Variability in the Light Absorption Coefficients of phytoplankton, non-algal particles and colored dissolved organic matter in European Coastal Waters: A Two-Year Dataset in the Context of Historical Observations

Potin, Paola; Mayot, Isabella; Santinelli, Chiara; Boss, Emmanuel; Brando, Vittorio E.; Costanzo, Margherita; Martinez-Vicente, Victor; Doxaran, David

doi:10.5194/egusphere-2026-4579

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https://doi.org/10.5194/egusphere-2026-4579

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07 Sep 2026

| 07 Sep 2026

Status: this preprint is open for discussion and under review for Biogeosciences (BG).

Variability in the Light Absorption Coefficients of phytoplankton, non-algal particles and colored dissolved organic matter in European Coastal Waters: A Two-Year Dataset in the Context of Historical Observations

Paola Potin, Isabella Mayot, Chiara Santinelli, Emmanuel Boss, Vittorio E. Brando, Margherita Costanzo, Victor Martinez-Vicente, and David Doxaran

Abstract. Coastal ecosystems play a major role in global biogeochemical cycles, which are challenging for ocean color satellite observations due to independent variability in the dynamics of phytoplankton, non-algal particles (NAP), and colored dissolved organic matter (CDOM). Field measurements and match-ups with satellite data are required to assess the validity of multi-sensor satellite products and optimize (or develop new) bio-optical inversion algorithms. For this purpose, the water reflectance, light absorption and backscattering properties of coastal waters must be measured together with the concentration, composition and size of the optically-active water constituents. In this study, we report the light absorption properties of phytoplankton, NAP and CDOM measured over two years along European coastal waters. Our results show distinct contributions of CDOM from the Atlantic to Mediterranean waters, with CDOM dominating the non-water absorption budget in most regions between 380 and 560 nm. Concerning phytoplankton absorption, the B95 model (Bricaud et al., 1995), linking chlorophyll concentration to phytoplankton absorption, reproduces the overall spectral shape but exhibits regional biases, with both over and underestimation, depending on the local phytoplankton community size structure, physiological photo-acclimation states, and specific taxonomic compositions. These results highlight limitations in the current parameterizations under contrasting coastal optical regimes. The mass-specific absorption coefficient of NAP (a_NAP^∗) reflects variability in particle assemblages and river inputs, with a systematic significant contribution in the near-infrared (NIR) part of the spectrum. Overall, our results provide improved constraints on regional optical variability and contribute to the refinement of bio-optical models and ocean color algorithms in complex coastal environments.

Received: 31 Jul 2026 – Discussion started: 07 Sep 2026

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Paola Potin, Isabella Mayot, Chiara Santinelli, Emmanuel Boss, Vittorio E. Brando, Margherita Costanzo, Victor Martinez-Vicente, and David Doxaran

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'Comment on egusphere-2026-4579', Anonymous Referee #1, 29 Oct 2026 reply
Within this manuscript the light absorption properties of phytoplankton, NAP and CDOM measured over two years along European coastal waters within the TARA Europe campaign funded by the HYPERBOOST project are presented. Results show distinct patterns in contributions of CDOM, from the Atlantic to Mediterranean waters, with dominating the non-water absorption budget in most regions in the shorter wavelengths. Also phytoplankton absorption reflects local community size structure, taxonomic composition and physiological photoacclimation states. Non-algal absorption reflects variability in particle assemblages and river inputs with significant contribution in the NIR. The detailed results highlight limitations in the current parameterizations concerning global and coastal modelling of optical properties and specifically for the European coastal waters. Overall, the related dataset to the manuscript which already has been made publicly available, the presentation and discussion is very valuable. I only see minor corrections (listed below) necessary concerning adding discussions on methodological shortcomings (uncertainty discussion), the acknowledgment of related research (referencing) and the clarity in method (mainly data set descriptions). After these improvements together with a few other minor edits are introduced in a revision of the manuscript, I agree to accept the publication of this manuscript in Biogeosciences.
Specific Comments:
Add information or discussion about the CDOM and particulate absorption and pigment measurement uncertainty. As the method description indicates no triplicate measurements / samples were measured for the particulate absorption and pigment data, the uncertainties of these measurements have not been accounted for in the presetation of results and discussion. This at least must be added or information on estimated uncertainty from previous studies using the same method should be added. Similarly, for the CDOM absorption measurements triplicate measurements were performed, however with a 10 cm cuvette only it is expected that at low CDOM conc. these measurements have very high uncertainty (see Mannino, A., Novak, M. G., Nelson, N. B., Belz, M., Berthon, J.-F., Blough, N. V., et al.(2019). “Measurement protocol of absorption by chromophoric dissolved organic matter (CDOM) and other dissolved materials, in inherent optical property measurements and protocols: absorption coefﬁcient,” in IOCCG ocean optics and biogeochemistry protocols for satellite ocean colour sensor validation. Editors Mannino, A., Novak, M. G).

