre-convective and non-pre-convective environment as a 3D picture of the atmospheric conditions.

The final goal is the test of a severe weather events nowcasting algorithm with high spatial resolution, and based on neural networks, for improving aviation safety. This is followed by the development of a user-friendly tailored final product, easily understandable by the Air Traffic Management stakeholder.

We have collected more than 600 cases suitable to develop the neural network algorithm. We show here the algorithm implementation and the meteorological characterization of deep convection usually developing on the Malpensa airport area.

How to cite: Biondi, R., Tournigand, P.-Y., Solazzo, E., Realini, E., Cimarelli, C., and Kauczok, S.: The airport-sCAle seveRe weather nowcastinG prOject (CARGO), EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-15177, https://doi.org/10.5194/egusphere-egu2020-15177, 2020.

D3363 |
Hugues Brenot, Nicolas Theys, Scott Wilson, Rory Clarkson, Lieven Clarisse, Adam Durant, Giuseppe Salerno, Stefano Corradini, Riccardo Biondi, Klaus Sievers, Christophe Lerot, Jeroen van Gent, Sheri Smith, and Michel Van Roozendael

Volcanic ash and gas is, like sulphur dioxide (SO2), a major risk for air traffic. To mitigate this risk and to improve situational awareness for air traffic management (ATM), we describe a new service using the SWIM (System Wide Information System Management) Yellow Profile – see https://www.eurocontrol.int/publication/eurocontrol-specifications-system-wide-information-management-swim – and aligned with the ATM Information Reference Model (AIRM) as required.

This new service provides early warnings of volcanic SO2 layer height (SO2LH) retrievals from 3 satellite instruments (TROPOMI on board S5P, and IASI-A&-B on board MetOp-A&B). The implementation of this service is enveloped in the framework of OPAS – Operational alert Products for ATM via SWIM – project, a KTN (Knowledge Transfer Network) Engage Catalyst funded project (Thematic Challenge 3; https://engagektn.com) of SESAR JU (Single European Sky ATM Research Joint Undertaking; https://www.sesarju.eu).

We present the TROPOMI SO2LH algorithm and the uses of inverse modelling and external observations from satellites and ground-based DOAS-FLAME instruments to validate TROPOMI SO2LH products for recent eruptions (i.e. Etna in Dec. 2018, Raikoke in June 2019, Ubinas in July 2019, Taal in January 2020). Cross-comparison with the satellite instruments CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization), IASI (Infrared Atmospheric Sounder Interferometer) and with GNSS (Global Navigation Satellite System) radio-occultations, is shown. 

This study will describe the specification of our SWIM service and highlight the point of view of an engine constructor (Rolls-Royce) directly in relation with airlines and ATM, with regard to the objectives of the APOS project. Note that due to engine susceptibility to aerosols, the avoidance of flights through volcanic plumes and SO2 clouds is critical.

The development of our new SO2LH products from TROPOMI contributes to an existing early warning system, so called SACS (Support to Aviation Control Service; http://sacs.aeronomie.be). This system is dedicated to support aviation and ATM, and was recently upgraded in the frame of EUNADICS-AV project (European Natural Airborne Disaster Information and Coordination System for Aviation; http://www.eunadics.eu), with many other alert products related to natural airborne hazard affecting air traffic (e.g. volcanic ash column and layer height, smoke from forest fires and desert dust).

How to cite: Brenot, H., Theys, N., Wilson, S., Clarkson, R., Clarisse, L., Durant, A., Salerno, G., Corradini, S., Biondi, R., Sievers, K., Lerot, C., van Gent, J., Smith, S., and Van Roozendael, M.: A yellow SWIM service dedicated to aviation and ATM by providing early warnings of volcanic SO2 layer height from TROPOMI and IASI sensors, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-15249, https://doi.org/10.5194/egusphere-egu2020-15249, 2020.

D3364 |
Abhinna Behera, Marie Boichu, and François Thieuleux

The adverse impact of volcanic gas and aerosol emission on global climate, air quality and ecosystem is well recognized. A better-refined knowledge of volcanic degassing mechanism and its interaction with the atmospheric environment can lead further to fill the persisting gaps in understanding well the impact of volcanic activities. The key is to monitor continuously the volcanoes at a global scale bearing also in mind the limitations of ground-based instruments during the ash-rich phase of emission. Thus, the space-borne sensors with a high spatial and temporal as well as spectral resolution are emerged but with complications in detecting low-altitude emissions, which are also limited to 12 h to 24 h of data acquisition frequency. Nonetheless, recently launched TROPOMI spectrometer onboard Sentinel 5P is shown to be a game-changer due to its high spatial and spectral resolution albeit the data acquisition frequency of only 24 h. To make further progress in retrieving high temporal SO2 emission, the contemporary inverse modelling method has already been shown to be promising. The obtained modelled parameters, viz., SO2 flux and altitude of injection, are reasonably compatible with the ground-based and space-borne observations [1] showing its importance in volcano monitoring [2] and towards forecasting large-scale plume dispersal [3]. The current work incorporates this advancing method and investigates a recent special volcanic event that occurred at Ambrym, Vanuatu during December 2018. The uniqueness of this eruption is the rapid shut down of decade long SO2 degassing and lava lake just after the eruption with the emplacement of a major dike [4]. Here, the hourly retrieved SO2 flux and altitude of injection are aimed to put to the fore the striking features of this unmonitored volcanic activity by assimilating the observations from several space-borne sensors.

To do so, the CHIMERE Eulerian chemistry-transport model (CTM) is used to simulate the Ambrym eruption at a large-scale during 13-19 December 2018. Weather Research and Forecast (WRF) model is used to force the meteorological fields in the CTM simulation, while ERA5 reanalysis data are used to force the initial and boundary conditions of the WRF simulation. The modelled SO2 column amount is then co-located with the TROPOMI, OMPS and GOME2 SO2 column amounts, respectively, to perform the inversion to estimate the modelled flux rates and altitude of injection. The high spatial and spectral resolution SO2 data from TROPOMI is shown to reshape significantly the results obtained from the inverse method in comparison to OMPS and GOME2 SO2 data. Furthermore, a proxy to the SO2 flux is then developed from the geostationary HIMAWARI data to validate the inversion results as the time resolution of HIMAWARI data acquisition is every 20 min. This work is further intended to explore more on the fate of sulphate aerosols formed during this eruption at a large-scale.



1. Boichu et al., Atmospheric Chemistry and Physics, 15(14):8381–8400, July 2015.

2. Boichu et al., Atmospheric Chemistry and Physics, 13(17):8569–8584, September 2013.

3. Boichu et al., Geophysical Research Letters, 41(7):2637–2643, 2014.

4. Shreve et al., Scientific reports, 9(1):1–13, 2019.

How to cite: Behera, A., Boichu, M., and Thieuleux, F.: Strength of TROPOMI observations on the retrieval of SO2 emissions at high temporal resolution from space, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18682, https://doi.org/10.5194/egusphere-egu2020-18682, 2020.