the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A compilation of global bio-optical in situ data for ocean-colour satellite applications – version three
- 1MARE - Marine and Environmental Sciences Centre, Faculdade de Ciências, Universidade de Lisboa, Campo Grande, 1749-016 Lisboa, Portugal
- 2Plymouth Marine Laboratory, Plymouth, PL1 3DH, UK
- 3EUMETSAT, Eumetsat-Allee 1, 64295 Darmstadt, Germany
- 4Sorbonne Université, CNRS, Laboratoire d'Océanographie de Villefranche, LOV, F-06230 Villefranche-sur-Mer, France
- 5Remote Sensing and Satellite Research Group, School of Earth and Planetary Sciences, Curtin University, Perth, WA 6845, Australia
- 6University of Southern Mississippi, Stennis Space Center, MS, USA
- 7Bigelow Laboratory for Ocean Sciences, 60 Bigelow Dr., East Boothbay, ME 04544, Maine, USA
- 8ARGANS Ltd, UK
- 9CSIRO Oceans and Atmosphere, Australia
- 10Australian Research Data Commons
- 11Bayworld Centre for Research and Education, Cape Town, South Africa
- 12Université du Québec à Rimouski, Rimouski (Québec), Canada
- 13European Commission, Joint Research Centre, Ispra, Italy
- 14Dokuz Eylul University, Institute of Marine Science and Technology, Izmir, Turkey
- 15Institute of Marine Research, Bergen, Norway
- 16Alfred-Wegener-Institute Helmholtz Centre for Polar and Marine Research, Bremerhaven, Germany
- 17Institute of Environmental Physics, University Bremen, Bremen, Germany
- 18CNR - ISMAR, Rome, Italy
- 19Monterey Bay Aquarium Research Institute, Moss Landing, CA, USA
- 20PLOCAN-Oceanic Platform of the Canary Islands. Carretera de Taliarte, 35214 Telde, Gran Canaria, Spain
- 21Naval Research Laboratory, Stennis Space Center, MS, USA
- 22Scripps Institution of Oceanography, University of California San Diego, CA, USA
- 23Spanish Institute of Oceanography (IEO), Corazón de María 8, 28002 Madrid, Spain
- 24Plentziako Itsas Estazioa/ Euskal Herriko Unibetsitatea (PIE/EHU), Areatza z/g, 48620 Plentzia, Spain
- 25Environmental Research Institute, North Highland College, University of the Highlands and Islands, Thurso, Scotland, UK
- 26NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
- 27Earth Observation and Geoinformatics Division, National Space Research Institute (INPE), Sao Jose dos Campos, Brazil
- 28Operational Oceanography Group, Federal Maritime and Hydrographic Agency, Hamburg, Germany
- 29Department of Ecology, Environment and Plant Sciences, Stockholm University, 106 91 Stockholm, Sweden
- 30University of California Santa Cruz, Santa Cruz, CA USA
- 31Instituto del Mar del Perú
- 32Laboratoire d'Océanologie et de Géosciences, Université du Littoral-Côte-d'Opale, Université Lille, CNRS, UMR 8187, LOG, 32 avenue Foch, Wimereux, France
- 33Physics Dept, University of Strathclyde, Glasgow, G4 0NG, Scotland
- 34NASA Goddard Space Flight Center, Wallops Flight Facility, Wallops Island, VA, USA
- 35Institute for Marine Remote Sensing/ImaRS, College of Marine Science, University of South Florida, FL, USA
- 36Fisheries and Ecosystem Advisory Services, Marine Institute, Rinville – Oranmore, Galway, Ireland
- 37NOAA/NESDIS/STAR/SOCD, College Park, MD, USA
- 38Lyell Centre for Earth and Marine Science and Technology, Heriot-Watt University, Edinburgh, UK
- 39IFREMER Centre de Brest, Plouzane, France
- 40Ocean Biogeochemistry and Ecosystems, National Oceanography Centre, Waterfront Campus, Southampton, UK
- 41Biology Department, Woods Hole Oceanographic Institution, Woods Hole, MA, USA
- 42Harbor Branch Oceanographic Institute, Fort Pierce, FL, USA
- 43University of Miami, Coral Gables, FL, USA
- 44Royal Netherlands Institute for Sea Research, Texel, Netherlands
- 45Australian Antarctic Division; IMAS, University of Tasmania; and the Antarctic Climate and Ecosystems Cooperative Research Centre, Hobart, Australia
