dataesr/scientific-paragraphs-categorization huggingface dataset:
We refer to the first as the original data, to the second as the data product, and to the third as the mapped product. The GLODAP products have been widely used. The first version formed the basis for the first data-based estimate of the global ocean inventory of anthropogenic carbon  (Sabine et al. , 2004) , and the descriptive paper on GLODAPv1. 1  (Key et al. , 2004)  has been cited more than 800 times according to Web of Science (Clarivate Analytics). For GLO-DAPv2, we have registered more than 120 applications. Examples include model evaluation  (Beadling et al. , 2018; Goris et al. , 2018; Tjiputra et al. , 2018; Ward et al. , 2018) , model initialization  (Orr et al. , 2017) , water mass analyses  (Jeansson et al. , 2017; Peters et al. , 2018; Rae and Broecker, 2018) , ocean acidification  (Fassbender et al.
, 2017; García-Ibáñez et al. , 2016; Perez et al. , 2018)  calibration of Argo biogeochemical sensor measurements  (Bushinsky et al. , 2017; Johnson et al. , 2017) , calibration of multiple linear regression (MLR) and neural-network-based methods for biogeochemical data estimation  (Bittig et al. , 2018; Carter et al. , 2018; Fry et al. , 2016; Sauzède et al. , 2017) , contextualization of paleo-oceanographic data  (Glock et al. , 2018; Sessford et al. , 2018) , and calculation of inventory, transport, and variability of ocean carbon  (DeVries et al. , 2017; Fröb et al. , 2016 Fröb et al. , , 2018;; Gruber et al. , 2019; Panassa et al. , 2018; Pardo et al. , 2017; Quay et al. , 2017). A full list of GLODAPv2 citations is provided at https://www. glodap. info/index. php/ glodap-impact/ (last access: 17 September 2019).
Key features of the update GLODAPv2. 2019 (Olsen et al. , 2019)  contains data from 840 cruises, covering the global ocean from 1972 to 2017. The sampling locations of the 116 cruises added in this update are shown alongside those of GLODAPv2 in Fig. 1 , while the coverage in time is shown in Fig. 2. Compared to GLO-DAPv2, the added data are mostly repeat observations and extend the coverage in time. Information on cruises added to this version is provided in Table  A1  in the Appendix. All new cruises were subjected to primary (Sect. 3. 1) and secondary (Sect. 3. 2) quality control (QC). These procedures remain essentially the same as those for GLODAPv2. However, the secondary QC aimed only to ensure the consistency of the data from the 116 new cruises to GLODAPv2. A consistency analysis of the full GLODAPv2.
2019 product (as done with the original GLODAPv2 product) has not been carried out, as it would be too demanding in terms of time and resources to allow for frequent updates, particularly in terms of application of inversion results. The QC of GLODAPv2 produced a sufficiently accurate data set that can serve as a reliable reference (this is in fact already done by some investigators to test their newly collected data; e. g. ,  Panassa et al. , 2018). The aim is to conduct a full analysis (i. e. , including an inversion) again after the completion of the third GO-SHIP survey, currently scheduled to be completed by 2023. Until that time, intermediate products like this will be released regularly (every 1 or 2 years). A naming convention has been introduced to distinguish intermediate from full product updates.
Data assembly and primary quality control The data for the 116 new cruises were retrieved from data centers (typically CCHDO, NCEI, PANGAEA) or submitted directly to us. Each cruise is identified by an EX-POCODE. The EXPOCODE is guaranteed to be unique and constructed by combining the country code and platform code with the date of departure in the format YYYYM-MDD. The country and platform codes were taken from the ICES library (https://www. ices. dk/marine-data/vocabularies/ Pages/default. aspx, last access: 17 September 2019). The individual cruise data files were converted to WOCE exchange format: a comma-delimited ASCII format for CTD and bottle data from hydrographic cruises. GLODAP deals only with bottle data, and their exchange format is briefly reviewed here with full details provided in  Swift and Diggs (2008).
The README section is followed by data column headers, their units, and then the actual data. The headers and units are standardized and provided in Table  1  for the variables included in GLODAPv2. 2019. Exchange file preparation entailed units conversion in some cases, most frequently from milliliters per liter (mL L -1 ; oxygen) or micromoles per liter (µmol L -1 ; nutrients) to micromoles per kilogram of seawater (µmol kg -1 ). The default procedure for nutrients was to use seawater density at reported salinity, an assumed lab temperature of 22 • C, and pressure of 1 atm. For oxygen, the factor 44. 66 was used for the milliliter to micromole conversion, while for the per liter to per kilogram conversion density based on reported salinity and draw temperatures was preferred, but draw temperature was frequently not reported and potential density was used instead.
