Volcanic eruptions eject large amounts of ash and trace gases such
as sulfur dioxide (SO2) into the atmosphere. A significant difficulty
in mitigating the impact of volcanic SO2 clouds on air traffic safety
is that these gas emissions can be rapidly transported over long distances.
The use of space-borne instruments enables the global monitoring of volcanic
SO2 emissions in an economical and risk-free manner. Within the
European Space Agency (ESA) Sentinel-5p+ Innovation project, the S5P
SO2 layer height (S5P+I: SO2LH) activities led to the improvements of
the retrieval algorithm and generation of the corresponding near real-time
S5P SO2 LH products. These are currently operationally provided, in
near real-time, by the German Aerospace Center (DLR) within the framework of the
Innovative Products for Analyses of Atmospheric Composition (INPULS)
project. The main aim of this paper is to present its extensive
verification, accomplished within the S5P+I: SO2LH project, over major
recent volcanic eruptions, against collocated space-borne measurements from
the IASI/Metop and CALIOP/CALIPSO instruments as well as assess its impact
on the forecasts provided by the Copernicus Atmospheric Monitoring Service (CAMS). The mean difference between S5P and IASI observations for the Raikoke
2019, the Nishinoshima 2020 and the La Soufrière-St Vincent 2021
eruptive periods is ∼ 0.5 ± 3 km, while for the Taal 2020
eruption, a larger difference was found, between 3 ± 3 km and 4 ± 3 km. The comparison of the daily mean SO2 LH further
demonstrates the capabilities of this near real-time product, with slopes
between 0.8 and 1 and correlation coefficients ranging between 0.6 and 0.8.
Comparisons between the S5P SO2 LH and the CALIOP/CALIPSO ash plumes
revealed an expected bias at -2.5 ± 2 km, considering that the injected
SO2 and ash plume locations do not always coincide over an eruption.
Furthermore, the CAMS assimilation of the S5P SO2 LH product led to much
improved model output against the non-assimilated IASI LH, with a
mean difference of 1.5 ± 2 km, compared to the original CAMS analysis,
and improved the geographical spread of the Raikoke volcanic plume following
the eruptive days.
Introduction
Over 10 years have passed since the ash cloud from the 2010 Icelandic
Eyjafjallajökull volcano caused an unprecedented disruption to air traffic
across Europe, affecting the flight schedules of approximately 10 million
passengers and resulting in nearly USD 2 billion in lost airline
revenue (Bolić and Sivčev, 2011). This eruption led to increased
awareness of the threat of volcanic ash to air traffic in Europe, and
numerous advances have taken place since then with respect to research,
regulation, and cooperation (Reichardt et al., 2017). Apart from the ash
cloud, the volcanic sulfur dioxide (SO2) plume is also hazardous to
aircraft, as it forms the corrosive sulfuric acid and can further deposit
sulfates in the engines (Prata, 2009). As the ash particles will deposit
faster than SO2, after the first post-eruption hours the two clouds
typically separate in elevation making the reliable detection, dispersal
and forecast of both clouds during significant explosive eruptions on a
global basis equally important (ICAO, 2019).
The disruption that the Eyjafjallajökull and Grímsvötn 2010
and 2011 eruptions had on airborne traffic has led the International Civil
Aviation Organization, ICAO, to change the previous zero tolerance policy on
volcanic ash to establishing ash concentration thresholds over Europe.
Zehner (2012) have translated these thresholds into specific
requirements for improved volcanic ash monitoring and forecasting services.
These include the early detection of volcanic emissions and the near
real-time (NRT) global monitoring of volcanic plumes, with open access and
delivery of data (Brenot et al., 2014, 2021), and also the quantitative
retrievals of volcanic ash as well as SO2 concentrations and altitudes
from satellite instruments, and their validation.
Quantifying the SO2 load emitted during explosive eruptions provides
insights into volcanic processes, assists in volcanic hazard mitigation and
permits the climatic impact quantification of major eruptions (Carn et al.,
2016). However, it is the accurate retrieval of the SO2 plume injection
height that drives the majority of current scientific advancements in the
field. Numerous eruptions have already been used as demonstrational case
studies using a variety of space-borne observations and modeling techniques
to infer the layer height (LH), such as eruptions by Mount Etna, Italy, (Boichu et
al., 2015), Nabro, Eritrea (Clarisse et al., 2014), Jebel at Tair, Yemen
(Eckhardt et al., 2008), Eyjafjallajökull and Grimsvötn, Iceland
(Carboni et al., 2016), and Calbuco, Chile (Pardini et al., 2018), to name but a
few.
Within the European Space Agency (ESA) Sentinel-5p+ Innovation SO2
Layer Height project (S5P+I: SO2LH) activities have led to the generation
of a near real-time SO2 LH product based on the
Sentinel-5P/TROPOMI observations, hereafter referred to as S5P SO2 LH. In this work, we present the direct evaluation of the retrieved
SO2 LHs for four recent major eruptions against independent
satellite information as well as its indirect verification via its
assimilation into the Copernicus Atmospheric Monitoring Service (CAMS)
forecast system.
The retrieval of the SO2 LH based on Sentinel-5P/TROPOMI
measurements is performed using the already established “Full-Physics
Inverse Learning Machine” algorithm (hereafter referred to as
FP_ILM). It is based on Hedelt et al. (2019) and is an
improvement of the FP_ILM algorithm developed by Efremenko et
al. (2017) for the retrieval of the SO2 LH based on the Global Ozone
Monitoring Experiment (GOME-2) instrument data using a principal component
regression (PCR) technique. In general, the FP_ILM algorithm
creates a mapping between the spectral radiance and atmospheric parameters
using machine learning methods. The main advantage of the FP_ILM algorithm over classical direct fitting approaches is that the
time-consuming training phase involving complex radiative transfer (RT)
modeling and neural network (NN) training is performed offline. The final
trained inversion operator itself is robust and computationally simple and
therefore extremely fast and can be applied in NRT
processing environments, as discussed in detail below. The FP_ILM algorithm was originally developed for the retrieval of cloud properties
(Loyola et al., 2016) and has also been used for the retrieval of ozone
profile shapes (Xu et al., 2017) as well as the retrieval of surface
properties accounting for bidirectional reflectance distribution function
(BRDF) effects (Loyola et al., 2020). Recently, Fedkin et al. (2021) have
applied the FP_ILM algorithm to retrieve the SO2 LH
based on Ozone Monitoring Instrument (OMI/Aura) observations.
The S5P SO2 LH algorithm was further optimized within the framework of the
ESA S5P+I: SO2LH project. The S5P+I project has been initiated to
develop novel scientific and operational applications, products and
retrieval methods that exploit the potential of the Sentinel-5P mission's
capabilities beyond its primary objective and was kicked-off at the end of
June/beginning of July 2019 and successfully finished at the end of 2021 and
addresses seven themes related to atmospheric composition and ocean color.
The SO2LH theme is dedicated to the generation of an SO2 LH
product for Sentinel-5p considering data production timeliness requirements.
More details about the project can be found on the ESA S5P+I website
(https://eo4society.esa.int/projects/sentinel-5p+innovation/, last access: 14 October 2021) as well as on the dedicated SO2 LH project website (https://atmos.eoc.dlr.de/so2-lh/, last
access: 14 October 2021), where all algorithm and product-related documents are
publicly available.
