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Geophys. J. Int. (2022) 228, 1281–1293 https://doi.org/10.1093/gji/ggab392
Advance Access publication 2021 September 24
GJI Seismology
Mayotte seismic crisis: building knowledge in near real-time by
combining land and ocean-bottom seismometers, first results
Jean-Marie Saurel ,1Eric Jacques,1Chastity Aiken ,2Anne Lemoine ,3
Lise Retailleau,1,4Aude Lavayssi`
ere,1Oc´
eane Foix,2Anthony Dofal ,1,5
Ang`
ele Laurent,1Nicolas Mercury,3,6Wayne Crawford,1Arnaud Lemarchand,1
Romuald Daniel,1Pascal Pelleau,2Maxime B`
es de Berc,6Gr´
egoire Dectot,7
Didier Bertil,3Agathe Roull´
e,3C´
eleste Broucke,8Alison Colombain,3H´
el`
ene Jund,8
Simon Besanc¸on,1Pierre Guyavarch,2Philippe Kowalski,1,4Micka¨
el Roudaut,2
Ronan Apprioual,2Jean Battaglia,9Soumya Bodihar,1Patrice Boissier,1,4Marie
Paule Bouin,1Christophe Brunet,1,4K´
evin Canjamale,1,4Philippe Catherine,1,4
Nicolas Desfete,1,4C´
ecile Doubre,6R´
emi Dretzen,8Tom Dumouche,1Philippe Fernagu,2
Val ´
erie Ferrazzini,1,4Fabrice R. Fontaine,1,5Arnaud Gaillot,2Louis G´
eli,2
Cyprien Griot,1,4Marc Grunberg,8Emre Can Guzel,10 Roser Hoste-Colomer,3
Sophie Lambotte,6Fr´
ed´
eric Lauret,1,4F´
elix L´
eger,1Emmanuel Maros,2Aline Peltier,1,4
J´
erˆ
ome Vergne,8Claudio Satriano,1Fr´
ed´
eric Tronel,7J´
erˆ
ome Van der Woerd,6
Yves Fouquet,2Stephan J. Jorry,2Emmanuel Rinnert,2Isabelle Thinon11 and
Nathalie Feuillet1
1Universit´
e de Paris, Institut de Physique du Globe de Paris, CNRS, F-75005 Paris, France. E-mail: saurel@ipgp.fr
2IFREMER, Centre de Bretagne, –Unit´
eG
´
eosciences Marines, 1625 Rte de Ste Anne, 29280 Plouzan´
e, France
3BRGM, French Geological Survey, Risk and Prevention Division, F- 45100 Orl´
eans, France
4Observatoire volcanologique du Piton de la Fournaise, Institut de Physique du Globe de Paris, F-97418 La Plaine des Cafres, La R´
eunion, France
5Universit´
edeLaR
´
eunion, Laboratoire G´
eoSciences R´
eunion, F-97744 Saint Denis, La R´
eunion, France
6ITES, Institut Terre Environnement de Strasbourg, UMR 7063, CNRS Universit´
e de Strasbourg, 5,rueRen
´
e Descartes, 67084 Strasbourg, France
7BRGM, French Geological Survey, Regional Division (Mayotte), F-97600 Mamoudzou, Mayotte, France
8EOST, Universit´
e de Strasbourg/CNRS, 5rue Descartes, 67084 Strasbourg Cedex, France
9Universit´
e Clermont Auvergne, CNRS, IRD, OPGC, Laboratoire Magmas et Volcans, F-63000 Clermont-Ferrand, France
10Istanbul Technical University, Faculty of Electrical and Electronics Engineering - Graduate School, Electronics and Communications Engineering
Department, 34469 Maslak/Istanbul, Turkey
11BRGM, French Geological Survey, Georesources, F-45100 Orl´
eans, France
Accepted 2021 September 22. Received 2021 September 14; in original form 2021 February 24
SUMMARY
The brutal onset of seismicity offshore Mayotte island North of the Mozambique Channel,
Indian Ocean, that occurred in May 2018 caught the population, authorities and scientific
community off guard. Around 20 potentially felt earthquakes were recorded in the first 5 d,
up to magnitude Mw5.9. The scientific community had little pre-existing knowledge of the
seismic activity in the region due to poor seismic network coverage. During 2018 and 2019,
the MAYOBS/REVOSIMA seismology group was progressively built between four French
research institutions to improve instrumentation and data sets to monitor what we know now
as an on-going exceptional submarine basaltic eruption. After the addition of 3 medium-band
stations on Mayotte island and 1 on Grande Glorieuse island in early 2019, the data recovered
from the Ocean Bottom Seismometers were regularly processed by the group to improve the
location of the earthquakes detected daily by the land network. We first built a new local 1-D
velocity model and established specific data processing procedures. The local 1.66 low VP/VS
ratio we estimated is compatible with a volcanic island context. We manually picked about
C
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1282 J.-M. Saurel et al.
125 000 Pand Sphases on land and sea bottom stations to locate more than 5000 events
between February 2019 and May 2020. The earthquakes outline two separate seismic clusters
offshore that we named Proximal and Distal. The Proximal cluster, located 10 km offshore
Mayotte eastern coastlines, is 20–50 km deep and has a cylindrical shape. The Distal cluster
start 5 km to the east of the Proximal cluster and extends below Mayotte’s new volcanic edifice,
from 50 to 25 km depth. The two clusters appear seismically separated, however our data set
is insufficient to firmly demonstrate this.
Key words: Indian Ocean; Volcano seismology; Volcano monitoring; Africa; Remote sensing
of volcanoes.
1. INTRODUCTION
Before 10 May 2018, Mayotte island, part of the volcanic Comoros
archipelago in the North Mozambique Channel of the Indian Ocean
(Fig. 1), was not considered as a significantly seismically active area
(Bertil & Regnoult 1998). The last reported widely felt earthquakes
occurred around 30 km west of Mayotte: a moment magnitude (Mw)
5.0 event on 9 September 2011 (EMS98 intensity V estimated) and a
magnitude (M) 5.2 event on 1 December 1993 (Lambert 1997) with
moderate damages (EMS98 intensity VI estimated). Together with
an unfelt M5.1 event on 23 March 1993, 80 km southwest of May-
otte, these were the only M5+earthquakes recorded within 100 km
of the island since the advent of the global seismological networks
in 1964 (Storchak et al.2017;ISC2020). As a consequence, only
one real-time seismic station (RA.YTMZ; R´
esif 1995) was installed
on the island at the onset of the 2018 seismic crisis. This station was
deployed by BRGM (Bureau de recherches g´
eologiques et mini`
eres,
the French geological survey) for the French accelerometric moni-
toring network (R´
esif-RAP, P ´
equegnat et al.2008).