Secondary quality control The aim for the secondary QC was to identify and correct any significant biases in the data from the 116 new cruises relative to GLODAPv2, while retaining any signal due to time changes. To this end, secondary QC in the form of consistency analyses was conducted to identify offsets in the data. All identified offsets were scrutinized by the GLODAP reference group at a meeting in Seattle in September 2018 in order to decide the adjustments to be applied to correct for the offset (if any). To guide this process, a set of initial miniwww. earth-syst-sci-data. net/11/1437/2019/ Earth Syst. Sci. Data, 11, 1437-1461, 2019  mum adjustment limits was used (Table  3 ). These are set according to the expected measurement precision for each variable, and are the same as those used for GLODAPv2, apart from TAlk and pH.
Any adjustment was applied uniformly to all values for a variable and cruise, i. e. , an underlying assumption is that cruises suffer from either no or a single and constant measurement bias. Except for where explicitly noted (Sect. 3. 3. 1), no adjustments were changed for data previously included in GLO-DAPv2. Crossover comparisons, MLRs, and comparison of deepwater averages were used to identify offsets for salinity, oxygen, nutrients, TCO 2 , and TAlk (Sect. 3. 2. 2 and 3. 2. 3). For pH, an additional evaluation of the internal consistency of the seawater CO 2 chemistry variables was used whenever possible (Sect. 3. 2. 4). For the halogenated transient tracers, examination of surface saturation levels and relationship among the tracers were used to assess the data consistency (Sect. 3.
Merging of sensor and bottle data Salinity and oxygen data can be obtained either by analysis of water samples (bottle data) and/or directly from the CTD sensor pack. These two types are merged and presented as a single variable in the product. The merging was conducted prior to the consistency checks, ensuring their internal calibration in the product. Note that we did not add data from the high-resolution CTD files (as obtained on the downcast) to the bottle data files. The merging procedures were only applied to the bottle data files, which commonly include values recorded by the CTD at the pressures of the upcast when the water samples are collected. Whenever both CTD and bottle data were present in a data file, the merging step considered the deviation between the two and calibrated the CTD values if required and possible.
Stations that are compared must be within 2 • arc distance (∼ 200 km) of each other, and only deep data are used. This minimizes effects of natural variability. Typically, we used 1500 dbar as the upper depth limit, but in regions where deep mixing occurs (such as the Nordic, Labrador, and Irminger seas) a more conservative limit of 2000 dbar was applied. As an example, the crossover for phosphate as measured on the two cruises 58GS20150410 and 64PE20070830 is shown in Fig. 3. For phosphate the offset is determined as a ratio. This is also the case for the other nutrients, oxygen, and the halogenated transient tracers. For salinity, TCO 2 , TAlk, and pH, absolute offsets are used, in accordance with the procedures followed for GLODAPv2. The phosphate values from 58GS20150410 are significantly higher, at 1.
12±0. 016 times those measured at the 64PE20070830 cruise; this is then the weighted mean offset. For each of the 116 new cruises, such a crossover comparison was conducted against all cruises possible in GLO-DAPv2, i. e. , all cruises that had stations closer than 2 • arc distance to any station for the cruise in question. The summary figure for phosphate at 58GS20150410 is shown in Fig. 4. Clearly, the phosphate data measured at this cruise are high when compared to the data measured at all nearby cruises included in GLODAPv2. An offset of this kind, exceeding the initial minimum adjustment limit (Table  3 ) and with no obvious time trend, qualifies for an adjustment of the data in the merged data product.