Make clear how the “coastlooc” data set is used in this manuscript (introduction, see also below) and in the method parts: add a short description (when data were sampled, where and what was measured), refer to its coverage. Which of the data set of coastlooc it is compared here and how the methodological aspects and regional sampling differ. How is the Massicotte et al. (2023) data set (COASTLOOC) related to the Babin et al. (2003) data set. Refer properly to the data set in the text and figure (captions). E.g. Fig. 4 b and 10b show HyperBoost and COASTLOOC data, at least the caption should make clear that HyperBOOST are the data from this study and COASTLOOC is based on Masciotte et al. (2023). Clarify in the text that/if Babin et al. (2003) is ased on the COASTLOOC data set. Zhen in line 175 you write about this study data set as Tara Europe data set, instead of HYPERBOOST. Can you refer once introduce in the manuscript just one name (either “this study”, “HyperBOOST” or “Tara Europe”) and then use it in the whole text and figures consistently.

Chapter 2 (most subchapters): I appreciate that most measurements have been done with triplicates ensuring to calculate a standard deviation. Instead of reporting just mean and standard deviation in the text, I suggest to add a table where for all parameters min., max., median, mean of standard deviation is reported (this could also be put into a supplement or maybe this information is provided in the Constanzo et al. submitted, but then update this reference and make clear where within this ms the information can be found and accessed). It also improves the discussion on limitation of the measurements (uncertainties) which should be introduced somewhere in the discussion. In case the following is not provided in Constanzo et al. (in revision), add more details on methodologies: a) add around line 114 details on how long the filters were stored before analysis in the lab (similarly also for the other parameters: SPM, POM, PIM, PIC, POC, pigments, particulate absorption); b) details for filtrations how much volume was filtered.

Line 335 to 350 discuss the regional differences in CDOM, DOM and aCDOM(443) to DOC ratio which is really interesting. However, it would benefit from more details on the relationship of spectral signatures and composition of the components: a) distinct spectral characterised is terrestrial DOM vs. maritime (line 338), b) what components cause a decrease in spectral slope from freshwater to marine (line 345), c) why does older CDOM (line 348) produce a lower spectral slope, and d) can you list what substances /molecule groups could be the non-absorbing compounds in the Med Sea basin (line 349) and what could be there sources?

Section 3.3 discusses very much in depth the signatures observed in aph (spectra, magnitude, aph*). I miss a short discussion about how other peaks than 443 and 675 nm are influenced by other pigments than chlorophyll-a. In addition, line 405 ff. “In the Baltic Sea, values tend to cluster near the upper confidence limit, suggesting high absorption efficiency.” contradicts what is shown in Fig. 5 for the Baltic Sea a*ph and how is discussed in lines 372ff.

Some references should be added to better acknowledge related research and developments and improve motivation and clarity of the text:

Line 65 ff. hyperspectral IOP retrievals with application to satellite data would further improve the motivation of the study to serve as a contribution to high quality validation data: - I suggest to checkout the latest IOCCG report (#22, https://doi.org/10.25607/OBP-2062, subchapter on spectral IOPs) to find suitable references to suitable satellite (hyperspectral) absorption products, e.g. for OLCI or PACE.