- 46Centre for Geography and Environmental Science, College of Life and Environmental Sciences, Penryn Campus, University of Exeter, Cornwall TR10 9FE, UK
- 47Science Systems and Applications, Inc., 10210 Greenbelt Road, Suite 600, Lanham, MD, USA
- 48Earth Research Institute, University of California, Santa Barbara, California, USA
- 49College of Marine Science, University of South Florida, 140 Seventh Avenue, South, St. Petersburg, FL 33701, USA
- 50School for Marine Science and Technology, University of Massachusetts Dartmouth, 836 South Rodney French Boulevard, New Bedford, MA 02744, USA
- 51Ocean Chemistry & Ecosystems Division, NOAA Atlantic Oceanographic and Meteorological Laboratory, Miami, FL USA
- 52Sorbonne Université, CNRS, Institut de la Mer de Villefranche, IMEV, F-06230 Villefranche-sur-Mer, France
- 53Institute of Carbon Cycles, Helmholtz-Zentrum Hereon, Geesthacht, Germany
- 54Marine Institute, Rinville, Oranmore, Galway, Ireland
- deceased
- 1MARE - Marine and Environmental Sciences Centre, Faculdade de Ciências, Universidade de Lisboa, Campo Grande, 1749-016 Lisboa, Portugal
- 2Plymouth Marine Laboratory, Plymouth, PL1 3DH, UK
- 3EUMETSAT, Eumetsat-Allee 1, 64295 Darmstadt, Germany
- 4Sorbonne Université, CNRS, Laboratoire d'Océanographie de Villefranche, LOV, F-06230 Villefranche-sur-Mer, France
- 5Remote Sensing and Satellite Research Group, School of Earth and Planetary Sciences, Curtin University, Perth, WA 6845, Australia
- 6University of Southern Mississippi, Stennis Space Center, MS, USA
- 7Bigelow Laboratory for Ocean Sciences, 60 Bigelow Dr., East Boothbay, ME 04544, Maine, USA
- 8ARGANS Ltd, UK
- 9CSIRO Oceans and Atmosphere, Australia
- 10Australian Research Data Commons
- 11Bayworld Centre for Research and Education, Cape Town, South Africa
- 12Université du Québec à Rimouski, Rimouski (Québec), Canada
- 13European Commission, Joint Research Centre, Ispra, Italy
- 14Dokuz Eylul University, Institute of Marine Science and Technology, Izmir, Turkey
- 15Institute of Marine Research, Bergen, Norway
- 16Alfred-Wegener-Institute Helmholtz Centre for Polar and Marine Research, Bremerhaven, Germany
- 17Institute of Environmental Physics, University Bremen, Bremen, Germany
- 18CNR - ISMAR, Rome, Italy
- 19Monterey Bay Aquarium Research Institute, Moss Landing, CA, USA
- 20PLOCAN-Oceanic Platform of the Canary Islands. Carretera de Taliarte, 35214 Telde, Gran Canaria, Spain
- 21Naval Research Laboratory, Stennis Space Center, MS, USA
- 22Scripps Institution of Oceanography, University of California San Diego, CA, USA
- 23Spanish Institute of Oceanography (IEO), Corazón de María 8, 28002 Madrid, Spain
- 24Plentziako Itsas Estazioa/ Euskal Herriko Unibetsitatea (PIE/EHU), Areatza z/g, 48620 Plentzia, Spain
- 25Environmental Research Institute, North Highland College, University of the Highlands and Islands, Thurso, Scotland, UK
- 26NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
- 27Earth Observation and Geoinformatics Division, National Space Research Institute (INPE), Sao Jose dos Campos, Brazil
- 28Operational Oceanography Group, Federal Maritime and Hydrographic Agency, Hamburg, Germany
- 29Department of Ecology, Environment and Plant Sciences, Stockholm University, 106 91 Stockholm, Sweden
- 30University of California Santa Cruz, Santa Cruz, CA USA
- 31Instituto del Mar del Perú
- 32Laboratoire d'Océanologie et de Géosciences, Université du Littoral-Côte-d'Opale, Université Lille, CNRS, UMR 8187, LOG, 32 avenue Foch, Wimereux, France
- 33Physics Dept, University of Strathclyde, Glasgow, G4 0NG, Scotland
- 34NASA Goddard Space Flight Center, Wallops Flight Facility, Wallops Island, VA, USA
