dataesr/scientific-paragraphs-categorization huggingface dataset:
As the frictional strength may change from rate-strengthening to rate-weakening at slip rates higher than 0. 1 m/s due to the thermal weakening mechanisms that facilitate fast earthquakes  [35] [36] [37]  , the narrow range of rate-strengthening behaviour between 10 -2 m/s and 0. 1 m/s may explain the scarcity of tsunami earthquakes. Alternative explanations for tsunami earthquakes are low rigidity materials  75  and inelastic material within and/or around the fault  76  , and the density and size of asperities  77  , which remain to be confirmed by further investigations. While the rock frictional behaviour may be controlled by different mechanisms, the rupture propagation of both slow and fast events on long faults can be predicted by the same 3D theory of and online databases  15, 20, 21  and calculated their rupture speed and peak slip rate.
A stronger nucleation, such as the overstressed nucleation condition, results in slight oscillations of rupture speed in the fully dynamic rupture models, but does not affect the steady rupture speed (Figure  S5 ). I use the boundary element software QDYN  81  for the quasi-dynamic SSE simulation, where the fault is infinitely long and the fault slip is horizontally periodic with a prescribed length, 11W. To avoid the interaction of the periodic fault segments, a buffing segment of length 5. 5W is set, where the frictional behaviour is ratestrengthening with a > b. Sufficient numerical resolution is guaranteed by setting a small grid size (∆x), that is, L c /∆x = 8. The simulated time is set long enough to capture the whole rupture propagation. For each single-rupture model, the rupture time on each node of the faults is determined by a criterion of slip rate, 10V i , and the rupture speed is computed based on the along-strike gradient of the rupture time.
A4. Fully dynamic earthquake rupture simulations The 2. 5D single-rupture simulations for earthquakes are fully dynamic, conducted by a spectral element software SEM2DPACK  82. For a quantitative comparison between SSE and earthquake simulations, the same friction law and pa-rameters are assumed in the dynamic earthquake rupture simulations, except for larger values of V c , and the additional thermal weakening 56, 83 at slip rate > 0. 1 m/s is not considered. Previous theoretical studies 51 have suggested that the additional thermal weakening can affect the rupture speeds via controlling the dissipated  57  and potential  83  energies on faults, which remains to be quantitatively investigated in the future. For simulations with rupture speeds close to the S-wave speed, a sufficiently large computational domain is set to avoid the effects of the reflected waves from the domain boundaries within the simulated time.
fracture mechanics and the rupture speed is quantitatively controlled by G c /G 0. Integrating laboratory and theoretical developments of frictional mechanisms in quantifying G c /G 0 , this basic model would enable a quantitative description of both the short-term slow ruptures and the long-term supercycle behaviours associated with devastating earthquakes within the same theoretical framework. This fundamental model integrates slow and fast ruptures, reconciles the debated scaling relations, and thus opens new avenues for assessing the future seismic hazard through integration of observations and models of frequently occurring SSEs and devastating earthquakes. MethodsA1. Estimates of rupture speed and peak slip rate To explore a universal scaling relation in global SSEs, earthquakes, and lab experiments, I compiled different datasets from the literature 14, [16] [17] [18] [19] 22.
Acknowledgements This manuscript benefited from discussions with  Jean-Paul Ampuero, M. P. A. van den Ende ,  Quentin Bletery , and  Jean-Mathieu Nocquet. I thank  Jean-Paul Ampuero ,  Frédéric Cappa , and  Allan Rubin  for their constructive comments in reviewing the early version of this manuscript. I am grateful to  Jean-Paul Ampuero  for his suggestion of empirically estimating the average slip rate of the observed SSEs and to analyze the recurrence time of earthquakes and moment-duration scaling resulting from the model. This work was supported by the  French government  through the Investments in the  Future  project  UCAJEDI  ( ANR-15-IDEX-01 ) managed by the  French National Research Agency (ANR). Correspondence Correspondence should be addressed to  Huihui Weng  (email: weng@geoazur.
g. Beck et al. , 1996 Beck et al. , , 2001;; Beck, 2009; Arnaud et al. , 2016). Lake sediments can be regarded as continuous archives in which discrete event layers can be recorded, including MTDs related to the occurrence of seismic events. In the study area, multiproxy sediment analyses in sequences from Lake Bourget (France) allowed the identification of an event layer related to a well-known historical seismic event: the 1822 CE earthquake  (Chapron et al. , 1999; Beck, 2009). This event has been characterized by an epicentral intensity of VII-VIII (MSK-64 macroseismic scale) in the French database of historical seismicity SIS-FRANCE  (Jomard et al. , 2021) , equivalent to Mw = 5. 5 AE 0. 3  (Manchuel et al. , 2018). In addition, the combination of seismic profiles and sediment core analyses in this lake has allowed the identification of a much thicker and older (approximately 9900 cal BP,  Arnaud et al.
