As a basis of our data set, we chose the 1990s data collection by . This was established to investigate variations in δ13CPOC with temperature and latitude. The δ13CPOC sample data and measurements were conducted by investigating zooplankton, net plankton or particulate organic matter. We cross-checked and extended this data set by looking up all available primary sources. originally included 476 δ13CPOC data points from 17 contributions. The largest contributions came from with 107 entries, with 97, and with 78. Large extensions were possible, e.g., in the and data sets, incorporating more than 70 additional data points from these primary sources. With this extension, we could increase the data set to 626 data points for δ13CPOC.

We collected most data from the PANGAEA data platform, an open-access online library archiving and providing geo-referenced Earth system data, hosted and monitored by the – Helmholtz Centre for Polar and Marine Research (AWI) – and the Center for Marine Environmental Sciences, University of Bremen (MARUM). With the data made available therein, we could further extend the data set by an additional ∼ 3500 measurements of δ13CPOC. Most δ13CPOC data from PANGAEA are associated with samples collected during the Joint Global Ocean Flux Study , with more than 2000 δ13CPOC data points. Additionally, 529 samples are contributions by the Antarctic Environment and Southern Ocean Process Study , 342 are by the Archive of Ocean Data and 279 are by the SFB313 research project .

Other collected data were provided by Robyn Tuerena and Anne Lorrain. Robyn Tuerena provided a data contribution coming from the data set mentioned in , which we will refer to as the Tuerena data set. This contains 595 data points including 501 from and covers samples within the euphotic zone and an observation time frame of 1964–2012. Moreover, we included 69 unpublished data points provided by Anne Lorrain, covering the years 2012–2015 and sampled during the cruises CASSIOPEE, PANDORA, OUTPACE, NECTALIS-3, NECTALIS-4 and KH-13. We refer to this data set as the Lorrain data set.

A recent collection of 303 measurements of δ13CPOC has been provided by , largely based on data gathered from individual publications referenced therein. Since our analyses originally relied on data sources that differed from those of , we find our collection to be as yet incomplete. Especially measurements from national databases might provide a huge future benefit.

All data were taken with as many details as possible from the sources and have been reshaped to fit the structure of the data set. No rounding or cutoff of detailed data was made. Spatial coordinates originally given as depth intervals were replaced by their respective midpoints. Time intervals were not changed in this way. If they contained just 1 month or year, this was included; otherwise the time information was omitted. Sample depth given as “surface” was denoted as 1 m. Longitude values were converted to the format [-180∘,180∘] by the transformation 2Longnew=Longold-360∘for all Longold∈180∘,360∘Longoldotherwise. Wherever possible the data were taken from their original publication. Changes made to the data by are described in Table  and changes to all other data in Table . The complete structure is presented in Table .

Most data listed in the data set could be gathered from the original publications directly. Some data are not accessible from an original source, including those data labeled as “Harrison”, “Hobson” and “Schell”, which were included as unpublished data by personal communication in . Also, we could not identify the original data sources of “Voss (1991)” and “Sackett et al. (1966)”. Data from these sources are used as provided by . All other data could be directly compared with and linked to their origin. According to Table  we complemented the data with the month, year, depth, sample method, cruise, trap duration and references wherever available. Special notes given in were conserved in our “project/cruise”-named meta-information. Rounded values were adjusted to their source values as well as data with interchanged longitudinal information, which is shown in detail in Table .

In two cases we identified multiple δ13CPOC data sets from a single event (time, place, investigator) where the data had been subject to different stages of processing or different types of measurement: in , we chose the “mass spectrometer” data set because this was the originally measured one. In , we used the “blank corrections” data set of δ13C, since this set of δ13Corg values is recommended to be considered .

The primary source of the Tuerena and Lorrain data was mentioned in our data set in the project/cruise column. In the data set from , this was originally labeled as “source” and in the Lorrain data set as “campaign”. In both data sets the longitude was converted to [-180∘,180∘] from a [0∘,360∘] format by Eq. (). In the data of we deleted a typo where the depth value was set equal to the negative longitude value. We disregarded the trap duration given in , which was given as the negative value -1.

The csv-format data file includes δ13CPOC measurements, anomalies and meta-information in its columns. A full description of the content, value range and coverage of the individual columns is given in Table . Anomalies of δ13CPOC were calculated, based on the arithmetic mean of the full data collection. The mean was calculated, rounded to two digits after the floating point and used as 3meanδ13CPOC=-23.96‰. Anomalies contain all the relevant information with respect to the variability in the δ13CPOC data in space and time. This way it becomes easier to analyze bias information separately, e.g., during the first steps of model calibration.

