dataesr/scientific-paragraphs-categorization huggingface dataset:
Upon publication at the ORNL DAAC, a formal citation, including the authors, title, and date of publication, and a unique Digital Object Identifier (DOI) was issued for each data product. The data citation and DOI provide a convenient and traceable identity for each specific data set that can be cited in the scholarly literature and linked to subsequent research efforts and products. In order to increase the visibility and maximize the scientific impact of NASA data products, the ORNL DAAC provides searchable metadata to Earth and Space Science a variety of relevant data catalogs, advertises the data online through email, news, and the DAAC website, and provides user support services. Throughout the ACT-America project, data files were revised, recalibrated, and updated, as necessary. Close communication, and automated monitoring of data availability, were essential for keeping the LaRC data repository and the holdings at ORNL DAAC in sync.
Merged Airborne In Situ Data Products The airborne measurements from the ACT-America campaign were recorded on different native sampling time intervals ranging from milliseconds (e. g. , 10 Hz for MFLL measurements) to multiple seconds (e. g. , 5s temporal resolution for GHG measurements,  Campbell et al. , 2020). Additionally, instrument teams are responsible for reporting only their own data, without any of the navigational or meteorological parameters essential to its interpretation. Merging these various data files to a common standard sampling interval brings coherence to the data, creates geolocated data products, and makes it much easier for the data users to perform holistic analysis of the ACT-America data products. The ACT-America merged data products are generated at 1-s, 5-s, 60-s, and time intervals corresponding to flask sample fill times.
Merged data files in ICARTT format were prepared by the LaRC through a weighted average based on the overlap between the measurement and merge time intervals as described in  Chen et al. (2018). The merge files are updated to reflect revisions of any observational data sets. For each individual RF, four key in situ observations collected by multiple instruments were merged: (a) navigational data, (b) GHG and trace gas mole fractions, (c) meteorological variables, and (d) flask samples. For the B-200, which needed refueling to cover long flight distances, the first and second sorties (L1 and L2, respectively) were also merged into a single file. In contrast, the C-130 endurance was long enough so that such sortie-merging was not required. During the conversion of the merged data products from the ICARTT format to the netCDF format at the ORNL DAAC, the flight metadata flags  (Davis et al.
, 2018)  were added. The flight metadata flags provide information such as the type of aircraft maneuver underway (e. g. , profile vs. level leg), whether or not the data are within the ABL, and the location of the data with respect to its synoptic environment (cold sector vs. warm sector of a mid-latitude weather system). These flags enable users to readily partition the data for analyses. In the future, we will add surface influence functions that use an atmospheric transport reanalysis to provide a quantitative connection between the airborne data and regions upwind whose fluxes impact those airborne observations. The file header of an example C-130 5-s merged file (version 1. 2)  (Davis et al. , 2018)  with all meteorological variables, trace gases, navigations, and flight metadata flags can be found in Table  S2.
Earth and Space Science The goal of model data management for ACT-America is to facilitate the use of model data within the ACT-America science team. To achieve this goal, we followed lessons learned  (Wei et al. , 2014 ) from past research projects, i. e. , the Multi-scale Synthesis and Terrestrial Model Intercomparison project (MsTMIP)  (Huntzinger et al. , 2013) , to apply management practices for ACT-America model data products. Specifically, we ensured appropriate resources for model data planning, preparation, and management; established close collaboration between data experts and science researchers; produced model data and metadata in proper formats and standards; provided detailed data documentation, including the model data provenance; and provided an on-demand approach to distributing data.
The CF-compatible netCDF format was chosen for ACT-America model data products to increase usability and interoperability. The THREDDS data server allows data to be accessed through standard Web API (i. e. , Open-source Project for a Network Data Access Protocol; OPeNDAP) in an on-demand manner. Users can choose to subset and access data in a region or temporal range of interest, instead of downloading the entire data files. For model data, besides the fundamental characteristics (e. g. , spatial extent, temporal extent, and variable names), one additional key metadata is their provenance, including the version of the transport model used, boundary conditions, and prior fluxes used in a particular simulation, and major model parameters. The data management team at the ORNL DAAC worked with the modeling scientists to document such provenance metadata for each simulation output.
