dataesr/scientific-paragraphs-categorization huggingface dataset:
The data from RCEW-CZO are also used for the validation and testing of distributed models. The East River, CO, watershed is part of the Upper Colorado River Basin and was specifically designed to improve predictions of hydrology-driven watershed biogeochemical behavior  (Hubbard et al. , 2018; Fig. 1, no. 3 ). Research includes the identification of key controls on hydrology-driven biogeochemistry and testing new approaches for characterizing and simulating behavior-up to the floodplain scale. A particular emphasis has been placed on exploring the value of fine space or time scale information for informing reactive transport models and improving the prediction of floodplain-scale exports of carbon to the Colorado River. Research includes consideration of the floodplain microbial community diversity and metabolic potential, the contribution of vadose zone microbial respiration to the floodplain carbon cycle, the identification of hotspots and hot moments using geophysical approaches, and the impact of hotspots and hot moments on floodplain reactive transport predictions of floodplain exports to the Colorado River.
More specifically, the following research topics are addressed: (i) water efficiency of plants under drought conditions and their adaptation mechanisms to water stress; (ii) groundwater-surface water interaction and their eco-hydrological effects; (iii) eco-hydrological processes across scales and involved scaling issues; (iv) response of watershed eco-hydrological processes under climate change and human activities; and (v) integration of the comprehensive observational data into models. The Cryospheric Hydrometeorology Observation System (CHOICE) is a satellite site of the Heihe observatory and was established in 2008 in the Hulu River catchment  (Han et al. , 2018; Fig. 1, no. 9b ). The CHOICE observatory is located upstream of the Heihe observatory and focuses on cryospheric hydrometeorology observation.
The Danish HOBE hydrological observatory was initiated in 2007  (Jensen and Refsgaard, 2018; Fig. 1, no. 12 ) and aims to: (i) establish an observatory for detailed measurements and experiments in a catchment representing temperate climate conditions and with groundwater-dominated streamflow; (ii) establish scientific datasets to support fundamental research of hydrological processes at various scales; (iii) test new innovative field instrumentation and observation techniques from ground-based as well as air-and satellite-borne platforms; (iv) investigate the interaction VZJ | Advancing Critical Zone Science p. 7 of 10 between hydrological and (v) integrate in complex integrated hydrological models to address the primary research question, which is water balance closure at different scales.
, 2017). This is required not only for improving data analysis and model-driven design of catchment experiments, but also to perform hydrological forecasts at larger, perhaps global scales, to develop interdisciplinary research at all scales, and to better address the pressing societally relevant environmental problems related to the impacts of climate and land use change on the hydrologic cycle. The presented hydrological observatories and their associated databases are crucial for the advancement of integrated hydrological models that consider complex feedback mechanisms between the hydrological compartments. Thus, in our view, it is essential to increase the awareness and knowledge of these infrastructures in the international hydrological community to increase their utilization for the exploration of new hypotheses in hydrology and related disciplines.
, 2005; Deptuck et al. , 2012; Sylvester et al. , 2012). Models of slope-fan stratigraphic architecture and evolution are predominantly based on insights from shallow-subsurface three-dimensional (3-D) seismic-reflection data (up to ~200 Hz peak frequency), with limited core penetrations (e. g. ,  Beaubouef et al. , 2003). These datasets can constrain the 3-D geometry of packages of strata as thin as several to tens of meters in the subsurface, but they lack the depth of penetration and deep-time perspective of conventional industry seismic-reflection data (e. g. , generally <40 Hz peak frequency;  Normark et al. , 1993; Prather et al. , 2012). Moreover, core calibration is limited and does not provide a strong 3-D lithologic control, which can be of importance to the spatial variation in properties in oil and gas reservoirs (i.
e. , heterogeneity;  Lake and Jensen, 1989). These datasets provide insights into the compensational stacking of architectural elements and the stratigraphic evolution from ponded to perched fan deposits. However, an important uncertainty is the lateral continuity and vertical connectivity of sandy and muddy architectural elements at higher resolution. These architectural elements control the static and dynamic connectivity of slope-fan reservoirs and influence fluidflow behavior during hydrocarbon production (e. g. ,  Glenton et al. , 2013; Sutton et al. , 2013). Deptuck et al. (2008)  used high-resolution 2-D seismic-reflection profiles (900-7000 Hz frequencies) and piston cores to investigate the causes of heterogeneity in Pleistocene submarine fans offshore East Corsica. This work provided new details of the hierarchical levels of compensational stacking of deposits: individual beds stack to form lobe architectural elements, which stack to form more composite submarine fans.