The reference includes the citations in as much detail as possible. Wherever available, this is taken from the original source. Otherwise, we tried to include the author, title, publication year and platform, and DOI. For unpublished data like Harrison's (unpublished data, quoted from ) from the data set or those included by the co-authors, we specified from where we took the data.

Coordinates are given in decimal degrees over [-90∘,90∘]×[-180∘,180∘]. The sample depth is given in meters measured positively from the ocean surface downwards. Data published as measured at 0 m were included as this, while no surface microlayer measurements were included. The month and year were used to describe the sample date; specific days are neglected.

Anomalies of δ13CPOC are given in the δ ratio described in Eq. (). A sample method was added, wherever available. Any special sampling circumstances were given in the “Note” column. Activity duration of sediment traps was denoted in the last column.

The “Origin” columns listed the associated project or cruise or author note. Some samples were given with multiple project connections; all of them were given in this column.

The interpolated δ13CPOC data are available as NetCDF files on two global grids with different resolutions. NetCDF files are machine-independent and support the creation, accessing and sharing of array-oriented scientific data. On the UVic grid, we provide seven different files, each of them independent of time and averaged over the available spatial information. Six of them contain an individual decade each (from the 1960s through the 2010s). The seventh file comprises a combined set of all interpolated δ13CPOC data. On the WOA grid, we provide 13 files including all δ13CPOC measurements with complete spatial–temporal information, averaged across time and space.

One major aim of this work is to support reliable validation and calibration of δ13CPOC-simulating models. Hence, we chose the grid of the UVic model version 2.9, as used, e.g., in . Horizontally, it consists of 100×100 cells with a resolution of 1.8∘×3.6∘, arranged from 0 to 360∘ in longitude (LONG) and -90 to 90∘ in latitude (LAT). Vertically, it is split up into 19 vertical layers (DEPTH), decreasing in resolution with depth. The two uppermost layers reach down to depths of 50 and 130 m, respectively, and they are supposed to comprise the upper ocean's euphotic zone.

The WOA grid is based on the 1∘×1∘ grid of the World Ocean Atlas . It has a horizontal resolution of 360 arranged from -180 to 180∘ in the longitude (LONG) and 180 arranged from -90 to 90∘ in the latitude (LAT) direction. Vertically, it is split up into 102 layers (DEPTH). The time axis (TIME) increases in increments for each year from 1964 to 2015 by 1 and has a size of 52. This interpolation includes only δ13CPOC data with full spatio-temporal metadata coverage; i.e., additionally to latitude, longitude and depth, we also required and included year and month information.

Ferret scripts were used for the interpolations. These averaged the irregularly measured data points within the ocean grid to one single data point representing each covered grid cell. The interpolation function SCAT2GRIDGAUSS by performed the spatial averaging under PyFerret v7.5. Calculations in this function are based on a work by and can be summarized as follows: let (x1,y1),…,(xn,yn)⊆R2 be an equidistant grid and (x1̃,y1̃),…,(xm̃,ym̃)⊆R2 be irregular measurement locations of a real tracer Dj,j∈{1,…,m}. Then the value Di∈R at grid point (xi,yi),i∈{1,…,n} becomes interpolated as 4Di:=∑j=1mDjWi,j∑j=1mWi,j, where 5Wi,j:=0;τi,j<e-CX0;τi,j<e-CYτi,jotherwise, where τi,j:=exp⁡-xj-xi2X2+yj-yi2Y2 is the Gaussian weight function, X,Y∈R comprises scaling arguments and C∈R the cutoff parameter. We set X=1.8, Y=0.9 and C=1 in our script.

Since the interpolation into the WOA grid excluded all data without full spatio-temporal metadata coverage, we focus the following descriptions of interpolated data on the UVic grid interpolations. These also include data without month information in the six decadal files and even completely without temporal information in the seventh time-independent file.

The data distribution is presented by its KDE in Fig. . The interval of δ13CPOC values ranges over [-55.15,-4.5] with a mostly smooth distribution. Most of our data exhibit values around δ13CPOC≈-24 ‰, which becomes clearly identifiable as a single maximum in the KDE. Two smaller modes are visible at around δ13CPOC≈-27.5 ‰ and δ13CPOC≈-22 ‰ (see also Table  in the Appendix). A steep decline to zero is visible outside the two outer modes. The steep decline in the KDE stops at around δ13CPOC=-37 ‰ and δ13CPOC≈-14 ‰. Between δ13CPOC≈-37 ‰ and δ13CPOC≈-55.15 ‰ as well as between δ13CPOC≈-14 ‰ and δ13CPOC≈-4.5 ‰ the KDE closely aligns to the x axis, which indicates very few data points lie in this range.