The optimized FP_ILM algorithm description
The FP_ILM S5P SO2 LH algorithm combines a principal
component analysis (PCA) and an NN approach to retrieve the
SO2 LH based on Sentinel-5P/TROPOMI backscattered UV earthshine
measurements in the wavelength range between 311 and 335 nm. The PCA is used
to reduce the dimensionality of the high-resolution spectral measurements
and to extract the information related to the LH, whereas the NN is used to
directly retrieve the LH based on the extracted principal components (PCs)
and other input parameters.
In a first step, the FP_ILM algorithm is trained using
synthetic spectral UV data generated with the Linearized Discrete Ordinate
Radiative Transfer (LIDORT) model including inelastic rotational Raman
scattering (RRS) implementation (Spurr et al., 2008). Approximately 500 000
reflectance spectra on a smart parameter grid (Loyola et al., 2016) in the
wavelength range 311–335 nm have been generated, which are then convolved
with the TROPOMI instrument spectral response function (ISRF). This
simulated dataset is split into two datasets: 90 % are used for training
the PCA and NN and the remaining 10 % are set aside and used as an
independent test dataset to determine the accuracy of the FP_ILM training. A PCA is then applied to the training dataset to extract the
first N=10 principle components to reduce the dimensionality of the
spectral dataset. By characterizing the set of simulated measurements with
fewer parameters, a simpler, more stable, and computationally efficient
inversion scheme can be realized.
In the second step, the PCs of each training sample along with the total
ozone vertical column density (O3 VCD), viewing angles, surface
pressure and albedo are used as input to train a feedforward artificial NN,
with the corresponding SO2 LH of each training sample as the output
layer. The NN consists of two hidden layers with 40 nodes in the
first and 10 nodes in the second layer. A hyperbolic tangent layer
activation function (tanh) is used and a regularization is applied to
prevent the NN from overfitting and to reduce the generalization error. Put
together, the trained PCA operator and the trained NN form the
FP_ILM inversion operator, which is then applied to real
spectral measurements in the operational phase.
In the operational phase, the trained PC operator is applied to TROPOMI
spectral measurements, which feature enhanced SO2 levels, such as after
a volcanic eruption, to extract the first 10 PCs and thus reduce the
spectral dimension. With this information (along with the other measured
input parameters) the trained NN inverse function is then applied to
retrieve the SO2 LH. Note that neither the SO2 SCD nor the
SO2 VCD is input to the NN, since they depend on the SO2 LH both
directly and indirectly via the air mass factor calculation and the
temperature dependency of the absorption cross-section at the SO2 layer
altitude.
In the operational TROPOMI/S5P ground segment, level 2 (L2) data are
generated within 3 h after sensing. Once this L2 data are available and a
volcanic eruption occurs, the SO2 LH algorithm is able to retrieve the
corresponding LH within a few milliseconds per ground pixel. Even
for a huge volcanic eruption with an SO2 cloud spanning about 3 % of
the entire orbit (i.e., approximately 50 000 pixels), the whole SO2 LH retrieval
is performed within 3 min. Note that the largest volcanic eruptions
detected by satellites so far (e.g., Raikoke, Kasatochi, Sarychev, Nabro)
lead to typically 1 %–3 % of ground pixels to be processed for a limited
number of orbits. The FP_ILM algorithm is several orders of
magnitude faster than any of the direct fitting approaches for UV LH retrievals developed so far.
Closed-loop retrievals with the independent test dataset show that the
SO2 LH can be retrieved with an accuracy of less than 2 km for SO2
VCD > 20 Dobson units (DU, see Hedelt et al., 2019; SO2 LH
algorithm theoretical baseline document, ATBD, Hedelt and Koukouli, 2021 and
SO2 LH validation report, VR, Koukouli et al., 2021). Note here that in
the presence of volcanic ash, which can be initially collocated with the
SO2 cloud in the young volcanic plume, the retrieved SO2 LH can be
underestimated by several kilometers since the FP_ILM
inversion operators were trained without taking ash absorption into account
(see an extensive discussion in S5P SO2 LH ATBD, Hedelt and Koukouli, 2021).
From the analysis presented in the S5P SO2 LH VR (Koukouli et al.,
2021) it was deduced that the optimal accuracy was achieved when filtering
the reported LH values using a quality assurance (QA) value (indicating the quality of the
retrieval) greater than 0.5, a LH flag (indicating warnings and errors
during the retrieval) less than 16 and an associated SO2 load greater
than 20 DU. For the comparison against the independent datasets, the
SO2 LH were then gridded onto a 0.1×0.1∘ spatial plane at 6 h
intervals per eruptive day.
Comparative datasets
Two different IASI/Metop SO2 LHs are used for the
evaluation of the S5P SO2 LHs: the EUMETSAT ACSAF Brescia v201510
product (Clarisse et al., 2012, 2014; Astoreca et al., 2018), hereafter
IASI ULB/LATMOS, as well as the University of Oxford product (Carboni et
al., 2012, 2016), hereafter IASI AOPP. The two IASI approaches vary to such
an extent as is discussed below, that we can assume that they provide two
semi-independent datasets available for the validation of the S5P SO2
LHs. In addition, the CALIOP/CALIPSO space-borne lidar observations of the
ash plume (Winker et al., 2012; Prata et al., 2017) are compared to the
S5P SO2 LHs for the case of the Raikoke stratospheric eruption.
Furthermore, the S5P SO2 LH product was assimilated into a CAMS experiment (Inness et al., 2022), and
the assimilated fields were compared to the independent IASI ULB/LATMOS
observations, indirectly validating the S5P SO2 LH v4.0 product.
The IASI/MetOp SO2 ACSAF column data are fully described in Clarisse et
al., 2012, where a algorithm for the sounding of volcanic SO2 plume
above ∼ 5 km altitude was presented and applied to IASI. The algorithm
is able to view a wide variety of total column ranges (from 0.5 to 5000 DU), exhibits a low theoretical uncertainty (3 %–5 %) and near real-time
applicability and was thence demonstrated on the eruptions of Sarychev in
Russia, Kasatochi in Alaska, Grimsvötn in Iceland, Puyehue-Cordon Caulle
in Chile and Nabro in Eritrea. Furthermore, an expansion of the algorithm to
also provide SO2 LHs for the Nabro eruption using forward trajectories
and CALIOP coincident measurements is described in Clarisse et al. (2014).
The IASI ULB/LATMOS dataset includes five SO2 column data at assumed
LHs of 7, 10, 13, 16 and 25 km, as well as a retrieved best
estimate for the SO2 LH. It is important to note that the SO2 LHs
provided by this algorithm are quantized every 0.5 km, which renders simple
scatter-type comparisons not as straightforward. This dataset is publicly
available from https://iasi.aeris-data.fr/ (last access: 18 April 2022).