On 10 May 2018, the first felt earthquake, quickly followed by
many others, surprised inhabitants. More than 130 M4+earth-
quakes were recorded in the following months, with the strongest
being a Mw5.9 on 15 May 2018 (GCMT project, Dziewonski et
al.1981;Ekstr
¨
om et al.2012; Lemoine et al.2020a). After about
50 d of very intense seismic activity, this unprecedented seismic
sequence continued less intensively. During the summer of 2018,
Global Navigation Satellite System (GNSS) data from the locally
continuously recording sites began to show rapid surface displace-
ments of the island (Briole 2018;Cescaet al.2020; Lemoine et al.
2020a). Their elastic modelling evidence a large regional deflation
centred east of Mayotte’s shorelines (Cesca et al.2020; Lemoine
et al.2020a). On 11 November 2018, a very low frequency tremor
was recorded worldwide (Satriano et al.2019; Cesca et al.2020;
Lemoine et al.2020a), confirming that the seismic crisis was very
likely of magmatic origin. This was later confirmed by the discov-
ery of a new submarine volcanic edifice offshore Mayotte during
the MAYOBS1 scientific expedition onboard RV Marion Dufresne
in May 2019 (Feuillet et al.2021). This large eruption began either
on June 18 (Cesca et al.2020) or on 3 July 2018 (Lemoine et al.
2020a).
Since the onset of the crisis, collaborations were progressively
established between French research institutes to improve the under-
standing and knowledge of the on-going crisis. These collaborations
enhanced the seismic monitoring of the region, which included in-
stalling additional real-time sites onshore, access to real-time data
recorded by existing regional stations and offshore deployments.
During the first year of the crisis, the monitoring network thus
evolved rapidly (Lemoine et al.2020a). In March 2019, 1 month
after funding, four seismic stations were installed onshore (three
on Mayotte island and one on Grande Glorieuse island) and six
Ocean Bottom Seismometers (OBS) were deployed offshore, within
a radius of 40 km around the seismically active area. A seismol-
ogy team was created among the researchers, engineers, and stu-
dents belonging to the participating French institutions (BRGM;
Institut de Physique du Globe de Paris—IPGP; Institut Franc¸ais
de Recherche pour l’Exploitation de la Mer—IFREMER; Insti-
tut National des Sciences de l’Univers du Centre National de la
Recherche Scientifique—INSU-CNRS). In July 2019, the Mayotte
seismo-volcanic monitoring network (R´
eseau de surveillance vol-
canologique et sismologique de Mayotte—REVOSIMA) was cre-
ated with all four institutions. The aim of the team is to process
newly acquired data as quickly as possible and to obtain first hand
results in almost real-time, to improve the daily monitoring and the
knowledge of the volcano-seismic crisis.
In this paper, we review the local seismic network improvements
since the beginning of the crisis and our scientific developments. We
detail how this collaborative work was orchestrated for maximum
efficiency and how it led to an improved local velocity model and
a seismic catalogue from February 2019 up to May 2020 to better
document the Mayotte 2018-ongoing seismo-volcanic crisis.
2. SEISMIC NETWORK EVOLUTION
AND DATA PROCESSING
From May 2018 to June 2019, the Mayotte local real-time seis-
mic network progressively evolved from 1 to 8 stations. Daily data
analysis protocols have also been continuously adapted in several
Institutes by our group to take advantage of the increasing number
of local stations and to produce better locations for the detected
events (see details in Section 2.2). In 2019, we also developed a
new protocol to efficiently process OBSs data during pickathons,
when, at the same place, several analysts dedicate a few days to
work together on the newly recovered data.
2.1 Development of the monitoring network
2.1.1 The in-land network
At the beginning of the seismic crisis, Mayotte’s seismicity was
monitored by the BRGM with the only local real-time seismic
station from the French R´
esif-RAP accelerometric RA network
(YTMZ; R´
esif 1995) and some regional stations from international
networks (IRIS/IDA, GEOFON and GEOSCOPE in Madagascar,
Kenya, Seychelles and La R´
eunion). In the Comoros archipelago,
the Observatoire Volcanologique du Karthala (OVK) monitors the
Karthala volcano (Grande Comore) since 1988. The OVK seismic
network, while located 250 km northwest from Mayotte (Fig. 1b),
was crucial for characterizing Mayotte’s seismicity, particularly at
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Mayotte seismic crisis: first results from marine and land seismic deployments 1283
Figure 1. Maps of seismological land stations and Ocean Bottom Seismometers (OBSs) used in this study with the red volcano symbol representing the
location of the new volcanic edifice (Feuillet et al.2021). (a) Map showing the regional stations contributing to the monitoring (yellow inverted triangles).
Red rectangles highlights the Comoros archipelago area shown in (b) and the Mayotte area shown in (c). (b) Map of the Comoros archipelago showing the
temporary stations used for previously-developed velocity profiles (orange squares), historical M>5,0 earthquakes close to Mayotte (white stars) and the
Karthala seismic network (yellow inverted triangles). (c) Map of the local land stations (green inverted triangles, most of them installed in 2019) and all OBSs
deployed between February 2019 and May 2020 [blue inverted triangles, the blue hue depends on the MAYOBS deployment timing as seen in (d)]. The MAYO
station (orange square) is the temporary station used by Dofal et al.(2018) receiver function study. The white dots represent the 5000 manually relocated
earthquakes. (d) Time evolution of the number of recording stations since the onset of the crisis. All regional stations (dark grey) are available in real-time.