- 35Institute for Marine Remote Sensing/ImaRS, College of Marine Science, University of South Florida, FL, USA
- 36Fisheries and Ecosystem Advisory Services, Marine Institute, Rinville – Oranmore, Galway, Ireland
- 37NOAA/NESDIS/STAR/SOCD, College Park, MD, USA
- 38Lyell Centre for Earth and Marine Science and Technology, Heriot-Watt University, Edinburgh, UK
- 39IFREMER Centre de Brest, Plouzane, France
- 40Ocean Biogeochemistry and Ecosystems, National Oceanography Centre, Waterfront Campus, Southampton, UK
- 41Biology Department, Woods Hole Oceanographic Institution, Woods Hole, MA, USA
- 42Harbor Branch Oceanographic Institute, Fort Pierce, FL, USA
- 43University of Miami, Coral Gables, FL, USA
- 44Royal Netherlands Institute for Sea Research, Texel, Netherlands
- 45Australian Antarctic Division; IMAS, University of Tasmania; and the Antarctic Climate and Ecosystems Cooperative Research Centre, Hobart, Australia
- 46Centre for Geography and Environmental Science, College of Life and Environmental Sciences, Penryn Campus, University of Exeter, Cornwall TR10 9FE, UK
- 47Science Systems and Applications, Inc., 10210 Greenbelt Road, Suite 600, Lanham, MD, USA
- 48Earth Research Institute, University of California, Santa Barbara, California, USA
- 49College of Marine Science, University of South Florida, 140 Seventh Avenue, South, St. Petersburg, FL 33701, USA
- 50School for Marine Science and Technology, University of Massachusetts Dartmouth, 836 South Rodney French Boulevard, New Bedford, MA 02744, USA
- 51Ocean Chemistry & Ecosystems Division, NOAA Atlantic Oceanographic and Meteorological Laboratory, Miami, FL USA
- 52Sorbonne Université, CNRS, Institut de la Mer de Villefranche, IMEV, F-06230 Villefranche-sur-Mer, France
- 53Institute of Carbon Cycles, Helmholtz-Zentrum Hereon, Geesthacht, Germany
- 54Marine Institute, Rinville, Oranmore, Galway, Ireland
- deceased
Abstract. A global in-situ data set for validation of ocean-colour products from the ESA Ocean Colour Climate Change Initiative (OC-CCI) is presented. This version of the compilation, starting in 1997, now extends to 2021, which is important for the validation of the most recent satellite optical sensors such as Sentinel 3B OLCI and NOAA-20 VIIRS. The data set comprises in-situ observations of the following variables: spectral remote-sensing reflectance, concentration of chlorophyll-a, spectral inherent optical properties, spectral diffuse attenuation coefficient and total suspended matter. Data were obtained from multi-project archives acquired via open internet services, or from individual projects, acquired directly from data providers. Methodologies were implemented for homogenisation, quality control and merging of all data. Minimal changes were made on the original data, other than conversion to a standard format, elimination of some points after quality control and averaging of observations that were close in time and space. The result is a merged table available in text format. Overall, the size of the data set grew with 151,673 rows, with each row representing a unique station in space and time (cf 136,250 rows in previous version; Valente et al., 2019). Observations of remote-sensing reflectance increased to 68,641 (cf 59,781 in previous version; Valente et al., 2019). There was also a near tenfold increase in chlorophyll data since 2016. Metadata of each in situ measurement (original source, cruise or experiment, principal investigator) are included in the final table. By making the metadata available, provenance is better documented, and it is also possible to analyse each set of data separately. The compiled data are available at https://doi.pangaea.de/10.1594/PANGAEA.941318 (Valente et al., 2022).