The observations by all Metop IASI instruments were treated as one, gridded
onto a 0.1×0.1 grid at 6 h intervals or each day. The choice of the temporal
field was applied since the S5P and Metop orbits differ on average by 3–4 h
and this temporal range was found to be the optimal trade-off
resulting in a successful collocative dataset while also ensuring the
comparisons view the same parts of the SO2 plumes. Recall also that
IASI, an infrared sounder, also performs observations 12 h later, during
nighttime. For high enough latitudes, the time zones collapse onto one another,
so in the case of high latitude volcanoes, such as Raikoke, a collocation
closer in time can be achieved. For this dataset, the reported SO2 LHs were restricted to altitudes less than 25 km where a successful
SO2 column retrieval was performed.
The University of Oxford employs an optimal estimation scheme (Carboni et al., 2012, 2016) to estimate the SO2 column amount, the height of the
SO2 profile and the surface radiating temperature from IASI/MetOp-A,
/MetOp-B and /MetOp-C measurements. The Oxford retrieval has two steps.
Firstly, a linear retrieval developed by Walker et al. (2011, 2012) is
applied. In the retrieval scheme a detection is considered “positive” if the
output of the linear retrieval is greater than a defined positive threshold
(0.49 effective DU, following Walker et al., 2012). The detection limits are
variable-dependent on the height of the plume and the atmospheric
conditions. For a standard atmosphere (with no thermal contrast) the
detection limits are estimated to be: 17 DU for a SO2 plume between
0–2 km, 3 DU between 2–4 km, and 1.3 DU between 4–6 km (Walker et al.,
2011). The detection scheme can miss part of an SO2 plume under certain
circumstances, such as low-altitude plumes, conditions of negative thermal
contrast (i.e., where the surface is colder than the atmosphere), and where
clouds are present above the SO2 plume, masking the signal from the
underlying atmosphere. The IASI SO2 retrieval is not affected by
underlying clouds. Secondly, an iterative retrieval is performed for the
pixels that provide positive detection results. The scheme iteratively fits
the forward model (simulations) with the measurements, through the error
covariance matrix, to seek a minimum of a cost function. The forward model
is based on RTTOV (Radiative Transfer for TIROS Operational Vertical Sounder (TOVS)) which is a very fast
radiative transfer model for passive visible, infrared and microwave
downward-viewing satellite radiometers, spectrometers and interferometers
(Saunders et al., 1999). The error covariance matrix used is the global
error covariance matrix described by Carboni et al. (2012), defined to
represent the effects of atmospheric variability not represented in the
forward model (FM), as well as instrument noise. A comprehensive error
budget for every pixel is included in the retrieval.
A quality control was applied to the IASI AOPP dataset to include valid data
points where the minimization routine converged within 10 iterations, the
retrieved SO2 amount was positive, the retrieved plume pressure was
between 0 and 1100 mbar and the cost function was less than 10. Additional
filters were applied in this work to include only pixels with SO2 LH ≤ 25 km, SO2 LH error ≤ SO2 LH and the
retrieved altitude ≠ a priori altitude at 400 mbar. The latter would
indicate that the retrieval reverted back to the a priori for lack of signal
in the measurement, hence would not provide any novel information to the
retrieval. After the additional filters were applied, the IASI/AOPP dataset
was also gridded onto a 0.1×0.1 grid at 6 h intervals per eruptive day.
CALIOP/CALIPSO volcanic LH dataset
Cloud-Aerosol and Lidar Infrared Pathfinder Observations (CALIPSO), is a joint NASA and Centre National d' Études Spatiales (CNES)
satellite and part of the A-Train constellation of satellites. It is
designed to study aerosols and clouds and aims to provide profiling
information at a global scale for improving our knowledge and understanding
of the role of the aerosols in the atmospheric processes. The main
instrument, Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), is a dual-wavelength (532 and 1064 nm) elastic
backscatter lidar with the capability of polarization-sensitive observations
at 532 nm (Winker et al., 2010). The high-resolution profiling ability
coupled with accurate depolarization measurements make CALIPSO an
indispensable tool to monitor specific aerosol species and clouds (Liu et
al., 2008). CALIPSO is the first polarization lidar to provide global
atmospheric measurements and is able to identify volcanic eruption plumes
related to the SO2 LH identification and retrieval (e.g.,
Fedkin et al., 2021; Hedelt et al., 2019; Koukouli et al., 2014; Tournigand
et al., 2020). The CALIPSO observations close to the volcanic source can be
employed in SO2 LH validation studies, since ash (and/or aerosols) are
initially collocated with the SO2 cloud, before the gas and ash plumes
separate. Note that the footprint of CALIOP measurements is only 100 m,
hence the global coverage is very low and detection of a volcanic ash plume
is rare.
The CALIOP optical properties retrieval scheme is based on the successful
cooperation of three major algorithm steps whose main mission objective is
to produce the CALIPSO L2 data (Vaughan et al., 200; Omar et al.,
2009). Finally, CALIPSO data consist of three basic types of information:
(a) layer products, (b) profile products and (c) the vertical feature mask
(VFM). Layer products provide layer-integrated or layer-averaged properties
of detected aerosol and cloud layers. Profile products provide retrieved
extinction and backscatter profiles within these layers. Because information
on the spatial locations of cloud and aerosol layers is of fundamental
importance, the VFM was developed to provide information on cloud and
aerosol locations and types. Layer properties include layer top and base
altitudes, as well as physical properties of the feature, such as the
integrated volume depolarization ratio, some of which are described below.
Layer top and base altitudes are reported in units of kilometers above mean
sea level. Between -0.5 and ∼ 8.2 km, the vertical
resolution of the lidar is 30 m. From ∼ 8.2 to
∼ 20.2 km, the vertical resolution of the lidar is 60 m.
Above ∼ 20.2 km, the vertical resolution is 180 m. The
on-board averaging scheme provides the highest resolution in the lower
troposphere where the spatial variability of clouds and aerosols is the
greatest and coarser resolutions higher in the atmosphere The CALIPSO data
products used in this validation study are summarized in Table 1.
CALIOP/CALIPSO parameters used in this study.
ParameterVersionLevelResolution due to averaging HorizontalVertical (< 8 km)Total_attenuated_backscatter_532v.4.1011/3 km30 mExtinction_coefficient_532v.3.41, v.4.2025 km60 mAerosol layer_top/base_altitudev.3.41, v.4.2025 km30 mFeature_classification_flagsv.3.41, v.4.2025 km60 m
The CALIPSO version 4 (V4) product determines the locations of layers within
the atmosphere, discriminates aerosols from clouds and categorizes aerosol
layers as 1 of 11 subtypes, 7 in the troposphere and 4 in the
stratosphere (Omar et al., 2009; Kim et al., 2018) providing also the
optical depth of each detected aerosol layer (Winker et al., 2012). The most
fundamental update in V4 is that aerosol layers are now classified as either
tropospheric aerosol or of certain stratospheric aerosol feature types. The
tropospheric aerosol types include the following subtypes: clean marine,
dust, polluted, continental/smoke, clean continental, polluted dust,
elevated smoke and dusty marine. Stratospheric aerosol subtypes have been
introduced for ash, sulfate or other, smoke and polar stratospheric aerosol.
Note that below the tropopause, ash and sulfate plumes are given by the
tropospheric aerosol subtypes: volcanic ash is often classified as dust or
polluted dust and volcanic sulfate is often classified as elevated smoke.
