dataesr/scientific-paragraphs-categorization huggingface dataset:
The whole database of VEx/VIRTIS-H comprised a total of 200, 036 spectra after selecting values of SZA and EA lower than 80 • (the signal-to-noise for higher values of SZA and EA is found to be too low). Despite this restriction, low-quality retrievals were frequently obtained, hence, additional quality criteria were applied. We discarded retrievals where: (a) no clear single minimum was present in the χ 2 function; or (b) this minimum was placed at the maximum/minimum temperature perturbation (in our case at ±60 K); or (c) the inversion was possibly outside the linear regime, i. e. the absolute value of the difference between the temperatures for best fit and first fit was higher than the step of 10 K used for temperature perturbations (i. e. |T BF -T FF | > 10 K) or this difference was more than twice the error bars for the best fit.
3 µm band. To evaluate the impact that this uncertainty has on the temperature retrieval, two different profiles were used when generating the database of pre-computed spectra. One of these is the VTS3 daytime profile  (Hedin et al. 1983) , possibly more appropriate for near-subsolar soundings, and the second one is a colder and isothermal profile, presumably closer to higher SZA and near-terminator conditions. Both profiles were disturbed in a similar way, with 10 K steps within the pressure range of interest, 10 -2 -10 -5 mb. Figure  4  shows these reference atmospheres in isobaric coordinates (left-hand panel). Nevertheless, a word of caution is needed for comparisons with other results. Our retrieval scheme is well defined in a pressure scale but the actual altitudes may change depending on the actual thermal structure.
Results and discussion After applying specific criteria to discard lower quality retrievals (see Sect. 3), we obtained a total of 133 015 dayside temperatures covering more than five years of data (from 2006/05/14 to 2011/06/05). These errors are typically between 5-10 K with a slight increase towards the terminator (see Sect. 3). Also, as explained previously, these temperatures were averaged onto a grid of latitude and local time with bins of 5 • in latitude and 0. 25 h in local time to maximize the spatial coverage and minimize errors. The number of spectra or temperatures in most of these boxes varies between 5 and 20, with a few boxes with more than 25 values. The magnitude of the standard deviation within each bin is about 15 K, interpreted to be caused by the atmospheric variability.
8  shows the variations of this model with latitude (panel A) and with local time (B) around the subsolar point. Their simulations were performed for solar cycle conditions representative of the VEx data set (near solar minimum). For a coherent comparison, data from the VTGCM were averaged for the interval 10 -2 -10 -5 mb with our Jacobian functions (see Fig. 3 ) as well as interpolated onto the same grid of latitude and local time as VIRTIS-H. Figures  7  and 8  clearly exhibit a colder atmosphere than in the VTGCM, with temperatures reaching differences of 20-25 K near the subsolar point that were smaller away from this point and increasing up to 30 K at the near terminator, although our data and retrievals here are noisier. The standard deviation in the VTGCM bins is maximum at the subsolar point, about 25 K, and smaller, about 15 K, near the terminator.
Finally, we examined long-term and short-term variations in the UMLT region. The time variation of the mean temperature for latitudes 30 • S-30 • N of the subsolar region (10 h-14 h) and evening (14h-16h) is shown along years (Fig. 8D ) and days   Brecht & Bougher (2012)  and averaged for the pressure interval 10 -2 -10 -5 mb; C) difference between temperatures from the VTGCM and VIRTIS-H; D) nightside temperatures inferred with stellar radio-occultation data from VEx/SPICAV  (Piccialli et al. 2015)  and averaged for the pressure interval 10 -2 -10 -5 mb. (Figs. 8E). In the case of the long-term behaviour, temperatures have been also averaged along series of consecutive days covering no more than 40 days, depending on the availability of data. For the short-term behaviour, we only display daily averages.
Conclusions In this paper, we have measured for the first time the horizontal distribution of the dayside temperatures in the UMLT of Venus at the pressure interval 10 -2 -10 -5 mb. A total of 133 015 dayside temperatures covering more than five years of data have been obtained by means of an inversion procedure applied to the NLTE CO 2 dayglow nadir spectra at 4. 3 µm, as measured by the instrument VIRTIS-H on board VEx. Our dayside temperatures peak is about 195 K in a broad region around the subsolar point, extending to the latitude interval 20 • S-20 • N and to local times 10 h-15 h. This is in contrast to VTGCM results, which peak precisely at the subsolar point and reach 215 K. When there is coincidence, our results are in good agreement with the few previous ground-based and remote sensing measurements available at these altitudes.
