dataesr/scientific-paragraphs-categorization huggingface dataset:
(2016)  for the DUACS DT2014. Taburet et al. (submitted)  give the full description and validation of the DUACS-DT2018 global and regional products. The main differences between the DUACS-DT2014 and the DUACS-DT2018 processing consist of an improved along-track processing (e. g. , improved orbit correction, wet troposphere correction, ocean tide correction and a new mean sea surface) and updated a priori knowledge of the SLA variance and optimized selection of the data in the optimal interpolation. The maps tested here are computed specifically for this study in several constellation scenario, keeping at least 1 mission out to allow an independent assessment of the resolution. The DUACS-DT products, formerly known as AVISO products, are referenced in the CMEMS catalogue as "OCEAN GRIDDED L3/4 SEA SURFACE HEIGHTS AND DERIVED VARIABLES REPROCESSED" products.
Method Our method to estimate the effective resolution is based on the "Magnitude Square Coherence" (MSC) between mapped SLA signal and the signal originating from the independent datasets previously mentioned. The MSC represents the squared correlation between two signals in the spectral domain. We somewhat subjectively define the effective resolution to be the wavelength above which the MSC exceeds 0. 5. The principle of the method follows three main steps as illustrated in Figure  1 : 1) data selection over common period and area, 2) colocation of SLA signal between independent dataset and maps of SLA and 3) cross-spectral analysis between the two SLA signals. A full description of the method is given in Appendix A. To justify the choice of the 0. 5 criterion for the estimation of the resolution, we follow an explanation given by  Bendat and Piersol (1986) , and specifically, their case study #2 (No output noise; uncorrelated input noise) in their section 6.
Effective resolutions of the DUACS-DT2018 maps The effective spatial resolution of the DUACS-DT2018 global maps is shown in Figure  2a. Resolution was computed for maps constructed with three altimeters (Cryosat-2, HY-2, Jason-2) over the period 20140412-20151231 and Saral/Altika data were used as an independent dataset. We believe that this assessment of the spatial resolution based on maps constructed with three altimeter missions may be considered as a reasonable averaged estimation since ~3 altimeter missions are used in the merging for the CMEMS products 70% of the time over the period 19930101-20170515. The resolution ranges from ~100 km wavelength at high latitudes to ~800km wavelength near the Equator, with a mean resolution at mid-latitude near 200km. Considering that eddy radius characteristic can be estimated as 20-25% of the wavelength  (Chelton et al.
Evolution of the DUACS system We here investigate the impact of the DUACS system upgrade from 2010 to 2018 to highlight the progress of the DUACS processing. Resolutions were computed for maps constructed with two altimeters (Topex-Poseidon and Jason1) over the period 20030101-20041231 and Geosat Follow On data were used as independent dataset. To identify the impact of the DUACS system upgrade, we computed the relative improvement/deterioration of the effective resolutions (expressed in percentage) for the upgrade DT2010 to DT2014, and DT2014 to DT2018 (Figure  4 ). Negative (positive) value means finer (coarser) resolution with the upgrade. The comparison of the DT2010 and DT2014 processing shows finer resolution (improvement > 2%) in the DT2014 than in DT2010 in the high variability region, e.
These improvements are linked to the new mapping standard (optimized selection of the observations in the turbulent region and a priori knowledge of the SLA variance based on a longer period in DT2018). The loss of resolution in the South Equatorial Atlantic is not understood yet. Similar comparison is performed for the Mediterranean and Black Sea regional products focusing on the upgrade DT2014 to DT2018. Resolutions were computed for regional DUACS maps constructed with three altimeters (Jason-2, Cryosat-2, HY-2) over the period 20140412-20151231 and Saral/Altika was used as an independent dataset. The resolution capability of the Mediterranean Sea maps is slightly finer (~4%) in DT2018 than in DT2014 (Figure  4c ). The largest improvements (>6%) are found the western Mediterranean basin.
Impact of altimeter constellation on the effective spatial resolution Since the number of altimeter data processed by the DUACS system varies with time (according to the availability of satellites and the data quality), we investigated the impact of the constellation on the effective spatial resolution. Figure  6  illustrates the impact of the number of altimeters (2 or 3 missions) used in the mapping on the effective spatial resolution. We verify, with our diagnostic, modest increases of resolving capabilities in the DUACS maps with increasing number of altimeters and found a globally averaged gain of resolution of ~5% from maps constructed with two altimeters to three altimeters. Regional gains of resolution can be larger than 10%. Additionally, it is possible to identify the improved resolving capability when a mission is introduced in the DUACS system: for example, Figure  6a  illustrates the improved resolving capability when mission HY-2 is introduced in the mapping, Figure  6b  illustrates the improved resolving capability when mission Cryosat-2 is introduced in the mapping.