, 2018) , resulting in dominant strike-slip to oblique thrust faulting  (Mazzotti et al. , 2020; Larroque et al. , 2021)  over the area. In addition, geodetic data also reveal a current and general uplift, ranging between 0. 5 mm/yr near the studied lakes and increasing up to 2. 0-2. 5 mm/yr in the higher chain  (Sánchez et al. , 2018 , Sternai et al. , 2019). The instrumental seismicity in the area appears mostly diffuse, even though some significant instrumental events could be related to the activity of the mentioned faults, such as the 1996 Epagny earthquake triggered along the Vuache fault (Mw = 4. 9;  Manchuel et al. , 2018). In addition, several damaging events are reported in macroseismic catalogues, for instance, more than twenty earthquakes of epicentral intensity greater than VII (MSK-64 macroseismic intensity scale) in the SISFRANCE database of historical seismicity  (Jomard et al.
Bathymetry A bathymetric survey was conducted in October 2017 in Lake Aiguebelette using a Reson 8101 multibeam echo-sounder (Teledyne Reson, Slangerup, Denmark). Measurements were made in two phases, the first with a 1. 5 by 2°beam width and 210 kHz frequency and the second with a 1. 2 by 1°beam width and 400 kHz frequency. Between 0 m and 5 m depth, the maximum angular coverage (mac) was 120 to 130°; between 5 m and 20 m, mac was 110°, and below 20 m, mac was 90°. The absolute depth accuracy depends on the motion sensor's capability to compensate movements due to waves and positioning accuracy. The water depth accuracy is in the range of centimetres in shallow waters to a few decimetres at depths of >50 m. Data were acquired and processed by iXBlue company, with QINSy 8. 15. 0 software (QPS, The Netherlands).
Reflection seismic A total of 17. 5 km of seismic profiles were acquired in November 2020 in Lake Aiguebelette by the iXblue company. An Echoes 10 000 (5-15 kHz) chirp subbottom profiler (iXblue, Saint-Germain en Laye, France) designed for shallow water environments was used at 2 kVA power. A 10 ms pulse was emitted using frequency modulation of 5 to 15 kHz, thus delivering highresolution (<8 cm) seismic data (CHIRP signal was processed for 10 ms for the total length signal). Seismic profiles were recorded in SEG-Y format using a global positioning system (GPS used is Garmin GNSS differential without RTK correction allowing a precision lower than 10 m) and processed with Delph Seismic software. Data processing involved digital subtraction noise filtering, water bottom mute and bandpass filtering.
Grain-size analyses To determine grain-size distributions within the main event layers (ELs) and compare them to those of the continuously accumulated background sediments, the cores were sampled with a 2 cm sampling step (r). Depending on the encountered facies, the step-resolution, r, was decreased (i. e. sandy layer) or increased (i. e. transition between facies) with 1 cm < r < 5 cm. Analyses were conducted with a Beckman Coulter Life Science 13230 XR laser particle-size analyzer (Beckman Coulter, Brea, CA, USA) at the EDYTEM laboratory. To avoid flocculation, the sonication tool was enabled during measurements. Grain-size distribution datasets were processed with MATLAB R2019b software. The sediment grain size in THU10 was determined at a 2 cm step resolution using a Malvern Mastersizer 2000G laser particle sizer (Malvern Panalytical, Malvern, UK).
Acoustic velocity measurements To process seismic data with accurate sound velocity values, P-wave velocity was measured on an upper interval (0 to 151 cm MCD). This interval was selected because it is representative of the Holocene facies. The unavailability of unopened cores representative of the Late Glacial facies in this sequence did not allow us to perform P-wave measurements on older sediments. Measurements were performed with a Discrete P-Wave (MSCL-DPW) benchtop instrument at the Chronoenvironement laboratory (Besanc ßon University, France) designed to make precise measurements of P-wave velocity on rock or sediment samples.