g. ,  Moscardelli et al. , 2006; Moscardelli and Wood, 2008; Wood and Mize-Spansky, 2009; Garciacaro et al. , 2011b ) (Fig. 3 ). The seismic-reflection dataset is also the subject of unpublished MS theses at the University of Texas at Austin (e. g. ,  Mize, 2004; Sullivan, 2005). Exploration drilling in block 25A (Haydn-1 well) revealed a thick section (>3 km) of Pliocene-Pleistocene slope-fan deposits  (Patterson et al. , 2001 ) (Fig. 2 ). Moscardelli et al. (2006)  interpreted the seismic-reflections immediately above their '2' and '1' horizons to be Pleistocene mass-transport deposits at the base of the shallowest depositional sequence in block 25A. Brami et al. (2000)  and  Moscardelli et al. (2006)  interpreted leveed-channel deposits of a slope fan between the top of the mass-transport deposits and the seafloor (Fig.
Forward Stratigraphic Modeling DionisosFlow TM software is a four dimensional process-based deterministic multilithology forward stratigraphic model that simulates basin filling  (Granjeon, 1997; Granjeon and Joseph, 1999; Granjeon, 2014). A range of sedimentary processes are modeled including diffusive sediment transport, delta autoretreat, incision, large-scale avulsion, and slope failure in response to tectonic, climate, and sea-level fluctuations during millennia and longer time scales (e. g. ,  Pinheiro-Moreira, 2000; Rabineau et al. , 2005; Alzaga-Ruiz et al. , 2009; Gvirtzman et al. , 2014; Harris et al. , 2016; Hawie et al. , 2017). Detailed fluid dynamics are not considered in this model; the goal is to simulate the large-scale (10 2 -10 3 m cell size) and long-term (10 3 -10 5 yr time steps) evolution of basin fill.
ACKNOWLEDGMENTS We thank the sponsors of the  Quantitative Clastics Laboratory  (http://www. beg. utexas. edu/qcl). We are grateful to Paradigm® for a generous donation of SeisEarth® interpretation and visualization software. We thank  Lorena Moscardelli  for discussions on project scope and the geology offshore Trinidad. We are grateful to  Richard Sech ,  Morgan Sullivan ,  Ashley Harris , and  Tao Sun  for conversations regarding reservoir modeling and forward stratigraphic modeling. We thank two anonymous reviewers for recommendations that improved the clarity of this manuscript.
2 m/yr, a "wet" region along the southeastern and southwestern margins of the GrIS where C is greater than 1 m/yr and the rest of Greenland where accumulation is intermediate. NPS-0k reproduces quite well the "wet" zone simulated by MAR thanks to its relatively high resolution. The "dry" zone is also well simulated, even if in the central part of South Greenland the net accumulation is less in NPS-0k than in MAR. In central Greenland, the lower annual mean accumulation in NPS-0k compared to MAR is due to the greater summertime sublimation in NPS-0k than in MAR. GrIS-averaged seasonal accumulation, melting and SMB for NPS-0k and MAR are presented in Table  2. These spatial integrations were computed after interpolating output from both models on an rectilinear grid and masked over the same exogenous Greenland mask obtained from the Global Database of Administrative areas (GADM, http://www.
Acknowledgements The authors would like to thank  X. Fettweis  ( University of Liège, Belgium ) for providing a regional simulation from MAR for the period 1979-2012. The main author is grateful to  Aurore Voldoire  for her help in handling the CNRM-CM model. Supercomputing resources were provided by  Météo-France/DSI  that we thank for their support and guidance. The figures were produced thanks to the  NCAR Command Language (NCL) Software  (doi: 10. 5065/D6WD3XH5NCL ) and the  PCMDI Climate Data Analysis Tools (CDAT) , the use of which is hereby acknowledged.
