dataesr/scientific-paragraphs-categorization huggingface dataset:
The role of the International GODAE Steering Team GODAE started thanks to the leadership and initial vision of Neville Smith and Michel Lefebvre. The role of the International GODAE Steering Team has then been central. It was formed in 1997 and took the responsibility for the development of GODAE under the responsibility of Neville Smith. From 2005 to 2008, I co-chaired the IGST together with Mike Bell. Many scientists have served as members and contributed greatly to the success of GODAE. There was an excellent "spirit" and willingness to share data and products, expertise and experience (GODAE common). The team was supported by the GODAE Patrons (sponsors) and an active project office. Several symposia and summer schools were organized. At the end of GODAE in 2008 after the GODAE final symposium in Nice, it was decided to move towards a long-term program: GODAE OceanView which is now led by a new Science Team co-chaired by Andreas Schiller and Eric Dombrowsky.
The altimetry community now has a much better understanding and recognition of the value of multiple altimeters. Operational oceanography now uses high to very high-resolution models with data assimilation. This poses much stronger requirements for an altimeter constellation. Today, we are almost facing similar challenges as 20 yr ago and the altimeter constellation is not significantly improved. Observation capabilities lag behind. It is critical to ensure a long-term optimized high-resolution operational altimeter system for the next decade. Success of the development of GMES/Copernicus in Europe with the advent of Sentinel-3 missions and the development of the Jason-CS series (continuation of the Jason-1-2-3 series) is thus essential. We also need to maintain our collective expertise and efforts on instrument development, quality monitoring, intercalibration and the development of high-level products.
The future SWOT mission should allow us to address the observational component. Other components must be developed in parallel: the development of very high-resolution modelling (1 km at the global scale) and new theoretical frameworks for a better understanding of submesoscale dynamics, vertical motions and their role for the coupling between physics and biology. It is also critical to prepare the main evolutions of Argo for the next decade: biogeochemical observations, deeper measurements, under-ice operations in the polar seas and sampling of marginal seas. All of these evolutions are essential to improve our knowledge of the role of the ocean on climate. They are also required for operational oceanography. Operational oceanography finally needs to move its focus from physics to ecosystems (further integration) and from large scale to coastal scale both for observations, modelling, data assimilation and services.
Acknowledgements. I feel very much honored to receive the prestigious Nansen medal. I consider it as recognition for a truly collective work, in particular, of the satellite altimetry community. Thanks to many outstanding colleagues and friends at  CLS ,  CNES, Ifremer ,  Mercator Ocean  and in the T/P and  OST, Argo  and  GODAE international science teams. A particular thanks to the entire  CLS Space Oceanography Division  where I truly enjoyed 20 yr of mutual adventure. Edited by:  N. Wells.
For example,  Pommier et al. (2012)  used such data to validate IASI O 3 at high latitudes. The Airborne Extensive Regional Observation over Siberia (YAK-AEROSIB) campaigns provide threedimensional 'snapshots' of the Siberian tropospheric composition in spring and summer (review in  Paris et al. , 2010a). Six such campaigns have been performed between April 2006 and April 2010: four in summer and two in spring. In this paper, which describes for the first time the data collected in the 2010 campaign, we investigate O 3 and other trace gases (CO 2 , CO and CH 4 ) in the troposphere over Siberia as measured in situ during several instrumented aircraft flights in April 2010. Through case studies, we focus on the respective contributions of various terms of the regional O 3 budget, such as STE, long-range transport, or O 3 atmospheric photochemistry.
Instruments used and data processing During the flights, concentrations of O 3 , CO 2 , CO, CH 4 and meteorological (wind speed, temperature, pressure, humidity) data are collected with in situ continuous analysers. The measurement equipment used for the YAK-AEROSIB campaigns is described in  Paris et al. (2010a; consult Fig. 3  and Table  A1  in the cited reference). Technical details of the instrumentation are summarised in Table  2. The O 3 analyser is based on a commercial instrument (UV absorption; Thermo Instruments Model 49) modified to match aircraft requirements (pressure, temperature, vibrations). The instrument is calibrated in laboratory before and after the campaign with an O 3 generator. The instrument uncertainties are 2 ppb (2%) for an integration time of 4 seconds. For the 2010 campaign, a CH 4 analyser was added to the instrumental package by the Institute of Atmospheric Optics of Tomsk.
