dataesr/scientific-paragraphs-categorization huggingface dataset:
This  Hammouya's et alii [1998]  H 2 O-CO 2 -S magmatic gas composition for Soufrière Hills (e. g. , with HCl not being considered) is close our above-derived composition for the Boiling Lake (Figure  6 ). Soufrière Hills and BL gases show, for instance, nearly identical CO 2 /S T ratios of 5. 1 and 5. 2, respectively. The ongoing (1992-present) degassing crisis of La Soufrière dome (references in  Bernard et al. [2006] ) makes of nearby Guadeloupe Island the second most significant volcanic gas spot in the region. Here again, however, the number of published gas reports is relatively small [e. g. ,  Brombach et al. 2000 , Bernard et al. 2006 , Ruzié et al. 2012]. When this previous dataset is combined with results of our recent Multi-GAS observations in March 2012  [Allard et al. 2013]  the Soufrière of Guadeloupe volcanic gases display an almost linear compositional array, from the S-poor (CO 2 /S T of 11-474) compositions reported for the early 1997 activity by  Brombach et al.
Acknowledgements. The staff of the  Crescent Moon Cabins (Dominica) , and especially the local guide David, are particularly acknowledged for their logistic support to field work. We wish to thank  Dr. D. Rouwet  and anonymous Reviewer for constructive comments. This research was funded by  Miur-UniPa  (A. A. , R. D. N) and research contract  ANR DOMOSCAN 08-RISKNAT-002-01  (P. A. and A. A. ). The research leading to these results has also received funding from the european research council under the European Union's  Seventh Framework Programme  ( FP7/2007/2013)/ERC grant agreement n1305377.
Data collection Two hydrographic surveys were conducted in August 2009 and 2010 comprising of 5 and 7 conductivity, temperature, turbidity and depth (hereafter called CTD) casts at Rink Fjord and 12 and 11 casts at Store Fjord respectively. The CTD casts were taken along and across each fjord, at a distance of between 200 m and 20 km from their respective calving fronts (Figs. 1  and 2 ) and to a maximum depth of 750 m. The hydrographic instrument used was a MIDAS Valeport 2000 conductivity-temperature-depth profiler, equipped with a Seapoint turbidity sensor (Table  1 ). Measurements were logged at a sampling rate of 4 Hz with a descent rate of 1-2 m s -1 , yielding 10 to 20 samples for every 5 m of vertical profile. The instrument also logged on recovery, which at a slower ascent rate of 0.
Acknowledgements. We wish to acknowledge fieldwork support from  NERC  Grant  NE/G010595/1 , the  Aberystwyth University Research Fund  and the  Royal Geographical Society. N. Chauché  is supported by an  Aberystwyth University   Research Studentship  and wishes to acknowledge the support of  LOCEAN (University of Pierre and Marie Curie, UPMC). J. E. Box  was supported by The  Ohio State University 's Climate Water and Carbon initiative managed by  D. Alsdorf  and the  Geological Survey of Denmark and Greenland. J. -C. Gascard  acknowledges the support of  Arctic Climate Change, Economy and Society (ACCESS). We are indebted to the tireless crew of  S/V Gambo  and all those who have supported this project, particularly the  Uummannaq Polar Institute and Children's Home. Edited by:  E. Larour.
The fi rst Oxfordian limestone, O1 (depth = 159 m), is an oomicrite (grain size = 0. 1-0. 5 mm) with a porosity of ~15. 4 vol%. We also note the occasional microfossil (foraminifera) and shell fragment. The second, O3 (depth = 174 m), is an oomicrite (grain size = 0. 2-1. 0 mm) with a porosity of ~15. 0 vol%. Finally, O6 (depth = 364 m) is a biomicrite with a porosity of ~6. 7 vol%. O6 is very heterogeneous and contains large intraclasts (>1 mm in diameter) containing cemented shell debris and cement overgrowth, and large (>1 mm in length) shell fragments. The Dogger limestone (depth = 747 m) is a micrite with a porosity of 3. 4 vol%. The Dogger limestone contains both thin (20-500 μm) and thick (1500-3000 μm) stylolites. More information on the materials of this study can be found in the GSA Data Repository 1.