Biological Data Breeding success data were collected between 1993 and 2017 as part of the program 109 of the French Polar Institute (IPEV), on the colonies of Ile des Pétrels, which ranged from 10,849 to 20,957 breeding pairs over these 24 seasons. Active nests (with at least one egg) were counted in November, and the number of chicks that were still alive was counted in February. The breeding success was calculated as the number of chicks in February divided by the number of active nests in November (see  Jenouvrier et al. , 2006  for more details). Foraging activity of Adélie penguins was monitored in the frame of the IPEV program 1091 through the deployment of miniaturized GPS devices (CatLog TM GPS, Catnip Technologies, USA, and AxyTrek TM GPS-accelerometry loggers, Technosmart, Italy).
These devices were temporarily attached to the back feathers of the penguins using marine tape  (Wilson et al. , 1997)  and recorded the position of the birds every 15-30 min during the long trips of the incubation phase, and every 3 min in the shorter trips of the chick-rearing phase. Location data were processed following the methods described in  Widmann et al. (2015) , which showed that, typically, females travel at sea for 15 days after laying the eggs, followed by the foraging trip of males that last between 10 and 15 days. The egg hatches after the return of the male. Thereafter, foraging trips become shorter, getting as short as a few hours to 3-4 days during the chick rearing phase. Foraging trip duration (days) and maximum distance (km) from the colony was calculated for each trip.
Environmental Data Meteorological data (monthly air temperature and direction of prevailing winds in degrees from the north) between 1956 and 2017 were downloaded from the British Antarctic Survey website (https://legacy. bas. ac. uk/met/READER/). The percentage of seaice cover was calculated as the percentage where sea-ice concentration was more than 15% in an area ranging from 135 and 145 • E and 61 and 67 • S (foraging range of Adélie penguins at Ile des Pétrels,  Widmann et al. , 2015)  and over a period ranging from 1992 to 2017, using the data provided by the Institut Français de Recherche pour l'Exploitation de la Mer (ftp://ftp. ifremer. fr/ifremer/cersat/products/gridded/psiconcentration/data/antarctic/). Sea-ice extent was calculated as the distance (km) from the colony to the nearest open water (seaice concentration < 15%).
, 2009  for a similar test case). In addition, 2015-16 is the only year of high breeding success for which we have tracking data. The season 2013-14 showed the largest sea-ice extent and cover in our dataset (since 1992) in the beginning of the breeding season in November (Figures  2A, B ). Interestingly, 2016-17 had the smallest sea-ice extent in the beginning of the breeding season but both years kept a larger than usual extent later in the summer. While it was compact in 2013-14, the sea ice in January was sherbet-like in 2016-17 and did not break for the whole summer. There was no polynya opening in vicinity of the colony in 2013-14 and 2016-17, closest opened water was 80-90 km away. In contrast, a polynya started to open in front of the colony in November 2015 and connected with the open sea by January 2016.
FUNDING This study was financially supported by the  French Polar Institute Paul Emile Victor (IPEV) , the  WWF-UK  through  R. Downie , the  Zone Atelier Antarctique et Subantarctique -LTER France of the CNRS. This study was approved by the ethic committee of IPEV. This study is a contribution to the program SENSEI funded by the  BNP Paribas Foundation.
Microscale Y speciation Microprobe elemental analysis of Y revealed a selection of ashes (App-FA-1, App-FA3, IL-FA1, PRB-FA1, and PRB-FA-2) for which we could collect mXANES data for Y-enriched spots in the samples. Linear combination tting of the mXANES data yielded R-factors between 0. 00081 and 0. 0080 (Tables  S4  and S5  †). The summed weights of Y references in the ts were between 95. 9% and 103. 5%. For Appalachian Basin ashes, we observed Y hotspots with spectral features that resembled YPO 4. Points 1 and 2 of App-FA1 (shown in Fig. 6 ) were t by 50-74% YPO 4 , while the bulk XANES t contained no YPO 4. The Y hotspot in Map 4 for App-FA3 closely matched the YPO 4 spectrum, suggesting that this point was a discrete Y-phosphate particle (Fig. 7 ). In contrast, the Y-enriched areas of Map 6 from the same sample resembled the bulk XANES ts for Appalachian Basin ashes (Y 2 O 3 and Y-doped glass) and the Y abundance was more distributed across Map 6 compared to the concentrated spot in Map 4.
Acknowledgements This work was supported by the  U. S. National Science Foundation  (# CBET-1510965  and  CBET-1510861 ), the  NSF Partnership for International Research and Education  (# OISE-1243433 ), and the  U. S. Department of Energy  ( DE-FE0026952 ). RKT was partly supported by a  Graduate Scholarship in Solid Waste Research  from the  Environmental Research and Education Foundation.