58 )0. 58 and 26 vertical levels and the European Centre for Medium-Range Weather Forecasts' (ECMWF) model with a resolution of 18 )18 and 91 vertical levels. All the figures were plotted using the ECMWF products. The FLEXPART model output (reported as ns. kg (1 ) is proportional to the residence time of the particles in a given volume of air and corresponds to potential emission sensitivity (PES). When convolved with the gridded emission fluxes from an emission inventory, maps of potential source contributions (PSC) are obtained. Integrating these maps over the globe yields a model-calculated mixing ratio of the emitted species at the location of the aircraft. EDGAR fast track 2000v3. 2 (Emission Database for Global Atmospheric Research from PBL Netherlands Environmental Assessment Agency) was used for anthropogenic CO emissions other than biomass burning.
esrl. noaa. gov/psd/data/reanalysis/), such high O 3 concentrations suggest that stratospheric air must have been mixed into the troposphere earlier, or that a tropopause fold was occurring simultaneously to the flight. The sampling of 'fresh' stratospheric air is confirmed by in-situ measured meteorological parameters: the wet bulb potential temperature was 300 K, about 20 K lower than the tropopause mean at this latitude (but almost 5 K higher than measured ambient air at 7000 m in the area), suggesting a quasi-adiabatic intrusion (2000Á3000 m des-cent stretching over about 150 km) of stratospheric air, from the tropopause to mid/upper troposphere. Over the area where the O 3 excess was measured (spanning roughly 58 by 58), meteorological datasets (mainly ECMWF potential vorticity fields) suggest a frequency of 20Á50 tropopause fold events per year  (Beekmann et al.
, 1997). During frontal episodes, the dry intrusion air stream associated with extra-tropical cyclones generates a positive potential vorticity anomaly associated with the downward flux of stratospheric air. Under these particular circumstances, isentropic transport from stratosphere to troposphere can occur and the tropopause can drop to 320 K (i. e. 300Á400 hPa or 6Á8 km) for latitudes between 40 and 908N  (Holton et al. , 1995). During Flight 4, the occurrence of a stratospheric intrusion was confirmed by different independent data sets: in situ measured meteorological parameters, satellite imagery and ECMWF analysis fields. The intrusion is associated to a cut-off cyclone (about 150 km wide in its core, with an arm spanning over about 700 km; centred where we observe stratospheric air) with high wind speeds ( !30 m.
Acknowledgements We thank the scientific and flight crew for their expertise and for carrying out successfully the campaigns since 2006. The measurement campaigns were funded under the project  LIA YAK-AEROSIB  by the  ANR Blanc POLAR-CAT, CLIMSLIP-LEFE, CNRS , the  French Ministry of Foreign Affairs, CEA  (in France), and  RAS  and  RFBR  (in Russia). A. Stohl was supported by the  Norwegian Research Council  in the framework of the  CLIMSLIP  project. Funding support from the  French ANR Blanc SIMI   5Á6 021 01  Climate Impact of Short-lived Pollutants and  Methane in the Arctic (CLIMSLIP)  is acknowledged.
Acknowledgments This work was performed in the framework of the transverse axis DEBAT ( DEgradation Biotique et AbioTique de  la matiè re organique en milieu marin: processus et interactions) of the MIO and funded by research grants from the  PHOTOMED  ( MERMEX WP4 ) and TRANSPHYTOBAC ( EC2CO-Microbien ) research projects. This study is a contribution to the international IMBER and SOLAS projects. We wish to thank  Nicole Garcia  for the analysis of chlorophyll a. The PhD scholarship was provided by  Aix Marseille University  ( EDSV 251 ) and the  Ministry of Research and Technology. The authors acknowledge the anonymous reviewers and editor for constructive comments on the manuscript.
If no epitope candidate had been tested positively by mutations to alanine, a second series of candidates would have been defined. For this, the mean exposure of residues constituting LF N (29%) would have been utilized as the solvent exposure threshold, in addition to the similarity threshold. These two thresholds, each defined as a mean value characterizing the antigens, would have identified five additional regions as epitope candidates, constituted of a total of 25 residues, and these regions would have been tested similarly than the first series. Our first attempt to map the scFv 2LF epitope utilized five synthetic peptides corresponding to the candidates selected by the in silico analysis. Their reactivity with 2LF was tested by ELISA. The peptide corresponding to LF(97-103) was the only peptide that bound to the 2LF antibody, but it did not compete with LF for scFv 2LF binding (data not shown).