In the winter, fossil fuel influence was broadly observed throughout the entire observational domain. Feng et al. (2021)  documented biases in biological models of summertime CO 2 fluxes and compared inferences from the ACT-America flight data to NOAA tall tower and AmeriFlux flux towers. Rigorous investigation of atmospheric GHG modeling systems is also underway. ACT-America airborne data are being used to evaluate OCO-  High-resolution models  (Hu et al. , 2021; Samaddar et al. , 2021)  of the elevated CO 2 band observed along the frontal boundary shown in  Pal et al. (2020a)  have been evaluated using the ACT-America airborne data, as has a newly developed global CO 2 transport model  (Zheng et al. , 2020). As noted previously, OCO-2 XCO 2 variability at local to synoptic scales has been evaluated using ACT-America lidar and in situ observations  (Bell et al.
Accessibility of the ACT-America Data NASA promotes the full and open sharing of the Earth Science data with the research and applications communities, private industry, academia, and the general public (details at https://earthdata. nasa. gov/ earth-observation-data/data-use-policy). Final data from ACT-America are available for free and open to the public from the ORNL DAAC, which is a CoreTrustSeal Certified Repository (https://www. coretrustseal. org/) and adheres to the Findability, Accessibility, Interoperability, and Reusability (FAIR) data principles  (Wilkinson et al. , 2016). Intermediate ACT-America data are currently available from NASA LaRC and PSU DataCommons (see Acknowledgments for details). A free NASA Earthdata Login account (https://urs. earthdata. nasa. gov) is required to access the ACT-America data from the ORNL DAAC.
By establishing an account, users can be notified of changes or updates to the data. To better support the carbon cycle modeling research, ACT-America airborne and tower GHG observations are also integrated into the NOAA/ GML Observation Package (ObsPack) data products  (Masarie et al. , 2014). ObsPack brings together direct atmospheric greenhouse gas measurements derived from one or more national or university laboratories. The Airborne Data Visualizer (ORNL DAAC, 2020) was developed to enhance the understanding and accessibility of the data collected for the ACT-America mission. It runs on a server maintained by the ORNL DAAC and takes advantage of the rich metadata packaged with the instrument measurements in the netCDF files to create an informative interface for exploration of the data.
The citations and DOIs are provided on the landing page and the User Guide of each final ACT-America data product published at the ORNL DAAC. To acknowledge the science teams who have created and shared data products, users should include a bibliographic citation to any data products used in publications. Proper citations, including the authors, title, publisher, and DOI, will help others find and re-use the data and also establish methods to track the impact of the ACT-America mission.
Summary The ACT-America study is a multi-year effort to better understand and quantify sources and sinks of major greenhouse gases. ACT-America provides a unique and valuable asset of high-quality airborne measurements of atmospheric CO 2 , CH 4 , trace gases, and meteorological properties over the Central and Eastern US, along with tower-based measurements and modeled atmospheric greenhouse gases mole fractions and regional carbon fluxes. Through all five seasonal campaigns, a total of 121 RFs, more than 1,140 h of observations, 570 level legs, and 1,363 vertical profiles were conducted using the two aircraft, i. e. , C-130 and B-200. ACT-America data products, including the merged airborne in situ data, provide a valuable asset to improve the accuracy and precision of regional inverse flux estimates of GHGs and beyond.
A specific case of frontal contrasts of GHGs and a summary of broader science applications using data products generated from the ACT-America project are highlighted. A full catalog of known ACT-America publications can be found at the ORNL DAAC ACT-America website (https://actamerica. ornl. gov/publications. shtml). Better estimates of greenhouse gas transport, sources, and sinks, enabled by the detailed data collected by ACT-America, will help to reduce uncertainty in terrestrial carbon cycle models at regional to continental scales and to monitor regional carbon fluxes to support climate-change mitigation efforts. WEI ET AL. 10. 1029/2020EA001634.