5B ). Two east-west-oriented seismic profiles crossing the channel-shaped feature's southern distal lobe give an estimation of the lev ee bulge height (Fig. 5D ). The bulges are inherited from the channel-shaped feature underlying the drape visible on both seismic profiles. The bulge height is estimated from the seismic profiles and ranges between 36 m and 152 cm. Lake Aiguebelette deepest subbasin sediment data (AIG17III).
Among several possible explanations, a seismic origin is favoured, supported by sedimentological analysis, and in particular by a high foliation of the anisotropy of magnetic susceptibility in the event layer interpreted as the consequence of a seiche in the lake. At a regional scale a new MTD at the YD-EH transition in lake La Thuile, was also observed (depositional time range: 11 652-12 426 cal BP). In Lake Annecy and Lake Bourget, available published datasets show transparent seismic facies indicative of major and multiple MTDs underneath the Holocene sediment infill. Hence, the extent and occurrence of major MTDs in the study area at the YD-EH transition suggest a strong influence of this abrupt climate transition. From seismotectonic data available in the region, the authors propose that the evidenced event layers may be related to moderate nearby seismic events rather than from the occurrence of large regional events.
This hypothesis however implies that seismicity rates were higher than those observed in the history. In light of Ó 2022 The Authors. Sedimentology published by John Wiley & Sons Ltd on behalf of this, warming climate during the Late Glacial, subsequent deglaciation, mass transfer and stress rearrangement may have been possible triggers of transient and increased seismicity rates. bathymetric data would not have been possible without Conservatoire des Espaces Naturels de Savoie, CCLA and R eserve Naturelle R egionale du Lac d'Aiguebelette. 14 C analyses were acquired thanks to the CNRS-INSU ARTEMIS national radiocarbon AMS measurement programme at Laboratoire de Mesure 14C (LMC14) of the CEA Institute at Saclay (French Atomic Energy Commission). We are grateful to iXBlue for their help in acquiring seismic reflection data and providing access to DELPH interpretation software.
This article presents a curated database of the sea-level measurements acquired by the network of the five geodetic tide gauges managed over French Polynesia by the Geodesy Observatory of Tahiti from 13 June 2009 to 28 January 2021. A unique feature of this database, with respect to previous databases that host the same raw data, like the Intergovernmental Oceanographic Commission database (IOC, www. ioc-seale velmo nitor ing. org) and the database of 'Réseaux de référence des observations marégraphiques' (REFMAR, http://refmar. shom. fr) is that all the time-tags of the raw measurements (1-or 2-min sampling) have been validated and, if necessary, corrected with a precision of 2 min (time shifts of up to 1 hr can be present in the raw data). Possible outliers have also been flagged, but not removed.
In addition, smoothed hourly data are also provided, along with tidal analysis results and estimations of the sea-level trends for the five tide gauges, with respect to their local geodetic datum. The database, entitled 'SEA LEVEL collected from TIDE STATIONS in South Pacific Ocean from 2009-06-13 to 2021-01-28', can be accessed on the NOAA data servers as 'NCEI Accession 0244182' and contains two subsets: The first one is relative to the original sampling rate and the second one is relative to an hourly re-sampling with harmonic tide models for each tide gauge station.
MONITORING IN FRENCH POLYNESIA This study presents the results of the preprocessing, calibration, database encapsulation and preanalysis of the sea-level monitoring of the five stations installed and managed by the University of French Polynesia (UPF) in the French Polynesia part of the South Pacific area (Figures  1  and 2 ) and maintained by the hydrographic and oceanographic survey branch of the French Naval Hydrographic and Oceanographic Service (SHOM). Spread over an area between 134°W-155°W longitude and 7°S-28°S latitude, French Polynesia also known as Tahiti and her islands, covers a vast expense (5,500,000 km 2 ) and remote (7,000 km from Los Angeles, 4,000 km from Australia) of ocean located in the middle of the South Pacific. This French overseas territory, with a large political autonomy, is made up of a swarm of 121 islands or islets, including high volcanic islands (35) and low coral islands or atolls  (86) , which together represent a surface area of 3,668 km 2 of emerged land (half of Corsica) and 12,800 km 2 of lagoons.