Affinity measurements Affinity constants (K D ) and dissociation constants (k d ) of scFv 2LF for LF, EF and their variants were measured by surface plasmon resonance (SPR) with a Biacore X (Biacore, Uppsala, Sweden) instrument. ScFv 2LF was immobilized at a maximum of 250 resonance units on a CM5 chip (Biacore) via amine coupling. A flow rate of 30 ml/min was maintained during measurements. A minimum of seven dilutions of LF, EF and their variants (220 to 14 nM) in HBS-EP buffer (Biacore) was tested for 1500 s. After each dilution, the chip was regenerated with glycine 1. 5 buffer (Biacore), run at 10 ml/min for 30 s. Results were analyzed with the Biaevaluation software (a 1:1 (Langmuir) binding model for K D measurements, and a 1:1 (Langmuir) dissociation model for k d. Biacore experiment to evaluate the reactivity between anti-LF polyclonal antibodies and the two LF variants, in which LF(178-184) or LF (231-236) had been shaved in alanine.
In vivo neutralization test ScFv 2LF was reformatted as a full-sized IgG, IgG 2LF, by expression of its variable regions in fusion with human constant regions (Fc) of c1 and k isotypes. Human constant regions were preferred to their murine counterparts because the IgG has therapeutic potential, and a human Fc ensures better tolerance. The in vivo neutralization test was adapted from a previous study  [35]. The edema toxin (ET) was obtained by mixing equal weights of PA and EF. Twentymg of ET, premixed with 0, 2, 5 or 10 mg of IgG 2LF in a final volume of 25 ml in PBS, or 25 ml of PBS alone as a control, were injected into the right rear footpad of five Balb/c mice. The sizes (dorsal/plantar) of the footpads were measured in triplicate, with digital vernier caliper. Identification of epitope candidates by combined identity and solvent exposure analysis LF and EF sequences were retrieved under the access numbers P15917 and P40136, respectively.
The ends of LF N and EF N were defined in accordance with sequence annotations (LF N begins at residue E27 and EF N begins at residue N64) and the two sequences were aligned with the CLUSTALW tool at the PBIL server (http://pbil. univ-lyon1. fr), using standard parameters (figure  4 ). For each position in LF N , a score of 1 or 0 was attributed when the EF N counterpart residue was identical or different, respectively. When alignment gaps occurred, a score of 0 was attributed to the LF residues having no counterparts in EF. A curve averaging the identity percentage over a window of five residues was calculated to visualize the portions shared between EF N and LF N , as a length of five residues was considered as corresponding to the length of epitopes  [36]. X-ray crystallographic structures for LF (1J7N)  [4]  and EF (1XFV)  [37]  were retrieved from the Protein Data Bank (www.
To account for this effect, air measurements were processed only after a time delay of 13 minutes. This time period was found appropriate for this particular PICARRO device during its installation and calibration. These frequent calibrations allow to assess the stability of the measurements. Starting from June 2012, instabilities were identified during calibrations, due to leakage in one of the SDM syringes. This may lead to two biases: (i) fractionation in the syringe itself by exchange with ambient air, and (ii) introduction of air bubbles into the SDM and instabilities of injected flux and resulting measurements. The calibration module was subsequently replaced using a new type of glass syringe in September 2012, leading so far to very stable calibrations. The quality of the post-processed data strongly depends on the stability of the calibrations.
7/ln(q v ) for YEKA standard, were q v stands for humidity (ppmv). And secondly, humidity corrected measurements of reference standards were linearly interpolated to the time of the air measurement. A linear regression between the standards measured values 245 against theoretical values of these standards were calculated and then applied to ambient air measurements. The validity of calibrations is estimated based on the evaluation of the stability of the instrument. Although this methodology worked mostly correctly, 250 sometimes the PICARRO SDM experienced breakdowns and data acquisition stopped. In this case, the PICARRO switches automatically back to air measurements and data are stored in its logging protocols. In order to fulfill missing SDM data, this logging protocol was also reprocessed and 255 missing data were pulled out.
