Introduction
Among the various gaseous compounds released by volcanoes, sulfur
emissions are of major concern as they exert a fundamental role on the
atmosphere and climate . The
impact on climate of major eruptions, which emit sulfur-rich gases
(and mainly sulfur dioxide; SO2) directly into the
stratosphere, has long been recognized
. In addition to major
eruptions, more frequent intermediate-size eruptions impacting the
lower stratosphere have also been pointed out as a possible cause of
the recent pause in the global warming trend
. Secondary
sulfate aerosols, which result from the oxidation of sulfur gases in
the atmosphere, are the main protagonists of this volcanic
forcing. Micron-size sulfate aerosols, whose lifetime may reach a few
years in the stratosphere, are capable of scattering solar radiation
and cause transient cooling of the atmosphere from regional to global
scales . They may also
catalyze the destruction of the stratospheric ozone
.
In contrast, less powerful tropospheric eruptions are generally
considered harmless in terms of climatic impact. Indeed, in the
troposphere, aerosols are rapidly washed out by precipitations and
have a short lifetime
. However, sulfate
aerosols may reduce ice crystal nucleation rate and impact the
properties of high altitude cirrus clouds which play a crucial role in
the climate system
. Furthermore,
even the degassing processes of lowest intensity, such as persistent
passive degassing outside of eruptive episodes, may provide a large
natural background of aerosols which may substantially affect the
properties of low altitude meteorological clouds and the radiative
state of the atmosphere
.
Apart from their climatic impact, volcanic sulfur-rich emissions may
also fuel episodes of considerable air pollution. Such pollution is
recorded both locally near the volcanic source as well as at a far
distance, as exemplified by two long-lasting icelandic eruptions, the historical
1783–1784 Laki eruption and
the 2014–2015 eruption of Bardarbunga volcano .
Enhanced air pollution by sulfate particles was also recorded at a large distance for eruptions with much lower sulfur budgets
(e.g. in Germany on 19 April 2010 by the Eyjafjallajökull icelandic eruption ).
Acid precipitations triggered by sulphur-rich emissions also have
detrimental effects on the environment and ecosystems
.
The altitude of injection of volcanic sulfur in the atmosphere
strongly impacts the trajectory and long-range dispersal of sulfur
gases, but also their lifetime. Indeed, the amount of oxidizing agents
required for the oxidation of SO2 to sulfate aerosols as well
as the amount of precipitation depend on altitude at a first order
. For its part, the release rate of sulfur dioxide integrated over the duration of the eruption determines the total mass
of SO2 gaseous precursor emitted into the atmosphere.
Volcanic emission flux and altitude are prone to significant
variations with time, even during the course of a single volcanic
event, as the type and intensity of eruptive activity are subject to
dramatic changes in response to complex magmatic and hydrothermal
processes taking place in the interior of the volcanic system
. Therefore,
a specific strategy for determining the flux and altitude of volcanic
sulfur-rich gas emissions has to be developed in order to improve the
characterization of the effects of volcanism on the atmosphere. In
order to be applicable to both (1) remote volcanoes lacking any
monitoring facility on the ground, which is the rule rather than the
exception, and (2) volcanic events that might be so intense that
ground measurements become dysfunctional, such a strategy has to rely
on satellite observations.
Volcanic flux can be reconstructed using satellite imagery according
to different methods involving various degrees of sophistication
. Among these,
inverse modelling approaches are currently capable of retrieving the
volcanic flux with an hourly temporal resolution using
a chemistry-transport model in combination with SO2
hyperspectral imagery
. These
methods usually rely on independent information on the altitude of
SO2 emissions at the source in order to initialize the
chemistry-transport model.
On the other hand, reconstruction of altitude, independently of flux,
can be achieved from back trajectory studies by looking at the location
of a particular gas parcel at a particular time
. First attempts
at reconstructing flux and altitude simultaneously have focused on the
retrieval of the emission profile with altitude, assuming a constant
volcanic flux emitted on a short time span
. More recently,
strategies for inverting both flux and altitude in a single pass based
on SO2 column amount (CA) maps have been proposed and
implemented on specific cases
. However, the success
of such strategies strongly depends on the existence of sufficient
wind shear, either transverse to the plume or along the plume, in
order to distinguish different trajectories and/or advection
velocities for gas parcels emitted at different altitudes. Such
favourable conditions are not always met, depending on the
meteorological conditions that prevail at the time of the eruption, as
well as the range of emission altitudes during the eruption. For
instance, the recent May 2010 Eyjafjallajökull eruption has
provided an example where the volcanic cloud transport has been shown
to be less dependent on the assumed altitude of injection
.
In order to improve the robustness of inverse modelling schemes, it is now
becoming possible to assimilate independent observations of volcanic cloud
altitude derived directly from space imagery. These recently developed
algorithms allow for mapping the SO2 cloud altitude using the same
hyperspectral images as the ones used for SO2 load estimation, which
makes them particularly suitable for a simultaneous inversion of flux and
altitude. Such algorithms have been developed for various sensors working in
the infrared (IR), such as IASI, or in the ultraviolet (UV)-visible, such as
OMI and GOME-2 . These advanced products yield complementary
detection levels in terms of concentration and altitude.
In this paper, we explore the possibility and limits of assimilating
volcanic SO2 altitudes from spaceborne imagery in inverse
schemes. We focus on the case of the 10–11 April 2011 lava fountain
eruption of Etna volcano (Italy), which was captured by multiple
hyperspectral IR IASI satellite images. We combine SO2 column
amount observations derived from IASI with the Eulerian
chemistry-transport model CHIMERE, through an inverse modelling
procedure, so as to quantify the flux and altitude of emissions as
a function of time during the course of the eruption.