| TIDE GAUGE RAW DATA AND TIME-TAGGING The sea-level data acquired by these five stations were (and still are) being transferred in real time by a UHF radio-link to the NOAA (National Oceanic and Atmospheric Administration of the USA) through the GOES satellite constellation (GOES -Geostationary Operational Environmental Satellite), but without neither GPS in situ time-tagging nor GPS positioning data, to save transmission bandwidth, and were ex situ timetagged again upon arrival at the NOAA datacentres. A long-term data archive is provided by the Sea Level Monitoring Facility database of IOC (Intergovernmental Oceanographic Commission, www. ioc-seale velmo nitor ing. org). This data transfer through the GOES satellite constellation was the only way to have real time transfer during most of this data acquisition period, as the only undersea optical cable was running between Hawaii and Tahiti and data transmission through commercial satellites was too expensive.
All the raw data, including in situ GPS timetagging and positioning, were also locally recorded on flash drives at the tide gauges and manually transferred to the UPF database when maintenance took place. Sometimes the local recording at the tide gauges was not operating, so the only source of data for this study was the IOC database, sometimes the GOES data link was not operating, so the only source of data was the local records on the tide gauges. We started our validation process by doing a crosscomparison of the IOC datasets versus the raw UPF datasets. We found that the time-tagging on the IOC database was often off by several minutes with respect to the GPS time-tagging done at the tide gauges, and sometimes shifts up to 1 hr were found (Table  2 ). We therefore elected to retain the UPF dataset whenever possible.
INTERMEDIATE DATABASE The raw data cannot be directly inputted in a tidal analysis software. A preprocessing step is necessary, to identify and remove gross errors (incorrect or missing data producing spikes and gaps or timing problems). This preprocessing was done as part as the Tsoft tidal visualization/ modelling environment, developed and maintained by the Royal Observatory of Belgium (see TSoft manual, Van Camp & Vauterin, 2005, see http://seism ologie. be/en/ downl oads/tsoft). This software and the tidal analysis software ET34-ANA-V80 V80  (Ducarme & Schueller, 2018; Schueller, 2015; Schueller, 2017)  are using specific data presentations called 'PRETERNA and ETERNA formats', described in  Wenzel, 1995 Wenzel, , 1996. The procedure is divided into three data levels, as shown in Figure  3.
LEVEL 1 data are obtained by rewriting the original records (UPF or IOC data) in the so-called PRETERNA format  (Wenzel, 1995). Between LEVEL 1 and LEVEL 2, the data sequence is checked, and preliminary tidal analyses are performed on the less perturbed parts of the data to prepare a preliminary tidal model and to detect timing errors. It is always possible to detect any timing error by considering the coherence of the phase of the main tidal waves with the phase computed from the UPF data, which were archived with the correct in situ timing. In the semidiurnal band, a timing error of 2 min produces a phase difference of one degree at the frequency of 2 cpd (cycles-per-day). If necessary, a time shift is applied. Corrections are applied by means of the software Tsoft and a 'remove-restore' procedure: The preliminary tidal model is subtracted from raw data; the corrections are applied on the residuals and the corrected tidal signal is reconstructed by summing up again the removed tidal signal.
The outliers, mainly unwanted 'spikes', are identified by eye and removed and small interruptions (gaps no larger than 24 h) are automatically tagged and interpolated with the same procedure. Between LEVEL 2 and LEVEL 3, the data are averaged down to a 1-hr sampling rate. This averaging process filters out short period noise but maintains all signals with period larger than the lowest Nyquist period considered in our tidal analysis (2-hr period). Besides, this unifies datasets acquired in the same station but with different sampling rates, for example, 1 and 2 min, as it occurred in Mangareva and Tubuai. These LEVEL3 data are convenient for most applications except detection of transient signals such as tsunamis or sea swells, which require a higher sampling rate. The averaging is performed by means of a standard least-squares low-pass filter provided by Tsoft.
This filter has a cutoff frequency at 12 cpd and a half-a-length of 1 day, that is, 1,440 or 720 samples for a 1 min or 2 min sampling rate. The LEVEL3 provides the final dataset from which the nontidal sea-level variations are derived from the tidal analysis performed by the software ET34-ANA-V80. The latest version of the software proposes a special option for ocean tides analysis and prediction in agreement with oceanographic conventions (i. e. phases refer to Greenwich and phase lags are counted positive, the changes of sign of the tidal potential with latitude are not taken into account). This program can be downloaded from http://ggp. bkg. bund. de/etern a/. These tidal residuals outputted by this tidal analysis software are a preliminary representation of the variations of the Mean Sea Level (RSL) due, up to the first order, to meteorological phenomena and, up to the second order, to climate related effects.