Data Availability Statement The latest version of majority ACT-America observational data has been published and is open and freely available from the ORNL DAAC (https://daac. ornl. gov/actamerica). Some observational data (including the MFLL data and merged airborne in situ data) are still undergoing minor revisions. These intermediate revisions can currently be accessed from the NASA LaRC website (https://www-air. larc. nasa. gov/missions/ACT-America/), which will remain active until all final versions of ACT-America observational data are published by the ORNL DAAC and open and freely available from https://daac. ornl. gov/actamerica. The ACT-America model results are currently available from PSU DataCommons (reference simulations: https://doi. org/10. 26208/7a4p-q224; ensemble simulations: https://doi.
org/10. 26208/z864-qk73). Selected model data, including the Carnegie-Ames-Stanford Approach (CASA) model ensemble biogenic fluxes, influence functions, and the reference simulations, have been or are being published at the ORNL DAAC and are or will be open and freely available from https://daac. ornl. gov/actamerica. ACT-America airborne and tower GHG observations are also integrated into the NOAA/GML ObsPack data products: https://www. esrl. noaa. gov/gmd/ccgg/obspack/.
These were successfully deployed by the specialist societies in October 2020, and the decision was taken to deliver the EECC 2020 on-line with remote proctoring in March 2021, leaving time for any unsuccessful candidates to re-sit the examination on the planned date in June 2021. The EECC 2020 exam questions had been written, selected, and standard set before the decision to postpone. However, in parallel with the delivery of the 2020 exam, the 2021 exam had to be developed. Fortunately, the exam uses an on-line database for question writing, selection and standard setting, so using the same tools, the face-to-face meetings were replaced with videoconferencing. The question editing meeting was shortened from 2-days to 1, with writers submitting 6 questions each, instead of the usual 12. The format was highly successful and achieved the same level of scrutiny and high-quality questions as in previous years.
Increasing surface melting on the Greenland ice sheet requires better constraints on seasonally evolving basal water pressure and sliding speed. Here we assess the potential of using inverse methods on a dense time series of surface speeds to recover the seasonal evolution of the basal conditions in a well-documented region in southwest Greenland. Using data compiled from multiple satellite missions, we document seasonally evolving surface velocities with a temporal resolution of two weeks. We then apply the inverse control method using Elmer/Ice to infer the basal sliding and friction corresponding to each of the 24 surface-velocity data sets. Near the margin where the uncertainty in the velocity and bed topography are small, we obtain clear seasonal variations that can be mostly interpreted in terms of a effective-pressure based hard-bed friction law.
1 ). Hereafter, this area is referred to as Russell sector. Extensive measurements of the ice thickness were carried out over the studied region using radar sounders, especially through NASA's Operation IceBridge mission  (Morlighem et al. , 2013; Lindbäck et al. , 2014). This dense dataset with an average radar-line spacing of less than 500 m is exceptional by Greenland standards, where most radar lines are generally separated by tens of kilometers. In addition, because of its relative accessibility, this sector has been the subject of numerous complementary geophysical investigations such as boreholes, seismometers, or GPS  (Smeets et al. , 2012; Dow et al. , 2013; Wright et al. , 2016; Harper et al. , 2017; Kulessa et al. , 2017; Maier et al. , 2019) , making it a privileged study site for numerical investigations  (Bougamont et al.
Seasonal surface velocities We have derived a time series of horizontal surface ice velocity of the Russell sector at a spatial resolution of 150 m using satellite images collected between 2015 and 2019 by Landsat-8, Sentinel-1, and Sentinel-2. The details on the data processing can be found in  Derkacheva et al. (2020) , and are summarized below. A cross-correlation approach is used to estimate the features (or radar speckle) displacement between master and slave images taken on two different dates, which is further converted to the v x and v y surface flow speed components  (Mouginot et al. , 2017; Millan et al. , 2019). Only the measurements with time intervals shorter than 32 days (1 month) are used in order to capture rapid dynamic changes in ice flow. To reduce the noise and relatively large errors associated with these short revisit   (Smeets et al.