Discussion and conclusions The present study investigates the resolving capability of the DUACS delayed-time gridded products (Global, Mediterranean Sea and Black Sea) delivered through the CMEMS catalogue. The key results are summarized in Table  1. Our method is based on the spectral coherence and is similar to the approach proposed by  Yale et al. (1995)  or Smith (2015) to estimate along-track resolution. While along-track altimeter data resolve scales in the order of few tens of kilometers  (Dussurget et al. , 2011 , Dufau et al. 2016) , we found that the merging of these along-track data into continuous maps in time and space leads to properly resolved structures with a feature radius resolution of 25km (effective resolution of 100km wavelength) at high latitudes to 200km (effective resolution of 800km wavelength) near the Equator in the global gridded product and with a temporal scale of about 28-day period.
The improvement patterns between DT2014 and DT2010 global maps is similar to those found by  Pujol et al. (2016)   Several studies showed that at least two altimeters are required to accurately map the SSH mesoscale structures (Le  Traon and Dibarboure 1999; Ducet et al. 2000; Pujol and Larnicol 2005; Dibarboure et al. 2011; Chelton et al. 2007; 2011)  and up to four altimeters are required for Near-Real-Time products  (Pascual et al. 2006). The present study reinforces these findings, showing that the resolution capability increased ~10-20% at regional scale from two to three altimeters merging. It is worth noting, that we probably underestimate the resolution capability of the maps since we are estimating the spatial effective resolution of degraded maps to keep an independent dataset aside.
Ocean Sci. Discuss. , https://doi. org/10. 5194/os-2018-156 Manuscript under review for journal Ocean Sci. Discussion started: 7 January 2019 c Author(s) 2019. CC BY 4. 0 License. Observing System and Climate and Ocean Variability, Predictability and Change (GLOSS-CLIVAR) network and is used to estimate the effective temporal resolution. GLOSS-CLIVAR data are worldwide and available with daily sampling.
using statistical comparison between maps and independent along-track, and drifters' datasets. The improvement patterns between DT2018 and DT2014 global maps coincide with those found by Taburet el al. (submitted) for the validation of the DT2018 products. Using statistical comparison between maps and independent along-track, Taburet et al. (submitted) also found improvement (~3-4%) of the mapped mesoscale structures, in the high variability region and in the western Mediterranean Sea basin. Note that, at global scale, Taburet et al. (submitted) diagnosed the largest improvements between DT2018 and DT2014 in the coastal regions which are partially edited (along 100km coastal band) in the processing for estimating the spatial scale in this study, but they are detected with the temporal scale analysis, showing shorter timescale in the DT2018 compared with DT2014.
Code and data availability. The DUACS system source code is not publicly available. The code for the spectral analysis is released under GNU General Public License v3. 0 and is available at https://github. com/mballaro/scuba. DUACS all satellites gridded data and along-track data are available through the CMEMS website: http://marine. copernicus. eu/. Specific maps used in our study are based on merging of three or two satellites and are available on request by contacting M. Ballarotta (mballarotta@groupcls. com).
Building the emulators We use Gaussian Process regression ('kriging' when used for spatial interpolation), because it is flexible, non-parametric, and provides uncertainty estimates  46. As usual for emulation of computer models, we set the 'nugget' to zero because the ice sheet model is deterministic. We refer to 'the emulator' in the main text for simplicity, but this comprises separate emulators for each scalar output: Pliocene and LIG sea-level change, present day (1992-2017 change in the RCP4. 5 simulation) and the change from 2000 to every even-numbered year up to 2500 for the three RCPs. We construct, validate, calibrate and make predictions using the R software packages DiceKriging and a modified version of DiceEvaluation. Let the function f(x) be the ice sheet model, which simulates sea-level change in a particular era (e.