Local stations (added to the regional stations; in grey)—significantly increased in number in 2019. The number of OBSs (added to the local and regional
stations; in light grey) varies over time depending on the MAYOBS deployment period (blue scale on bottom right numerated as the MAYOBS oceanographic
campaigns that recovered them). The dashed line represents the evolution in time of the number of real-time stations.
the beginning of the sequence. Real-time seismic data recorded at
Karthala volcano were shared during the first weeks of the crisis
via its French partner in the Indian Ocean, the Observatoire Vol-
canologique du Piton de la Fournaise (OVPF-IPGP). In June 2018, a
medium-band station was installed at a Mayotte school (ED.MCHI),
cofunded by the local representation of the ministries of environ-
ment (DEAL) and of education as well as the BRGM, within the
program Edusismo (Virieux 2000). By the end of June 2018, the
seismicity decreased after one and a half month of intense activ-
ity. At that time, the BCSF-R´
eNaSS (Bureau Central Sismologique
Franc¸ais—R´
eseau National de Surveillance Sismique), in charge of
the macroseismic and intensity investigations on the national ter-
ritory, performed a macroseismic field survey on Mayotte (Sira et
al. 2018) and took advantage of this mission to install two Rasp-
berryShake instruments (B `
es de Berc et al.2019) from the AM
network (Raspberry Shake Community et al.2016): RAE55 and
RCBF0. RCBF0 station unfortunately failed after 2 weeks. The lo-
cal onshore network (Fig. 1) was not upgraded again until March
2019 with the installation of three stations: two Guralp CMG40T
medium-band sensors from the 1T temporary network (Feuillet, Van
der Woerd and RESIF, 2022)—MTSB and PMZI; and one Nano-
metrics Trilium120PA broad-band sensor from the QM network—
KNKL. Safety and rapid deployment on a small island, as well as
network geometry, were key criteria to choose the station sites. The
stations were therefore installed in city halls or public buildings to
ensure a stable power supply and protection from theft. In the same
time, a seismic station with triggered data transmission from the QM
network (GGLO) was installed on Grande Glorieuse, a small island
250 km northeast from Mayotte, completing the regional network in
March 2019. Finally, two RaspberryShake instruments were added
to the AM network by R´
eNaSS in June 2019 on Mayotte: R1EE2
and R0CC5 (colocated with RA.YTMZ station).
2.1.2 The OBS network
At the end of February 2019, six short-period OBSs from the
INSU-IPGP OBS facility were deployed from a barge around the
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1284 J.-M. Saurel et al.
earthquake locations that were known at the time (Bertil et al.
2019). The INSU-IPGP OBSs are free-fall instruments with 1-yr
maximum autonomy, whose sensors are a 3-channel geophone and
a broad-band hydrophone. There have been several recoveries and
redeployments of OBSs since then, but there have always been
4–16 OBSs deployed (Fig. 1d), which have greatly improved the az-
imuthal coverage of the local seismic network, as will be discussed
later in the paper. The INSU-IPGP OBSs were regularly comple-
mented with IFREMER micrOBSs or LotOBSs, hosting a similar
geophone and a short-period hydrophone but with an autonomy,
respectively, limited to 45 or 120 d maximum. After the initial de-
ployment, area specific location protocol establishment and much
more precise location of the seismicity, the OBS network geometry
remained stable and a number of positions were re-occupied during
subsequent deployments (Figs 1c and d).
Data acquisition protocol differs depending on the instruments—
land or ocean-bottom based. Data from land stations are acquired
and transferred in real-time, except the regional QM.GGLO sta-
tion from which only triggered data can be transmitted via a low-
bandwidth satellite link. The onshore data are centralized at the
IPGP data centre and then made available through the same pro-
tocol on its public SeedLink server. The three stations installed on
Mayotte in March 2019 were not equipped with internet connec-
tion during the first months of recording but were brought online
in May 2019. Their data were manually collected from the internal
storage just before the departure of the RV Marion Dufresne for the
MAYOBS1 oceanographic campaign in May 2019 (Feuillet 2019).
The OBSs are regularly serviced for maintenance and data recov-
ery (every 3–4 months for INSU-IPGP, every month for micrOBSs).
As of May 2020, nine different OBSs deployments have been con-
ducted. When the OBSs are recovered, their data are downloaded and
time-corrected for internal clock drift and converted to miniSEED
format using L-Cheapo tools (Orcutt & Constable 1996). These data
are then integrated in the main waveform database at the IPGP data
centre, along with the local and regional land station data.
2.2 Data analysis
2.2.1 Daily monitoring
For daily monitoring of the crisis, only the real-time data from land
stations can be used. Several institutes successively participated in
the day-to-day seismic data processing, using SeisComP3 (Weber et
al.2007) with slightly different setups. The BRGM office in May-
otte was involved first and maintained a seismic catalogue from the
beginning of the crisis in May 2018 (Bertil et al.2018,2019). The
events from Bertil et al.(2018,2019) were located from manu-
ally picked waveforms using the LocSAT algorithm (Bratt & Bache
1988) and a slightly modified IASPEI91 velocity model (Kennett
& Engdahl 1991). During the summer of 2019, with the addition
of new local stations available in real-time, the R´
eNaSS hosted by
the Ecole et Observatoire des Sciences de la Terre in Strasbourg
(EOST) improved the settings of its SeisComP3 automatic detec-
tion system by using STA/LTA automatic picking and grid-search
location. They took over the role of manually picking all automat-
ically detected events for the newly created R´
eseau de surveillance
Volcanologique et Sismologique de Mayotte (REVOSIMA) work-
ing group. The R´
eNaSS also used LocSAT but with the original
IASPEI91 model. In April 2020, the daily manual picking and lo-
cation duty was transferred to OVPF-IPGP in La R´
eunion, which
uses the NonLinLoc (NLL) location software (Lomax et al.2014)
and a new hybrid velocity model described in Section 3. The NLL
configuration and 1-D local velocity model used by OVPF-IPGP in
La R´
eunion were developed during MAYOBS1 campaign in 2019
(Feuillet et al.2019;Saurelet al.2019; Feuillet 2019).
While a daily manual screening of continuous waveforms with
WebObs (Beauducel et al. 2020) and identification of every event
has been performed since early 2019, the composite earthquake cat-
alogue is based on the automatic detection of events from land sta-
tions. The land stations influence the magnitude detection threshold
for two reasons. First, the land-based seismic network has evolved
since May 2018, and second, the chosen sites that offered equipment
safety are often affected by anthropogenic noise, implying a daily
variation of the magnitude detection threshold. Since the drastic
improvement of the local land network in spring 2019, the detec-
tion threshold is around M2.0 at nighttime and around M2.5 during
daytime.
2.2.2 OBS integration
After each OBSs data recovery, we manually pick phases on the OBS
data and offline land stations to improve the locations in the exist-
ing earthquake catalogue during dedicated pickathons that continue
today. Adding new phase picks significantly improved the location
of the earthquakes already detected and first located only by the
land network. Since there are already a great number of events to
relocate in the existing catalogue, we do not search for new events
from the OBS data set. Searching for new events in the OBS data
set is a work in progress and will be reported in future studies.