Furthermore, enhancements in VLF activities recorded onboard Demeter have been claimed to be earthquake-related. We clearly show that these waves are linked to lightning activity. Moreover, it must be stressed that a large statistical study by  Piša et al. (2013)  with VLF Demeter data shows a decrease in the electric field at a frequency close to 1. 7 kHz a few hours before the earthquakes. This frequency is the usual cut-off frequency of the waves propagating in the Earth-ionosphere waveguide during nighttime, and this electric field is mainly due to the numerous whistler waves triggered by the thunderstorm activity. If the intensity of the electric field decreases, it means that the cut-off frequency is Published by Copernicus Publications on behalf of the European Geosciences Union. increasing, and then that the height of the ionosphere is statistically lower above epicenters.
We have been able to check, using the WWLLN database, that Demeter passes over a large region where numerous lightnings occur in the Asian sector. It is thus natural to attribute the VLF signal detected by Demeter to the effect of lightnings instead of invoking a hypothetical precursor to an earthquake (see also  Inan et al. , 2007; Parrot et al. , 2013). Furthermore, the electron bursts, when displayed in a energy-time spectrogram, show the typical dispersion structure resulting from their interaction with monochromatic waves. Recently,  Selesnick et al. (2013)  performed a full simulation of the effect of the NWC waves on the radiation belt electrons based on a stochastic model of electron transport that includes pitch angle diffusion, radial diffusion, energy loss, and azimuthal drift. They showed that the Demeter electron-dispersed structures are in agreement with their calculations.
, 2006; Perler et al. , 2011) , as well as by UCAR (USA)  (Braun et al. , 2001). A first experiment of GPS tomography was conducted in France in 2001 in the framework of the ESCOMPTE campaign  (Bock et al. , 2004; Walpersdorf et al. , 2004)  which took place in the Marseille region. For that study, the tomographic routine (LOFFTK) was employed for the GPS inversion  (Champollion et al. , 2005; Bastin et al. , 2005). Based on this experience, a new software, called TSAAR (Tomography Software for wAter vApour Retrieval) has been developed by the authors. A full series of tests and validations are presented in  Reverdy (2008)  whereas its application to the COPS campaign is described in  Van Baelen et al. (2011). TSAAR will be used for the GPS tomography in this study. The OHM-CV GPS measurement campaign aims at covering efficiently the region between the Mediterranean and the OHM-CV water sheds.
GPS data analysis and sensitivity tests The GPS data analysis has been performed with MIT's GAMIT/GLOBK package  (GAMIT version 10. 3, Herring et al. , 2006). The temporary network (21 stations) has been completed with 11 permanent stations from the French RENAG network (REseau NAtional GPS permanent, http://webrenag. unice. fr), 11 of the EUREF and the IGS network, and with 1 station from ROA, Spain. The furthest reference stations are situated at 2000 km distance from the local network, which will enable us to de-correlate vertical positioning from tropospheric parameter estimation  (Tregoning et al. , 1998). IGS final orbits have been held fixed in the analysis, and corresponding earth orientation parameters have been employed. The mapping function used for the tropospheric parameter estimation is  Niell's (NMF, 1996).
For example,  Haase et al. (2003)  used three sub-networks for tropospheric parameter estimations in a regional network of 51 stations, and indicated that 7 mm was a good estimate for the random error of GPS ZTD. For our network of 44 stations, we calculated one reference solution including all stations, covering the test interval from 20-22 October 2002. Then we tested different sub-networks sizes and geometries and could infer a value for the uncertainties of tropospheric parameters with respect to the various sub-network choices. A graphical representation of the variability of ZTD and GRAD between different tests and the reference solution is given in Fig. 3  (note that GAMIT software provides horizontal gradient components normalised to an elevation of 10 • ). The details about the 36 different network choices and the numerical results can be found in Appendix.
12b ) or an interpolation scheme that takes also into account the horizontal gradients (Hermite interpolation, Fig. 12c ). A presentation of this method of interpolation can be found in  Sandwell (1987). Our study uses the v4 biharmonic matlab routine. Automatically, this routine considers also ZTD and gradients uncertainties and minimises their effects to obtain the final global Hermitian interpolant. Note that to be taken into account in interpolation, gradient components (provided at 10 • of elevation) have been mapped in the zenith direction using the Niell's mapping function  (NMF, 1996). The ZTD maps of Fig. 12b  and c  demonstrate the benefit of including the horizontal gradients in the interpolation scheme in order to resolve more detailed features (see  Brenot et al. , 2013). This is true although the current GPS network has small inter-station distances (less than 10 km) and, hence, the spatial variation of ZTD should coincide with the horizontal gradients evaluated at single stations  (Walpersdorf et al.