To deal with this phenomenon, we assume that the total magnitude of our time series was not severely affected and so we only consider the norm of the velocity vector for the model inversions, keeping the vector direction to be defined by the model itself. According to theoretical expectations, the ice flow is most likely to be affected by seasonal variations in surface runoff reaching the bed across the area that is under the equilibrium line. At Russell, the long-term equilibrium line is estimated to be at 1500 m  (Van De Wal et al. , 2012). Even so, the GPS records have shown the presence of a short summer speed-up further inland as well  (Bartholomew et al. , 2012; Greskowiak, 2014) , with acceleration of about +5 % up to 50 km inland from the equilibrium line  (Greskowiak, 2014). That corresponds to about +1 m/yr above the local MWS and is within the noise level in our velocity dataset.
In Fig. A1 , we show the misfit maps as the difference between observed and modeled surface ice speeds (only for the early half of the months). The periods showing the largest misfit correspond to the transition between different surface conditions. This is especially true in June, July and September, when the surface changes from snow-covered to melting-ice or vice-versa. Note that the November dataset seems more likely to be corrupted by poor satellite imagery than by the surface conditions. The uncertainty in the observed velocity maps are indeed the most important for these periods, often exceeding 30 m/yr, which represents a significant relative uncertainty in the upper part of the domain where speed is below 100 m/yr. However, the surface velocity stays captured relatively accurately in the first 50-70 kilometres from the margin, and the inversions give a good match between the adjacent time steps, giving us confidence in the interpretation of the basal fields in these areas.
Acknowledgements. Elmer/Ice computations and ice velocity time series presented in this paper were performed using the GRICAD infrastructure , which is supported by Grenoble research communities. J. M. acknowledges support from the  French National Research Agency (ANR)  grant ( ANR-19-CE01-0011-01 ). We thank  Neil Humphrey  for the inclinometery data funded by the  NSF Office of Polar Programs-Arctic Natural Sciences  awards # 1203451  and # 0909495 ,  SKB ,  NWMO ,  Posiva Oy , and  NAGRA.
Freeze-dried collagen was then analyzed by EA-IRMS (Europa Scientific EA analyzer coupled to Europa Scientific 20-20 IRMS; IsoAnalytical Ltd, Crewe, UK). Isotopic values were corrected using at each run in-house standards calibrated with IAEA standards. Internal error (calculated on within-run replicate standards) is 0. 1‰ for CN and 0. 2‰ for S. The quality of collagen and the reliability of isotopic data were controlled according to international recommendations: C>30 %, N>10 %  (Ambrose 1993) , C/N between 2. 9 and 3. 6  (DeNiro 1985) , S between 0. 15 and 0. 35%, C/S between 300-900 and N/S between 100-300  (Nehlich and Richards 2009). Statistical analyses were performed using R 4. 0. 2 (R Core Team 2020) within Org mode  (Schulte et al. 2012 ). Percentile bootstrap with 9999 replicates was used to compute confidence intervals for differences in means or variances among groups  (Zieffler et al.
2011 ). These confidence intervals were computed at both the classical nominal level (95%) and an adjusted level provided by  Hesterberg (2014)  as a correction for small samples. Permutation tests were also used to derive empirical p-values in group comparisons. More theoretical details, along with additional results and all the R code written for this study is available as Supporting Information 5, and the R packages used are detailed in the Appendix. The present study's data are available online on Zenodo  (Rey et al. 2020).
2016; Goude et al. 2020a; Stuart-Macadam and Dettwyler 1995). Further information regarding the potential length of weaning can be obtained by analyzing first molars from the same individuals. A comparison with previous isotope data obtained in children's bones is proposed in Fig 4. A decrease in δ 15 N values with age is observed in the bones of children under 14 years old, especially for males (b). However, the bone samples of children recorded the signal of those who did not survive into adulthood. They may have had specific nutrition related to their health condition (e. g. ,  Beaumont et al. 2018; Goude et al. 2020a). The lowest values, in particular, may reflect a specific diet or some (patho-)physiological stress associated with a positive nitrogen balance  (Petzke and Fuller. 2012 ).