Acknowledgements T. L. E. , N. E. and P. H. were supported by  EPSRC REsearch on Changes of Variability and Environmental Risk  (ReCoVER:  EP/M008495/1 ) under the  Quantifying Uncertainty in ANTarctic Ice Sheet instability (QUAntIS)  project ( RFFLP 006 ). T. L. E. was also supported by the  EPSRC-funded Past Earth Network  ( EP/M008363/1 ) and the  Université Joseph Fourier -Grenoble International visitor fund 'Campagne INVITES'. N. R. G is supported by contract  VUW1501  from the  Royal Society Te Aparangi. I. N. was supported by the  NERC  iSTAR-C project Dynamical control on the response of  Pine Island Glacier  ( NE/J005738/1 ) and now by the  NASA   Sea Level Change program. A. W. is supported by the  Open University Faculty of Science, Technology, Engineering  and  Mathematics. Thanks  to  Rob DeConto  for running additional simulations necessary for the analysis, suggestions and helpful discussions, and to  Kelsey Ruckert  and  Anders Levermann  for providing data.
Code availability All emulation was performed in R using the DiceKriging and DiceEvaluation packages with minor modifications by TLE. The scripts and input data for the main analysis (sea-level projections at 2100) are available as a downloadable R package on GitHub (https://github. com/tamsinedwards/revisitmici, v1. 0. 2) and can be run without installation on the cloud-based computational reproducibility platform Code Ocean at https://doi. org/10. 24433/CO. 4ebd8cda-35c0-4d8f-9b7c-d1b064109437.
Data availability All projections from this study are available on request. Simulations of the LIG and Pliocene, 1992-2017 mean and 2100 sea level change for all DP16 ensemble members are available in the Code Ocean data folder at the above link. Simulations at 2500 for the subset of the DP16 ensemble passing their calibration are available also in the Supplementary Materials of DeConto and Pollard (2016).
Properties of tested soil and sample preparation To identify the potential geohazard of the AMV, Fugro conducted an offshore geotechnical survey in 2014  (Dan & Po, 12/09/2017, pers. com. )  including rotary drilling with sediment coring up to 34 meters deep (Figure  1  for location) and in situ CPTu measurements (Cone Penetration Testing, with piezocone;  Lunne, 2010; Boggess & Robertson, 2011). These data and cores are used in the present work to characterize the geotechnical properties of the natural and remolded sediments. 2019 ) for more details). The rotary drilling MVF1, located on the mudflow, is also displayed. CPTu profiling and sediment type classification acquired at the MVF1 drilling site, on the western mudflow of the AMV  (Dan & Po, 12/09/2017, pers. com. )  show the presence of three different mechanical intervals.
Acknowledgments Data describing the natural mud properties are available at the following link: https://figshare. com/articles/Absheron_mud_analysis/7448153. This study was conducted in the scope of the PhD of  Arthur Blouin  under the joint direction of the  Pau University  ( E2S-UPPA ), Ifremer and Total S. A. The authors would like to thank  Claire Fialips  for the mud mineralogy analysis,  Mickaël Rovere  for his help during compressibility/permeability analyses, as well as  Mickaël Roudaut  and  Ronan Apprioual  for the experimental set-up conception/assembly and their technical support. Constructive comments by the associate editor and two anonymous reviewers helped to improve the paper.
Ozone concentration measurements made with a Thermo Fisher Model 49i Ozone Analyzer were obtained from the Mobile Aerosol Observing System-Chemistry (MAOS-C). Due to some issues with the NO x analyzer deployed at T3 by the MAOS-C during the wet season, NO x data reported here is weakly reliable. The values reported here are only qualitative indications of NO x levels in the studied period. OH radicals concentrations were provided by an OH chemical ionization mass spectrometer  (Sinha et al. , 2008, OH-CIMS). Organic compounds in the gas phase were measured with selected reagent ion proton transfer reaction time-of-flight mass spectrometer (SRI-PTR-ToFMS,  Jordan et al. , 2009a, b). Aerosol composition was monitored by a high-resolution time-offlight aerosol mass spectrometer (HR-ToF-AMS)  (DeCarlo et al.
Acknowledgements. The  National Center for Atmospheric Research  is sponsored by the  National Science Foundation. We gratefully acknowledge support from  U. S. Department of Energy (DOE) ASR  grant  DE-SC0016331. JLJ and BBP were supported by  NSF   AGS-1822664  and  EPA 83587701-0. This manuscript has not been reviewed by  EPA , and thus no endorsement should be inferred. Dr. Shrivastava  was also supported by the  U. S. DOE, Office of Science, Office of Biological and Environmental Research  through the  Early Career Research Program. Data were obtained from the  Atmospheric Radiation Measurement (ARM) User Facility , a  U. S. DOE Office of Science user facility  managed.