Other consistency analyses A few new cruises had no or very few valid crossovers with GLODAPv2 data. In that situation two other consistency analyses were carried out for salinity, oxygen, nutrients, TCO 2 , and TAlk data, namely MLR analyses and deepwater averages, broadly following  Jutterström et al. (2010). For the MLRs, the presence of bias in the data for the cruise in question was identified by comparing the MLR gener-   4  in  Key et al. , 2010)  or are the deepest sampling depth. The interpolation do not extrapolate to this. Panel (d) shows the mean difference (as a ratio) profile (black, dots) with its standard deviation, and also the weighted mean offset (straight, red) and weighted standard deviation. Summary statistics are provided in (b). ated with the measured value, while for the deep-water averages the approach is trivial.
pH scale conversion and quality control A total of 77 of the 116 new cruises included pH data. For about 30 % of these, the pH data were not supplied on the total scale, and at 25 • C and 0 dbar pressure, which is the GLODAP standard. These data were converted to total pH scale and temperature and pressure of 25 • C and 0 dbar. The conversions were conducted by using CO2SYS  (Lewis and Wallace, 1998)  for MATLAB  (van Heuven et al. , 2011)  with reported pH and TAlk as inputs, and generating pH output values at total scale at 25 • C and 0 dbar of pressure (named phts25p0 in the product). Whenever TAlk data were missing, these values were approximated as 67 times salinity. The proportionality (67) is the mean ratio of TAlk to salinity in the GLODAPv2 data. This is sufficiently accurate for scale-temperature-pressure conversions.
, 2013; Liu et al. , 2011; Patsavas et al. , 2015; Yao et al. , 2007)  that challenge the viability of the uniform adjustments applied  (Carter et al. , 2018). While we have continued to apply such uniform offsets for this update, we have chosen the higher initial minimum adjustment limit of 0. 01, which is twice that used for GLO-DAPv2 (0. 005), to minimize the possibility of false corrections. The full ramifications and a revised strategy for identifying and minimizing bias in pH data is a topic for future development of the GLODAP data synthesis procedures. The full collection of pH values in GLODAPv2. 2019 should only be considered to be consistent between cruises to 0. 01 to 0. 02 pH units.
Updates and corrections for GLODAPv2 Several minor omissions and errors have been identified in the GLODAPv2 data product since its release in early 2016. Most of these have been corrected in this release. In addition, some recently available data have been added for a few cruises. The changes are as follows. -For 29 cruises spectrophotometric pH data were available but not included in the data product despite having passed secondary quality control. The data from 24 of these cruises are now included, while for the other five cruises the data have been discarded following more indepth quality control. Whenever possible (Sect. 3. 3. 2), TAlk or TCO 2 was calculated for these cruises as well. -The extension ". 1" has been removed from the three EXPOCODES 316N19720718. 1, 316N19871123. 1, and 316N19871123.
1. -For 33LG20090901 salinity has been included. -For 35TH20040604 nutrient data have been replaced with updated data from the PI. -For 09AR20071216 TAlk and TCO 2 data have been updated. -For 33AT20120324 and 33AT20120419 DOC, TAlk, and SF 6 data have been updated. -For 35UCKERFIXTS TAlk and TCO 2 data have been adjusted by -45 and -39 µmol kg -1 , respectively. -Secondary QC flags for calculated carbon variables are corrected. -For 99 records in GLODAPv2 unrealistic differences between sampling pressure and depth were noted. This has been corrected by using the original reported pressure and recalculating depth. -Impossible dates (e. g. , 31 November) and time stamps (e. g. , minute = 81) were fixed for a small number of cruises. -Recently available/updated data for radioisotope and stable isotopes as well as noble gases were added to eight cruises.
-For 06AQ19960317 the 3 H data have been flagged as bad. -For 21 cruises the δ 13 C values have been adjusted according to the results from  Becker et al. (2016). To enable identification of δ 13 C subjected to secondary QC, a secondary QC flag for δ 13 C has been included in the GLODAPv2. 2019 product file. -For 64PE20070830 and 06M220090714 halogenated transient tracer data have been updated. -Some outliers detected since the release have been removed (from the merged GLODAPv2. 2019 product) and flagged as bad/questionable (in the original cruise data files). -Neutral density, γ , was recalculated for the entire product file using the global polynomial of  Sérazin (2011) , which consists of a set of polynomials for each ocean basin, joined together at their boundaries by weighting functions.
Merging The new data were merged into a bias-minimized product file following the procedures used for GLODAPv1. 1  (Key et al. , 2004; Sabine et al. , 2005) , CARINA  (Key et al. , 2010) , PACIFICA  (Suzuki et al. , 2013) , and GLODAPv2  (Olsen et al. , 2016) , but with minor changes. Data from the 116 new cruises were merged and sorted according to EXPOCODE, station, and pressure. Cruise numbers were assigned consecutively, starting from 1001, so they can be distinguished from the GLODAPv2 cruises that ended at 724. Whenever nitrate plus nitrite were reported instead of nitrate and explicit nitrite concentrations were also given, these were subtracted to get the nitrate values; otherwise, NO 3 + NO 2 was renamed as NO 3. As nitrite concentrations are very small in the open ocean, this has no practical implications.