Methodology Most observations of lava features were made in road cuts with minor use of stream sections and small quarries. The latter provided some degree of 3-D exposure. Altitudes and flow thicknesses used to construct the stratigraphic log of the section (Fig. 4 ) were derived by combining data from repeated measurements utilising an aneroid altimeter, GPS altimeters and a Jacob Staff with a Dumpy Level. Samples for wholerock geochemical analysis were collected in road cuts and analysed for major and trace elements by wave-length dispersive X-ray Fluorescence spectrometry using a Philips 1480 spectrometer at Rhodes University, South Africa. During sample preparation care was taken to remove any amygdales. Duncan et al. (1984)  provide full details of the analytical procedures.
Acknowledgments We thank  S. Reidel ,  S. Passey ,  L. Vanderkluysen ,  G. Kereszturi ,  R. Duraiswami  and the editor  R. Brown  and  A. Harris  for their reviews and  J. Besse ,  M. Gérard ,  A-L. Chenet  and  H. Bouquerel  for their invaluable help in the field;  M. Balme ,  S. Blake ,  S. Self  and  D. Rothery  for reading the manuscript and suggesting improvements. We also thank the staff of the  Walkerbouts Inn  for reviving us each evening and the farmers adjacent to the  Naude's Nek , who allowed us to cross their land. This is IPGP contribution 3900.
Acknowledgments: We are grateful to  Y. Chancerelle  and  G. Siou  ( CRIOBE-Moorea ) for the logistic and scientific support. We are grateful to the  Drollet family (Teahupo'o, Tahiti)  and to the local organizers of the professional surf competition " Billabong Pro Tahiti " of the  World Surf League (WSL)  for allowing and helping to position our PTs during the competition. A. R. wants to acknowledge the  WSL PURE (Protecting, Understanding, and Respecting the Environment) community  for the discussions during the yearly Trestles meeting (California).
V. P. provided the main ecological inputs to the model. All authors reviewed and provided detailed feedback during data analysis and the production of the manuscript. Competing interests: The authors declare that they have no competing interests. Data and materials availability: All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials. The bathymetric profiles, wave and tide tables, and XBeach parameter files that support the findings of this study are available in figshare at https://figshare. com/s/57b852ba5095640bcd63. Additional wave data that support the findings of this study are available from the corresponding author upon reasonable request.
The computation and determination of the mineral species was done with Andrew Locock's software (2013)  [24]  which follows the recommendations of the IMA 12. The values of Si (expressed in atoms per formula unit: apfu) and Mg/Mg+Fe 2+ ratio were plotted on the diagram (Si apfu versus Mg/Mg + Fe 2+ ). An estimate of the ferric iron content (Fe 3+ ) was obtained by calculation with Andrew Locock's software. With the EMP-WDS, the uncertainty on the Mg/Mg+Fe 2+ ratio is negligible and that on the Si apfu value is on the order of ± 0. 3%. Using TEM-EDS, the uncertainty on these same values is greater. The major component of this uncertainty is the consideration of "maximum tolerated error" of 10% on the elementary analyses required in LSAD laboratories. The calculated uncertainty is ± 2. 4% on Si apfu and on Mg/Mg+Fe 2+.
UndifferenƟated-acƟnoliƟc-amphibole Spot chemical analyses were acquired with EMP-WDS from actinolite-asbestos bundles observed on polished thin sections. The TEM-EDS chemical analyses were performed on actinolite-asbestos fibres observed on TEM, coming from ground elements from the same samples. The chemical analyses were acquired on the one hand with the University of Montpellier's EMP-WDS and on the other hand with AD-LAB's transmission electron microscope EDS. Calculations were then done using Locock's software. The results obtained are presented below for comparison (Tab. 3, Fig. 9 ). The values obtained are grouped in the same sector as the range of actinolite. The variability observed between the values is compatible with the variations observed on this type of material. The measurements with the UndifferenƟated-acƟnoliƟc-amphibole microprobe have been made at the base of the fibres in order to avoid the release of gases that occur when measurements are made with the evaporation of water trapped between the actinolite fibres.