Mechanical data and acoustic emissions During the first stage of deformation at a temperature of 583 K, the sample was strained by 5 % and the differential stress increased towards a peak stress of approx. 3 GPa, i. e. the level of the confining pressure (Fig. 2 ). The differential stress decreased continuously during syndeformational heating of the sample. A total axial strain of 40 % was accumulated by the time the temperature reached 1073 K. In total 10 acoustic emissions were recorded between 10 to 19 % axial strain. Two events recorded at around 12 % and at approx. 19 % axial strain, respectively, were large events almost reaching voltage saturation of the recording system (5 V).
Acknowledgements The authors thank the two reviewers  Greg Hirth  and  Ashley Griffith  for their comments and suggestions that helped improving the manuscript. The authors also thank  Anja Schreiber  for the preparation of the FIB sections and  Christian Chopin  who provided the blueschist sample. Special thanks to  Frans Aben ,  François Passelègue , and  Yehuda Ben-Zion  for their help and discussions and to  Paul Meakin  for a careful review of an early version of the manuscript. The study received funding from the  Alexander von Humboldt-foundation  ( Feodor Lynen-fellowship  to S. I. ) and support from Geo. X in form of a travel Grant (to S. I. ). Further funding came from the  People Program  ( Marie Curie Actions ) of the European Union's  Seventh Framework Program FP7/2017-2013/ and Horizon 2020  under REA grant agreements n°  604713  (to A.
S. ) and n°  669972  (to B. J. ),  EAR-1661489  for the development of AE experiments (Y. W. ). This research used resources of the  Advanced Photon Source , a  U. S. Department of Energy Office of Science User Facility  operated by  Argonne National Laboratory  (contract n°  DE-AC02-06CH11357 ). Financial support for H. M. F through funding provided by the  German Helmholtz Recruiting Initiative  (award number  I-044-16-01 ) to  Liane G. Benning  from the  GFZ  is acknowledged.
By doing so, we seek to extend our understanding of the effects of volcanic eruptions on climate by combining multiple climate-sensitive variables measured in tree rings that were clustered around the time of the major volcanic eruptions (Table  1 ). We focus our investigation on remote tree-ring sites in Siberia, two at high latitudes (northeastern Yakutia   Zielinski et al. (1994) ,  Sigl et al. (2015)  NA -not available. -YAK and eastern Taimyr -TAY) and one at high altitude (Russian Altai -ALT), for which long tree-ring chronologies were previously developed with highly climate-sensitive trees. We assemble a dataset from five tree-ring proxies: TRW, MXD, CWT, δ 13 C, and δ 18 O in larch tree-ring cellulose chronologies. This is done in order to (1) determine the major climatic drivers of the tree-ring proxies, and to evaluate their individual and integrative response to climate change, and to (2) reconstruct the climatic impacts of volcanic eruptions over specific periods of the past (Table  1 ).
Study sites The study sites are situated in Siberia (Russian Federation), far away from industrial centers (and 1500-3400 km apart from each other), in zones of continuous permafrost in northeastern Yakutia (YAK: 69   Hughes et al. , 1999; Sidorova and Naurzbaev, 2002; Sidorova, 2003, for YAK; Naurzbaev et al. , 2002; Panyushkina et al. , 2003, for TAY; Myglan et al. , 2008, for ALT). Due to the remote location of our study sites, we used meteorological data from monitored weather stations located at distances ranging from 50 to 200 km from the sampled sites. Temperature data from these weather stations are significantly correlated (r > 0. 91; p < 0. 05) with gridded data (http://climexp. knmi. nl, last access: January 2018). However, poor correlation is found with precipitation data (r < 0.
Anomalies in tree-ring proxy chronologies after stratospheric volcanic eruptions Normalized TRW chronologies show negative deviations the year following the eruptions at all studied sites (Fig. 2 ). Regarding CWT, a strong decrease is observed in 537 CE at all study sites. Only two layers of cells were formed in 537 CE (-1. 8σ ) and 541 (-2. 4σ ) for YAK compared to the 11-20 layers of cells formed on average during "normal" years. In addition, we also observe the formation of frost rings in ALT between 536 and 538 CE, as well as in 1259. An abrupt CWT decrease is recorded in TAY in 537  (-3. 1σ  ). Furthermore, we found decreasing MXD values at ALT (-4. 4σ ) in 537 CE and YAK (-2. 8σ ) in 536 CE. However, for TAY, the data show a less pronounced pattern of MXD variation (Fig. 2 ). In this regard, the sharpest decrease was observed in the CWT chronologies from YAK in 540 CE (-1.