GPS water vapour tomography and comparison to rain fields The data observations used for the tomographic inversion are the slant wet delays. They will be later converted into slant precipitable water vapour following a similar conversion strategy as the conversion ZWD to PWV mentioned in Sect. 3. For convenience, we will express hereafter slant precipitable water vapour in terms of SIWV (Slant Integrated Water Vapour), equivalent but more widely used in the literature. For each GPS station, the corresponding ZWDs and wet components of the gradients are projected into the direction of the different satellites in sight using the appropriate mapping function to produce the SWDs  (Niell, 1996; Chen and Herring, 1997). One way post-fit phase residuals have not been considered in this work. The original measurements of ZTD and horizontal gradients are extracted at an interval of 15 min from their time series.
6  and 7  (3 mm for ZTD, 9 mm for EW GRAD and 10 mm for NS GRAD) but larger std (4 mm for ZTD, 14 mm for EW GRAD and 16 mm for NS GRAD). Finally, we have shown that one way post-fit phase residuals could consist to a large part of a tropospheric signal of higher order than ZTD and gradients. Including these high resolution observations (available for every station-satellite pair every 30 s) could therefore increase the information of the anisotropic troposphere. However, persistent patterns due to local signal multi-path should be carefully filtered out first. In any case, the contribution of an observed maximum residual of 20 mm at zenith is small compared to ZTD and GRAD (5 % of ZTD while gradients contribute with 12 % to ZTD). In conclusion, we found that a good compromise for an efficient operational analysis is to use sub-networks of 24 stations including 10 widely spread reference stations and with a cluster of 8 local stations and 4 permanent stations in intermediate, regional distances, to minimise calculation time (20 min for a GAMIT solution on a Linux PC).
If we consider maximum errors of 15-20 % SWD as quantified by our methodological work (adding biases and standard deviations for ZTD and GRAD), we can evaluate uncertainties in the order of 1. 5-2. 0 g m -3 for average densities of 10 g m -3 in the 500 m altitude cross section. However, constraining the tomographic inversion to fit the more precise PWV measurements at the station locations should decrease this error, joining the results of sensitivity tests made with the TSAAR software  (Reverdy, 2008). These tests indicated about 1 g m -3 as typical uncertainty for water vapour density measured above the OHM-CV network, taking into account the real OHM-CV network geometry and altitude distribution. The spatial resolution of the tomographic inversion corresponds to the mean station spacing in the horizontal direction (5 km) and 500 m in the vertical direction for atmospheric layers close to the ground.
Acknowledgements. We would like to thank all collaborators contributing to the project with their expertise ( J. -P. Glot ,  S. Anquetin ,  O. Bock ,  P. Tabary ), and the public and private persons permitting the installation of a GPS station on their ground over the two months time span. The PhD thesis grant of  H. Brenot  and the measurement campaign were sponsored by the  French research programme ACI CatNat , the PATOM and PNRH research programs of the  CNRS-INSU  (the  National French Institute of Universe Sciences). The PhD thesis of M. Reverdy was a  French ministerial grant. Edited by:  V. Amiridis The publication of this article is financed by  CNRS-INSU.
The PIR is a WMO first class pyrgeometer that measures the downward longwave irradiance in the spectral range 3. 5-50 µm, I LW. The downward irradiance is derived from the measured signal and instrument temperatures using the  Albrecht and Cox [1977]  formula. The PIR calibration was verified by comparison with a recently calibrated PIR installed at the ENEA station at Lampedusa (http://www. lampedusa. enea. it/) in 2008. Additional calibrations were made at Thule by comparison with two CGR4 pyrgeometers during 2010 and 2011. The calibration error is estimated to be less than 1%. The total uncertainty associated with the PIR measurements is less than 1. 7%. The radiometers installed at #1985 have the horizon free from obstacles; the domes of the instruments are cleaned weekly and the data are acquired every minute.
Acknowledgements. This material is based on work also supported by the  National Science Foundation  under grant  0936365  and by the  Programma Nazionale di Ricerca in Antartide (PNRA)  under grant  2009/A3. 04. We would like to thank  David Seibert  of the  Thule Air Base Weather Forecast Office  for providing the 1951-2006 meteorological data, the  ECMWF  for its temperature and pressure reanalyses, and the MLS team at  JPL  for the Aura MLS temperature data. MODIS data are distributed by the  Land Processes Distributed Active Archive Center (LP DAAC) , located at the  US Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center  (lpdaac. usgs. gov). Very sadly,  Prof. Giorgio Fiocco  passed away in July 2012. The Italian atmospheric remote sensing activities at Thule, which started back in 1990, the international collaborations and all the science that originated from these 20+ years at Thule have his signature, his crucial and enlightening contribution.