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André Valente et al.
Status: closed
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CC1: 'Comment on essd-2022-159', Francis Gohin, 31 May 2022
Providing easy-to-use datasets to a wide community is an excellent initiative. Regarding the file of chlorophyll concentrations, Ifremer's data are available through the ices collection (stations of the french coastal REPHY network, up to 2007) and through the mermaid collection. In this latter group, mermaid_MAREL-carnot, mermaid_MAREL-itroise and mermaid_MAREL-vilaine data are derived from fluorescence measured at the MAREL instrumented buoys. Although most of these MAREL data are of good quality I would suggest suppressing them as they are not free of errors, particularly in case of biofouling of the sensors.
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AC1: 'Reply on CC1', Andre Valente, 25 Aug 2022
Thank you very much for the comments. Please find below the responses to each of your comments.
Comment 1
Providing easy-to-use datasets to a wide community is an excellent initiative.
Response:
Thank you.
Comment 2
Regarding the file of chlorophyll concentrations, Ifremer's data are available through the ices collection (stations of the french coastal REPHY network, up to 2007) and through the mermaid collection. In this latter group, mermaid_MAREL-carnot, mermaid_MAREL-itroise and mermaid_MAREL-vilaine data are derived from fluorescence measured at the MAREL instrumented buoys. Although most of these MAREL data are of good quality I would suggest suppressing them as they are not free of errors, particularly in case of biofouling of the sensors.
Response
Thank you for bringing this to our attention, we were not aware of this issue. The mentioned data will be removed from the dataset in the revised version of the manuscript.
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AC1: 'Reply on CC1', Andre Valente, 25 Aug 2022
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RC1: 'Comment on essd-2022-159', Anonymous Referee #1, 10 Jul 2022
This is an important effort because this kind of database will contribute to validate various ocean colour products and improve their interoperability. The continuous update is also meaningful.
In this revision, aph was especially increased and the grids of wavelengths became increased. I’ve read the data files and operated them, and did not have any problem.
In the operational point of view, it was not easy to read the increasing text table (e.g., about 1000 columns for Rrs and 2500 columns for IOP), so I hope it will be stored by NetCDF (or other better ways) in the future version.
I just find a minor mistypo:
Figure 2: unit of rrs seems wrong: m^-1 should be sr^-1
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AC2: 'Reply on RC1', Andre Valente, 25 Aug 2022
Thank you very much for the comments. Please find below the responses to each of your comments.
Comment 1
This is an important effort because this kind of database will contribute to validate various ocean colour products and improve their interoperability. The continuous update is also meaningful.
Response
Thank you
Comment 2
In this revision, aph was especially increased and the grids of wavelengths became increased. I’ve read the data files and operated them, and did not have any problem.
In the operational point of view, it was not easy to read the increasing text table (e.g., about 1000 columns for Rrs and 2500 columns for IOP), so I hope it will be stored by NetCDF (or other better ways) in the future version.
Response
Regarding the data format, we have chosen to keep the CSV format, as it has allowed for a wider range of users to manipulate the dataset, as many users still cannot manipulate other types of files, such as NETCDF files. The recommendation of changing the data format to NETCDF in future versions will be considered.