As a result, contiguous aerosol features crossing the tropopause will have
aerosol subtypes which switch from tropospheric to stratospheric subtypes,
depending on the relationship between the attenuated backscatter centroid
altitude of the layer identified by the feature finder and the tropopause
altitude. Refer to the Data Quality Summary Document for further details
(Vaughan et al., 2020).
CALIOP weighted extinction height
An important indicator for vertical profiles is the weighted extinction
height, a parameter that gives in a single number an indication of the
altitude of the detected aerosol plume distribution. This parameter is
considered ideal for comparisons with aerosol LH from passive
satellite sensors (e.g., GOME-2, IASI, TROPOMI) and the future Sentinel
missions, since these retrievals are very sensitive to the location of the
aerosol mass maximum within the detected layers. For the validation of the
TROPOMI SO2 LH, we used CALIOP L2 version 4.10 aerosol extinction
profiles at 5 km spatial resolution, retrieved from CALIOP observations of
attenuated backscatter at 532 nm (Winker et al., 2010). Quality flags are
also included in the L2 CALIOP products and are used to avoid cloud
contamination of aerosol retrievals, which means that cloud features are
identified and removed, as described in Winker et al. (2013) and Campbell et al. (2012).
To facilitate quantitative comparison of aerosol altitude, we used a mean
extinction height calculated from the CALIOP extinction profile, following
Koffi et al. (2012):
ALHext=∑i=1nβext,i⋅Zi∑i=1nβext,i,
where Zi is the height from sea level in the ith lidar vertical
level i (km), and βext,i is the aerosol extinction coefficient
(km-1) at the same level. In the CALIOP L2 products, aerosol
extinction is only retrieved for the layers in which aerosols are detected,
depending on the instrument's signal-to-noise ratio (SNR). In the case when
aerosols are present over clouds, ALHext will be situated in the center
of the aerosol layer, with any undetected aerosol layers below the cloud
layer not included in the calculations due to attenuation of the signal
beyond the cloud layer. According to this validation method, the CALIOP
532 nm channel observations are chosen for analysis as the conclusions from
the analysis of the results do not change when the 1064 nm channel
observations are used instead (Nanda et al., 2020).
SO2 LH for 2 example days of the Raikoke 2019
eruptive period, 23 June (a, c, e) and 2 July (b, d, f). S5P+I: SO2LH (a, b), IASI AOPP LH (c, d) and IASI ULB/LATMOS LH (e, f), including both ascending and descending orbits.
ResultsComparisons with the IASI/Metop SO<inline-formula><mml:math id="M122" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> LHRaikoke 2019
On 22 June 2019, a vast plume of ash and volcanic gases with more than
1000 DU of SO2 was emitted during the eruption of the Raikoke
volcano, Kuril Islands (McKee et al., 2021). This eruption could be detected
even 2 months after the end of eruptive event, which rendered it an
important case study for testing different satellite observations retrieval
methods; the original FP_ILM methodology applied to TROPOMI
observations (Hedelt et al., 2019), a probabilistic enhancement method using
the Cross-track Infrared Sounder (CrIS) on the Joint Polar Satellite System
(JPSS) series of satellites (Hyman and Pavolonis, 2020), a synergistic
analysis of different satellite observations and dispersion modeling (Kloss
et al., 2021) and the recent application of the FP_ILM
algorithm to OMI on Aura observations (Fedkin et al., 2021). This eruption was
also used in numerical atmospheric modeling in simulating the dispersion of
the Raikoke SO2 cloud in the UK Met Office numerical
atmospheric-dispersion modeling environment (de Leeuw et al., 2021) and
CAMS (Inness et al., 2022).
SO2 integrated mass (kt) against plume altitude (km) for 2
example days of the Raikoke 2019 eruptive period–24 June (a, b)
and 25 June (c, d)–for the S5P SO2 LH product in blue, IASI AOPP in orange (a, c), and IASI ULB/LATMOS in orange(b, d). In each set, the respective collocations are shown.
In Fig. 1, 2 example days of the 2019 Raikoke eruption, 23 June (left) and 2 July (right) are shown for the S5P SO2
LH (upper), the IASI AOPP LH (middle) and the IASI ULB/LATMOS LH (bottom)
observations. These demonstrational figures do not represent collocative
datasets, but show the spatial extent of the plumes reported by each
dataset, after filtering and gridding are performed. Due to the restriction
in SO2 load necessary (> 20 DU) in the S5P SO2 LH
algorithm, the thinner parts of the plumes are not captured by the S5P
observations; however, its NRT capabilities renders it an
excellent tool for early detection in view of aviation safety. The
equivalent maps for the SO2 load are presented in Fig. S1, where it
is shown that the extensive plumes reported by both IASI products are
associated with loads of less than ∼ 20 DU. A point to stress
here is the undeniable fact that the S5P LH is retrieved in the UV
wavelength range, which is sensitive to other atmospheric levels than the IR-based LH retrieval based on IASI data, hence different parts of the volcanic
cloud are detected. Although the IASI LH gives a first estimate of the height
of the volcanic cloud, this information cannot be used in S5P SO2
retrievals due to the difference in overpass time and pixel resolution. As
the main limitation of the S5P LH product is that it can only be applied to
modest to high volcanic eruptions, with SO2 VCD > 15–20 DU,
weak volcanic eruptions, or the weaker parts of SO2 plumes
cannot be retrieved. This point explains the different plume structure shown
in Fig. S1.
The vertical distribution of the Raikoke SO2 plume can be examined in
the integrated SO2 mass profiles presented in Fig. 2. The reported
SO2 load was integrated every 1 km, between 0 and 20 km, on the
collocated gridded datasets. In these 2 eruptive days, we note how the
SO2 mass dispersed is placed with respect to the retrieved LH
among the three datasets. Overall, the location of the peak SO2 mass is
within 2 km between S5P and IASI; however, for IASI AOPP the
amount of ejected SO2 mass is systematically lower in magnitude, even
though it is well placed in height. This is most likely linked to the
quality control applied to the IASI AOPP SO2 results, which excludes a
number of pixels within the core part of the plume, due to the poor fit
between the measured and modeled spectra.
Figure 3 shows the comparisons for the entire Raikoke eruptive period
between the S5P SO2 LH and the IASI/AOPP LH (left) and the IASI ULB/LATMOS LH (right) in histogram mode. For both comparisons, the mean S5P
SO2 LH is reported at 10.75 ± 3.50 km for the IASI/AOPP and at
∼ 10.20 ± 2.80 km for the IASI ULB/LATMOS collocations
IASI/AOPP places the plume at ∼ 11.40 ± 2.50 km and IASI ULB/LATMOS at ∼ 10.00 ± 1.0 km, resulting in an excellent
mean difference between sensors of ∼± 0.5 ± 3 km
on average.
Comparisons between spatiotemporally collocated plume heights for
the Raikoke 2019, eruptive days. (a) Left panel, histogram distribution
for the S5P LHs (blue) and the IASI/AOPP LHs (orange) and right panel, their
absolute differences. (b) As per (a) for the comparisons to the IASI ULB/LATMOS dataset.