We start with a comparison of the SO2 flux determined by the
inversion against continuous SO2 emission rates measured from
a ground-based UV spectroscopic monitoring network installed on the
flanks of Etna. Such a comparison between space-derived emission rates
and ground observations is only possible under rare circumstances, as
few volcanoes are instrumented on the ground with such facilities
. This opportunity allows us to discuss
the possibility of combining both monitoring strategies (ground-based
versus space-based) in order to capture the full range of emission
rates that characterize the successive stages of an eruption.
Furthermore, the consistency of the predicted altitudes is tested
against several independent sources of information. First,
a high-spatial resolution RGB MODIS image capturing the volcanic cloud
at short range from the volcano is used to validate the estimations of
emission altitudes derived from our inversion. To do so, we use the
MODIS image in combination with forward trajectories from the
Lagrangian HYSPLIT model. Second, semi-direct observations of the
volcanic cloud altitude at large distance from the source are
compared with our predictions. SO2 altitudes derived
directly from IASI images allow for assessing the potential bias
between our inversion results on one hand and the IASI advanced
algorithm on the other. Detection of the volcanic cloud captured by
a track of the spaceborne CALIOP lidar is also compared to our
estimated altitude. The potential implications in terms of
a simultaneous retrieval of SO2 gas and sulfate aerosol
components in volcanic clouds are discussed in light of the latter
comparison.
Results and validation
<inline-formula><mml:math display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> flux emissions: ground versus satellite
A series of four IASI SO2 column amount maps (Fig. left) are used for constraining the
reconstruction of both flux and altitude of Etna's emissions by inverse modelling (histograms in Top of Fig. ).
On the first map (Fig. a left), a few pixels indicate the presence of SO2 close to Etna on
10 April at around 08:00 UT, which supports an eruption
start before this time. The assimilation of these acquisitions in the inverse scheme dates the first release of SO2 between
05:00 and 07:00 UT, with a low flux of ∼50 th-1. So early, UV radiation is insufficient for ground UV-spectrometers
to operate (top of Fig. , green line).
Maps of SO2 column amounts (DU) in the Etna volcanic cloud on 10 and 11 April 2011 (left) retrieved from
IASI observations acquired over a time window centered at the date indicated, and (right) simulated with the CHIMERE
chemistry-transport model initialized with emissions reconstructed by the inversion procedure. Regions in grey indicate column amounts <0.1 DU.
![]()
Etna emissions during the 10 April 2011 eruption. (Top) Temporal evolution of the SO2
flux (t h-1) measured from ground-based UV-DOAS observations during daylight hours
(from ; green line) and retrieved
using the inversion procedure which assimilated IASI SO2 column amount observations (histograms).
Yellow and pink areas indicate the proportion of the flux emitted at 4 and 7 kma.s.l respectively.
The dashed envelope corresponds to the total flux. The grey zone indicates presence of ash
. (Bottom) Root mean square
amplitude of the seismic tremor (0.5–5 Hz) recorded at the station closest to the
south-east Crater where the eruption took place (from ).
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Acquisition of the second image around 20:00 on 10 April highlights
a large SO2 cloud with a complex horseshoe shape, which could
suggest the existence of significant wind shear
(Fig. b left). The location and mass load of
the part of the volcanic cloud with the highest SO2 column amount is well
reproduced (Fig. b right). However, the
observed SO2 cloud appears thinner than in the model which does
not manage to fully reproduce its complex shape. This discrepancy may
be due to the overestimation of plume dispersion resulting from
numerical diffusion inherent to Eulerian models
.
SO2 cloud detections at distance from Sicily at 20:00 indicate that a large batch of SO2 has been released
from Etna between the previous IASI detection at 8:00 and well before 20:00. Although IASI observations at 20:00 were acquired hours
after the end of the eruption, the assimilation in the inverse procedure of these data as well as observations acquired later on 11 April,
allows us to reconstruct in details the chronology of the gas emissions in the hours preceding the eruption, throughout the paroxysmal phase
and until the end of this episode of unrest (top of Fig. ). After weak emissions characterized by low flux
values of ∼50 th-1 early morning on 10 April, a significant increase of the SO2 flux is observed from ∼8:00. This
increase is simultaneously measured with the ground network of UV-spectrometers which records similar flux values (up to
600 th-1; (top of Fig. – green line), well in excess of background values of ∼62 th-1 recorded
between 8 and 9 April 2011 and early morning on 10 April . Tremor amplitude,
which is commonly used to track changes of the volcanic activity at Etna , also indicates
a simultaneous increase of the seismicity (bottom of Fig. ).
Whereas most emissions were released before 10:00 at an altitude of 4 kma.s.l. according to the model, the
jump of emissions to a higher altitude (7 km) seems to occur concurrently with the intensification of degassing
from 11:00. This escalation of the flux, reaching values up to ∼1600 th-1 between 12:00 and 13:00,
coincides with a sharp increase of the tremor seismic activity (bottom of Fig. ).