Acknowledgements. J. P. and MA. L-V acknowledge the  Spanish MICINN  for funding support through the  CONSOLIDER program  "ASTROMOL"  CSD2009-00038  and project  AYA2011-23552. J. P. also thanks the  JAXA International Top Young Fellowship program , GG thanks CNES postdoc contract and A. P. acknowledges funding from the  European Union Seventh Framework Programme  ( FP7/2007-2013 ) under Grant agreement No. 246556. We also thank  J. L. Bertaux  and  F. Montmessin  for their support with VEx/SPICAV.
Chloride database The quantity supplied and the quality of the main groundwater resources in the Armorican Massif are monitored through a public well network (ADES: banque nationale d'Accès aux Données sur les Eaux Souterraines, national database for groundwater resources, http://www. ades. eaufrance. fr/). For most of these wells, hydrogeological information (geographical location, altitude, depth, drilling log, borehole parameters, water inflow points, etc. ) is available through a second public database of drillings (BSS: Base de données du Sous-Sol, http://infoterre. brgm. fr/). The precise location of water inflows is not described for each well, and it has been considered that the water inflow corresponds to the base of the well. This assumption is valid, taking into account the drilling goal, which is to stop the well drilling when sufficient water inflow is found.
The network of wells investigated covers the whole Armorican basement and includes more than 1800 drillings with an average depth of approximately 40 m. Chemical records, such as chloride or nitrate concentrations, are available for each drilling. We first preprocessed the database of 1874 chloride measurements and removed wells that are potentially not representative of natural chloride concentrations. We removed wells close to a potential anthropic pollution source (industrial estate, garbage dump, mill pond, etc. ), and wells with a large variability through time (large standard deviation of chloride concentration higher than 30 %). We also did not consider the wells at a distance of less than 1 km from the current coastline, whose concentration may be directly influenced by current saltwater intrusion.
It is the CO 2 -driven changes in these variables that drive the biological impacts from ocean acidification  (Gattuso and Hansson, 2011; Kroeker et al. , 2013; Wittmann and Pörtner, 2013)  and degrade most the ocean's capacity to absorb CO 2  (Sarmiento et al. , 1995; Orr, 2011). These equilibrium computations are made with numerous software packages, either those developed and used by individual scientists or, more commonly, those that have been made available publicly. The latter have become indispensable for many ocean scientists, whether they study marine chemistry or impacts of ocean acidification on marine biota. Yet how packages differ is seldom addressed. Lewis and Wallace (1998)  documented differences in basic variables among three existing packages at a time when no such package Published by Copernicus Publications on behalf of the European Geosciences Union.
, 2007; Dickson, 2010) , that differences among currently available packages are less than what was found 17 years ago. But even that poor level of agreement has not been established. A quantitative understanding of the accuracy and precision of these packages is needed to rigorously compare studies that aim to assess, e. g. , air-sea CO 2 fluxes and thresholds associated with ocean acidification. Ten publicly available software packages were included in this comparison. The first was CO2SYS, but that now exists in four different variants: the original program written in QBasic and running on DOS  (Lewis and Wallace, 1998) , two variants as Excel spreadsheets  (Pierrot et al. , 2006; Pelletier et al. , 2007) , and most recently a variant as MATLAB scripts  (van Heuven et al. , 2011). We will refer to these packages as CO2SYS-QBasic, CO2SYS-Excel-Pierrot, CO2SYS-Excel-Pelletier, and CO2SYS-MATLAB.
Another package, csys, was also written in MATLAB, but it was released a decade earlier as a supplement to the book by  Zeebe and Wolf-Gladrow (2001). The development of csys inspired seacarb, an R library (R Development Core Team, 2012) released 2 years later  (Proye and Gattuso, 2003)  and frequently improved with new revisions  (Gattuso et al. , 2015). About the same time as the release of the two Excel variants of CO2SYS, the swco2 package was also released with a similar spreadsheet interface but a distinct library of core routines written in Visual Basic  (Hunter, 2007). Three years later, oceanographers saw the release of two new carbonate chemistry packages, CO2calc and ODV, both of which also exploit the core CO2SYS code. While CO2calc provided a new tool for Mac, PC, and iOS  (Robbins et al.