Taal 2020 and La Soufrière 2021 eruptions
The Taal volcano in Batangas, the Philippines, erupted on the afternoon of
12 January 2020, 43 years after its previous eruption in 1977.
Strong explosions began around 15:00 and spewed an ash column exceeding 1km in thickness. By 19:30, volcanic activities intensified as
continuous eruptions generated a tall, 10–15 km, steam-laden
tephra column (Jing et al., 2020). Perttu et al. (2020) analyzed infrasound
observations to the east of the volcano and estimated a plume height and
duration for further ash dispersion modeling, reporting the plume at a mean
height of 15 km. The high spectral resolution lidar of the Manila
Observatory (http://www.observatory.ph/2020/01/17/taal-volcano-2020-eruption-impact-on-air-quality-part-i/,
last access: 13 October 2021) reported a massive ash cloud ingested and
transported above the 12 km altitude in the first post-eruption hours, a
finding further corroborated by the volcanic ash detected by the advanced
meteorological imager on board the GEOKOMPSAT-2A platform (Ahn et al., 2021)
whose analysis also placed the ash cloud at 12 km. The presence of ash
hinders the detection of the SO2 cloud by both UV-visible and
infrared sensors and partially explains the larger spread in reported
SO2 LHs by TROPOMI and IASI shown in Fig. S2. A large
disagreement on the altitude of the SO2 plume is found between
datasets in this case, with differences between -3 and -5 km between the
observations, also attributable to the ∼ 3 h difference in
sensing time and its importance when studying the first few hours after a
volcanic eruption (see maps in Fig. S3 in the Supplement).
On the morning of 9 April 2021, the La Soufrière volcano on the
Caribbean island of Saint Vincent began erupting, spewing ash at least 7.5
km in the air, for the first time since 1979. The volcano continued to erupt
over the next several days, with multiple violent explosions. Ash blanketed
Saint Vincent and winds carried ash to Barbados, about 120 miles (190 km) to the east. The
Smithsonian Institute Global Volcanism Program, https://volcano.si.edu/volcano.cfm?vn=360150, last access:
13 October 2021, reported a period of explosive activity and strong pulses of ash
emissions at 03:30 on 10 April, and the resulting ash plumes rose
to ∼ 10–16 km altitude throughout the day. On 12 April, at 04:15, another large explosion produced an ash plume that rose to
∼ 13 km altitude. The spread of the SO2 plume sensed by
TROPOMI and both IASI algorithms is shown in Fig. S4, where the SO2 plume reached very high altitudes, above 15 km, when close in location to
the volcano and decreasing in height as it progressed to the east over the
sea. For both comparisons in Fig. S5, the agreement of the collocative
datasets is within 1 km, all instruments placing the SO2 plume at an
average height of 14–15 km.
Summary of the comparisons with the IASI/Metop observations
The overall statistics for the comparisons of the SO2 plume altitude
for four eruptions between 2019 and 2021 for S5P and the IASI AOPP
comparisons are shown in Table 2, while those of the IASI ULB/LATMOS are
given in Table 3. The collocations refer each time to those of each of the
two sets. Note that for the Nishinoshima, Japan, eruptive period in July and
August 2020, collocations are only available for the IASI ULB/LATMOS
datasets. Overall, per eruptive period, the mean plume altitudes are
similarly placed by both UV-visible and infrared instruments, with a mean
difference of ∼ 0.20 ± 3.30 km for the Raikoke,
Nishinoshima and La Soufrière eruptions and ∼-3.60 ± 2.90 km
for the Taal eruption.
Overall statistics for the comparison between S5P LH and IASI AOPP LH for
the eruptive periods.
Scatter plots of the mean daily average reported SO2 LHs by TROPOMI/S5P and (a) IASI/AOPP for
the Raikoke, Taal and La Soufrière eruptions and (b) IASI ULB/LATMOS for the Raikoke, Taal and La Soufrière and Nishinoshima eruptions. The error bars represent the standard deviation of the mean, while the shaded areas represent the 95 % confidence interval of the fit.
CALIOP lidar measurements for the Raikoke eruption along the track
indicated in Fig. 6 on 25 June 2019. (Top) Total attenuated
backscatter profile (in sr-1 km-1), (middle) vertical feature mask
image showing the location of all layers detected and (bottom) aerosol
subtype. The area outlined in red denotes the volcanic feature detected from
CALIOP. Images courtesy of NASA: https://www-calipso.larc.nasa.gov/products/ (last access: 18 April 2022).
The comparisons between S5P and IASI AOPP SO2 LHs are shown in Fig. 4, on the left, and IASI ULB/LATMOS on the right, for all eruptive days where the
mean plume height reported for each of the 27 d of collocations is shown
as a scatter plot. For the IASI AOPP SO2 LHs (left) the comparison is
very promising, with a slope close to 0.91 ± 0.21, y-intercept of
1.20 ± 2.54 km and correlation coefficient of 0.66 for the 27
collocation days for the Raikoke, Taal and La Soufrière eruptions. The
outlier point, where S5P reports a high LH at ∼ 10 km, while IASI AOPP reports low at ∼ 5 km, belongs to the Taal
comparison, discussed previously. For ULB/LATMOS comparison, the mean
SO2 LHs, as expected, follow a straight line with a slope of
∼ 0.98 ± 0.19 and y-intercept of ∼ 0.77 ± 2.06 km, and a correlation coefficient of 0.73. Nearly 20 d
belong to the Raikoke eruptive period, and the rest to the Taal,
Nishinoshima (only for ULB/LATMOS) and La Soufrière eruptions.
Comparisons with CALIOP/CALIPSO volcanic ash LHRaikoke 2019
Within this study, the availability of overpasses of CALIOP/CALIPSO after
the eruption of the Raikoke volcano on the 22 June was examined.
Volcanic ash and sulfate aerosols are identified in CALIOP profiles based
on collocated TROPOMI pixel values. The closest distances between the CALIOP
footprint of the CALIPSO overpass and the locations of the TROPOMI center
pixels are selected to create collocated datasets, usually
with the two orbits being within 1 h of one another. To illustrate the
reliability of the TROPOMI SO2 LH product, we discuss in detail a
selected case of collocated and concurrent TROPOMI-CALIPSO observations
close to the detected SO2 plume from the Raikoke eruption on 25 June 2019.
We use the 532 nm Total Attenuated Backscatter (TAB) data version 4.10 from
one CALIPSO orbit in order to detect the aerosols and clouds and their
heights. The TAB signal strength (Fig. 5, top) is color-coded in a manner
that the blue background represents molecular and weak aerosol scattering
while aerosols typically appear in the shades of red, orange and yellow. The
gray scales represent the stronger cloud signals, while the weaker cloud
signals, being similar in strength to the strong aerosol signals, also
appear in the shades of red, orange and yellow. The TAB is sensitive to both
water and ice droplets, as well as numerous types of atmospheric particles.
The equivalent VFM image (Fig. 5, middle) shows the aerosol type, which is
retrieved according to the aerosol classification algorithm for all the
detected aerosol layers. The VFM describes the vertical and horizontal
distribution of both aerosols and clouds. After detection of the aerosol
features, they are then classified into types and subtypes. As shown in
Fig. 5 (bottom), the plume scene is well captured and according to the V4
algorithm, is classified as volcanic ash and sulfate (Kim et al., 2018). The
volcanic plume of the 25 June 2019 is outlined in red.