Acknowledgments. Support from the  NOAA Climate Program Office  (Grant  NA10OAR4310202  and  NA13OAR4310139 ) and  NSF   EaSM2  ( OCE1242989 ) is gratefully acknowledged. We thank  Gokhan Danabasoglu ,  Guillaume Gastineau ,  Mike Spall ,  Jiayan Yang , and  Steve Yeager  for helpful discussions, and the three anonymous reviewers and the editor  Peter Gent  for their thoughtful comments.
We present new knowledge concerning the nature and thickness of the crust and the continent-ocean transition zone off Jijel. Then the relation between superficial sedimentary formations and deep crustal structures will be examined. In particular, the presence of salt, its distribution and interplay with sedimentary processes and regional tectonics will be addressed. High resolution seismic data have been acquired along Algerian margin during the Maradja 2003  (Domzig et al. 2006)  and Maradja-Samra 2005  (Kherroubi et al. 2009)  cruises. It was a high resolution acquisition but without a deep investigation (about 3-4 km). Deep structure in this area had not been studied with large-offset seismic data. During the SPIRAL Project, a total of five transects combining MCS and wide-angle seismic were acquired: to the west in the area of Mostaganem city  (Badji et al.
External zones are represented in the study area by the Tellian nappes  (Vila 1980). The offshore geological formations are deduced from seismic data and we distinguish from top to bottom: (1) Thick Pliocene-Quaternary deposits at the foot of the margin to be thinning towards the north. DSDP site 371 (Deep Sea Drilling Project) borehole has been drilled in this area and proved a complete Pliocene-Quaternary sequence. The drill through 551 m of sediments in a water depth of 2792 m reached Messinian evaporites  (Hsü et al. 1973; Mauffret et al. 2004). (2) Messinian Upper Unit placed between the Messinian Mobile Unit and the Pliocene-Quaternary. (3) Thick pre-Messinian sequences in the abyssal plain and its thick Miocene cover, supported by an undifferentiated basement, are dipping towards the south  (Mauffret et al.
DATA ACQUISITION The deep seismic data used in this study were acquired during the SPIRAL cruise conducted on board R/V L'Atalante (IFREMER) in    (Bouillin 1977; Vila 1980; Wildi 1983 ): Lesser and Great Kabylia, LK and GK, (internal zones) and Tellian nappes, TN, (external zones). The limit between the internal and the external zones is marked by a black line. For the offshore part, the bathymetry is extracted from the Maradja surveys and ETOPO1 1-minute global relief (www. ngdc. noaa. gov). The multichannel seismic profiles Spi14 and Spi22 of this wide-angle survey are marked by black lines. Locations of ocean bottom seismometers (OBS) are indicated by red circles, and land stations by yellow circles (good signal-to-noise ratio) and blue circles (noisy data). The multichannel seismic profiles L1, L2 and L3 from Algeria offshore 2-D seismic survey are localized with black dashed lines.
These MCS profiles were acquired using a 3000 cubic inch air-gun array at 1950 psi pressure, towed at 6 m depth with a 25 m shot-point interval, and 6000 km long streamer of 480 channels towed at 8 m depth. Simultaneously, during the SPIRAL cruise, additional data were acquired along all MCS profiles, including: magnetic, gravity and bathymetry data. Gravity data was acquired by a LOCKHEED MARTIN BGM-5 IFREMER. Measurements are provided every 10 s with an accuracy of 1mGal (10 -5 m s -2 ). Using a SeaSPY magnetometer, magnetic data were recorded. The measurement accuracy is about 0. 2 nT. Also further gravimetric data from Sonatrach have been used in this study.
MCS data The main goal of the data processing workflow was to prepare prestack depth migrated (PSDM) gathers suitable for velocity refinement and horizon adjustment in depth. First, conventional processing in the time domain was performed using the Geocluster (CGG) processing software at 4 ms time sampling interval for 6. 25 m Common Depth-Point (CDP) spacing. An accurate time and space inverse Q filtering was applied in the pre-stack domain. Because of the single bubble source, the signature was converted to minimum phase prior to deconvolution. Then a pre-stack surface-consistent deconvolution was applied to improve the temporal resolution followed by a zero phase conversion. Conventional normal moveout (NMO) velocity analysis was then performed on every 500th CDP gather. For each velocity location, multivelocity function stack, semblances and gathers were displayed interactively, allowing stack velocities to be determined.