, 2010) , ODV provided carbonate chemistry calculations as an add-on to an already widely used visualization and analysis tool  (Schlitzer, 2002). Parallel to those developments for the observational and experimental communities, the Ocean Carbon-Cycle Model Intercomparison Project (OCMIP) provided routines to compute surface pCO 2 and air-sea CO 2 fluxes from simulated A T and C T  (Orr et al. , 1999). Those were adapted to include the full suite of other carbonate system variables  (Orr et al. , 2005) , then later improved and released publicly as the mocsy package  (Orr and Epitalon, 2015). To assess the consistency of these packages, we compared results generated by running them with common sets of constants, pH scales, and input data. Two other public packages, AquaEnv  (Hofmann et al.
Some users may well prefer spreadsheet-based programs (CO2SYS-Excel-Pierrot, CO2SYS-Excel-Pelletier, CO2calc, and swco2). Others who use ODV for general oceanographic data analysis and visualization can easily compute carbonate system variables using its predefined derived-variable facility. Users with some programming experience may prefer packages that are available in languages that they are already familiar with. They can choose from CO2SYS-MATLAB and csys in MATLAB, seacarb in R, swco2 in Visual Basic, and mocsy in Fortran. Python programmers can use either mocsy or seacarb.
, 2007) , none are available for computed variables. Hence we chose CO2SYS as a relative reference for three reasons: (1) it was the first publicly available package; (2) its core routines already serve as the base code for two other packages (CO2calc and ODV); and (3) its documentation and code reveal the intense effort that its developers have put into ferreting out the right coefficients from the literature and the most appropriate version of formulations for the constants. Our choice of the reference had to be refined, however, because, as mentioned, CO2SYS comes in four variants: the original in QBasic running on DOS  (Lewis and Wallace, 1998) , two others that run with Excel  (Pelletier et al. , 2007; Pierrot et al. , 2006) , and finally MATLAB code  (van Heuven et al. , 2011). The original variant is still used by some, but it does not provide options to use formulations for K 1 and K 2 from  Lueker et al.
(2000) , as recommended for best practices  (Dickson et al. , 2007). Thus, we reduced our choices for the reference to the other three variants of CO2SYS (MATLAB and both Excel variants), all of which provide options to use all constants recommended for best practices (with one minor exception). All three versions give nearly identical results (Fig. 1 ). But they differ significantly from the original version run with the closest substitutes for Lueker et al. 's K 1 and K 2 , namely the previous refits by  Dickson and Millero (1987)  of the same measured constants from  Mehrbach et al. (1973) (DM87). With that older set of K 1 and K 2 , however, the original version produces results that match those from the Excel-Pierrot version when also run with DM87. Another requirement was efficiency, since one aspect of our comparison required use of a global-scale input data set with nearly 1 million records (Table  2 ).
Features The 10 packages compute results from the same thermodynamic equilibria, but software features differ, including available input pairs, pH scales, and constants. Package diversity covers all commonly used operating systems: all packages run on Windows, eight packages on Mac OSX, and five packages on Linux and Unix (Table  3 ). Source code is available in seven packages in standard programming languages (QBasic, Visual Basic, MATLAB, R, Fortran 95), thereby allowing code validation and improvements by users on all three operating systems mentioned above. The number of possible input pairs of carbonate system variables varies widely between packages, from 1 to 20 (Table  4 ). The mocsy package  The three most recent variants (MATLAB and both Excel versions) are run with constants recommended for best practices (BP).
The QBasic variant does not offer the same K 1 and K 2 , so we used an earlier refit by  Dickson and Millero (1987)  of the same data (DM87) and compared it to one Excel version also with DM87. treats only one input pair: A T -C T , the two carbonate system variables carried by models. The four CO2SYS variants and its two derivatives (CO2calc and ODV) allow the user to select from six commonly measured pairs (A T -C T , A T -pH, A T -pCO 2 , C T -pCO 2 , C T -pH, and pH-pCO 2 ); in addition, they allow equivalent pairs where f CO 2 replaces pCO 2. The csys package provides 10 more input pairs by allowing pair members to include one or more of the three inorganic carbon species CO * 2 , HCO - 3 , and CO 2- 3. Although the two former species can only be calculated, promising new techniques are being developed to measure the latter  (Byrne and Yao, 2008; Martz et al.