Below δ13CPOC=-37 ‰ we find 17 data points ranging down to δ13CPOC=-55.15 ‰. Down to δ13CPOC=-48‰ these were all taken from and , measured in September or October 2003, around the location 10∘ N, 104∘ W and below 2500 m depth in the vicinity a hydrothermal field close to the Pacific coast of middle America. The lowest outlier at δ13CPOC=-55.15 ‰ was taken from from November 1996 and at 62.52∘ S, 169.99∘ E at the ocean surface south of New Zealand.

Above δ13CPOC=-10 ‰ we find 15 data points ranging up to δ13CPOC=-4.5‰. Three of them were taken from and measured at 800 m depth at a hydrothermal vent located 30.125∘ N, 42.117∘ W in the middle north Atlantic. Ten were taken from . All of these were measured between 636 and 901 m depth around 49∘ N, 130∘ W close to the American coast of the Pacific, and all of them were measured in February or May, except one in August. The final two were part of the Lorrain data set. Both were measured at the ocean surface in the South Pacific, in July at 5.3∘ S, 164.9∘ E and December at 20.9∘ S, 159.6∘ E.

Since more than 98 % of the data (4668 of the 4732 data points) have values that lie between δ13CPOC=-35 ‰ and δ13CPOC=-15 ‰, we will focus on this range in our following analyses.

We tested the robustness of our KDE approach in a subsampling experiment. We considered 500 random subsets of 20 % of the original data over the range with the highest data density [-35,-15] and visualize their KDEs in Fig. . They show peaks at δ13CPOC≈-23 ‰, fitting the maximum and the second smaller mode to the right of it, and at δ13CPOC≈-27.5 ‰. Outside [-27,-22] the KDEs are closely aligned. The mean of and standard variation in the KDE ensemble also show the highest variability around the two modes at δ13CPOC=-23 ‰ and δ13CPOC=-27.5 ‰.

Various sampling methods were involved in obtaining the δ13CPOC data. Around 67 % of the data had associated sampling-method information, which included 18 different sampling methods. In principle, all 18 methods could be grouped into five main observational types: bottles, intake, nets, traps and diverse. “Bottle” data include samples taken from Niskin bottles and samples collected via Sea-Bird submersible pumps. By “intake” we refer to all versions of pumps and underway cruise track measurements, as well as multiple-unit large-volume filtration systems (MULVFSs). “Net” data represent all occurring versions of plankton nets, and “traps” refers to all represented sediment traps and moorings. Finally, the deep-sea manned submersible (MIR2) is not classified into any of these groups and was assigned to a cluster that we refer to as “diverse”.

All sample devices provided data over all sample depths. Deeper samples were mainly taken from traps and pump systems and the upper samples from bottle and net data. Most data sampled deeper than 2600 m were collected by sediment traps. At 3800 m there were several trap contributions by Calvert e.g.,, mostly from the late 1980s. Data sampled by a deep-sea manned submersible were given at locations down to 2520 m .

For resolving differences between sampling methods we chose data from the Atlantic Ocean which comprise all four major methods (with data embracing a region between 45∘ S and 80∘ N and 70∘ W and 20∘ E). In addition, data were distinguished by tropical, temperate and polar subregions. By crudely sorting the data according to their sampling locations, we gain some insight into methodological variability within a subregion and may relate this to variations between the three subregions (Fig. ). Overall, we do not find any severe bias with respect to any particular method. Bottle data seem to cover most of the lower δ13CPOC values that typically range between -28 ‰ and -21 ‰, which could be due to samples collected at greater depths. Intake and net measurements are rather restricted to the upper ocean layers, and these methods often yield δ13CPOC values larger than -25 ‰, with some polar net measurements being a notable exception (Fig. d). For the tropical Atlantic (30∘ S–30∘ N) the net and intake measurements vary around -21 ‰, with 95 % confidence limits between -24 ‰ and -18 ‰ (see Table  in the Appendix). According to our comparison, we could not identify any method that yields much greater variance of δ13CPOC values than others. The spatio-temporal variations of the δ13CPOC compare well among different methods, but we advise caution when comparing bottle measurements with data of other methods because of potential differences in the depth range covered.

In the full Atlantic Ocean, densities of intake and net data are most representative of the maximum full δ13CPOC sample. From the intake data shown here, ∼80 % were sampled within 30∘ S and 30∘ N. When restricting data to this area, net data better resemble the full data. Of all net sample data, ∼80 % were collected between 30 and 60∘ N, where they fit the overall δ13CPOC density best, followed by trap data. Trap and bottle data deliver the lowest δ13CPOC measurements in the Atlantic Ocean. Of both data kinds, ∼74 % to 85 % were sampled north of 60∘ N. A restriction to this area shows trap and bottle samples being closely aligned to the full data in this region.