When bottom depths were not given, they were approximated as the deepest sample pressure +10 dbar or extracted from ETOPO1  (Amante and Eakins, 2009) , whichever was greater. For GLODAPv2, these values were extracted from the Terrain Base (National Geophysical Data Center/NESDIS/NOAA/U. S. Department of  Commerce, 1995). This change has no practical implications, as the variable is only included for drawing approximate bottom topography for sections. Whenever temperature was missing, all data for that record were removed and their flags set to 9. The same was done when both pressure and depth were missing. For all surface samples collected using buckets or similar, the bottle number was set to zero. All data with WOCE quality flags 3, 4, 5, or 8 were excluded from the product files (value set to -999/NaN) and their flags set to 9.
Adjustment summary The secondary QC actions for the 12 core variables are summarized in Table  5. Compared to GLODAPv2, the fraction of data that is adjusted is smaller. A percentage of 0 %-10 % of the 116 new cruises are adjusted for each core variable, whereas for the 724 cruises in GLODAPv2, 5 %-30 % were adjusted for each core variable. The number of adjusted cruises is particularly low for salinity (only one of the new cruises was adjusted, i. e. , 1 % compared to 5 % for the 724 GLODAPv2 cruises), for the halogenated transient tracers (0 %-3 % adjusted, depending on variable, compared to 6 %-10 % for GLODAPv2), and for TCO 2 (two cruises, i. e. , 2 % compared to 17 % for GLODAPv2). The distributions of the magnitude of adjustments applied are presented in Fig. 5  and Table  6. For salinity, oxygen, and silicate, adjustments between 1 and 2 times the initial minimum adjustment limit are most prevalent.
However, six out of seven of the negative bias cruises were Japanese. A tendency for bias in Japanese cruises to be negative was also identified in GLO-DAPv2 and may be due to the use of internal reference material. We note that the TAlk data from 23 out of 29 Japanese cruises with viable deep crossover checks had no apparent deep offset, so the majority of new TAlk data from Japan were consistent with GLODAPv2 even with the lowered threshold. The prevalence of positive pH adjustments may relate to the fact that at low pH (as is common in the deeper waters where crossover analyses are done), measurements made with purified dyes tend to be lower than pH determined using electrodes, using impure spectrophotometric dyes with older dye coefficients  (Clayton and Byrne, 1993) , or calculated from TCO 2 and TAlk  (Carter et al.
But this does not imply that the data were initially consistent everywhere. Rather, for some regions and variables there are substantial improvements when the adjustments are applied. For example, Arctic Ocean oxygen and phosphate, Atlantic Ocean nitrate and phosphate, Indian Ocean silicate, and Pacific Ocean TAlk data all show considerable improvements. For the Arctic and Atlantic oceans there are substantial offsets for many variables with respect to GLODAPv2 even after the adjustments have been applied. This relates to actual variability in deep waters of the northern North Atlantic and Arctic regions. For example, the weighted mean of the absolute offset for Arctic Ocean silicate for the adjusted data is 11. 1 % and that for salinity is 10 ppm (i. e. , a salinity of   3 ); orange: absolute adjustment is between limit and 2 times the limit, red: absolute adjustment is larger than 2 times the limit.
Data availability The GLODAPv2. 2019 merged and adjusted data product is archived at NOAA NCEI under https://doi. org/10. 25921/xnme-wr20 (Olsen et al. , 2019). These data and ancillary information are also available via our web pages https://www. glodap. info/ and https: //www. nodc. noaa. gov/ocads/oceans/GLODAPv2_2019/ (last access: 19 September 2019). The data are available as comma-separated ascii files (*. csv) and as binary MATLAB files (*. mat). Regional subsets are also available for the Arctic, Atlantic, Pacific, and Indian oceans. There are no data overlaps between regional subsets and each cruise exists in only one basin file even if data from that cruise cross basin boundaries. The station locations in each basin file are shown in Fig. 9. The product file variables are listed in Table  1.