Yet, although the paroxysmal phase is observed through flux values reconstructed from spaceborne observations and seismic
activity, ground UV observations instead record simultaneously a sharp decrease of the SO2 flux around 11:00. In the same period of time, ash emissions start to be released
(;
grey area in Fig. ), which reveals the increasing degree of explosivity of
the eruption and the occurrence of magma fragmentation triggering ash discharge. The comparison between ground and
satellite-derived fluxes therefore indicates a good agreement during ash-poor periods of the Etna eruption. In contrast,
the increasing plume opacity associated with the abundance of ash likely leads to an underestimation of SO2
emission rates derived from ground measurements, reaching almost an order of magnitude (a factor 8 here), during the ash-rich paroxysmal phase of the eruption.
The existence of significant wind shear is confirmed by IASI acquisitions on
11 April at ∼08:00 and 18:30, which indicate a large elongation and
dispersion of the SO2 cloud (Fig. c and
d left). The SO2 cloud covers now more than 1200 km, only
12 h after the previous observations that indicated a much more
spatially concentrated SO2 cloud
(Fig. b left). The model is able to reproduce the
SO2 cloud elongation as well as the gradients of SO2 load
within the plume (Fig. c and d right).
Nevertheless, we find a discrepancy between observations and model on
these days. The observed SO2 cloud appears extremely narrow which is
in disagreement with the model. Numerical diffusion may induce more spreading
of the modelled volcanic cloud than observed. Also, in case of a lower
SO2 load, the presence of thick meteorological clouds close to the
core of the plume on 11 April a.m. and p.m. maps, illustrated by the
cloud cover fraction from Eumetsat IASI Level 2 products, can hamper the
detection of SO2, leading to artifactual gaps in observations
(Fig. c and d).
Maps of the cloud cover factor (CCF). The Etna IASI SO2 cloud is shown in grey in the background.
![]()
(Left) MODIS/AQUA RGB image of Etna plumes on 10 April 2011 at 12:30 UT obtained
from visible channels. (Right) Same as left panel, overlaid with the forward trajectories from
the Lagrangian HYSPLIT model initialized with (yellow line) an emission at 4±1 kma.s.l.
starting at 09:00 UT and (pink line) an emission at 7±1 kma.s.l. starting at
11:00 UT in agreement with the modelled source term with the inversion procedure (same colour
code as in Fig. ). Trajectories are computed until 13:00 UT.
![]()
Altitude of emissions and near-source <inline-formula><mml:math display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> cloud
Modelling and IASI acquisitions show a relatively compact SO2
cloud composed of two linked pieces on
10 April p.m. (Fig. b). In contrast,
subsequent maps indicate a torn apart, elongated plume
(Fig. c and d). This behaviour demonstrates
the existence of an intense wind shear in the meteorological fields
leading to very different trajectories followed by parts of the
SO2 cloud initially originating from a single location. Such
an example illustrates the necessity and importance of rigorously
accounting for the varying altitude of emissions in order to
accurately describe the long-range dispersal of volcanic clouds.
The temporal evolution of the emission altitude reconstructed with the
inversion procedure indicates emissions mainly at
4 kma.s.l., i.e. 500 m above the summit of Etna,
until 10:00 on 10 April (top of
Fig. ). Afterwards, a rapid
increase of the altitude, from 4 to 7 kma.s.l., is recorded
little ahead of the paroxysmal phase of the eruption, the latter being
characterized by a substantial increase of the SO2 flux and
intense ash emissions. This result is consistent with the common
observation on volcanoes of an increase of the altitude of emission
coincident with increasing ash release rate
.
These modelled emissions, with contrasting altitudes in a meteorological field
prone to intense wind shear, are expected to fuel plumes that subsequently
follow different trajectories. Such variations in the altitude of the
emissions are confirmed by the MODIS observations acquired at 12:30, shortly
after the paroxysm (Fig. left). Thanks to
favourable meteorological conditions around Sicily, MODIS radiances at three
channels in the visible spectrum (RGB) can be used to track volcanic plumes.
The histogram which represents the distribution of the number of pixels at each radiance level, for the blue channel of
the RGB MODIS image here, has been stretched to enhance fainter parts of the image and provide a higher contrast. Thanks
to this image processing, we are able to visualize two Etna plumes travelling out from Sicily, including the weakest one
associated to low radiances. These two plumes, showing different opacities, follow different directions.
To validate the modelled altitude of emissions, we run the HYSPLIT trajectory
model in forward mode. HYSPLIT test is initialized with a first emission at
an altitude of 4 kma.s.l. at 09:00 a.m. and a second
emission at 7 kma.s.l. at 11:00 a.m. which coincides with
the start of the paroxysmal phase. The trajectory is computed until 13:00,
the closest time to the MODIS acquisition at 12:30 given the hourly
resolution of HYSPLIT. Computed trajectories are in perfect agreement
with the direction of the two plumes visible on the RGB MODIS image (Fig. right).
Uncertainties on modelled trajectories have been evaluated by varying the altitude of emissions initializing HYSPLIT runs by ±1 km (Fig. right).
Whereas the HYSPLIT trajectory for a 4 km-high emission at 09:00 a.m. is in agreement with the direction of the Etna plume described by the RGB MODIS image, emissions injected at the same time at an altitude of 3 or 5 km follow very different paths.
Concerning emissions at 11:00 a.m., they follow a similar direction whatever their altitude of injection (at 6, 7 or 8 km).
However, the velocity of the volcanic plume is drastically different depending on the altitude of emission. Precisely, the velocity increases
with the altitude of emissions. Hence, only the HYSPLIT trajectory computed with a 7 km-high emission as input is able to reproduce the
length of the volcanic plume observed with the RGB MODIS image. These results consequently attest to the weak uncertainty on the altitude of
emissions deduced from HYSPLIT runs. They also validate the altitudes and the good timing of the modelled emission retrieved from the inversion procedure.