The variance of the intake and trap data is ∼3 ‰ and lower than the variance of all δ13CPOC together, which is ∼5 ‰, the highest value observed here. Both bottle and net data show a variance of less than 2 ‰. Furthermore, trap, net and full δ13CPOC show a pronounced second mode in their densities, while bottle and net data show a clear individual maximum. Median values of net and intake data are ∼1 ‰ to ∼2 ‰ higher, respectively, than the one of the full data. This has a median of δ13CPOC=22.46 ‰. Both bottle and trap data show a ∼2 ‰ lower median. Analytical errors and uncertainties are typically 0.2 ‰ or lower and thus are not likely to significantly contribute to the much larger variance in the observations

Depth values are available for more than 80 % of the sample data with most of them located in the upper ocean. The distribution of depth measurements is shown in Fig. . An approximation of the depth measurements by Gaussian KDE is visualized in Fig.  along with the δ13CPOC value distribution over them in the main ocean basins. The KDE resolves the best data coverage for the uppermost ∼500 m of the oceans and a second far smaller maximum at ∼3800 m. The depth ranges presented in Fig.  correspond to the depth intervals of the UVic grid; only the two uppermost layers are presented in more detail, and the last four are combined. Within the first 130 m we observe the highest data density and find nearly 2500 measurements of δ13CPOC, where nearly 1000 of them were measured within [0m,10m). A total of 200 δ13CPOC values were available in the depth interval [3430m,3900m). The two deepest values were taken from and and sampled at 4500 and 4850 m depth, respectively.

Values of δ13CPOC are, apart from in the North Pacific, closely aligned within the individual ocean basins. The Atlantic, South Pacific and Indian Ocean show values mostly of -28 ‰ to -19 ‰. The δ13CPOC values in the Arctic reach down to approximately -30 ‰ and those in the Southern Ocean even to approximately -35 ‰. The North Pacific shows a wide spread of δ13CPOC values, especially between 50 and 100 m depth and at 2500 m depth. There they reach either down to less than -40 ‰ or up to more than approximately -10 ‰ at a depth of 2500 m.

Measurements in the North Atlantic, North Pacific and Indian Ocean reach down to more than 3500 m. Measurements down to nearly 5000 m were sampled in the Southern Ocean. The South Pacific was sampled down to a depth of 2500 m and the Arctic Ocean and South Atlantic only in the uppermost few hundred meters.

All global oceans are covered with δ13CPOC data. In Fig.  the horizontal distribution of available data is depicted for both grids. For the UVic grid we show data from the file including all data independent of time; the WOA grid is averaged over all times. In both cases, we averaged data over all depths and also added data without depth information to best visualize the horizontal coverage. A similar plot, although with a different purpose, is given later in this work in Fig.  showing only surface data locations.

Many cruises are visible as lines formed by connected grid cells in Fig. , especially in the Atlantic and Indian Ocean and less so in the Southern Ocean. Also, smaller sample spots occur, mainly located in the Pacific, Arctic and Southern Ocean. The Atlantic Ocean provides the best data coverage. Then the Southern and Indian oceans contain the next best coverage with the North Pacific having the sparsest.

The highest δ13CPOC values are evident in low-latitude regions. In the Atlantic Ocean the highest values were measured between 0–30∘ N and 30–60∘ W as well as close to the western coast of France, reaching up to at least -17 ‰. The Indian Ocean shows generally high values of approximately -20 ‰. In the Pacific Ocean the highest values are close to the Peruvian coast and Papua New Guinea. We also find high values in the Bering Strait and on the northern edge of the Southern Ocean at around 65∘ E.

The lowest δ13CPOC values are mostly found in the Southern Ocean. Nearly all measured grid cells here belong to δ13CPOC values lower than around -28 ‰. The Arctic Ocean shows low values as well, for instance in the Kara Sea. The lowest values in the Pacific Ocean occur in the Southern Ocean at high latitudes.

We show the north–south trend of δ13CPOC over the Atlantic Ocean based on the time-independent UVic grid and restricted to the uppermost 130 m, which resembles the euphotic zone in the UVic model. We chose this section due to it having the best data coverage. A biome mask according to was applied to the gridded data, thereby defining latitudinal zones in the entire Atlantic Ocean. Distributions of δ13CPOC within the biomes are shown in Fig.  (see also Table  in the Appendix).