Nine packages compute saturation states for aragonite A and calcite C from the product of the concentrations of Ca 2+ and CO 2- 3 divided by the corresponding solubility product, either for aragonite K A or calcite K C  (Mucci, 1983) , respectively. Only the csys package does not provide output for A and C. To simplify comparison, most figures plot results as absolute differences: computed values are shown after subtracting off corresponding results from the reference.
Constants To better assess the most likely causes of differences in computed carbonate system variables, we also compared associated constants. For the four packages where source code was available and easily modified (CO2SYS-MATLAB, csys, seacarb, mocsy), we used existing routines or slightly modified versions to output all the constants for the same physical input data (T , S, and P ) that we used for computing variables. For CO2SYS-Excel-Pelletier, the constants are also available. For swco2, we retrieved its constants using its documented parameter numbers and its routine to extract anything with a parameter number. For packages where source code was not available, we computed constants from output variables when possible. With output from CO2calc and CO2SYS-Excel-Pierrot, we computed its K 0 , K 1 , K 2 , K B , K W , K A , and K C ; from ODV output, we computed its K 0 , K 1 , K 2 , K A , and K C.
Pressure corrections Until recently, no public package accounted for pressure effects on K 0 (needed to convert CO * 2 to f CO 2 ) and the corresponding fugacity coefficient C f (needed to convert f CO 2 to pCO 2 ) as originally proposed  (Weiss, 1974, Eqs. 5 and 9). Instead, the total pressure term in those equations was simply assigned to be that of the atmosphere only (1 atm). Hence, their computed subsurface f CO 2 and pCO 2 may be considered as being referenced to the surface. These pressure effects are accounted for, however, in the latest versions of two packages, mocsy 2. 0 and seacarb 3. 0. 6. Both allow users to compute f CO 2 and pCO 2 in three ways: (1) the same "com-mon" approach that computes K 0 and C f with total pressure of 1 atm and in situ T , (2) the "potential" approach that likewise uses atmospheric pressure only but also uses potential temperature θ instead of in situ T , and (3) the "in situ" approach that uses the true total pressure (atmospheric + hydrostatic) and in situ T.
at 5000 m, where csys is 0. 001 larger than other packages, which agree within 0. 0003; for the Revelle factor R f , packages agree within 0. 02 throughout the water column except for seacarb, whose discrepancy grows to 0. 2 at 5000 m. Although seacarb computes R f with an efficient analytical formula  (Frankignoulle, 1994) , that approach neglects effects of P T and Si T on total alkalinity, unlike the less efficient numerical approach used in other packages  (Orr and Epitalon, 2015). Overall, discrepancies among packages are larger at depth, but they remain negligible (Table  8 ) except for pH and pCO 2. Yet agreement was not always so close. For some perspective, the same CO2SYS-MATLAB reference was also compared to older versions of four packages: CO2calc (version 1. 0. 4 revised on 18 June 2013), csys (version revised on 3 February 2010), seacarb (version 2.
007 in pH. Those discrepancies are associated with coding errors in the K 1 and K 2 formulations from  Lueker et al. (2000) , errors that were corrected in CO2calc version 1. 2. 0. With the previous version of csys, surface pCO 2 is about 1 µatm lower than the reference because that variable was mislabeled; it was actually f CO 2. As for seacarb v2. 3. 3, there are no significant discrepancies. However, with an even earlier version of seacarb (v2. 0. 3 released in 2008, not shown), the only package that maintains public access to all previous versions, discrepancies at depth are much larger (e. g. , -7 µmol kg -1 in CO 2- 3 and -0. 165 in pH at 4000 m). Because earlier versions of packages often have much larger discrepancies, users would be wise to keep their carbonate system software up to date.