Far-range altitude of the <inline-formula><mml:math display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> cloud
IASI <inline-formula><mml:math display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> altitude
IASI column amounts were used in the inversion procedure to
reconstruct the rate and altitude of SO2 emissions. We compare
here the altitude of the dispersed Etna SO2 cloud predicted by
the model (Fig. right) against the
SO2 height retrieved independently using recently developed
algorithms exploiting the high spectral resolution of IASI
observations (;
Fig. left). At a given pixel, the
modelled altitude corresponds to the altitude at the middle of the
layer with a maximal SO2 concentration.
Maps of the altitude (kma.s.l.) of the Etna SO2 cloud on 10 and
11 April 2011 (left) retrieved from IASI observations and (middle) predicted by the forward
CHIMERE chemistry-transport model initialized with emissions reconstructed from the inversion procedure
(Fig. ). (Right) Scatter plot of IASI altitudes with modelled altitudes.
Symbol colour and size depend on observed IASI SO2 column amount (DU).
![]()
Overall, we observe an agreement between modelled and observed
altitudes which follow the same trend within the volcanic
cloud. Whereas the Etna SO2 cloud on 10 April p.m. presents
a relatively compact shape, we observe that it covers a broad range of
altitudes (Fig. b). These
variations likely result from the rapid variations of the altitude of
emission with time (Fig. ). The
Western part of the horseshoe shape lies at an altitude between 4 and
6 kma.s.l. according to model and observations. The Eastern
part reaches an altitude of up to 9 km with the model while
IASI indicates altitudes up to 12 km. The two parcels undergo
an intense wind shear over this range of altitudes, explaining their
very different trajectories. This fuels a substantial elongation of
the SO2 cloud, with ending parts lying at drastically
different altitudes. This feature is well described by model and
observations (Fig. c and
d). Nevertheless, apart from isolated points with a very high altitude
above 11 km, IASI always detects the Eastern part of the
SO2 cloud a few kilometres higher than the model. These
outlier values likely correspond to noisy spectra, often at the edge
of the volcanic cloud, with a too weak SO2 signature to
extract any information from them.
HYSPLIT backward trajectories
The modelled altitude of the far-range SO2 cloud is also
compared with the results obtained from HYSPLIT backward trajectories
(Fig. ). On 11 April at
08:00 UT, the modelled SO2 cloud (colocated in time and
space with IASI observations,
Fig. c) is significantly elongated
(top of Fig. ). This date is chosen
for comparison with HYSPLIT as it allows us to select parts of the
volcanic cloud that are geographically distant from each other, which
reduces the uncertainty in HYSPLIT outputs.
HYSPLIT indicates that the trajectories initiated at the front of the
SO2 cloud, which has almost reached the south-east corner of
the Mediterranean Sea, have to start at an altitude between 7 and
8 kma.s.l. to reach Etna in backward mode (bottom right of
Fig. ). This range of altitudes for
the SO2 front is in agreement with the modelled altitude
between 7 and 8.5 km. HYSPLIT trajectories initiated at the
tail of the SO2 cloud, above Libya, have to start at an
altitude between 4 and 5 kma.s.l. to reach back the Etna
(bottom left of Fig. ). This is
also in agreement with modelled altitudes between 4 and 5.5 km.
Comparison of the altitude (kma.s.l.) of the dispersed Etna SO2 cloud on
11 April 2011 08:00 UT (top) simulated with the CHIMERE chemistry-transport model,
initialized with emissions reconstructed by the inversion procedure and (bottom) deduced from
HYSPLIT backward trajectories starting from two opposite extremities of the SO2 cloud
either above Libya (32.5∘ N, 21.0∘ E; bottom left) or offshore Egypt (33.0∘ N, 29.0∘ E; bottom right).
![]()
CALIOP spaceborne lidar observations
A single track of the CALIOP lidar encountered the Etna volcanic cloud, on 11 April at about 00:26 UT.
Spaceborne lidar observations do not directly measure gaseous SO2 but
can detect aerosols of various type within the volcanic cloud, either sulfate
aerosols or ash . Nevertheless, sulfate
aerosols, which are produced by conversion of the SO2 gaseous
precursor during its transit in the atmosphere, may co-exist with SO2
within the volcanic cloud. This co-existence is confirmed here by the
exploration of the Level 1 and Level 2 CALIOP products and allows us to
validate the modelled SO2 cloud altitude by independent observations.
Our model, based on the assimilation of IASI SO2 column
amounts, predicts an SO2 cloud at an altitude between 6.4 and
7.5 kma.s.l. at the location and time of the CALIOP track
(Fig. ). According to the
simulated SO2 maps, the CALIOP track has crossed parts of the
plume that would have already travelled, at that time, over
1300 km, being 12–15 h old. We consequently expect
CALIOP to detect a diluted volcanic cloud, although modelled
SO2 maps predict that this track would cross the densest part
of the volcanic cloud (bottom of
Fig. ). Indeed, the CALIOP total
attenuated backscatter signal at 532 nm detects a weak signal,
yet above the noise level, at the location of the SO2 cloud
predicted by the model (top of
Fig. ). For latitudes between 34.3
and 35.3∘ N, algorithms delivering CALIOP Level 2 products
analyze this signal as the result of an aerosol layer between 7 and
7.5 km of altitude (bottom of
Fig. ). The detection of
this thin layer of aerosols benefited from the higher signal-to-noise
ratio characterizing night tracks and from its high altitude placing
this layer as the first one encountered by the laser beam. The rest of
the aerosol layer predicted by the model at latitudes below
34.3∘ N may produce too weak of a signal to exceed the level of
noise.
