the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Characterisation of uncertainties in an ocean radiative transfer model for the Black Sea through ensemble simulations
Abstract. In this paper, we investigate the influence of uncertainties in inherent optical properties on the modelling of radiometric quantities by an ocean radiative transfer model, in particular irradiance and reflectance. The radiative transfer model is coupled to a three-dimensional physical-biogeochemical model of the Black Sea. It describes the vertical propagation of incident irradiance within the water column along three streams in downward (direct and diffuse) and upward directions, with a spectral resolution of 25 nm in the visible range. The propagation of the irradiance streams is governed by the inherent optical properties of four major optically active constituents found in seawater and provided by the biogeochemical model: pure water, phytoplankton, non-algal particles and coloured dissolved organic matter. Sea surface reflectance is then derived as the ratio between simulated upward and downward irradiance streams, directly connecting the model with remote-sensed data. In this configuration, the coupling is in one-way: the radiative transfer model is only projecting model variables into the space of satellite observations, working as an observation operator. In the stochastic version of the model, uncertainties are injected in the form of random perturbations of inherent optical properties of water constituents. Different ensemble configurations are derived and their quality is assessed by comparison with in situ and remote-sensed observations.
We find that the modelling of the uncertainties in the radiative model parameterisation allows to simulate distributions of radiative fields that are partially consistent with observations. Ensemble quality is consistent with remote-sensed reflectance data in summer and autumn, especially in the central parts of basin. The quality of the ensemble is lower in winter and early spring, suggesting the existence of another major source of uncertainty, or that the quality of the deterministic solution is insufficient. CDOM dominates absorption in short wavebands with relatively high uncertainty that influences irradiance and reflectance outputs. This dominant role calls better representation of CDOM to improve model calibration. Contributions from phytoplankton and non-algal particles are more significant for (back-)scattering. The results of this paper suggest that the integration of a radiative transfer model into a physical-biogeochemical model would be beneficial for calibration, validation and data assimilation purposes, offering a better link between model variables and radiometric observations.
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RC1: 'Comment on egusphere-2024-3682', Anonymous Referee #1, 21 Mar 2025
Review of the manuscript “ Characterisation of uncertainties in an ocean radiative transfer model for the Black Sea through ensemble simulations” by Loïc Macé et al.
The authors investigate the influence of uncertainties in the inherent optical properties on the modelling of radiometric quantities adopting a radiative transfer model applied to the Black Sea. A detailed study is presented that considers several important optical components and discusses their role in light propagation. An advanced stochastic approach is used to understand the uncertainty and the relative contribution of plankton, nap, CDOM.
The results are clearly explained, the approach used is new and represents an important advance for biogeochemical modelling as it increases the realism of the models. Moreover, the analysis presented could be useful for the marine biogeochemical modelling community.
Below I list some minor revisions that I think could improve the text.
Pg2 lines 47-48 “Over the years, various models were developed with different approaches to refine the representation of light in models (Gregg and Casey, 2009; Mobley et al., 2009).” I would remove the repetition of models.
Pg 3 lines 69-70 “The penetration of the spectral irradiance is determined by the absorption and scattering properties of the medium that are derived from concentrations of optically active components, in 33 wavelengths.” I would substitute with “The penetration of the spectral irradiance is determined in 33 wavelengths by the absorption and scattering properties of the medium that are derived from concentrations of optically active components.”
Pg 6 Eq.4 I would give the unit of measurement of PAR. Since the previous section mentions the one-way coupling with the RT model, I would explain why the PAR is introduced by the RT model since there is no feedback with biogeochemistry.
Pg 15 Ensemble simulations. I would suggest that the authors create a table summarizing the properties of each of the 4 experiments.
Pg 17 line 426. “until in increases” should be “until it increases”.
Pg 18 Figure 6 is very small and very difficult to read. Units of measurement in the y-axis are missing. In general, many of the illustrations in this manuscript are very small, especially the fonts, and the fonts, size and legibility should be enlarged.
Pg 22 Figure 10, again the figure is very small. PAR should normally be expressed in quanta, and the PAR data from the BGC Argo float is also normally expressed in quanta. How did you convert to have W/m2? Perhaps the conversion formula could explain the discrepancy in PAR in Figure 10?
Pg 22 lines 513- 521 Rank diagrams should be explained in more detail so that they are fully understandable, especially for the readers without expertise in ensemble modelling.