Previous analysis has illustrated how discrepancies vary spatially across the global ocean, but the realistic gridded input data sets that were exploited did not allow us to isolate how discrepancies vary with individual physical variables and chemical input options. We will now focus on those factors, individually, by exploiting simple artificial input data. (Locarnini et al. , 2010; Antonov et al. , 2010; Garcia et al. , 2010). Curves are shown for each package and variable after subtracting off corresponding results for the CO2SYS-MATLAB reference. The csys package does not provide results for A and the Revelle factor. It also neglects nutrient alkalinity, but its curves were adjusted to include the effects of P T and Si T as computed by mocsy. Figure  3. Global-mean vertical profiles of variables computed from the same gridded data products as in Fig.
2. For each software package, corresponding results from the reference (CO2SYS-MATLAB) have been subtracted. The csys curves are adjusted as in Fig. 2. In all comparisons, the csys results are computed with the option ocdflag = 1; its discrepancies would be larger with ocdflag = 0. b Following  Weiss (1974) , f CO 2 = CO * 2 / K 0 exp (1 -P ) vCO 2 /RT , The exponential term vanishes when P is set to 1 atm (common and potential approaches) but is intended to represent total pressure (in situ approach). The potential approach uses θ in place of in situ T (common and in situ approaches) in the above equation and in the calculation of K 0. a Area-weighted global means from same gridded input data as in Table  9. b Following  Weiss (1974) , pCO 2 = f CO 2 /C f , where C f = exp B + 2 x 2 2 δ 12 P /RT and P is the total pressure (atmospheric + hydrostatic) as adopted for the in situ approach; the other two approaches assume that P is only atmospheric pressure.
2 and 3). One package, swco2, does indeed exhibit substantial discrepancies with deep water at 13 • C but only negligible discrepancies at 2 • C. At 5000 db, its discrepancies at 13   3  and 2. The four older versions include CO2calc (v1. 0. 4), csys (from 3 February 2010), seacarb (v2. 3. 3), and mocsy (non public predecessor from  Orr et al. , 2005). As before, results are shown after subtracting off corresponding results from the same CO2SYS-MATLAB reference.
Nutrients Both P T and Si T contribute to the total alkalinity. Thus they affect computed carbonate alkalinity A C when their concentrations are significant and one member of the input pair is A T. One of the packages, csys, neglects this nutrient alkalinity, assuming P T and Si T concentrations are always zero. All other packages account for nutrient alkalinity. Two of those exhibit discrepancies relative to CO2SYS-MATLAB that become significant as nutrient concentrations are increased to the maxima observed in the ocean (Fig. 10 ). Discrepancies for swco2 grow linearly with nutrient concentrations, reaching -0. 2 µatm in pCO 2 , +0. 07 µmol kg -1 in CO 2- 3 , and +0. 0002 units in pH. These discrepancies are largely associated with Si T ; those from P T are more than 10 times smaller. For CO2calc, discrepancies in pH seem to reach up to nearly 0.
Total boron Relative to the standard formulation for total boron (Uppström, 1974), the new formulation  (Lee et al. , 2010)  represents about a 3% increase of borate alkalinity throughout the ocean. Hence we first assessed whether or not packages gave consistent responses when changing from the standard to the new formulation. For the six packages that allow for the new formulation (CO2SYS-MATLAB, both CO2SYS-Excel variants, CO2calc, mocsy, and seacarb), computed changes agree within 0. 15 µatm for pCO 2 , 0. 02 µmol kg -1 for CO 2- 3 , and 0. 00006 for pH, i. e. , with the A T -C T pair across observed ranges of T , S, and P (Fig. 11 ). With other input pairs, agreement is closer still, but the comparison is limited to fewer packages (mocsy treats only A T -C T ). Much larger are the actual changes themselves.
K 1 and K 2 The formulations for K 1 and K 2 from  Lueker et al. (2000)  are recommended for best practices  (Dickson et al. , 2007) , but they are intended to be restricted to waters with S between 19 and 43 and T between 2 and 35 • C. For waters with physical conditions outside of those ranges, there are no recommended K 1 and K 2 formulations. However, formulations exist, such as those from the most recent reassessment by  Millero (2010) , which are applicable over wider ranges of S (1-50) and T (0-50 • C). With an analysis analogous to that shown in Fig. 5  (Sect. 3. 2. 1), we replaced formulations for K 1 and K 2 from  Lueker et al. (2000)  with those from  Millero (2010)  to assess the consistency of computed variables in the six packages that include this newer option (CO2SYS-MATLAB, both CO2SYS-Excel variants, CO2calc, seacarb, and mocsy).