The same processing methodology was applied afterwards. Finally, we use both hourly and daily average values to present this data set and compare it with ECHAM5-wiso model results. For the period from 1 April to 30 Septem-260 ber 2012 over which we will compare data and model results, 2476 hourly PICARRO measurements were produced which corresponds to 67% of the total duration (3671 hours). As both FTIR (section 4) and GOSAT (section 5) data are specifically used to get information about δD v in the water 265 column, we will hereafter focus on this parameter both for the discussion of the dataset and its comparison with model results The currently available δD v dataset extends to November 21. We have, in Figure  2 , displayed both hourly individual 270 measurements and a smooth curve (5 point running mean) limited to periods over which there are at least 6 hourly measurements successively.
The amount of water vapour (as measured by the PICARRO instrument) has been reported on the same figure along with surface temperature using ei-275 ther measurements at the site available since 1 April or ERAinterim reanalysis data for the entire period (as used for the simulation). As expected, the deuterium time series shows a clear seasonal cycle with it lowest values in spring (minimum -232‰ 280 on April 5) and in fall (minimum -246‰ on November 18) and highest levels during summer (-103‰ reached on July 14 and August 11). While the highest monthly mean values are observed in June-August, the highest single hourly value is recorded to occur in spring(-92‰ on May 10th). In-4 K. Gribanov et al. : ECHAM5-wiso water vapour isotopologues simulation and its comparison with retrievals deed, large, and for some of them, rapid δD v variations are superimposed on this seasonal cycle which will be fully described when winter data will be available.
Surface δD v : model data comparison The ECHAM5-wiso results are first compared to the observed hourly water vapour PICARRO data q v (Fig. 2 , panel c, red lines). The model correctly captures the patterns and magnitude of variability, with a very large correlation coefficient (r = 0. 89). Absolute values of water vapour measured with the PICARRO instrument are up to 20% higher than the related model values. This might be explained by the fact, that the ECHAM5-wiso values represent the mean of the lowest atmospheric model level (surface to approx. 60m) while the PICARRO measurements were carried out at a height of 7 m. Simulated δD v values are often 30-40‰ less depleted than the corresponding PICARRO data. This suggests a lack of depletion either along air mass trajectories or due to boundary layer mixing.
Description of the data and comparison tehnique Ground-Based Fourier-Transform Intrared (FTIR) spectrometers are widely used for remote measurements of the atmospheric composition  (Notholt and Scherms, 1994; Wunch et al. , 2010 Wunch et al. , , 2011;; Hannigan et al. , 2009). Data from the Ural Atmospheric Fourier Station (UAFS) in Kourovka astronomical observatory (57. 048N, 59. 545W, 270 m altitude, 80 km to the West from Yekaterinburg city) were used for comparison with ECHAM5-wiso output. UAFS provides highresolution ground-based observations of atmospheric transmittance in the spectral region of 4000-11000 cm -1. At TC-CON sites, operating instruments are Bruker IFS-120HR and 615 IFS-125HR  (Wunch et al. , 2010 (Wunch et al. , , 2011) )  which provide accurate and precise retrieval of column-averaged atmospheric concentrations of such gases as CO 2 , CH 4 , H 2 O, HDO, etc.
UAFS is equipped with Bruker IFS-125M mobile spectrometer (aligned by TCCON members in July 2012). At present, TCCON does not accept mobile versions of IFS-125 instruments but some studies show that they are able to achieve the required accuracy and precision ( < 0. 20% for XCO 2 , and < 0. 16% for XCH 4 )  (Petri, 2012). Values of δD v were derived from total column abundances 625 of HDO and H 2 O retrieved from the measurements from July to August 2012 in Kourovka. For data processing, the standard TCCON software GFIT was used  (Wunch et al. , 2010 (Wunch et al. , , 2011)). GFIT retrieves the total number of molecules in the vertical atmospheric column, using the algorithm of profile scaling retrieval with the assumption that the shape of the profile of the retrieved gas is well known. H 2 O, temperature and pressure a-priori profiles are based on reanalysis data provided by National Centers for Environmental Prediction and the National Center for Atmospheric Research.
635 (NCEP/NCAR)  (Kalnay et al. , 1996). The HDO a-priori profile is calculated from H 2 O profile as follows  (Wunch et al. , 2011) : x apr HDO = 0. 16x apr H2O (8. 0 + log 10 (x apr H2O )) where x apr HDO is the a-priori HDO volume mixing ratio (vmr) profile, and x apr H2O is the a-priori H 2 O vmr profile. Ex- 640 amples for H 2 O and corresponding δD v a-priori profiles for each day of July 2012 are shown in Fig. 7. Microwindows containing saturated H 2 O lines were excluded from final results to achieve more robust retrieval. As data base of spectral parameters, the revised water line list was used  (Shillings et al. , 2011). Since the model provides hourly-averaged output data, data retrieved from FTIR measurements taken within 1 hour were also averaged. For the comparison between model and FTIR observations we assume that the modeled HDO and 650 H 2 O profiles are true, and we simulate the measurement of the instrument by applying the following equation to the model result  (Rodgers and Connor, 2003; Risi et al.