Temperature proxies We found strong negative summer air temperature anomalies at all sites after the 535 and 1257 CE volcanic eruptions. The temperature decrease was found in the TRW and CWT datasets at all sites and also in the MXD datasets at YAK and ALT (Fig. 5 ). For the volcanic eruptions in later centuries, the evidence for a decrease in temperature was not as pronounced. Whereas no strong decline in summer temperature was found at ALT in 1642 CE, we observe a slight decrease in TRW, MXD, and CWT values in 1643. By contrast, a cold summer was recorded by most tree-ring parameters at YAK, except for δ 18 O. The absence of strong cooling is even more striking during the years that followed the 1815 CE Tambora eruption. In 1816 CE, only the MXD from YAK shows colder than normal conditions (Fig.
Tree-ring sites in northeastern Yakutia (YAK), eastern Taimyr (TAY), and Altai (ALT) and weather stations used in the study. Monthly air temperature (T , • C), precipitation (P , mm), sunshine duration (S, h month -1 ), and vapor pressure deficit (VPD, kPa) data were downloaded from the meteorological database: http://aisori. meteo. ru/ClimateR (last access: January 2018).
, 1977). High-resolution image data available since the early 2000s have revealed that outside these tributary canyons and huge landslides, the dissected, pristine morphology shows a variety of smaller-scale geomorphological features which are familiar to mountain geomorphologists, with the association or superimposition of a rich variety of landforms controlled by mountain permafrost degradation, fluvial erosion, talus de-velopment, and gravity  (Mège and Bourgeois, 2011; Gourronc et al. , 2014; Dębniak et al. , 2017). The difference with alpine mountain geomorphology on Earth is therefore not that much a matter of morphological details; it rather lies in the size of the land systems. In the main troughs, the height of the Valles Marineris slopes is several kilometres, and up to 9 km, whereas typical mountain slopes on Earth are hundreds of metres to a few kilometres high.
, 2019) , much larger than any terrestrial landslide, which help populate the landslide dataset for voluminous landslides that propagate on nearly flat surfaces. Similar to landslides, DSGSD occurs on mountain slopes that are much smaller on Earth than on Mars, and at the first order, their origin may be similar. However, like in the case of landslides, the difference in scale may be associated with differences in controlling parameters. We will not answer this complex question in this work, but instead provide quantitative information that may help in future works aiming at constraining the parameters that control DSGSD over a broad range of sizes.
Data The observations of the Valles Marineris trough system (Fig. 1a ) reported here were made using Mars Reconnaissance Orbiter/CTX imagery as a baseline. Higher-resolution images from Mars Reconnaissance Orbiter HiRISE were used for more detailed research when available. For topography, the resolution of the HRSC digital elevation model (DEM) mosaic of Valles Marineris  (Gwinner et al. , 2009)  is too coarse for this work, whereas HiRISE DEMs would be adapted but were either not available in the study sites or did not cover enough surface to be used. DEMs were generated from CTX stereo pairs using SocetSet ® , have the appropriate vertical precision of ca. 15 m, and were used to extract topographic profiles. Nevertheless, some DSGSD sites (including e. g. in Ius Chasma) could not be investigated due to the poor geometry of the CTX images available during the lifetime of this project, which did not make possible the generation of good-quality DEMs.
DSGSD scarps were studied in the Tatra Mountains during two periods of fieldwork. Elevation data in the Tatra Mountains were collected using the GPS device Garmin GPSMap 62s in differential (WADGPS) and non-differential mode, as explained in  Kromuszczyńska et al. (2016) , during two field campaigns conducted in September 2012 and June 2013 in the higher Tatra Mountains in Poland and Slovakia and the lower Tatra Mountains in Slovakia.
Acknowledgements. This work has been financially supported by the  Foundation for Polish Science , project  FNP TEAM/2011-7/9  "Mars: another planet to approach geoscience issues", and the OPUS/V- MACS  project no. 2015/17/B/ST10/03426  of the  National Science Centre, Poland. ASTER GDEM is a product of  METI  and  NASA. Both reviewers are thanked for help in methodological clarification and in improvement of many details. Financial support. This research has been supported by the  Foundation for Polish Science  (grant no. TEAM/2011-7/9 ) and the  National Science Centre, Poland  (grant no. 2015/17/B/ST10/03426 ). Review statement. This paper was edited by  Mary Bourke  and reviewed by three anonymous referees.