Figure 6 shows the TROPOMI SO2 LH pixels retrieved by the
FP_ILM algorithm for SO2 VCDs greater than or equal to
20 DU, QA > 50 and LH flag < 16, overlaid with the
calculated CALIPSO weighted extinction ALH pixel values (colored circles)
which are color-coded according to the range of height values (in km). The
CALIOP overpass time of this area is between 01:00 and 01:15 UTC, and the
TROPOMI overpass time is between 01:25 and 01:30 UTC, a time difference of
mere minutes. The TROPOMI plume shows several layers with SO2 LHs ranging from 5–6 km up to 14 km for this day. In the area of the
plume observed by both TROPOMI and CALIOP (54–58∘ N and 176–178∘ E), the CALIOP VFM and aerosol subtype mask
identify some volcanic ash at approximately 13 km altitude, and
meteorological clouds mixed with tropospheric aerosols (dust, polluted dust
and elevated smoke) at lower altitudes. The clouds below the ash plume are
shown in blue in Fig. 5, middle panel.
TROPOMI SO2 LH pixels for the Raikoke volcanic eruption,
measured on 25 June 2019. Only pixels with SO2 VCDs
greater than or equal to 20 DU are shown. The black line indicates the
CALIPSO ground track and the colored circles along the line indicate
weighted extinction height product values (in km), for the results shown in
Fig. 5.
The spatiotemporal collocation between TROPOMI and CALIOP on that day is
near perfect (Fig. 7, left) and the spatial agreement between SO2 LH
and CALIOP weighted extinction altitude is satisfactory, considering the
differences between the ash and SO2 plumes, confirming the presence of
volcanic plumes. Both instruments yield high altitude values; however,
TROPOMI retrieves higher altitudes especially for the western part of the
plume. A comparison scatterplot of collocated ash-flagged pixels is shown in
Fig. 7, right. The pixel-by-pixel scatter of the 57 common points shows a
high correlation of 0.73, even though the SO2 plume is placed
approximately 2 km lower than the ash plume.
(a) The latitude and longitudes of the collocated pixels. (b)
Comparison between TROPOMI SO2 LH and CALIPSO weighted extinction
height for 25 June 2019, color-coded depending on the TROPOMI
SO2 column amount. The orange line is the regression line of the
TROPOMI-CALIPSO observations; the gray line is the 1:1 line.
Overall, seven TROPOMI (at 22 June 02:20; 23 June 00:20; 24 June 00:00; 25 June 01:30;
28 June 02:00; 29 June 02:00 and 30 June 01:30) and CALIPSO collocated overpasses (at
22 June 02:30; 23 June 01:30; 24 June 00:30; 25 June 01:00; 28 June 03:00; 29 June 03:35 and
30 June 02:40) were identified. A statistical analysis has been performed using
all resulting 241 collocated pixels for 22, 23, 24,
25, 28, 29 and 30 June 2019. Figure 8 shows
the distribution of TROPOMI SO2 LH and CALIOP calculated weighted
height differences for all days, as a scatter plot on the left and on a
histogram representation on the right. The colored dots in the scatter plot
denote each individual eruptive day. The overall agreement is adequate and
as expected, with mean and median residual values around ∼-2.4 and ∼-3.0 km respectively, and a standard deviation of
∼ 1.7 km. The CALIOP ALHext is higher than TROPOMI
SO2 LH in the majority of the cases. This could partially be due to
CALIOP underestimating the aerosol layer thickness due to strong attenuation
of the lidar signal at the top of the detected aerosol layer (Rajapakshe et
al., 2017), whereas the TROPOMI SO2 LH product does not suffer from
such attenuation.
(a) Scatter plot of the TROPOMI SO2 LH and CALIPSO
weighted height for all collocated pixels on 22, 23,
24, 25, 28, 29 and 30 June 2019, for
the Raikoke eruption. (b) Histogram distribution of the absolute
differences between TROPOMI SO2 LH and the corresponding CALIPSO
weighted extinction height measurements, calculated for the 241 collocated
points.
Sinabung 2018, Nishinoshima 2020 and La Soufrière 2021 eruptions
On 19 February 2018, at 08:53 LT, the Indonesian
stratovolcano Mount Sinabung on Sumatra (2460 m summit elevation) erupted
jetting a large ash plume that quickly rose to heights of approximately 15–17 km. Although the eruption was spatiotemporally small an excellent
overpass was found against the CALIPSO instrument (Fig. S6, left). The
CALIOP track crossed the main part of the volcanic cloud, across the
north-south axis. Its overpass time was between 07:08 and 07:22 UTC, a
mere 45 min after the TROPOMI overpass time, between 06:24 and 06:26 UTC.
The CALIPSO observations showed both the ash cloud as a layer around 5 km,
as well as two vertical ash clouds extending from the volcano up to
∼ 10 km altitude. As shown in Fig. 9, where the S5P SO2
LH retrievals are shown in the red dots, the presence of clouds appeared along
the CALIPSO path indicated by the stronger attenuated backscatter than the
aerosol layer.
Sinabung, 19 February 2018, 07:15 UTC. The colors show the
CALIOP/CALIPSO total attenuated backscatter at 532 nm and the white-red dots
show the TROPOMI SO2 LH.
This case of mixing between ash and clouds over a volcanic eruption renders
the retrieval of the ash plume altitude by the lidar algorithm very
difficult, since it cannot separate clouds from aerosols, especially when
the aerosol amount is low. The CALIPSO feature mask (not shown here) hardly
identifies any of the Sinabung backscatter signals as aerosol. The main
plume, at ∼ 15 km is flagged as a cloud feature, while below this
feature everything is masked as “totally attenuated”, which is not
expected to be the case. Most probably liquid water or ice particles are
contaminating the volcanic ash signal, as already discussed in Hedelt et
al. (2019). Even though the maximum TROPOMI SO2 LH agrees with the
maximum backscatter height between 2–3∘ latitude, a large spread
of TROPOMI SO2 LHs is also reported. As discussed also in the work of
de Laat et al. (2020), the presence of either a nearly transparent or a
bright cloud may result in the TROPOMI algorithm reporting heights far lower
than both the ash and the cloud plumes. For the cases of Nishinoshima 2020
and La Soufrière 2021 eruptions, both provided a satisfactory
collocation to the CALIOP orbital path without the difficulties found in the
case of Sinabung 2018, enabling a meaningful comparison to be made. For
Nishinoshima, spatial collocations for 1 August 2020 are shown
in Fig. S7 (left), while the scatterplot of height values is shown on the
right. The geographical collocations between TROPOMI and CALIOP are not
optimal; however, the agreement between SO2 LH and CALIOP weighted
extinction altitude is satisfactory, and tends to confirm the presence of
volcanic plumes. The CALIPSO observations confirm the presence of volcanic
clouds around 5 km, while S5P reports slightly higher loads, at
∼ 7.5 km. For the case of La Soufrière, spatial
collocations for 11 April 2021 are shown in Fig. S8 (left),
and the scatterplot of collocations is shown Fig. S8 (right). In this case, both CALIPSO and TROPOMI
collocated pixels confirm the presence of a volcanic cloud up to and around
∼ 20 km.