During each pickathon, the time span of the OBSs data we need
to process is divided across three teams using the same software
setup and each team manually locates earthquakes in descending
order of magnitude (Saurel et al.2019; Fig. 2). When the OBSs
are recovered from an oceanographic research vessel, such as RV
Marion Dufresne, large enough to board a team of around 10 ana-
lysts, we divided the work in three 4-hr-shifts (i.e. 2 or 3 analysts
by shift) we can manually pick earthquakes 24/7. Otherwise, the
MAYOBS/REVOSIMA seismology group meet—either virtually
or at one of the group institutes—for 2 d to process the recently re-
covered data, produce graphics demonstrating the evolution of the
crisis, and interpret the results together. Whether the phase pick-
ing, location, and interpretation are done onboard or on land, we
use the same setup/configuration, starting database, and software
to analyse the recently recovered data. We assigned uncertainty to
each phase, from a common predefined list of values. Time un-
certainties assigned to the S-phase were always equal to or larger
than the uncertainty assigned to the P-phase. Impulsive P-phase
polarity onset is also reported for first motion source mechanisms
studies later use. We were able to locate events as small as M0.8,
but despite improvement since July 2019 and the use of more sta-
tions in the STA/LTA automatic processing, their detection is far
from complete and mainly depends on the land station daily noise
level. We estimate that the magnitude of completeness is below M
3.0 (see Section 4) whatever the time allocated to the processing
during each pickathon and the number of events processed. We
typically process around 1000 earthquakes during pickathons when
performed onboard scientific cruises and around 500 earthquakes
during pickathons conducted on land. So far, our catalogue contains
more than 5000 manually picked earthquakes from February 2019
to May 2020, relocated using combined land and OBS data.
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Mayotte seismic crisis: first results from marine and land seismic deployments 1285
Figure 2. Typical pickathon organization. After each OBS recovery, the deployment time-span is divided in three groups, that is Group 1, Group 2 and
Group 3. Each group processes the same number of events, by decreasing magnitude order, using the same software setup and the same picking guidelines
and recommendations. The daily catalogue of events, automatically detected and manually confirmed on land-based network data (BRGM then R´
eNaSS and
OVPF-IPGP), is synchronized in the pickathon database. It also feeds in real-time the REVOSIMA/MAYOBS catalogue. When OBS recovery is performed by
a research vessel, each group alternates a 4-hr day and night shift. At the end of the pickathon, the relocated events, with additional manual picks and polarities
on OBSs data, is merged within the REVOSIMA/MAYOBS database for further use for monitoring and research. The same procedure is applied to on land
pickathons, only the work is completed during 2.5 normal work days instead of 24-hr shifts.
To enable this collaborative work, we use techniques and configu-
rations developed during the last 10 yr for the daily routine process-
ing of earthquakes in IPGP volcanic and seismologic observatories.
Waveform data and event databases are held by a SeisComP3 in-
stance (Weber et al.2007). Each earthquake analyst uses their own
laptop and, regardless of their laptop’s Operating System, they run
a VirtualBox pre-configured Linux machine with the SeisComP3
Origin Locator GUI client (scolv, Weber et al.2007). We use NLL
software and the new local 1-D velocity model described in the
following section to locate the events. Magnitudes are computed
with the embedded local magnitude (ML) formula in SeisComP3
(Richter 1958). The horizontal signals are converted to a Wood-
Anderson seismometer response (Urhammer & Collins 1990)be-
fore measuring their pick amplitude. We have not yet calibrated this
magnitude as very few of the earthquakes since 2019 have been
characterized with a moment tensor magnitude by the global mon-
itoring agencies (GCMT project, Dziewonski et al.1981;Ekstr
¨
om
et al.2012).
3. IMPROVED 1-D LOCAL VELOCITY
MODEL
A local velocity model is essential to provide precise location of
this dense swarm seismicity. One of the first challenges in improv-
ing earthquake locations was then to build a reasonable 1-D local
velocity model, because only global models were available so far.
This was done onboard RV Marion Dufresne during the MAYOBS1
campaign (Feuillet 2019).WeusedthedataofthefirstOBSsre-
covery and of three local land stations (see Section 2). We first
produced modified Wadati diagrams (Chatelain 1978) and consid-
ered two different existing velocity profiles from the area. The first
profile, named ‘Coffin449’, is based on a P-wave velocity (VP)
profile derived from a 1980 active-seismic sonobuoy. That experi-
ment was located 100 km southeast of Mayotte (Coffin et al.1986,
instrument 449; Fig. 1b) and extended beyond 10 km depth with
a Moho interface 15 km deep (Jacques et al.2019). The second
profile, named ‘ADofal’, is based on a S-wave velocity (VS)pro-
file determined from receiver functions (Dofal et al.2018) using the
MAYO temporary station deployed on Mayotte island between 2011
and 2014 (RHUM-RUM project, doi:10.15778/RESIF.YV2011;
Fig. 1b). After adding phases from OBSs to 100 events during
an onboard pickathon, we located them with Hypo71 (Lee & Lahr
1972) and the ‘Coffin449’ model with a VP/VSratio of 1.80 ex-
trapolated from Eastern and Central Afar studies (Jacques et al.
1999; Grandin et al. 2011). The modified Wadati diagrams (Chate-
lain 1978) indicated a local (OBS and Mayotte land stations)
VP/VSratio of 1.66 and a regional VP/VSratio of 1.72 (Figs 3a
and b).
We then tested different combinations of velocity model parame-
ters (2 velocity profiles and 3 VP/VSratios) on a more complete data
set of 800 events with OBS phases, using NLL software (Lomax et
al.2014). Contrary to Hypo71, NLL allows the use of depth vari-
ations of the VP/VSratios and different velocity models depending
on the station. Its probabilistic approach (Lomax et al.2014) also
makes the reported ellipsoidal errors more meaningful and easier
to interpret than estimated horizontal and vertical errors given by
Hypo71. We first used only local stations (Mayotte land stations
and OBSs) arrivals to assess the best local 1-D velocity model.
We compared the distributions of maximum ellipsoidal error for
the 2 velocity models and 3 VP/VSratios for the 800-earthquakes
MAYOBS1 data set. The ellipsoidal error major axis ranges be-
tween 2 and 10 km, with most of the events at 4 ±2 km. The
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1286 J.-M. Saurel et al.