CALIOP track crossing the Etna volcanic cloud on 11 April 2011 00:27 UT. (Top) CALIOP
total attenuated backscatter signal at 532 nm. (Bottom) Cross-section and dispersion map of
the modelled Etna SO2 cloud at the time and location of the CALIOP track.
![]()
This aerosol layer is characterized by a small total colour ratio of
0.16 in average (up to a maximum of ∼0.32 if we take into account the large uncertainty on colour ratios due to backscatter
signals of low intensity), which is far lower than the colour ratio of neighbour meteorological clouds
in 0.5–0.8 (top of
Fig. ). Such a low total
colour ratio indicates aerosols of small size and represents a value
among the lowest that can be detected from spaceborne lidar
observations .
Particle depolarization depends on the aerosol shape and has been used to
discriminate spherical particles, such as sulfate aerosols or liquid water
droplets, from non-spherical particles (ash, ice crystals) in volcanic clouds
. Whereas the particle depolarization ratio
at 532 nm falls in the range 0.17–0.6 for volcanic ash according to ground- and space-based lidar observations
and 0.3–0.5 for cirrus ice crystals
(Fig. ), particles with a near-spherical shape are expected to present
a ratio close to zero. Here, the detected layer of Etna aerosols presents a low
particulate depolarization ratio of 0.08 on average (up to a maximum of 0.16 if we take into account uncertainties), far lower than the ratios
characterizing neighbour meteorological clouds which evolve at the same
altitude, in the range 0.29–0.41 (middle of
Fig. ) and lower than the range of ratios characterizing volcanic ash recorded in the literature (Fig. ). Aerosols characterized by
such a small particulate depolarization ratio tend to be spherical. However,
we note a particle depolarization ratio (0.08) slightly larger than the very
low volume depolarization ratio (0.025) for these aerosols, which may
indicate a small component of non-sphericity
.
In conclusion, according to colour and depolarization lidar ratios, Etna aerosols observed in this study are fine and rather
spherical in shape. As a consequence, they likely correspond to sulfate aerosols with lidar characteristics similar to those observed for sulfate
aerosols in stratospheric volcanic clouds .
The slight component of non-sphericity might suggest that these aerosols, which
travel at the same altitude as neighbour cirrus clouds, could play the role of
ice nuclei and represent partially crystallized sulfuric acid droplets . As
ash particles were emitted during this eruption of Etna , we cannot entirely
exclude the existence of very fine ash particles, which have not yet settled down, and may present a more spherical shape than expected due to their coating by sulfate aerosols.
CALIOP track crossing the Etna volcanic cloud on 11 April 2011 00:27 UT. (Bottom)
Altitude (top and base) of the highest layer of aerosols (blue, red) or meteorological clouds
(green, orange) retrieved from Level 2 CALIOP analysis is superimposed on the total attenuated
backscatter signal at 532 nm. White, black and dashed contours indicate respectively Etna
modelled SO2, collocated aerosols and neighbour meteorological clouds. (Middle) Volume and
particulate depolarization ratios for aerosols (blue, red) or clouds (green, orange). Maximum
uncertainty on particulate depolarization ratios of Etna aerosols is indicated (uncertainties on
volume depolarization ratios are smaller than symbol size). (Top) Total colour ratio for aerosols (blue) or clouds (green).
![]()
Depolarization ratios of (red) Etna aerosols detected by CALIOP in the 12–15 h-old
plume (Fig. , middle) in this study (cross indicates
mean value while error bar includes both the range of variability and uncertainties), compared with
the range of ratios recorded in the literature for (blue) volcanic ash and (green) cirrus ice clouds .
![]()
Discussion
Complementarity with ground- and space-based ultraviolet observations
Results presented in Sect.
demonstrate that methods based on satellite imagery are capable of
constraining the temporal evolution of large SO2 fluxes
emitted by volcanoes during paroxysmal eruptive phases. On the other
hand, ground UV measurements are less likely to succeed in such
conditions, as previously illustrated by the 2010 eruption of
Mt. Merapi (Indonesia; ).
Indeed, large gas emissions are generally concomitant with abundant
ash discharge. When a gas-rich magma rises in the crust toward the
surface, magma pressure decreases, favouring volatile exsolution and
gas bubble nucleation
. Further
decompression fuels the growth of these gas bubbles. When bubbles are
expected to occupy a large volume of the erupting mixture exceeding
the threshold of 70–80 %, magma fragmentation takes place
. Violently expanding bubbles tear
the magma apart into fragments which are ejected into the atmosphere,
where they solidify into ash particles.
The significant plume opacity associated with the abundance of ash may
explain the underestimation of the SO2 flux (by a factor of up
to 8 here at Etna) by ground UV-DOAS observations during ash-rich
phases of the eruption relative to flux values reconstructed from
satellite IR
observations.
pointed out the significant underestimation (up to 90 %) of
SO2 emission rates for high SO2 column density plumes
with conventional DOAS (Differential Optical Absorption Spectroscopy)
retrieval of ground UV observations which do not take into account
a realistic radiative transfer. Plume opacity associated with abundant
ash load is expected to be greater than the opacity of high-SO2 density plumes.