Summary of the comparisons with the CALIPSO/CALIOP observations
The combination of CALIOP and TROPOMI data measurements has permitted the
identification of volcanic aerosol layers produced by three individual
volcanic eruptions. A summary plot of the comparisons between S5P
SO2 and CALIPSO ash LHs is presented as a scatter plot in Fig. 10,
showing the mean ash and SO2 plume height reported for each of the 9 d of collocations. The comparison is very promising, with a slope close
to 0.95, y-intercept of ∼ 1 km and correlation coefficient of
0.86 for the 9 collocation days for the Raikoke, Nishinoshima and La
Soufrière eruptions. The majority of cases, 7 d, belong to the
Raikoke eruptive period, and the remainder 2 d to Nishinoshima and La
Soufrière eruptions. From Table 4 it is worth noting that
the standard deviation of the mean heights reported by both instruments are
low, typically much less than 1 km. This can most likely be attributed to
the tight spatiotemporal collocation criteria that were possible for these
comparisons. The behavior of altitude range differences are also
corroborated by the works of Muser et al. (2020), De Leeuw et al. (2020) and
Osborne et al. (2022). These studies highlight that, for coarse-mode ash, the aging process is the determining factor of the vertical
distribution of aerosols and therefore the determining factor for the altitude at which the particles are transported, alongside the meteorological effects.
Statistics for the comparison between S5P and CALIPSO for the
eruptive days studied.
Eruptive dayMean CALIPSO LH (km)Mean S5P LH (km)Mean difference (km)Collocations no.22 June 201910.84 ± 0.49.40 ± 0.75-1.43 ± 0.56823 June 201912.06 ± 0.288.88 ± 0.76-3.17+0.981324 June 201912.33 ± 0.211.07 ± 1.24-1.26 ± 1.402225 June 201912.47 ± 0.19.41 ± 0.76-3.05 ± 0.545728 June 201913.12 ± 0.9211.53 ± 1.6-1.59 ± 2.138729 June 201914.06 ± 0.4710.84 ± 0.7-3.21 ± 0.994630 June 201913.16 ± 18.88 ± 1-4.28 ± 0.5681 August 20206.14 ± 0.127.48 ± 0.481.34 ± 0.46811 April 202119.28 ± 0.5420.35 ± 1.041.06 ± 1.4412
Scatter plot of the mean daily average reported SO2 LHs by
TROPOMI/S5P and CALIOP/CALIPSO for the 7 d of the Raikoke eruption
and one each for Nishinoshima and La Soufrière eruptions studied.
Generally, we note that features identified as volcanic ash by the CALIOP
aerosol subtype mask are captured by the TROPOMI algorithm, but the
surrounding clouds often affect the retrieval. Formation of high-altitude
condensed water or ice in the ash plume may shield part of the underlying
SO2 and ash amounts. The comparison of the TROPOMI SO2 LH product
within this project shows promising capability in detecting plumes of
volcanic origin, with some limitations related to existing or subsequent
creation of clouds. Furthermore, although ash and SO2 plumes are often
collocated, especially during the first hours after eruption, this is not always
the case, making direct comparisons challenging.
Application of the S5P SO<inline-formula><mml:math id="M294" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> LH in NRT data assimilation modeling
CAMS, operated by the
European Centre for Medium-Range Weather Forecasts (ECMWF) on behalf of the
European Commission, provides daily SO2 analyses and 5 d forecasts of
volcanic SO2 in NRT by assimilating total column SO2 retrievals
from TROPOMI and GOME-2 (Inness et al., 2022). As the operational NRT
TROPOMI and GOME-2 retrievals do not provide any information about the
height of the volcanic plumes, the SO2 increments are placed in the
mid-troposphere, around 550 hPa (∼ 5 km) in the current
operational CAMS configuration.
The procedure used to assimilate NRT TROPOMI/S5P and GOME2/Metop
SO2 loads in the operational CAMS NRT data assimilation system was
presented, alongside the simultaneous ingestion of the S5P SO2 LH, by
Inness et al. (2022). The assimilation was tested for the Raikoke 2019
eruption and was contrasted to the operational CAMS forecasts obtained when
assimilating only the TROPOMI SO2 load. In this paper 2 example days are shown to demonstrate how the CAMS assimilation of the S5P SO2 LH
product leads to much improved model output against the non-assimilated IASI
LHs, compared to the original CAMS analysis.
Raikoke eruptive days of 24 (a, c, e) and 25 (b, d, f) June 2019. (a, b) The IASI ULB/LATMOS SO2 LH in km. (c, d) The
CAMS BLexp SO2 LH (without assimilation). (e, f) The CAMS
LHexp SO2 LH (with assimilation).
In Fig. 11, upper row, the IASI ULB/LATMOS SO2 LH, gridded onto
the CAMS 1×1∘ spatial resolution and 3h temporal resolution, is
shown for 24 (left column) and 25 (right column)
June 2019, 5 d after the initial Raikoke eruption. In the middle panel,
the operational CAMS SO2 LH (called BLexp) is presented which
is deduced from placing the SO2 increment in the mid-troposphere,
around 550 hPa, clearly in the wrong altitude for the Raikoke eruption which
injected a huge amount of SO2 above the tropopause, well into the
stratosphere. In Fig. 11, lower panel, it can be seen that a vast
improvement to the CAMS forecast is achieved for both days when the S5P
SO2 LH data are used (called LHexp) as the structure of the Raikoke
SO2 plume is much improved and compares well with the independent IASI
SO2 LHs shown in the upper panel. For the entire eruptive
period of Raikoke between 22 and 29 June, the CAMS
forecast, which assimilates the S5P SO2 LH data, improves the bias in the
forecast height between CAMS and IASI to ∼-1.5 ± 2.5 km,
compared to a mean bias of ∼-5 ± 2 km for the
operational system. We can hence conclude that by assimilating the S5P
SO2 LH data, the vertical location of the Raikoke SO2 plume in
the CAMS system is improved, leading to better subsequent forecasts and
making the S5P SO2 LH product suitable for NRT assimilation and
forecasts of a possible strong future volcanic eruption.
Conclusions
The European Space Agency Sentinel-5p+ Innovation TROPOMI/S5P SO2
LH product has been verified against IASI/Metop SO2 LHs for the eruptive periods of the Raikoke volcano, 22 June to 30 July 2019, the Taal volcano, 13 January 2020, the Nishinoshima eruptive period
during July and August 2020 and the La Soufrière eruptive days of 10 to 11 April
2021. Two different algorithms that provide plume
altitudes from the IASI instruments were examined, the official EUMETSAT
ACSAF algorithm, ULB/LATMOS, and the University of Oxford, AOPP, algorithm.
Furthermore, collocations against ash LH observations by the
space-borne CALIOP/CALIPSO lidar system were identified and assessed.