012 3456
0
1
2
3
4
5
6
7
8
tsi−tsj (sec)
tsi−tsj (sec)
tpi−tpj (sec)
tpi−tpj (sec)
20 40 60 80 100 120 140 160 1800
Wadati modifed Local data:
Vp/Vs=1.66
Wadati modifed Regional data:
Vp/Vs=1.72
0
20
40
60
80
100
120
140
160
180
200
220
240
260
280
300
0
10
20
30
40
50
60
ADofal, Vp/Vs=1.66
Vp
Vs
Vp
Vs
123456789123456789
Velocity (km/s)Velocity (km/s)
0
10
20
30
40
50
60
Depth (km)
Depth (km)
Coffin449, Vp/Vs=1.72
(a)
(b)
(c)
(d)
Figure 3. Modified Wadati diagram of Pand Swaves arrival times for the first hundred OBSs+land relocated earthquakes. Differences in S-wave arrival times
(tsi, tsj) are plotted against differences in P-wave arrival times (tpi, tpj) for station pairs(i,j). (a) Plot for local stations only (Mayotte land stations and OBSs):
VP/VS=1.66. (b) Plot for local and regional stations: VP/VS=1.72. (c) ADofal gradient velocity model with VSfrom a Mayotte station receiver function and
1.66 VP/VSratio used for Mayotte land stations and OBSs. (d) Coffin449 velocity model with VPvelocity profile from sonobuoy experiment and 1.72 VP/VS
ratio, used for regional stations (Comoros archipelago and Grande Glorieuse).
best results (low average value and limited spreading of the ellip-
soidal errors) were obtained using the ‘ADofal’ velocity model with
VP/VS=1.66, for which 83.5 per cent of the events had maximum
ellipsoidal errors smaller than 5 km. The ‘Coffin449’ model was a
better match for the closest regional station arrivals (Comoros and
Grande Glorieuse), with VP/VS=1.72. The AK135 velocity model
(variable VP/VS, Kennet et al.1995) in combination with ‘ADo-
fal’ and ‘Coffin449’ gave lower residuals on global station arrivals
(Africa, Madagascar and Indian Ocean) than the IASPEI91 model.
Our final velocity model is a hybrid model (see Tables S1, S2 and
S3 for layered detailed values) composed of: the ‘ADofal’ model
with VP/VS=1.66 (Fig. 3c) for OBSs and stations on Mayotte; the
‘Coffin449’ oceanic model with VP/VS=1.72 (Fig. 3d) for regional
stations (between 200 and 400 km from Mayotte) and the AK135
global velocity model for more distant stations. NLL also computes
aVP/VSratio for each event, based on P-andS-arrival times and
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Mayotte seismic crisis: first results from marine and land seismic deployments 1287
independent from earthquake location, using a formula described
in the HypoEllipse manual (Lahr 2012). The NLL estimation, using
the 800 events, supports the mean VP/VSratios previously estimated
for local and regional stations on the first 100 events.
With this new hybrid 1-D velocity model, the earthquake lie be-
tween 25 and 55 km depth (Figs 4a–c). They are in the mantle, below
the Moho discontinuity, which has been estimated either at 17 km
depth under Mayotte island by Dofal et al.(2018)orat15kmdepth
offshore by Jacques et al.(2019). This is very unusual compared to
other volcanoes where deep seismicity is usually sparse and of low
energy (White & McCausland 2019). To confirm our earthquake
locations, we performed further robustness tests of our hybrid 1-D
velocity model to exclude any potential depth bias, for example a
soft-sediments layer impacting S-wave arrivals as has been influ-
ential along a segment of the SW Indian Ridge (Grevemeyer et al.
2019). The earthquake depth distribution remains stable whatever
the velocity models and VP/VSratios we tested (Figs 4a and b). Only
one model, the ‘Coffin449’ oceanic crust-like model, with an unre-
alistic VP/VSratio of 1.8 (with regards to the observed ratios from
arrivals time data), gives significantly shallower depths, between
10and40km(Fig.4b, red dashed line). In this case, the mean
time residual RMS increases from less than 0.2 s for all 5 other
velocity models to 0.3 s. We then compared the depth distribution
of a high-quality subset of the MAYOBS1 catalogue, that is 149
earthquakes with at least 5 P-wave and 5+-wave arrivals picked on
the OBSs data, using different altered configurations and velocity
models. Removing S-arrivals or adding a 0.2 kms–1 S-wave slow
velocity, 200-m-thick sediment layer—consistent with soft uncon-
solidated sediments—does not change significantly the depth range
of events (Fig. 4c). The mean time residual RMS however reaches
0.34 s with the sediment layer, compared to 0.24 s with our model.
We can conclude that the addition of a reasonably dimensioned
superficial unconsolidated sediment layer would thus only have a
small effect on the depth distribution, compared to the use of our
velocity model. Using Parrivals only confirms that there is no S
arrivals related bias in our velocity model. Finally, we used both P
and Sarrivals in uniform half-space velocity models with our 1.66
VP/VSratio (Fig. 4d). For a reasonable half-space P-wave velocity
between 5 and 9 km s–1, all events are located between 20 and 60 km
depth, with an average RMS lower than 1 s and best results obtained
with VP=6kms
–1. Except in the extreme cases, earthquakes were
always located deeper than 15 km (Jacques et al.2019).
4. EARTHQUAKES LOCATIONS
The REVOSIMA reported 30 000 events between 25 February 2019
and 10 May 2020, based on manual screening of the continuous
land data. Using NLL software and our new 1-D hybrid velocity
model within SeisComP3, we located more than 5000 of those
events, which have already been detected from the land stations
(Fig. 5;Saurelet al.2021). The mean absolute location accuracy is
around 2 km vertically (Fig. 5a) and 2.5 km horizontally (Fig. 5b).
The formal horizontal and vertical uncertainties are both lower
than 5 km with an azimuthal gap less than 175◦(Fig. 5c) for 95
per cent of all earthquakes. The location accuracy does not show
much variations with the different OBS network geometries and
the number of OBSs used for location (Fig. 5d). That is to say, the
OBSs network is always sufficient to reduce the azimuthal gap to
less than 175◦and to increase the number of phase arrivals used for
location to more than 15 phases. Because we processed the data in
descending magnitude order, we always achieved a magnitude of
completeness of 3.0 or lower (Fig. 5e). At present, we now have a
data set of nearly 125 000 manual Pand Sphases between February
2019 and May 2020 (Fig. 5f).