The biomes derived by are areas with consistent biological and ecological properties. The chosen biomes cover the Atlantic Ocean and extend to the Arctic Sea and parts of the Southern Ocean. The biomes are numbered 9 to 17, excluding 14. The biomes 15 to 17 represent parts of the Southern Ocean and were restricted to 70∘ W and 20∘ E. Their locations are shown in Fig. .

Observations by the biomes are consistent with the ones from Fig. . The two biomes showing the lowest δ13CPOC values from -28 ‰ to -29 ‰ are those located farthest south. The biome located farthest north contains the next-lowest values of about -24 ‰. The biomes with more positive δ13CPOC values are in the lower latitudes and show similarly higher values from -23 ‰ to -21 ‰.

Monthly clustered data of the Northern Hemisphere and Southern Hemisphere show monthly variations, but more observations are required to demonstrate robust seasonality within different regions. Since more than 50 % of the available δ13CPOC data originate in the 1990s, we selected data from this decade to exclude changes that might be introduced by longer-term trends. Furthermore, we restricted our data to the uppermost 130 m, which resembles the euphotic zone in the UVic model. In Fig.  we displayed all months with enough data points by a KDE and indicate the same months by the same colors. We excluded July, November and December in the Northern Hemisphere from this KDE representation because these months provided three or fewer data points each, which resulted in a KDE that overgrew the others by magnitudes and made their visual comparison difficult. The KDEs are supported by comparison of the median values of the individual months in Table .

The monthly resolved variations in δ13CPOC do not reveal any significant seasonal pattern (Fig. ; see also Table  in the Appendix). In general we find the highest δ13CPOC values in the Northern Hemisphere, with a median δ13CPOC of -20.4 ‰ in April and a median δ13CPOC of -21.5 ‰ in October, which are typical months with enhanced primary production (Northern Hemisphere spring and autumn blooms). Similarly high median δ13CPOC values cannot be ascertained for any month with data of the Southern Hemisphere, where values of δ13CPOC above -20 ‰ have rarely been observed at any time of the year. In fact, there is an overall tendency towards low δ13CPOC values for the Southern Hemisphere, which becomes well expressed during the months April and September, with medians of δ13CPOC=-28.1 ‰ and δ13CPOC=-28.5 ‰, respectively. However, interpretations of this north–south trend should be treated with caution because the apparent tendency is likely conditioned by some imbalance in the number of high-latitude data points. Compared to the number of data points from the Southern Ocean, samples from the Arctic Ocean are considerably underrepresented (see also Fig. ). Furthermore, the discrimination between data of the Northern Hemisphere and Southern Hemisphere is crude, and we encourage the use of our data collection for more advanced analyses of seasonal, monthly based changes in the δ13CPOC signal.

The decadal UVic grid NetCDF files are the basis for showing long-term changes in the δ13CPOC data. An overview of where the data within the individual decades were sampled is given in Fig. . This shows that the sparsest coverage was obtained in the 1960s, located close to the central American continent. Most data in the Indian Ocean were sampled in the 1970s. A cruise across the southern part of the Atlantic Ocean up to 30∘ N and some samples close to Iceland were also measured in this decade. The 1980s is similarly sparse in spatial coverage to the 1960s. Measurements of the 1980s were taken at locations in the Southern Ocean, in the Arctic and in the Atlantic close to the Equator. The 1990s has the best coverage including most ocean basins. Most Southern Ocean data were sampled within the 1990s. The 2000s provides good coverage of the Arctic Ocean. Finally, the 2010s data were mostly sampled in the Southern Hemisphere in the open Pacific and Atlantic. A smaller number of Eurasian continental sea data were also part of the 2010s samples.

We show the changes in δ13CPOC values over the available decades by density estimates in Fig.  (see also Table  in the Appendix) and by their median in Fig. . Figure  visualizes the sparse coverage of the Southern Ocean outside of the 1990s, which is why the area is not part of any further discussion here. The Southern Ocean is defined as the ocean area south of 45∘ S. All presented analyses were restricted to the euphotic zone, i.e., the uppermost 130 m resembling the two first layers of the UVic grid.

A clear decrease in δ13CPOC densities in Fig.  can be identified for the global ocean outside of the Southern Ocean. All decades but the 1980s show one clear maximum in their approximated densities. The 1980s shows a second expressed density maximum at lower values. The main maximum shifts from the 1960s at δ13CPOC≈-19.9 ‰ to the 2010s at δ13CPOC≈-23 ‰. This decrease is also clearly visible in the comparison of the decadal medians (Fig. ). The Southern Ocean provides far worse data coverage. Only the 1980s and 1990s include enough data to construct a comparable KDE. Due to this very low data availability, all of these results must be taken with the highest caution.