Comment 3
I just find a minor mistypo:
Figure 2: unit of rrs seems wrong: m^-1 should be sr^-1
Response:
The typo in Figure 2 will be corrected in the revised version of the manuscript.
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RC3: 'Reply on AC2', Anonymous Referee #1, 26 Aug 2022
Thank you for your reply.
About the format issue, I understand your direction. Off course, it is good to choose by considering convenience of majority of the users.
- AC5: 'Reply on RC3', Andre Valente, 03 Nov 2022
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RC3: 'Reply on AC2', Anonymous Referee #1, 26 Aug 2022
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AC2: 'Reply on RC1', Andre Valente, 25 Aug 2022
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RC2: 'Comment on essd-2022-159', Andre Belo-Couto, 08 Aug 2022
In my opinion the paper is very well crafted an of high very quality, as it is the dataset.
The dataset is a unique and of high interest for the ocean colour community.
However,
I do have a concern,
This paper is regarding a 3rd version of the dataset, meaning that there are already 2 other papers published previously regarding the this dataset. Hence, the dataset is not new, but updated.
As such, this paper shows that the number of observations for the recent years as increased significantly when comparing with the previous version(V2).
This paper, however, is basically a copy from the V2 paper (Valente et al. 2019) with some additional paragraphs to let the reader know how much new data there is. Even the figures, 16 of them, are the same as in the previous paper (except figure 1). Which might be the intentional, as it is indeed an update on the description of a previous version of the same dataset.
I don't know the policy of the journal regarding the publication of papers that describe/discuss the updated of a dataset.
In my view, it would be more interesting, and beneficial to the reader (and public in general), to present and discuss how the new update changed the past version(s) of the dataset. Whereas there would be no need to maintain the same text/discussions/figures from previous papers. As this knowledge is already published, thus, it already has a doi to be referred to. Unless, of course these results/discussions changed due to the new update.
Further general comments below:
. it would be useful to know up front, i.e. in the introduction, how much data from which project was added in this new version of the dataset.
. the new dataset is improved by
. v3 uses AERONET-OC v3
. more observations
. the description of a few datasets do not add anything from the previous dataset paper, for e.g., ARCSSPP does not add anything to a new version as it only provides data from 1954 to 2006
. the same as above for:
. GeP&CO it ran from 1999 to 2002
. BARENTSSEA 1997 to 2013
. BIOCHEM 1997 to 2014
. ESTOC from 1994 to 2011
. Figure 1 doesn’t seem to cover the beginning of the data range wavelengths, i.e., 313 nm, it seems to start between 360 and 340 nm
. ~15% increase of data from Valente et al 2019, from previous existing stations. This information should be in the introduction, so we know up front what the update is.
. Results section (copy from the v2 paper + some paragraphs stating that there is an increase of obs. in the current version)
4th paragraph - some general results on chla (as in V2 paper)
+ a sentence on increasing n obs between V2 and V3 (+5% fluor, +16% hplc)
. question: (not that it is significant, but) why are the limits for both types of chl methods different? I.e.,
0.001 < chla_fluor < 100
0.002 < chla_hplc < 99.8
6th paragraph - relationship between rrs ratio with chla
Id it change between different versions? If so, any mechanism that could explain it? (for e.g., predominance of El Nino/La Nina phases during the new coverage?)
. it would be interesting to see if some descriptive relationship statistics evolution between versions, for e.g. coefficient of correlation, between the nasa algorithms and the rrs/chla ratio found in the V1, V2 and V3
7th paragraph - general results of aph, adg, bbp
+ only new data for aph (+30%)
8th paragraph - Kd didn't change (as in V2 paper, no need to repeat, already discussed)
9ht paragraph – as in V2 paper
F1 is new from V2 paper
F2 to F 16 are as in V2 paper (with some, F6, F12, F13, F16 showing statistic values slightly changed)
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AC3: 'Reply on RC2', Andre Valente, 25 Aug 2022
Thank you very much for the comments. Please find below the responses to each of your comments.