This relocated earthquake data set, while only comprising a part
of the recorded seismicity allows us to identify two distinct seismi-
cally active zones (Fig. 6a).
The Proximal cluster, with 90 per cent of the located earthquakes,
is situated close to the Mayotte island of Petite-Terre. In map view,
it has a circular shape (Fig. 6c) and spans depths ranging 20–50 km
(Fig. 6b). Most of the seismicity is concentrated on the eastern
side of the circle, where the highest magnitudes are located (all
M4–M5+events of the cluster). On the western side of the circle,
closer to Mayotte’s coasts, the events magnitudes are lower, and
the seismicity is more diffuse. At depth, 2 different patches can be
identified (Fig. 6d): one patch is dipping towards Petite-Terre, with
events located between 35 and 45 km depth and a second patch
is more vertical, with events located between 25 and 40 km depth.
The north–south thin (2 km wide) cross-section (Fig. 6e) also shows
2 subvertical lines of earthquakes, suggesting a cylindrical cluster
with a lower earthquake density in the centre (Fig. S3). Based on
the earthquake density, we can estimate an outer diameter of 11 km,
and an inner diameter of 3 km.
The distal cluster is located just a few kilometers to the east of
the Proximal cluster, and contains earthquakes with depths ranging
between 25 and 50 km (Fig. 6g). It is not seismically connected to
the Proximal cluster in our data set. Its seismicity is spread on a
N130◦E trend extending towards the new volcano edifice (NVE).
Earthquakes along its northwest part are concentrated between 35
and 50 km depth. This area concentrates most of the highest magni-
tudes events located in the distal cluster. The depths of the shallowest
earthquakes progressively decrease up to 25 km (Fig. 6g) as they
approach the NVE. Because our velocity model was built during
the MAYOBS1 cruise, during which we still had intense seismic-
ity with most of the highest magnitude earthquakes of our data set
that occurred in the Proximal cluster (Feuillet et al.2021), only a
few events were located in the Distal cluster. Our velocity model is
then mostly constrained by the Proximal events. This may explain
why the seismicity close to the NVE seems less clustered and more
loosely located.
We did not locate any earthquake with reliable depths shallower
than 20 km during the period of investigation (Fig. 6d). However, be-
cause we only relocated events that have already been automatically
detected and located using only the land stations network, we might
have missed some shallow, local and low magnitude earthquakes.
5. DISCUSSION AND CONCLUSIONS
Thanks to the collaborations among several research institutions,
we, the MAYOBS/REVOSIMA seismology team, has facilitated
the deployment of multiple seismometers, as well as the collection
and interpretation of their data since early 2019. The numerous
pickathons we have held since then have improved our understand-
ing of the seismicity occurring offshore Mayotte. The seismicity
manually-picked and relocated in this study, from February 2019
to May 2020 is in agreement with the analysis of 2018 activity
(Cesca et al.2020; Lemoine et al.2020a;Table1), as seismic-
ity clusters identified in this work seems to have been active since
summer 2018. The Distal cluster correlates with the first cluster of
activity that represents rock fracturing and dyke opening from the
centre of deflation towards the volcano, leading to the creation of
the NVE (Cesca et al.2020; Lemoine et al.2020a; Feuillet et al.
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1288 J.-M. Saurel et al.
01020
Percentage of events
-60
-50
-40
-30
-20
-10
0
Hypocentral depth (km)
(a)
ADofal velocity model
Vp/Vs=1.6
Vp/Vs=1.66
Vp/Vs=1.8
01020
Percentage of events
-60
-50
-40
-30
-20
-10
0
Hypocentral depth (km)
(b)
Coffin449 velocity model
Vp/Vs=1.6
Vp/Vs=1.66
Vp/Vs=1.8
0102030
Percentage of events
-60
-50
-40
-30
-20
-10
0
Hypocentral depth (km)
(c)
149 best constrained events
P and S arrivals
P arrivals only
Thick sediment layer
246810
Vp (km/s)
0
5
10
RMS (s)
(d) Half-space constant Vp velocity
246810
Vp (km/s)
-100
-50
0
Hypocentral depths (km)
246810
Vp (km/s)
0
5
10
Vertical error (km)
Depths robustness tests
Figure 4. Depth robustness test results. (a) Distribution of the hypocentral depths of the OBSs+land catalogue for ADofal S-velocity model and the different
tested VP/VSratios. (b) Distribution of the hypocentral depths of the OBSs+land catalogue for Coffin449 P-velocity model and the different tested VP/VS
ratios. (c) Depth distribution changes when adding an unconsolidated sediment layer below the OBSs (200-m-thick sediment layer with low S-wave velocity
of 0.2 km s–1 below each OBS—dashed red) and when using Parrivals only (dotted–dashed blue). (d) Mean and standard variation of the RMS, depth and
vertical error distributions for various P-wave velocity speeds and this study’s VP/VSratio of 1.66 using a homogeneous half-space velocity model. All tests
were performed using NLL software.
2021). However, a notable difference with our catalogue is the lack
of earthquakes in the first 20 km below the volcano. This could be
explained by a magma path towards the surface now opened and
generating only very small events not detected by the land network
while the path fracturing the crust in 2018 implied strong felt earth-
quakes (Duputel et al.2019). The Proximal cluster correlates with
seismic activity that initiated during July 2018 (Cesca et al.2020;
Lemoine et al.2020a) and became very active at the end of August
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Mayotte seismic crisis: first results from marine and land seismic deployments 1289
(a)
Vertical uncertainty
0
5
10
0 102030
0
5
10
km
(b)
Horizontal uncertainty
0
5
10
0 102030
0
5
10
km
(c)
Azimuthal gap
50
100
150
200
250
300
0 102030
100
200
300
degree
(d)
Number of phases used
10
20
30
40
0 102030
10
20
30
40
Nb phases
(e)
Magnitudes
1
2
3
4
5
0 102030
Percentage of events
1
2
3
4
5
M
L
2019/04/01 2019/07/01 2019/10/01 2020/01/01 2020/04/01
0
5
10
Nb phases
10
4(f)
Cumulated number of phases
6
1
8
2
8
3-4
4
6
16
7
16
8
3
9
7
13
Legend
threshold
Locations accuracies over time
Figure 5. Distributions (left-hand panels) and time evolution (right-hand panels) for the 5174 earthquakes manually picked and relocated with OBSs data
between 25 February 2019 and 10 May 2020, processed during the pickathons. The dashed line on each graph represents the minimum or maximum threshold
reach for all the data set as described in this study. (a) Vertical uncertainties, mostly below 3 km. (b) Horizontal uncertainties, mostly below 4 km. (c) Azimuthal
gaps, mostly below 175◦. (d) The number of P- and S-wave phases used for each event, mostly above 15. (e) The local magnitudes of all events, with maximum
magnitude of completeness at approximately 2.80. (f) The cumulative number of manual phases picked over time. Light and dark grey bands represent the
different OBSs deployments over time. Italic numbers are the deployment IDs and relates to Fig. 1(d) indication. Bold numbers are the number of OBS
instruments used for each deployment. Four denser deployments of 8 and 16 OBSs (including IFREMER micrOBS instruments) allows to significantly reduce
the azimuthal gap. There are small gaps in the catalogue, which are due to the few days necessary to maintain and redeploy the OBS.