Line 68: In addition, previous validation efforts for complex water satellite absorption products (across water types and for the European waters explicitly) should be mentioned here as well: E.g., see Bracher et al. 2025 https://www.frontiersin.org/journals/remote-sensing/articles/10.3389/frsen.2025.1545664/full , Zibordi et al. 2023 doi: 1109/LGRS.2023.3298686). Also other simulation frame works need to be highlighted here: Loisel et al. 2023 doi: 10.5194/essd-15-3711-2023, Bi et al. 2023 doi: 10.3389/fmars.2023.1196352. Besides it is important to highlight the these simulated data sets already heavily are based on a lot of in-situ IOP data collections.

Line 83 ff., also the COASTLOOC data set (Masciotte et al. 2023) and the Röttgers et al. 2023 (doi: 1594/PANGAEA.950774) in situ absorption data sets should be mentioned here as historical compilations for European waters.

Line 94 and 95 add the references to TREC research programme and HyperBOOST project (e.g., referring to the specific websites , in case no peer-reviewed overviews exist).

Line 170 cites as the only work to use flow-cytometric data for parametrization, I think it is worth mentioning that after Uitz et al. 2006 many studies have adapted the DPA approach pigment-specific weighting coefficients based on the specific pigment data set used for parametrizations (e.g., for the Mediterranean Sea this was done in DiCicco et al. 2017 and 2025, see: doi: 10.3389/fmars.2017.00126 and https://doi.org/10.3390/rs17213586 ). Would be fair (and also improve the logic of the sentence) to refer to some of this work (at least the one concerning coastal European Waters)

Minor points:
Figure 2: add the regression line and R2 values. For POC vs. SPM two regression lines are provided, the caption should be more explicite about them.

Figure 3a

Line 361: provide full name for “Med”.

Figure 4a: x axis should start at 300 nm wavelength as then the regional differences are much more obvious. In addition, as from line 607 the contribution of the three optically active water components in the UV is discussed it requires to change the spectra shown also in Fig. 5 and 9 to start at least at 350 nm .

Line 441: remove “to the model”

Line 453: change to .. “At TChla concentrations …”

Fig. 5: add a,b, c, etc – so you can more precisely in the text refer to the subfigures. Als correct the x-axis for Med Sea 2 & 3 as they overlap (als in Fig. 9!, there also put station name Skagerak in 2 rows).

Fig. 9 also should show the measurements until 800 nm! Then the NIR part becomes much more obvious. The spectral structure would be visible as only the mean of 700 to 750 nm is taken as offset, as it is shown in Röttgers et al. 2014.

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Citation: https://doi.org/10.5194/egusphere-2026-4579-RC1
RC2: 'Comment on egusphere-2026-4579', Anonymous Referee #2, 10 Nov 2026 reply

The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2026/egusphere-2026-4579/egusphere-2026-4579-RC2-supplement.pdf
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Citation: https://doi.org/10.5194/egusphere-2026-4579-RC2
RC3: 'Comment on egusphere-2026-4579', Anonymous Referee #3, 12 Nov 2026 reply

Please see the attached PDF.

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Citation: https://doi.org/10.5194/egusphere-2026-4579-RC3

Paola Potin, Isabella Mayot, Chiara Santinelli, Emmanuel Boss, Vittorio E. Brando, Margherita Costanzo, Victor Martinez-Vicente, and David Doxaran

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Short summary

This study explores how light is absorbed by phytoplankton, non-algal particles, and colored dissolved organic matter in European coastal waters. Using measurements from 202 stations across diverse European marine regions, we reveal strong regional differences in optical properties. These results provide new insights into coastal optical variability and contribute to improving satellite-based observations and ocean color algorithms for monitoring complex coastal ecosystems.


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