Accordingly, infrared IASI spaceborne observations are also sensitive
to the presence of ash. However, the influence of ash presented here
is minimized by the use of the ν3 band of SO2 for its
retrievals. This band around 7.4 µm, lies well outside the
8–12 µm spectral window where ash has its largest impact. Despite
this, it is known that very heavy ash loadings can affect also the
ν3 band . While the IASI
retrieval algorithm which has been employed here has not been
investigated yet for the effects of such thick ash clouds, an
inspection of the spectra on 10 April revealed almost no detectable
ash. Ash emissions may likely consist of mainly coarse particles which
had already settled down at the time of IASI overpass. Possible
impact of ash on the SO2 IR retrievals can therefore be
excluded for this event. This property of IR observations is
fundamental to counterbalance the weaknesses of UV sensors. In
addition, thermal IR channels also allow for delivering images of the
SO2 cloud at night, which brings more information on the
volcanic cloud dispersal compared to UV observations acquired only
during daylight hours.
Nevertheless, the complementarity of IR and UV spaceborne sensors should not be
overlooked. Although UV satellite acquisitions from sensors like the
Ozone Monitoring Instrument (OMI) are less frequent, they have the
advantage of imaging SO2 clouds in very humid conditions and
at low altitude (i.e. below 5 km:
). For its part, IR IASI sensor
requires relatively dry conditions and a large thermal contrast
between the ground and the air (as in Siberia), to gain sufficient
sensitivity for the monitoring of SO2 emissions in the
boundary layer . In the near future, the
assimilation in our inversion procedure of both IR and UV observations
in synergy should allow us to benefit from the complementary
advantages of these various sensors. Unfortunately, such a synergy
could not be achieved in this study. OMI observations of the volcanic
SO2 on 10 April 2011 could not be exploited here as they were
largely hampered by the row anomaly, which has affected the quality of
the Level 1B radiance data for a particular viewing direction since
2007. A more detailed description of the OMI row anomaly is available at
www.knmi.nl/omi/research/product/rowanomaly-background.
Furthermore, the Ozone Mapping and Profiler Suite (OMPS) sensor
was not launched at the time of the eruption of Etna
.
This study has shown that ground-based UV observations miss a large
part of the SO2 emitted by volcanoes during ash-rich
eruptions. SO2 flux is widely used in volcanology for tracking
changes in the volcanic activity and providing crucial indications for
eruption forecasting and hazard assessment
. At Etna,
ground-based derived SO2 emission rate was observed to
drastically decrease, whereas the degassing and tremor seismicity were
in reality escalating during the paroxysmal period of the activity
(Fig. ). Therefore, temporal
variations of SO2 flux delivered by ground UV-observations
have to be treated with caution when degassing and volcanic activity
intensify. We note that thermal observations, which are commonly used
to monitor the volcanic activity as well, were also hampered by the
abundance of ash within the plume
.
These discrepancies between ground and spaceborne evaluations of
SO2 fluxes challenge our present estimates of the global
degassing of sulfur compounds by volcanoes
, which may have been
significantly under-estimated. Furthermore, the techniques for
estimating the abundance of other major chemical compounds degassed by
volcanoes (e.g. water, carbon dioxide (CO2), hydrogen sulfide
(H2S), halogen halides (including HCl, HF, HBr, etc.) do
not directly measure the flux of a specific species. These methods,
either Fourier Transform Infrared Spectroscopy or in situ sensing,
measure the ratio of concentrations of the specific compound
relative to SO2. The flux of these gas species is then
calculated by multiplying the SO2 flux, generally estimated
using UV-spectroscopy, by this ratio
. A revised
inventory of volcanic SO2 release should provide a deeper
understanding of the broad impact on atmosphere and climate of the
large panel of volcanic emissions.
Notwithstanding, today, only ground-based methods based on UV-DOAS
spectroscopy are sensitive enough to detect the low SO2 fluxes that
characterize pre-eruptive phases or persistent passive volcanic degassing
. At Etna, we were able to
detect by assimilation of IASI satellite imagery low pre-eruptive fluxes of ∼50 th-1 early morning
between 5:00 and 7:00. These emissions occurred just a few hours before IASI
overpass at 08:00, so that they were less affected by dispersion. As
a consequence, they can be used to provide an estimation of the minimum level
of satellite detection in terms of flux. However, this detection level is variable with
time due to plume dispersion. Indeed, for a given flux value, the possibility
to maintain a sufficient column amount in the volcanic cloud decreases as the
time interval between the date of emissions and the satellite overpass time
increases. The increasing spatial and spectral resolution of forthcoming
infrared sensors, such as IASI-NG , should provide
a better monitoring of volcanic degassing of low intensity.
For now, gathering ground-based and spaceborne SO2
measurements is therefore crucial in order to achieve reliable
estimates of the release rate of SO2, both during quiescent and eruptive periods. So far, few
attempts have been made at comparing observations of volcanic
SO2 acquired by satellite and by ground measurements
. The main reason for
this is that spaceborne or ground-based instruments generally do not
measure the same physical quantity in SO2 clouds, but rather
measure the integrated SO2 column amount in a line of sight
that is specific to the instrument. Most of the time, a rigorous
comparison of results obtained by the two methods (ground- vs.
satellite-based) can only be achieved by an estimation of a common
parameter, such as the SO2 flux emitted at the source. Our
method of assimilation of SO2 satellite observations using
inversion schemes paves the way for the hybridization of ground- and
spaceborne-SO2 observations from various UV and IR sensors in
an automatic manner.