To perform the different processing steps shown on Figure  3 , an intermediate database (see Annex) was set up to collate the raw and validated data as well as the analysis results and the nontidal sea-level fluctuations. The conception of this intermediate database was derived from the following considerations: • As already stated, we have two data sources: the University of French Polynesia and 'IOC, Sea Level Monitoring Facility' (www. ioc-seale velmo nitor ing. org). As the initial presentation of the data is different, the two sources were treated separately until the final analysis. • There are two sea-level sensors (and therefore data formats): RADAR and PRESSURE. The database (annex) was organized in 3 levels corresponding to the 3 levels of data processing described above: • LEVEL 1: raw data converted in PRETERNA format (sampling rate 1 min or 2 min); • LEVEL 2: data corrected with Tsoft and converted to ETERNA format  (Wenzel, 1995).
0158 ± 0. 003 * Theo RADAR (correlation coefficient r = 0. 9980) In Vairao: Theo PRESSURE = 1. 0118 ± 0. 002 * Theo RADAR (correlation coefficient r = 0. 9987) In Makemo, a large phase difference of 4° (8 min of time difference) is observed. In Mangareva, also a difference of phase of 2. 5° exists between PRESSURE and RADAR records, corresponding to a time difference of 5 min. We checked also the stability of the tidal amplitudes and phases of the main semidiurnal waves M2 and S2 (Table  4 ). For that purpose, we cut each dataset in two consecutive blocks in time and compared the results. The differences in phase reach a level of 1° (2 min of time). We can thus expect a precision of 0. 5° in phase on the complete dataset. The amplitudes are perfectly stable for the stations of Makemo, Tubuai and Mangareva.
| NONTIDAL EFFECTS The PRESSURE measurements show the same longterm fluctuations as the RADAR measurements, but are affected by jumps and a steady, and sometimes large, drift. For the determination of the mean sea level (RSL), we therefore only considered the RADAR data. Both dataset present long-period fluctuations with seasonal characteristics (Figures  4  and 5 ). The relative sea level (RSL), measured with respect to the tide gauge setting and obtained from the RADAR measurements, are given in Table  5  and Figure  6. Their variations (ΔRSL) can be transformed into variations of the mean sea level (ΔMSL) if we can measure the vertical displacement of the crust on the site (Δh), as we have. ΔMSL = ΔRSL + Δh. Almost all Polynesian islands are subject to slow subsidence (typically at the level of millimetre or submillimetre/year), caused by the thermal contraction of their underlying tectonic plates as they move away from mid-ocean ridges, as well as evolution towards isostatic equilibrium with the underlying lithosphere/mantle.
Later on, the apparent RSL remains quite stable with RSL = 530. 9 ± 1. Note: Amplitude and phases are rounded up to the last significant digit corresponding to the associated RMS error. The datasets were divided into two blocks for comparison purposes. 5 ) is certainly linked to a maintenance intervention at the restart of the station. Here also a fast drift occurred at the beginning of 2014 and this increase is probably an artefact, as a global adjustment provided the value RSL = 706. 0 ± 2. 1 mm with m0 = 74 mm and a variation ΔRSL = + 54 ± 5 mm over the time interval 2010-2020. The large sea-level fluctuation observed in the beginning of 2014 for Rangiroa, Vairao and Tubuai is not affecting the RSL value on the complete dataset but is hampering the determination of RSL values on smaller blocks (Tables  4  and 5 ).
At Mangareva, the records at the UPF station are missing between 2017 and 2018. An unusual event happened at the beginning of 2018, but the RSL is the same for the two blocks (before and after the gap, see Tables  4  and 5 ) and we get for the complete interval 2012-2020 a value RSL = 645. 2 ± 2. 0 mm. We tested the possibility to determine a temporal variation of the RSL. We got a variation ΔRSL = +7. 4 ± 5. 2 mm. This result is not significant as the associated RMS error is very large. Fortunately, a sea-level monitoring station of the University of Hawaii (UH), labelled Rikitea in the IOC catalogue, is installed a few 100 m apart from the UPF station (see Figure  7 ). We downloaded the data relative to this station from the IOC database and a comparison is presented in the next section.