The main findings in the comparisons of the SO2 volcanic plumes,
described in detail above, are:
For the Raikoke eruptive days: the difference between S5P and IASI/AOPP
SO2 LH datasets is 0.61 ± 3.72 km, with IASI/AOPP SO2 LH
reporting a mean height of ∼ 11.40 ± 2.5 km and S5P
reporting ∼ 10.75 ± 3.5 km, in excellent agreement. Between S5P and IASI ULB/LATMOS SO2 LHs a similar mean difference of
-0.15 ± 2.83 km is found with both sensors reporting on average LHs at
∼ 10.20 ± 2.80 and ∼ 10.00 ± 1.0 km
respectively.
For the Taal eruptive day: the SO2 LHs reported differ substantially
with IASI/AOPP reporting heights at 5.64 ± 1.5 km while S5P reports
higher columns, at ∼ 10.14 ± 3.5 km. IASI ULB/LATMOS also
reports lower heights, at 9.51 ± 1.78 km while and S5P places the plume
at ∼ 12.13 ± 3.95 km with a mean difference
of ∼-2.62 ± 3.0 km.
For the Nishinoshima eruptive days: both sensors place the plume at the same
altitude, with IASI ULB/LATMOS at ∼ 8.0 ± 1.04 km and S5P
∼ 7.73 ± 1.97 km and mean difference of ∼ 0.27 ± 2.79 km.
For the La Soufrière eruptive days: all three sensors report high plume
altitudes, between 13 and 16 km. For the collocations between S5P and
IASI/AOPP, the mean SO2 LH was found at 13.82 ± 2.49 and
13.47 ± 3.41 km respectively, with a mean difference of -0.35 ± 3.55 km. For the S5P and IASI ULB/LATMOS collocations, the mean SO2 LH was
found at 14.94 ± 3.87 and 15.7 ± 1.16 km, respectively, with a
mean difference of 0.76 ± 3.69 km.
Scatter plot comparisons of the daily mean volcanic SO2 plumes reveal
common SO2 LH patterns for the two sensors, with substantial
correlations ∼ 0.66 (0.72), slope ∼ 0.9 (0.98),
y-intercept of 1.2 km (0.8 km) for the IASI/AOPP and the IASI ULB/LATMOS, respectively. The standard deviation of the mean is relatively high, on
average ∼ 3 km; however, the mean heights are well within the 2 km accuracy requirement on the S5P SO2 LH product.
With respect to the comparisons between the S5P SO2 LH and the
CALIOP/CALIPSO volcanic ash LH, we report that:
241 excellently spatiotemporally collocated points between CALIOP and
TROPOMI were identified for 7 Raikoke eruptive days. CALIOP reported a
range of mean heights between ∼ 11 and 14 km, while TROPOMI
had a far narrower range between ∼ 9 and 11.5 km. Overall, the
mean difference in heights was found to be -2.4 ± 1.7 km (-3.0 km
median) for the 7 eruptive Raikoke days.
The comparisons for the Nishinoshima and La Soufrière eruptions showed
good agreement with plumes reported at ∼ 7 km and ∼ 19.5 km, respectively, for the two eruptions, and a height difference between
S5P and CALIPSO being within ∼ 1.0 km.
The mean daily height plot of the comparisons between S5P
SO2 LHs and CALIOP/CALIPSO weighted ALH, as expected, follow a straight
line, with slope of 0.95 and y-intercept of ∼ 1.0 km and
excellent correlation coefficient at 0.86.
Finally, the CAMS assimilation of the NRT S5P SO2 LH led to much
improved model fields against the non-assimilated IASI plume heights for the
Raikoke eruptive period, with a mean difference of 1.5 ± 2 km against
the independent IASI/Metop observations, and improved the geographical
spread of the Raikoke volcanic plume following the main eruptive day.
Data availability
The NRT S5P SO2 LH products are
operationally generated by DLR within the framework of the Innovative Products
for Analyses of Atmospheric Composition (INPULS) project, and are available
upon request from Pascal Hedelt (pascal.hedelt@dlr.de). The
IASI/MetOp ULB/LATMOS open source SO2 LH dataset is publicly
available from https://iasi.aeris-data.fr/so2_iasi_a_arch/ (IASI Portal, 2021). The
IASI/MetOp AOPP SO2 products are available on request from Isabelle
Taylor (isabelle.taylor@physics.ox.ac.uk). The CALIPSO data
were obtained from the online archive of the NASA Langley Research Center
Atmospheric Science Data Center (ASDC, 2022, https://asdc.larc.nasa.gov/project/CALIPSO). The Copernicus Atmosphere
Monitoring Service is operated by the European Centre for Medium-Range
Weather Forecasts on behalf of the European Commission as part of the
Copernicus program (http://copernicus.eu, last access: 18 April 2022) and CAMS data are freely available
from http://atmosphere.copernicus.eu/data (Copernicus Atmosphere Data Store, 2022). The SO2 analysis experiments used
in this paper are available from https://apps.ecmwf.int/research-experiments/expver/ (last access: 18 April 2022) with the DOIs:
10.21957/cygt-xf49 (ECMWF, 2022a) (BLexp), 10.21957/qfam-7474 (ECMWF, 2022b) (LHexp).
The supplement related to this article is available online at: https://doi.org/10.5194/acp-22-5665-2022-supplement.
Author contributions
MEK prepared the code to analyze all the different SO2 LH data, carried out all of the relevant validation parts and wrote most of the paper. KM prepared the code to analyze the CALIPSO data, carried out all of the relevant validation parts and wrote the relevant part of the paper. PH and DE provided the S5P/TROPOMI SO2 LH data. IT provided the IASI/Metop AOPP SO2 LH data under the supervision of RG. AI provided the CAMS experiments. LC is the PI of the IASI/Metop ULB/LATMOS SO2 LH data. DB and DL provided scientific support to this work. CR supervised the entire project. All co-authors provided useful feedback on the paper.
Competing interests
The contact author has declared that neither they nor their co-authors have any competing interests.
Disclaimer
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Acknowledgements
This work is performed in the framework of ESA
Sentinel-5p+ Innovation: SO2 Layer Height project (S5P+I: SO2LH),
https://eo4society.esa.int/projects/sentinel-5p-innovation-so2-layer-height-project/ (last access: 18 April 2022).
The comparative results presented in this work have been produced using the
Aristotle University of Thessaloniki high performance computing
infrastructure and resources. Maria-Elissavet Koukouli would like to acknowledge the support
provided by the IT Center of the Aristotle University of Thessaloniki
throughout the progress of this research work, as well as the Atmospheric
Toolbox®. Isabelle A. Taylor and Roy G. Grainger would like to acknowledge
EUMETSAT for providing the IASI spectra and ECMWF (ECMWF, 2012) and CEDA for the
meteorological profiles used in the IASI retrievals. Isabelle A. Taylor and Roy G. Grainger
further acknowledge support from the NERC Centre for Observation and
Modelling of Earthquakes, Volcanoes, and Tectonics (COMET). We thank the DLR
Innovative Products for Analyses of Atmospheric Composition (INPULS)
project, for continuously providing the S5P SO2 LH products in
NRT.
Financial support
This research has been supported by the European Space Agency (grant no. 4000127508/19/I-NS). The article processing charges for this open-access publication were covered by the German Aerospace Center (DLR).
Review statement
This paper was edited by Stelios Kazadzis and reviewed by two anonymous referees.
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