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1290 J.-M. Saurel et al.
Figure 6. Earthquake location distributions. (a) Map of Mayotte earthquakes from 25 February 2019 to 10 May 2020 located using OBS data and (b) their
distribution along a N113◦E cross-section: the two active seismic clusters are seemingly disconnected. (c) Proximal cluster zoom showing its round shape and
(d) 2-km-wide east/west cross-section and (e) 2-km-wide north/south cross-section suggesting a tube-like shape with subvertical alignments. More seismicity
is visible in the eastern part of the cluster where there are all the M>4.0 earthquakes (orange). The more diffuse seismicity on the west side is limited between
35 and 40 km depth within a vertical alignment dipping towards Mayotte island. (f) Distal cluster zoom showing the alignment of seismicity along a N130◦E
direction towards the NVE and (g) the N130◦E cross-section showing seismicity depth variation. Thick dashed black boxes: locations of the Proximal and
Distal cluster zooms; thin blue boxes: earthquake selection for the three cross-sections; green lines: associated topographic profiles; red triangles: location of
the new volcanic edifice.
Tab l e 1 . Comparison of cluster names from this study (Cesca et al. 2020; Lemoine et al. 2020a), and REVOSIMA monthly bulletins.
This study Lemoine et al. (2020a) Cesca et al. (2020) REVOSIMA monthly bulletins, 2019–2020
Distal cluster Cluster 1 and Cluster 2 Dyke volcano-tectonic (VT, blue, cyan, purple) Secondary
Proximal cluster Cluster 3 Sagging volcano-tectonic (VT, red, green) Primary
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Mayotte seismic crisis: first results from marine and land seismic deployments 1291
2018. This correspond to the beginning of the island subsidence
and eastward displacement as recorded in GNSS data, inferred to
be due to the drainage of an at least 30 km deep magma chamber
(Briole 2018; Cesca et al.2020; Lemoine et al.2020a; Feuillet et
al.2021). This proximal cluster appears not connected to the Distal
cluster in our data set and this seems to have been the case since
the beginning of the crisis. The Proximal cluster cylindrical shape
match existing interpretations of a slowly sagging caldeira piston
(Cesca et al.2020; Feuillet et al.2021), but it could also be an an-
cient fault zone re-activated by the massive changes in lithosphere
constraints due to the eruption. Further detailed interpretation of
the Proximal cluster seismic activity requires results from ongoing
studies (lithosphere structure studies, high-resolution relocations,
source mechanisms).
The 2 local and regional velocity models used in this study with
their respective VP/VSratios are consistent with the two main ge-
ological setting interpretations of the area. The ‘Coffin449’ model
upper low velocity layer and rapid increase up to a Moho at 15 km
depth is compatible with an oceanic crust. Its averaged VP/VSratio
can explain an oceanic crust or mixed oceanic and continental crust
at regional scale. The ‘ADofal’ model smooth velocity changes and
the low local VP/VSratios can be associated with an heterogenous
volcanic island context: hot material and presence of gas or fluid-
filled fractured rock. This low VP/VSratio is also consistent with
the H–kstacking from receiver functions performed by Dofal et al.
(2021) and could support their interpretation of a continental crust
with underplating similar to the magmatic continental domain of the
southeastern coast of Madagascar (Rindraharisaona et al.2017).
In terms of monitoring, the regular recovery and deployment of
OBSs and the subsequent and immediate data analysis have been es-
sential to monitor the Mayotte sismo-volcanic crisis. The wide col-
laboration between many scientists, engineers, and students, from
different institutes and universities, during the pickathons continues
to bolster rapid earthquake processing and has also fostered discus-
sions on the evolution of the seismicity with the most up-to-date
data. The magnitudes distribution over time (Fig. 5e) show that the
seismic activity seems to have decreased in 2019, until October
2019 since when the magnitudes distribution is stable. This evolu-
tion can then be compared with the bathymetry surveys indicating
the eruption is still ongoing at lower emission rates (REVOSIMA
2019). Onboard the monitoring cruises, information from this rapid
processing is used to prioritize operations (bathymetry survey) and
focus on the areas of interest and/or crisis. With each pickathon,
we progressively increased our knowledge of the area, which in
turn also feeds the hazard and risk assessment studies that will
help the authorities with the decision-making process. For exam-
ple, the Proximal cluster, while it does not seem directly linked to
the magma emission at the new volcano is of particular concern
since it is much closer to the island and even slightly expands be-
low Mayotte. Tsunami modeling studies (Lemoine et al. 2020b;
Poulain et al. 2021), up to impact mapping, were conducted with
tsunamigenic sources derived from this improved knowledge of the
seismicity.
The resulting high-quality data set of manually picked arrivals is
now used in several detailed on-going studies (lithosphere structure
investigations, seismicity time and space evolution, seismic sources
studies, high-resolution locations) that will better constrain the seis-
micity, active structures and geological setting of the area. Various
non-earthquake signals, such as hydro-acoustic or seismic waves
not clearly associated to earthquakes, have been discovered during
routine data screening and are currently being investigated. While
REVOSIMA has reported more than 30 000 events for the period
covered by the catalogue after daily manual screening of the contin-
uous land stations data, our refined 5000 earthquake locations and
1-D velocity model ascertained by using OBSs data provides a solid
foundation for future studies. Our anticipation is that our improved
earthquake location catalogue, coupled with geodetic modelling,
petrological studies of rock samples and geochemical analysis of
fluids in the water column, will bring understanding of the Mayotte
sismo-volcanic crisis and regional tectonics. On-going work using
machine learning picking algorithms should provide a much more
complete catalogue of the seismicity.