A lookup table for matching the EXPOCODE of a cruise with its GLODAP cruise number is provided with the data files. In the MATLAB files this information is also available as a cell array. A "known issues document" accompanies the data files and provides an overview of known errors and omissions in the data product files. It is regularly updated, and users are encouraged to inform us whenever any new issues are identified. It is critical that users consult this document whenever the data products are used. The original cruise files are available through the GLODAPv2. 2019 cruise summary table (CST) hosted by NOAA NCEI: https://www. nodc. noaa. gov/ocads/oceans/GLODAPv2. Each of these files has been assigned a DOI, but these are not listed here. The CST also provides brief information on each cruise and access to metadata, cruise reports, and the Adjustment Table entry for each cruise.
While GLODAPv2. 2019 is made available without any restrictions, users of the data should adhere to the fair data use principles. For investigations that rely on a particular (set of) cruise(s), recognize the contribution of GLODAP data contributors by at least citing the articles where the data are described and, preferably, contacting principal investigators for exploring opportunities for collaboration and co-authorship. To this end, relevant articles and principle investigator names are provided in the CST. This comes with the additional benefit that the principal investigators often possess expert insight into the data and/or particular region under investigation. This can improve scientific quality and promote data sharing. Cite this paper in any scientific publications that result from usage of the product.
Summary GLODAPv2. 2019 is an update of GLODAPv2. Data from 116 new cruises have been added to supplement the earlier release and extend temporal coverage by 4 years. GLODAP now includes 45 years, 1972-2017, of global interior ocean biogeochemical data from 840 cruises. Figure  7  illustrates the seasonal distribution of the data. There is a bias around summertime in the data in both hemispheres; most data are collected during April through November in the Northern Hemisphere while most data are collected during November through April in the Southern Hemisphere. These tendencies are strongest for the poleward regions and reflect the harsh conditions during winter months, which make fieldwork difficult. Figure  8  illustrates the distribution of data with depth. The upper 100 m is the best sampled part of the global ocean, in terms of both number (Fig.
8a ) and density (Fig. 8b ) of observations. The number of observations steadily declines with depth. In part, this is caused by the reduction of ocean  volume towards greater depths. Below 1000 m the density of observations stabilizes and even increases between 5000 and 6000 m; the latter is a zone where the volume of each depth surface decreases sharply  (Weatherall et al. , 2015). In the deep trenches, i. e. , areas deeper than ∼ 6000 m, both number and density of observations are fairly low. Except for salinity and oxygen, the core data were collected exclusively through chemical analyses of individually collected water samples. The data of 12 core variables: salinity, oxygen, nitrate, silicate, phosphate, TCO 2 , TAlk, pH, CFC-11, CFC-12, CFC-113, and CCl 4 were subjected to primary quality control to identify questionable or bad data points (outliers) and secondary quality control to identify systematic measurement biases.
The data are provided in two ways: as a set of individual exchange-formatted original cruise data files with assigned WOCE flags, and as globally and regionally merged data product files with adjustments applied to the data according to the outcome of the consistency analyses. Importantly, no adjustments were applied to data in the individual cruise files. The consistency analyses were conducted by comparing the data from the 116 new cruises to GLODAPv2. Adjustments were only applied when the offsets were believed to reflect biases related to measurement, calibration, and/or data handling practices. The Adjustment Table at https://glodapv2-2019. geomar. de lists all applied adjustments and provides a brief justification for each. The consistency analyses rely on deep ocean data (> 1500 or 2000 dbar depending on region).
For TCO 2 , TAlk, and pH, any data flagged 0 are calculated from two measured seawater CO 2 variables. Finally, while questionable (WOCE flag =3) and bad (WOCE flag = 4) data have been excluded from the product files, some may have gone unnoticed through our analyses. Users are encouraged to report on any data that appear suspicious. Based on the initial minimum adjustment limits and the improvement of the consistency from the adjustments (Tables 7 and 8), the data subjected to consistency analyses are believed to be consistent to better than 0. 005 in salinity, 1 % in oxygen, 2 % in nitrate, 2 % in silicate, 2 % in phosphate, Earth Syst. Sci. Data, 11, 1437 Data, 11, -1461 Data, 11, , 2019  www. earth-syst-sci-data. net/11/1437/2019/ 4 µmol kg -1 in TCO 2 , and 5 % for the halogenated transient tracers.