OBS and land-station data The processing sequence of the wide-angle data once downloaded from the instruments included: OBS's internal clock-drift correction; OBS's relocation on the seafloor from traveltime picks of water-wave direct arrivals; instrument positioning on a great-circle arc and definition of 2-D geometry; filtering to attenuate lowfrequency noise; signal deconvolution, to sharpen the wavelet and enhance the frequency content. In order to preserve the gain contrast between the first and secondary arrivals, no automatic gain control (AGC) was applied, but a scale proportional to offset was used. In addition, an FX deconvolution (in a moving 1. 9 s × 21 traces window) was applied to the onshore station data in order to attenuate the higher noise levels when compared to OBS. The land stations can be divided into two groups concerning the data quality: the first eleven stations from the coast to approximately 50-60 km southward (Fig.
Magnetic and gravity The magnetic and gravity measurements were processed with the Caraïbes software (IFREMER). The magnetic anomaly was computed against the IGRF 2005 model. The processing sequence applied for gravity data contain: Unit conversion, data merge with navigation, offset correction, Eötvös correction, instrument lag correction, latitude correction and base tie calculation, Bouguer correction, Bouguer gravity, data quality assessment and along-line gravity filtering and final editing.
A minimum structure approach has been used during modelling of the crustal and upper mantle, where only depth and velocity nodes necessary to fit the data in the limits of the picking order. In the sedimentary layers the structures from reflection seismic modelling were included; however care was taken to not unnecessarily introduce lateral velocity gradients. Forward modelling of wide-angle traveltimes was performed using the RAYINVR software  (Zelt & Smith 1992) , for 2-D ray tracing and traveltime inversion. The PSDM processing was undertaken using the Seismic Unix geophysical package (SU  ; Stockwell 1999a,b). The process is used to compute traveltime tables regularly spaced at 200 m along the profile by paraxial ray tracing on a 50 × 24 m spaced coarse grid, then traveltimes in shadow zones are compensated by solving the eikonal equation.
Finally, the 2 migrated OBS profiles of up and downward travelling waves are stacked to produce the final section. An initial up-downward travelling wave separation (e. g. Schneider & Backus 1964)  performed by combining hydrophone and vertical OBS components is not presented herein as it did not improve significantly the seismic image. On the three additional MCS profiles, the same key interfaces have been digitized and an estimate of each concurrent velocity model was built from our wide-angle model by copying its velocity nodes onto the new interfaces. This model was then used to transform the processed sections from time to depth. In order to verify the consistency of the velocity model with gravity data, the free-air anomaly was modelled using the GRAV-MOD software  (Zelt & Smith 1992).
DATA ANALYSIS Representative data records are displayed in Fig. 3 , for OBS3, OBS13 and OBS34 and for land station LS05. Right below OBS34 and OBS13 (Figs  3a  and b ), the uppermost sedimentary sequence is nearly transparent, and dominated by the water-wave source oscillations. At the base of this sequence, high amplitude reflections (PsP1) and a sharp refracted event (Ps1, with an apparent velocity above 3 km s -1 ) are observed. Ps1 does generally not extend beyond 10 km offset. The base of this high amplitude sequence is marked by a sharp reflection, named PsP2. On both sides of OBS34, a gap characterised by the absence of refracted arrivals is observed between the Ps1 and Pg1 branches (Fig. 3a ). This gap is also present on all data records, from OBS42 to OBS14, indicating a velocity inversion in the underlying layers.
5 to 5 km s -1 and from 5. 5 to 6. 5 km s -1 , respectively (Fig. 3 ). These arrivals are of high amplitude and clearly visible on all 42 OBS sections. Often, a reflection PgP1 associated to the Pg1 refraction can be identified. Only few PmP reflected waves from the Moho could be identified, for instance on OBS3 or LS05 (Fig. 3d ). Sedimentary reflected arrivals are better observed on the hydrophone channel while refracted waves are more distinct on the vertical component. The refracted wave Pn from the mantle is observed with high confidence, at offsets of up to 80 km on OBSs and larger than 100 km on land station data records.