Pg 22 lin 524 iis the reference to Fig. 9 correct? The matching between model and data in Fig. 9 are very good, so the comment is unclear.
Citation: https://doi.org/10.5194/egusphere-2024-3682-RC1 - AC1: 'Reply on RC1', Loïc Macé, 02 Apr 2025
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RC2: 'Comment on egusphere-2024-3682', Anonymous Referee #2, 25 Mar 2025
Review of “Characterisation of uncertainties in an ocean radiative transfer model for the Black Sea through ensemble simulations” by Loïc Macé et al.
The authors use a biogeochemical ocean model coupled one-way to a 3 stream radiative transfer model to show how modelled chlorophyll based on modelled spectral reflectance band ratios are more consistent with both satellite ocean colour and biogeochemical Argo float data than chlorophyll estimates derived directly from their physical-biogeochemical coupled model system, NEMO-BAMHBI. They demonstrate that introducing uncertainties in the form of random perturbations of inherent optical properties of different water constituents, improves the simulated distributions of radiative fields. The study is focused only in the deep central areas of the Black Sea, due to the limitations of the CDOM forcing used in the experiment.
This is an excellent piece of work. It significantly advances our understanding of how inherent optical properties of water constituents can be used to constrain biogeochemical models, leading to improved modelled predictions. Moreover, it opens new possibilities for integrating biogeochemical modelling, in situ optical observations and ocean colour remote sensing. The authors also demonstrate that preliminary results from a two-way coupling test show even more promising results.
The paper is well organised and well thought out. The approach and methods are valid. Limitations and assumptions inherent in their approach are discussed in depth and perspectives for future work are provided. I would be happy to see this published in Biogeosciences. It is a very timely and welcome contribution which unifies in situ marine optics, satellite ocean colour and biogeochemical modelling communities.
I have listed some minor comments below for the authors to consider.
- All of the figures (except figure 1) should be bigger, with larger fonts on the labelling.
- A table summarizing the different reference and ensemble runs would be useful.
- Some references are missing, or in the wrong place.
- Line 36: add Cahill et al., 2008, https://doi.org/10.1029/2008GL033595
- Line 49: add Bissett et al., 1999, https://doi.org/10.1016/S0967-0637(98)00063-6
- Dutkiewicz et al., 2015 should be referenced earlier, I think, line 59 after the sentence “In recent years, … reflectance (Dutkiewicz et al., 2015)
- In places, the English should be improved for better understanding, e.g.
- Line 39: “They can be described by the absorption and (back-) scattering spectra of each water …” instead of “They consist in absorption and …”
- Lines 67-68: at the end of the sentence “It solves the spectral wavebands corresponding to those typically used in remote sensing” add an example of what these wavebands are?
- Lines 86 – 89: Suggest converting the following into a numbered list, easier to comprehend sequence of analysis. “We first assess the effect of … that are consistent with observations.”
- Line 96: change last sentence to something like: “Finally in section 5, we discuss the limitations and assumptions of the study and provide an outlook for future work.”
- Line 109: change to “ … solved with NEMO 4.2 which is online coupled to the biogeochemical model.”
- Line 143: change to “Attenuation coefficients are derived from absorption …”.
- Lines 169 – 172: this paragraph appears without any explanation, should be qualified with a statement which explains why the product is mentioned, e.g. to validate the modelled reflectances.
- Lines 179-181: explain more clearly ecological reasons for choosing the band-ratio algorithm over the NN approach. Your study is focused on waters where the reflectance signal is dominated by phytoplankton, for example?
- Lines 207 – 208: change to “ … solved in BAMHBI: these are large flagellates ….and diatoms, all of which are the dominant species in the Black Sea”
- Line 249: change to “When run over the Black Sea, ….”
- Line 260: change to “… water column, the water constituent IOPs would not be altered.”
- Lines 365 – 371: add table summarizing different simulations.
- Line 426: change to “ … until it increases again …”
- Line 430: change to “… at 555 nm, as its contribution to …”
- Lines 447 - 448: change to “… phytoplankton early in the year with a lower contribution of CDOM in the ensemble spread.”
- Line 457: change to “ … gradually increases with depth …”
- Line 562: “surface chlorophyll is defined as the average concentration over the top 10m.” Is this based on some average of the 1st optical depth? Or? Maybe elaborate a little on this choice of depth over which to integrate the data.
Citation: https://doi.org/10.5194/egusphere-2024-3682-RC2 - AC2: 'Reply on RC2', Loïc Macé, 02 Apr 2025
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