GOSAT Sensor TANSO-FTS on board GOSAT satellite provides spectral measurements in thermal infrared (band 4, 650-710 2006 cm -1 ) which were used for this study. The retrieval method is based on technique of optimal estimation described by  Rodgers (2000). The initial guess vertical profiles for temperature and humidity were taken from NCEP Reanalysis data provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA from their web site at http://www. esrl. noaa. gov/psd/. Initial guess vertical profile of HDO was taken from  Rozanski and Sonntag (1982) ). TIGR 2000 database  (Chevallier et al. , 2000)  was used for temperature covariance matrix calculation. Model covariance matrices were generated for H 2 O and HDO vertical profiles joint retrieval. Only cloudless measurements of GOSAT were selected.
(4) Here (for the last stage of retrieval algorithm), x k is the vector combined of vertical profiles of H 2 O and HDO, x 0 is the initial guess, y is the measured spectrum, y k is the simulated spectrum at k-th iteration, I is identity matrix, A k is the Jacobian of forward radiative transfer model, S ε is the measurement error covariance matrix, and S a is the a-priori covariance matrix. Vertical profiles were represented on altitude mesh of 34 altitude levels from the surface to 65 km. The a-priori covariance matrix S a can be grouped into sub blocks as S a = S H2O 0 0 S HDO (5) In this study, off-diagonal blocks were filled with zeros. Because of absence of a sufficiently representative dataset of 750 directly measured vertical profiles of HDO, each diagonal sub block of the a-priori covariance matrix S a is modeled using the following formula: S ij = a 1 q i q j exp - |h i -h j | h 1 , (6) where q i and q j are concentrations at altitudes h i and h j respectively, a 1 and h 1 are parameters adjusted separately for 755 H 2 O and HDO.
Total column amounts of H 2 O and HDO (in moles per square meter) were used to calculate the column ratio of δD v. The averaging kernel of joint H 2 O and HDO retrieval is shown in Fig. 10. This figure demonstrates that the retrieval 760 method is not sensitive to H 2 O and HDO concentrations at surface. A modified version of the FIRE-ARMS software package  (Gribanov et al. , 2001)  was used for all retrievals. The 4-step retrieval scheme described above was applied to all summer spectra of 2012 selected by criteria of cloudless 765 and the proximity to Kourovka site. Fig. 11  shows daily means of PICARRO measurements in Kourovka and GOSAT measurements within 250 km range around. All adjustable parameters in the model covariance matrices were selected to reach the best correlation between direct PICARRO mea-770 surements in Kourovka and retrievals from GOSAT spectra measured in proximity to Kourovka.
Whole Genome Sequencing The Insectomime genome was sequenced on a 454 Roche GS20 instrument, as previously described  [8]. The reads obtained were assembled de novo with Newbler Assembly software  [29]. Protein encoding genes were predicted using the Gene-markS tool  [30]. Orthologous genes were searched for using the Proteinortho program [31] and were considered as the best reciprocal hits using a threshold of an e value <1e-3, an amino acid identity of >30% and a coverage of >70% on both the query and target sequences. To detect all the orthologs shared with other  marseilleviruses (Marseillevirus  [8]  , Lausannevirus  [32]  and Tunisvirus fontaine 2  [6]  ), we performed a non-reciprocal BLASTp search  [33, 34]  , using the thresholds 1e-4 for the e value and at least 25% for both the query and target coverage.
Phylogeny Reconstruction To construct a phylogenetic tree, proteic sequences were aligned using MUSCLE software  [36]  , the informational positions were selected using Gblocks  [37]  and the maximum likelihood phylogeny was performed using MEGA5 software  [38]. The phylogeny reconstruction, involving the marseilleviruses and A. polyphaga mimivirus as an outgroup, was performed after a concatenation of the selected blocks of the D6-D11 helicase, the major capsid protein, and the DNA polymerase B sequences.