Comment 1
In my opinion the paper is very well crafted an of high very quality, as it is the dataset.
The dataset is a unique and of high interest for the ocean colour community.
Response
Thank you.
Comment 2
However,
I do have a concern,
This paper is regarding a 3rd version of the dataset, meaning that there are already 2 other papers published previously regarding the this dataset. Hence, the dataset is not new, but updated.
As such, this paper shows that the number of observations for the recent years as increased significantly when comparing with the previous version(V2).
This paper, however, is basically a copy from the V2 paper (Valente et al. 2019) with some additional paragraphs to let the reader know how much new data there is. Even the figures, 16 of them, are the same as in the previous paper (except figure 1). Which might be the intentional, as it is indeed an update on the description of a previous version of the same dataset.
I don't know the policy of the journal regarding the publication of papers that describe/discuss the updated of a dataset.
In my view, it would be more interesting, and beneficial to the reader (and public in general), to present and discuss how the new update changed the past version(s) of the dataset. Whereas there would be no need to maintain the same text/discussions/figures from previous papers. As this knowledge is already published, thus, it already has a doi to be referred to. Unless, of course these results/discussions changed due to the new update.
Response
Regarding this main concern of using a similar structure (text/figures) of previous versions, we followed the policy of ESSD, and specifically we followed the ESSD paper "Global Carbon Budget", which is updated every year (https://doi.org/10.5194/essd-12-3269-2020). In each update of that paper the text and figures remain essentially the same. This was considered to be a valid approach for an updated dataset - the updated dataset accumulates all previous co-authors and data, while maintaining its structure (text/figures) and describing the new data, and becomes the new dataset to be cited (i.e., only the last version of the dataset needs to be cited). In our specific case, the updated version 3 does not adds new data sources – it updates/adds data from the previous 27 data sources. Thus the methods, and the data sources, need to be essentially the same. It should also be noted that the present version 3, although similar, is not a copy of v2 as there has been numerous changes across the text to improve the paper and to highlight the new data and changes regarding previous version (see track-changes in https://essd.copernicus.org/preprints/essd-2022-159/essd-2022-159-supplement.pdf). It is also noted that an additional effort to further reduce the similarity of v3 compared to v2 has already been carried out during the process of submitting to ESSD.
Comment 3
Further general comments below:
. it would be useful to know up front, i.e. in the introduction, how much data from which project was added in this new version of the dataset.
Response
An upfront description of how much data from which project was added in the present version, will be added to the revised version of the manuscript. This will be added to the third paragraph of section 2.1 (where the updated data is now currently stated) and not in the introduction since the compiled variables and data sources should to be firstly introduced (currently in the first paragraph of section 2.1).
Comment 4
. the new dataset is improved by
. v3 uses AERONET-OC v3
. more observations
. the description of a few datasets do not add anything from the previous dataset paper, for e.g., ARCSSPP does not add anything to a new version as it only provides data from 1954 to 2006
. the same as above for:
. GeP&CO it ran from 1999 to 2002
. BARENTSSEA 1997 to 2013
. BIOCHEM 1997 to 2014
. ESTOC from 1994 to 2011
Response
As noted in the response to the main concern (comment 2), the followed strategy is to present all datasets, including those that were not updated, keeping a similar structure of the paper.
Comment 5:
. Figure 1 doesn’t seem to cover the beginning of the data range wavelengths, i.e., 313 nm, it seems to start between 360 and 340 nm
Response
This will be corrected in the revised version of the manuscript.
Comment 6
. ~15% increase of data from Valente et al 2019, from previous existing stations. This information should be in the introduction, so we know up front what the update is.
Response
We will add this information to the third paragraph of section 2.1 (please see also response to comment 3).