Three classes of fibres were considered, classified in this work as fine (D > 10 mm), very fine (2 < D 10 mm) and ultrafine (D 2 mm). In practice, the actual thickness of the ultrafine fibres is not measurable by optical microscopy. These ultrafine particles are those which have the morphological characteristics closest to those of the asbestiform fibres, in particular a very high elongation (L/D ratio > 20) and curved in nature. Analyses (267) carried out on the electron microprobe then made it possible to acquire precise spot data concerning the chemistry of the identified fibrous amphiboles. This chemical information has very rarely been acquired from ultrafine amphibole fibres (D 2 mm) precisely because of their excessive fineness and their isolation in quartz, feldspar or carbonate matrices.
The German Space Agency (DLR) is responsible for the payload while the French Space Agency (CNES) is responsible for the platform (MYRIADE Evolution product line). The payload data processing centre is under CNES responsibility with significant contributions from DLR. MERLIN's active measurement is based on a space-borne integrated path differential absorption (IPDA) lidar. Just like a differential absorption lidar (DIAL), MERLIN's IPDA lidar uses the difference in transmission between an online pulse with a frequency accurately set in the trough of several CH 4 absorption lines and an offline pulse whose wavelength has a negligible CH 4 absorption  (Ehret et al. , 2008). Furthermore, the two wavelengths are set close enough in such a way that the differential effects of any other interaction, excluding Published by Copernicus Publications on behalf of the European Geosciences Union.
The much higher backscatter signal from these targets allows for a system with a relatively small power-aperture product as compared to a DIAL, which has to rely on atmospheric backscatter. The MERLIN measurements require a well-defined processing chain that ensures the final performance of the mission. The processing chain is divided into four levels. Level 0 (L0) consists of raw data (backscattered signals and auxiliary data), and level 1 (L1) processes the vertically resolved products and the differential absorption optical depth (DAOD) values for both individual calibrated signal shot pairs and for a horizontal averaging window. Level 2 (L2) computes the X CH 4 for both individual calibrated signal shot pairs and for a horizontal averaging window, additionally using operational analyses from numerical weather prediction (NWP) centres.
MERLIN must reach an unprecedented precision and accuracy on X CH 4 with a targeted RRE of 1 % (18 ppb). The targeted RSE must remain under 0. 2 % (±3 ppb) in 68 % of cases; a limited budget of 0. 06 % (±1 ppb for a X CH 4 of 1780 ppb) is allocated to biases introduced by averaging algorithms with algorithms to correct these averaging biases. To reach the RRE target, levels 1 and 2 of MERLIN's signal processing requires a horizontal averaging of data over 50 km along track  (Kiemle et al. , 2011). Thus, the single shot online and offline random error is reduced by a factor of √ 150 ≈ 12. For instance, for the typical target reflectivity (0. 1), the online and offline signal-to-noise ratios (SNRs) are of the order of 6. 1 and 16. 5, respectively, and the equivalent SNRs for the averaged signals  are, respectively, 79.
6 and 197. 2. This process greatly decreases the RRE of the X CH 4. Section 2 gives an overview of the IPDA measurement and MERLIN data processing. Section 3 defines and compares biases of several averaging schemes (described below) and suggests correction algorithms. Section 4 presents a comparative evaluation of these averaging schemes and associated bias correction procedures using modelled scenes based on real satellite data. And finally, in Sect. 5, the results of the simulation are described and a "best approach" algorithm (i. e. the least biased on tested scenes) is proposed for the MERLIN processing chain. 2 Overview of IPDA measurement and the MERLIN processing chain 2. 1 IPDA measurement MERLIN active measurement is based on a short-pulse IPDA lidar. The column content of methane between the satellite and a "hard" target (ground, vegetation, clouds, etc.
4 ). Figure  7  shows the global cumulative distribution of standard deviations of altitude of SRTM database worldwide. We notice that 67 % and 97 % of the scenes present a lower altitude standard deviation than the one considered on the Millau and Chamonix data, respectively. For sensitivity study purposes, the reflectivity relative variations from the SPOT-5 data set are multiplied by a reference mean reflectivity that can be chosen to obtain the usable scene reflectivity. Four mean reflectivity values will be considered: 0. 1 (vegetation), 0. 05 (mixed water and vegetation), 0. 025 (sea and ocean) and 0. 016 (ice and snow). The pressure grid P i,j and the pressure thickness grid P i,j are obtained from surface pressure P surf i from the ECMWF analyses data set using a hybrid sigma coordinate system.