Acknowledgement The authors are very grateful to  Philippe Chambon ,  Aline Thomas ,  Mélie Le Roy ,  Mona Le Luyer  and  Maïté Rivollat  who provided information or material for this study. This paper has been reviewed by a language editing assistant,  Karina Gerdau  (https://karinagerdau. com/)and by  Pauline Cross  and  Alizé Lacoste-Jeanson  whom the authors thank. Funding: This work was supported by the  Institut Danone France/Fondation pour la Recherche Médicale  2015 partnership (Women and diet at the beginning of farming, 5th -3rd millennium BC, France: a bio-anthropological approach; Dir. G. Goude 2016-2017; http://institutdanone. org/nos-prix/femmes-alimentation-les-premieres-societes-agropastorales-veiiie-millenaires-av-j-c-france-approche-bio-anthropologique/)and funded by a ministerial grant from the  Research National Agency  as a program of prospects investments  ANR-10-LABX-52  (project ' Diversité biologique et culturelle de l'Homme de la fin de la Préhistoire à la Protohistoire '; dir:  S Rottier ;  Université de Bordeaux, LaScArBx-ANR ;  2012-14 ).
Ezer and Dangendorf (2021)  focused on the energy budget of the western boundary regions. Here, we analyse datasets of mean sea level along US and Japanese eastern coastlines, identify major spatial modes of variability, and interpret this in terms of ocean circulation variability. We explore the statistical links between the sea-level changes and the western boundary current extension variability. This paper is organized as follows. Section 2 presents the data used in this study and the derivation of indices for the WBC extensions. The results of the analysis of the gauge records and their relationship to upstream and downstream WBC variability are presented and discussed in Sects. 3 and 4. A conclusion is presented in Sect. 5.
Tide gauge selection, treatment and adjustment for surge variability Tide gauge data were obtained from the Permanent Service for Mean Sea Level  (Holgate et al. , 2013 , PSMSL, 2020 , https://www. psmsl. org/, last access: 18 October 2021) on 17 August 2020. We selected tide gauge stations along the western boundary of the North Atlantic, on the coast of the United States and Canada, and along the western boundary of the North Pacific on the coast of Japan. To retain only measurements of sufficient quality, length and completeness, historical series with more than 10 % of missing monthly values as well as those flagged for quality issues are excluded. Consequently, the number of individual tide gauge records available is dependent on the chosen period. A summary of gauge details is given in Tables  S1  and S2  in the Supplement.
For the Atlantic, the period considered is January 1948-December 2019 due to the availability of the atmospheric reanalysis used to correct for surge effects. The island station on Key West is located onshore of the Gulf Stream and features a signal coherent with the Florida tide gauges. It is therefore included, leaving a total of 22 stations on the American east coast. The Japanese tide gauge network is more recent; therefore, the period considered for the Pacific is January 1968-December 2019. The records of most stations on the eastern coast of Honshū feature important offset shift and/or drift after the March 2011 tsunami and cannot be used as such, leaving a ∼ 700 km coastline strip depleted of any measurement. To remedy the issue, we retained the three long records of Onahama, Miyako II and Ayukawa and replaced existing or missing data after February 2011 with the closest SSH measurement with trend and offset adjustment.
Additional datasets Gridded monthly sea surface height (SSH), temperature (SST) and velocities (SSVs) derived from satellite altimetry are available from 1993 and were obtained from the Copernicus Marine Environment Monitoring Service (CMEMS) website (https://marine. copernicus. eu, last access: 18 October 2021). They are obtained from the ARMOR3D product  (Guinehut et al. , 2012; Mulet et al. , 2012). The three datasets have a regular grid of 0. 25 • × 0. 25 •. To examine the variability of the Gulf Stream extension and the Kuroshio extension, the EN4 quality-controlled subsurface (200 m depth) ocean temperature profiles  (Good et al. , 2013, EN4. Finally, we retrieved additional indices that infer oceanic and atmospheric variability. We make use of the GSNW index from  Joyce et al. (2000)  and of the Kuroshio Extension indices from  Qiu et al.