DATA AND RESOURCES
RA network (R´
esif 1995) YTMZ and MILA stations data avail-
able from R´
esif data centre (http://seismology.resif.fr). ED net-
work MCHI station data is available upon request at EduSismo.
1T (Feuillet, Van der Woerd and RESIF, 2022) land stations are
from the R´
esif-Sismob pool of instruments and data available upon
request at R´
esif data centre (P´
equegnat et al.2021).
The INSU-IPGP pool of OBS is managed and operated by IPGP
and CNRS (https://parc-obs.insu.cnrs.f r/). MicrOBS and LotOBS
are operated by IFREMER/Ressources physiques et Ecosyst`
emes
de fond de Mer/d´
epartement de G´
eosciences Marines/service de
Cartographie et Traitement de Donn´
ees d’Instrumentation. Data
are available upon request at IPGP data centre (http://datacenter.ipg
p.fr).
AM network (Raspberry Shake Community et al.2016) R0CC5,
R1EE2 and RAE55 stations data are acquired by Raspberry Shake
SA company and made available from IRIS data centre and Rasp-
berry Shake SA data centre.
ObsPy (Beyreuther et al.2010) was used to convert NonLinLoc
results into QuakeML files. GMT (Wessel et al.2019)wasusedfor
fig. 1 and fig. 6. Matlab was used for fig. 4 and fig. 5.
NonLinLoc software was used for earthquake locations with OBS
data. Hypo71 software was used for preliminary earthquake loca-
tions of the first MAYOBS1 data set. VirtualBox software was used
on all analyst’s computer to run SeisComP3 graphical user interface
client.
Lcheapo software (https://github.com/WayneCrawford/lcheapo)
was used to pre-process OBS data (clock correction and conversion
to miniSEED).
Past felt earthquakes statistics on Mayotte from SisFrance
database: http://www.sisfrance.net.
Map bathymetry from Mayobs1 (doi:10.17600/18001217), part
of the Mayobs set of cruises (doi:10.18142/291). Data available
upon request at SISMER.
ACKNOWLEDGEMENTS
The Tellus SISMAYOTTE project (broad-band land stations and
first OBSs, MAYOBS1, doi:10.17600/18001217) was funded by
INSU,CNRS and the Ministry of Environment (minist`
eredelatran-
sition ´
ecologique et solidaire—MTES). Since June 2019, all activi-
ties on Mayotte are monitored by REVOSIMA (R´
eseau de surveil-
lance volcanologique et sismologique de Mayotte) and funded by
the Minist`
ere de la Transition Ecologique (MTE), the Minist`
ere
de l’Enseignement Sup´
erieur, de la Recherche et de l’Innovation
(MESRI), the Minist`
ere des Outre-Mer (MOM) and the Minist`
ere
de l’Int´
erieur (MI) with the support of the DIRMOM (Direction
Interminist´
erielle aux Risques Majeurs en Outremer).
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1292 J.-M. Saurel et al.
All marine operations are performed as part of the MAYOBS set
of cruises (Feuillet et al.2019).
The MCHI station (Sismo `
a l’Ecole, http://edumed.unice.fr/fr)
was installed by Didier Bertil and Alison Colombain, with funding
from BRGM, DEAL-Mayotte and Rectorat de Mayotte.
The RaspBerry Shake instruments were installed by Maxime B`
es
de Berc, Marc Grunberg, Christophe Sira and Antoine Schlupp.
The Mayotte stations were installed by Maxime B`
es de Berc,
J´
erˆ
ome van der Woerd, C´
eleste Broucke, Alison Colombain, H´
el`
ene
Jund and Gr´
egoire Dectot. The Grande Glorieuse station was in-
stalled by Aline Peltier and Philippe Kowalski. They are main-
tained by CNRS/EOST/IPGS, BRGM and OVPF-IPGP through the
REVOSIMA.
OBS are deployed, recovered, maintained and data pre-processed
by Romuald Daniel, Simon Besanc¸on, Wayne Crawford and J´
er´
emy
Gomez.
MicrOBS are deployed, recovered, maintained and data pre-
processed by Pascal Pelleau, Pierre Guyavarch and Micka¨
el
Roudault.
JMS wrote the first draft of the manuscript and led the editing
work. All co-authors discussed and corrected the manuscript. CA
and WC provided English language check and editing. EJ compiled
geological information and bibliography to establish candidate ve-
locity models, and made figures. CS gave NonLinLoc and Python
support and expertise. All co-authors participated either in station
maintenance and deployment, in routine manual earthquake analy-
sis from land network or in the different pickathons to manually pick
the earthquakes. NF, YF, SJ, ER and IT led the different Mayobs
cruises and helped for data interpretation.
This is IPGP contribution 4238.
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SUPPORTING INFORMATION
Supplementary data are available at GJI online.
Tab l e S 1 : ADofal gradient velocity layer model.
Tab l e S 2 : Coffin449 constant velocity layer model.
Tab l e S 3 : ak135 constant velocity layer model.
Figure S1a: MOCE (centre) station showing delay of approximately
0.5 s.
Figure S1b: MONE (northeast) station in the abyssal plain, showing
delay of approximately 1 s.
Figure S1c: MONN (north) station, showing delayof approximately
0.5 s.
Figure S1d: MONO (northwest) station, showing delay of approx-
imately 0.75 s.
Figure S1e: MOSE (southeast) station, showing delay of approxi-
mately 0.5 s.
Figure S1f: MOSO (southwest) station, showing a complex conver-
sion response with possible multiple conversions and a first delay
of 0.5s.
Figure S2: (a) and (b): Map and cross-section of this study catalogue
(OBS locations with hybrid ADofal velocity model). (c) and (d):
Map and cross-section of the same earthquakes from Lemoine et
al.(2020a) catalogue with land-based seismic stations.
Figure S3: map of the log10 density of earthquakes. Density calcu-
lated using QGis heatmap plugin, a 0.01◦radius and uniform kernel.
The Proximal cluster, which has a donut shape, appears to have a
high density of events in its northeast side.
Please note: Oxford University Press is not responsible for the con-
tent or functionality of any supporting materials supplied by the
authors. Any queries (other than missing material) should be di-
rected to the corresponding author for the paper.
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