Comment 7
. Results section (copy from the v2 paper + some paragraphs stating that there is an increase of obs. in the current version)
As it can be seen in the
4th paragraph - some general results on chla (as in V2 paper)
+ a sentence on increasing n obs between V2 and V3 (+5% fluor, +16% hplc)
Response
As noted in the response to the main concern (comment 2), the followed strategy is to present all datasets, including those that were not updated, keeping a similar structure of the paper.
Comment 8
. question: (not that it is significant, but) why are the limits for both types of chl methods different? I.e.,
0.001 < chla_fluor < 100
0.002 < chla_hplc < 99.8
Response
The limits are different because the lowest and highest values of the compiled chla_fluor and chla_hplc are different (these two variables are measured with different protocols thus they do not need to have the same range).
Comment 9
6th paragraph - relationship between rrs ratio with chla
Id it change between different versions? If so, any mechanism that could explain it? (for e.g., predominance of El Nino/La Nina phases during the new coverage?)
. it would be interesting to see if some descriptive relationship statistics evolution between versions, for e.g. coefficient of correlation, between the nasa algorithms and the rrs/chla ratio found in the V1, V2 and V3
Response
Compared to the previous version, only a few concurrent Rrs_ratio VS Chl data points were added (N=13), which corresponds to a quite small 0.13 % increase. As already stated in the text: “Compared to the previous version (Valente et al., 2019), the relations between maximum band ratio and chlorophyll are not altered by the additional number of concurrent observations (N=13).”
Comment 8
7th paragraph - general results of aph, adg, bbp
+ only new data for aph (+30%)
8th paragraph - Kd didn't change (as in V2 paper, no need to repeat, already discussed)
9ht paragraph – as in V2 paper
F1 is new from V2 paper
F2 to F 16 are as in V2 paper (with some, F6, F12, F13, F16 showing statistic values slightly changed)
Response
As noted in the response to the main concern (comment 2), the followed strategy is to present all datasets, including those that were not updated, keeping a similar structure of the paper.
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RC4: 'Reply on AC3', Andre Belo-Couto, 26 Aug 2022
Very well then. If, within this manuscript, you are following journal's policy on how to describe dataset update. And, given that you do provide a specific example of a previous published paper of this ame journal that does so, with the same structure and ideology. I believe that this paper is in very good shape to be published, as it is of high quality standards and most wanted by the Ocean Colour comunity to refere to the most updated version of this unique dataset (assuming that the small typos/errors are corrected).
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RC4: 'Reply on AC3', Andre Belo-Couto, 26 Aug 2022
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AC3: 'Reply on RC2', Andre Valente, 25 Aug 2022
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RC5: 'Comment on essd-2022-159', Anonymous Referee #3, 09 Sep 2022
The paper describes a compilation of bio-optical in situ data with global coverage, which spans from 1997, now to 2021 (i.e. extended from 2018 to 2021). As this period corresponds to a period of a continuous satellite ocean-colour data record, this is a valuable contribution for validation of satellite data from various missions, including the new ESA’s Sentinel-3 OLCI and NOAA-20 VIIRS. The work is an update to data originally published in Valente et al., 2019.
Measurements of the following variables were considered: remote sensing reflectance, chlorophyll-a concentration, algal pigment absorption coefficient, detrital and coloured dissolved organic matter absorption coefficient, particle backscattering coefficient, diffuse attenuation coefficient for downward irradiance and total suspended matter.
As one of the largest data set collections of chlorophyll-a concentrations ever made public, it becomes a reference for the climate and biological scientific communities concerned with Ocean Colour. The primary objective is thus to make the measurements easily accessible by the broader scientific community.
As mentioned by another reviewer, the data set could benefit from being available in NETCDF format, these days accessable to wider audience. In addition, this reviewer suggest to make use of modern document file tools to generate a map with the measurement values available by interactive cursor pointing (over the map). Alternatively, the authors could consider making the data set available in tools such as “NASA WORLDVIEW” and/or the European “Ocean Virtual Laboratory”. This would make a nice addition to the publication.