Strategy towards the assimilation of <inline-formula><mml:math display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> cloud height imagery
By comparing the SO2 cloud altitudes predicted by the
inversion against altitudes derived from the analysis of IASI
observations, we find a general agreement. This agreement is
highlighted by the linear regression (applied on data without outlier values, as detailed below) with a slope near to unity
in
Fig. (correlation coefficient R2 ∼0.6). Nevertheless,
we may observe a scatter of the IASI altitudes that increases with
model altitude. A systematic bias toward IASI altitudes most often
larger than modelled ones may also be noticed. This bias is nevertheless small, as illustrated by the low value of the
Y-intercept of the linear regression model (equal to ∼1.3 km) given the vertical resolution of the CHIMERE
CTM with layer thickness up to ∼2 km for altitudes >7 km and uncertainties of 1–2 km on IASI altitudes.
Scatter plot of the altitude of the Etna SO2 cloud retrieved from IASI observations with
the modelled altitude predicted with the CHIMERE model initialized with emissions reconstructed from
the inversion of IASI SO2 column amounts (DU). All data from 10 April a.m. to 11 April p.m. 2011
are included. Symbol colour and size depend on IASI SO2 column amount (DU). Open circles correspond
to IASI outlier altitudes discussed in Sect. , associated
to pixels with SO2 CA < 0.3 DU (detection threshold) or pixels with both altitudes ≤ 2 km
and SO2 CA ≥ 4 DU). Inset plot shows the linear regression between observed and modelled
altitudes without these outliers. Note the change of scale in the Y axis at an altitude >15 km.
![]()
These discrepancies stem from a combination of factors related to (1)
SO2 column amount (CA) and (2) background atmosphere:
Altitude information in the ν3 band of SO2 is derived mainly from the interference with water vapour absorption,
which impacts the relative intensity of the different SO2 lines in the observed spectrum. Uncertainty in altitude increases
with decreasing spectral signature (and therefore decreasing SO2 CA or decreasing altitude). This explains in large part the
scatter of IASI altitude values for low SO2 CA. These are mostly found on the edges and in the tail of the volcanic cloud, as
the column amount comes close to the detection threshold (assumed equal to 0.3 DU here). A few isolated IASI pixels with
abnormally low IASI altitudes, also very likely correspond to small SO2 CA values (but inherent to the IR, assuming a too
low altitude, artificially results in larger column estimates). These points correspond to an altitude of ∼2 km
according to the IASI retrieval, against 7–8 km in the model. They match the forefront of the volcanic SO2 cloud
in the 11 April p.m. image (Fig. d left), where the plume features a conspicuous discontinuity.
These inconsistent values might also be related to the presence of relatively thick meteorological clouds leading to an underestimation of the retrieved altitude (Fig. ).
IASI retrievals were performed here using atmospheric parameters for the month of August 2011, over quite a large area around
Etna, following a near-real-time processing strategy. Biases in this standard atmosphere, as compared to the actual atmosphere on
10–11 April, are likely to affect the retrieved altitude of a few kilometres and explain a large part of the positive bias toward larger IASI altitudes.
Due to the existence of the different sources of uncertainties listed
above, the IASI-derived altitudes should be selected prior to the
assimilation process aiming at the reconstruction of the altitude of emissions. Indeed, biases affecting the retrieved altitudes
would tend to map into biases in the inverted source history due to
the trade-off between emission time and emission height resulting from
wind shear. To circumvent these pitfalls, a selection of data
characterized by an SO2 load exceeding a certain threshold
could be performed before their assimilation in the inversion
procedure. Isolated IASI data co-located with a high value of the
cloud cover factor could be also discarded for further analysis
(Fig. ).
This case study demonstrates the robustness of the altitude retrieval
by both the model and IASI NRT products for monitoring SO2
clouds of relatively weak intensity and altitude. Algorithms which
exploit spaceborne hyperspectral UV observations generally require
higher SO2 loads for delivering information on altitude
.
Under favourable meteorological conditions, volcanic SO2 clouds
can be detected as well with spaceborne infrared sensors such as MODIS
or SEVIRI (onboard the geostationary Meteosat Second Generation
satellite). These instruments cannot provide quantitative estimates on
the SO2 abundance in the plume. However, as discussed in
Sect. , the higher spatial
(1km×1km for MODIS IR channels and
250m×250 m for visible channels) or temporal
(acquisitions at a specific location every ∼15 min for
SEVIRI) resolution of these observations in the near-source region
provide crucial indications on the trajectory followed by the
SO2 plume in the vicinity of the source, as illustrated by the
animation using SEVIRI SO2 acquisitions and MODIS SO2
images for the Etna eruption on 10–11 April 2011
. Consequently, such
information could also be exploited and assimilated in an inversion
procedure to better constrain the altitude of SO2 emissions.
Strategy toward the assimilation of lidar observations
As shown in Sect. , reconstructing the altitude of SO2
emissions by inverse modelling could rely on information of the altitude of the dispersed SO2 cloud at distance from the volcanic source.
However, images of SO2 cloud height provided by infrared IASI satellite observations
are generally not sensitive to SO2 below 5 km. Similarly, the altitude of low-altitude volcanic aerosols,
which are often co-existing with SO2 within the volcanic cloud, may be hardly estimated from CALIOP spaceborne lidar observations, as the intensity of backscatter signals may be below the detection limit.
In a complementary manner, ground-based lidar measurements can deliver
continuous temporal information on the altitude of any aerosol-rich volcanic
cloud passing over the station, if not obscured by thick underlying meteorological clouds.
Unfortunately, Etna cloud mainly travelled above the Mediterranean Sea during the
2011 April eruption and did not overpass any ground-based lidar station. Notwithstanding, networks of ground-based
lidar are growing, especially in Europe and already proved successful in capturing volcanic particles from icelandic
eruptions .
More broadly, lidar colour and
depolarization ratios allow for characterizing the microphysical
properties of volcanic aerosols and for identifying the presence of sulfate particles
and [this study]. Therefore, they provide the
opportunity to gain a deeper understanding of the conversion of
SO2 to sulfate aerosols within volcanic clouds.
If available, SO2 differential absorption lidar (SO2 DIAL) observations could provide
simultaneously both SO2 flux and altitude profile at the volcanic source. To our knowledge, a single experiment of
this kind has been developed and proved successful to estimate volcanic SO2 release rates down to 10 t.d-1 .
Indeed, such an experiment requires a costly, heavy and bulky instrumentation with a high power requirement. Passive remote-sensing instruments, such as SO2 UV-cameras which are increasingly used in
volcanic environments , are less constraining techniques much more easily deployable in the field.
These imaging systems deliver the 2-D-distribution of SO2 with a high frame rate allowing for the retrieval of SO2 emission rate at high temporal
resolution. However, the main disadvantage of such techniques, with limited spectral information, relies on the difficulty for correcting UV spectra so as
to account for a realistic radiative transfer between the sun and the instrument, especially during ash-rich phases of eruptions .
In the presence of dense ash-rich plumes, active SO2 DIAL observations require less complex radiative transfer corrections compared to passive remote-sensing techniques and could prove useful.
Conclusions and perspectives
This study demonstrates our capability to describe accurately the
rapidly varying dynamics of volcanic SO2 release with time, in
terms of both emission rate and altitude, using inverse modelling
procedures combining spaceborne imagery and chemistry-transport
modelling.
Retrieved SO2 flux time series are validated against
measurements performed by a network of ground-based ultraviolet (UV) scanning
spectrometers during the 10 April 2011 eruption of Etna. While the two
methods are found to be in remarkable agreement during ash-poor phases
of the eruption, large discrepancies between ground and space-derived
fluxes are observed when the eruption shifts toward an ash-rich
explosive activity. Plume opacity, associated with abundant ash load,
leads to a sharp decrease of the apparent SO2 emission rate
retrieved from the ground. As a consequence, the SO2 flux is
underestimated by nearly one order of magnitude as the eruption
reaches its paroxysmal stage. As tracking changes in the SO2
flux is critical for monitoring volcanic activity, this bias suggests
that the interpretation of ground-based UV observations in the context
of hazard assessment and crisis management should be treated with
caution as the activity intensifies. Moreover, the substantial
underestimation of SO2 emission rate calls for the necessity
to revisit currently available inventories of the global budget of
sulfur released by volcanoes. More broadly, since the emission rates
of other volcanic gases are generally derived from SO2 flux
estimations, their respective budgets should also be
reassessed. Nevertheless, ground observations represent the most
sensitive technique for detecting the low SO2 fluxes that
characterize passive degassing or pre-eruptive phases. Hence,
a rigorous description of the whole range of volcanic degassing
activity, spanning from persistent degassing up to major explosive
eruptions, can only be achieved through a synergy between ground- and
space-derived SO2 flux time series.
Altitudes of SO2 emissions retrieved by the inversion
procedure are used as inputs to forward trajectories of the HYSPLIT
Lagrangian model. The near-source atmospheric pathways followed by Etna plumes, which are RGB-imaged
from MODIS satellite observations, coincide with the modelled
trajectories, which confirms the validity of the modelled emission
characteristics.
Moreover, the far-range altitude of the volcanic SO2 cloud
predicted by our model is validated against various independent
sources of information. First, the CHIMERE chemistry-transport model
initialized with modelled emissions predicts altitudes of the
SO2 cloud, at large distance from the source, which are in
agreement with recently developed products of SO2 height
retrieved from IASI observations, as well as with backward HYSPLIT
trajectories. Second, spaceborne CALIOP lidar observations support
the concomitant presence of sulfate aerosols alongside with the
modelled volcanic SO2 cloud at thousands of kilometres from the
source.
These results confirm that both flux and altitude of SO2
emissions are highly variable in time during an eruption. The
characterization of these two emission parameters is consequently
required to consistently describe the far-range dispersal of volcanic
clouds. We have shown that specific wind shear conditions are required
to derive the altitude of emissions simultaneously with the SO2
flux if only SO2 column amount maps are
assimilated. Alternatively, the assimilation of the volcanic cloud
altitude derived directly from hyperspectral imagery (e.g. IASI)
should be considered as a promising strategy if these atmospheric
conditions are not met. Nevertheless, as these observations would
strongly constrain the altitude of emissions retrieved in the
inversion procedure, care should be taken in accounting for the
various factors affecting observed altitude values. In the specific
case of IASI, such factors include the increasing uncertainty on the
retrieved altitudes for low SO2 column amounts, the
sensitivity to the background atmospheric conditions used in the
analysis, and the presence of thick meteorological clouds.
This study paves the way for a 4-D characterization of SO2
cloud dispersal using hyperspectral spaceborne imagery through
a combination of chemistry-transport modelling and radiative transfer
modelling. As these spatial and temporal features of SO2 clouds
become accessible, vertically-resolved lidar observations should
provide their full potential in bringing insights into the mechanisms
of formation and degradation of volcanic sulfate aerosols.