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AC4: 'Reply on RC5', Andre Valente, 03 Nov 2022
Comment 1
The paper describes a compilation of bio-optical in situ data with global coverage, which spans from 1997, now to 2021 (i.e. extended from 2018 to 2021). As this period corresponds to a period of a continuous satellite ocean-colour data record, this is a valuable contribution for validation of satellite data from various missions, including the new ESA’s Sentinel-3 OLCI and NOAA-20 VIIRS. The work is an update to data originally published in Valente et al., 2019.
Measurements of the following variables were considered: remote sensing reflectance, chlorophyll-a concentration, algal pigment absorption coefficient, detrital and coloured dissolved organic matter absorption coefficient, particle backscattering coefficient, diffuse attenuation coefficient for downward irradiance and total suspended matter.
As one of the largest data set collections of chlorophyll-a concentrations ever made public, it becomes a reference for the climate and biological scientific communities concerned with Ocean Colour. The primary objective is thus to make the measurements easily accessible by the broader scientific community.
Response
Thank you for the comment
Comment 2
As mentioned by another reviewer, the data set could benefit from being available in NETCDF format, these days accessable to wider audience.
Response
The original CSV text tables were converted to the NETCDF format and supplied as auxiliary files. The data files in netCDF format are now available from PANGAEA.
Comment 3
In addition, this reviewer suggest to make use of modern document file tools to generate a map with the measurement values available by interactive cursor pointing (over the map). Alternatively, the authors could consider making the data set available in tools such as “NASA WORLDVIEW” and/or the European “Ocean Virtual Laboratory”. This would make a nice addition to the publication.
Response
We were unable to provide a bespoke visualisation due to completion of this part of the project; however, by providing NETCDFs researchers may perform what the reviewer suggests by ingesting the data into a visualisation system of their choice, using subsets where appropriate, relevant to their own applications.
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AC4: 'Reply on RC5', Andre Valente, 03 Nov 2022
Status: closed
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CC1: 'Comment on essd-2022-159', Francis Gohin, 31 May 2022
Providing easy-to-use datasets to a wide community is an excellent initiative. Regarding the file of chlorophyll concentrations, Ifremer's data are available through the ices collection (stations of the french coastal REPHY network, up to 2007) and through the mermaid collection. In this latter group, mermaid_MAREL-carnot, mermaid_MAREL-itroise and mermaid_MAREL-vilaine data are derived from fluorescence measured at the MAREL instrumented buoys. Although most of these MAREL data are of good quality I would suggest suppressing them as they are not free of errors, particularly in case of biofouling of the sensors.
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AC1: 'Reply on CC1', Andre Valente, 25 Aug 2022
Thank you very much for the comments. Please find below the responses to each of your comments.
Comment 1
Providing easy-to-use datasets to a wide community is an excellent initiative.
Response:
Thank you.
Comment 2
Regarding the file of chlorophyll concentrations, Ifremer's data are available through the ices collection (stations of the french coastal REPHY network, up to 2007) and through the mermaid collection. In this latter group, mermaid_MAREL-carnot, mermaid_MAREL-itroise and mermaid_MAREL-vilaine data are derived from fluorescence measured at the MAREL instrumented buoys. Although most of these MAREL data are of good quality I would suggest suppressing them as they are not free of errors, particularly in case of biofouling of the sensors.
Response
Thank you for bringing this to our attention, we were not aware of this issue. The mentioned data will be removed from the dataset in the revised version of the manuscript.
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AC1: 'Reply on CC1', Andre Valente, 25 Aug 2022
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RC1: 'Comment on essd-2022-159', Anonymous Referee #1, 10 Jul 2022
This is an important effort because this kind of database will contribute to validate various ocean colour products and improve their interoperability. The continuous update is also meaningful.
In this revision, aph was especially increased and the grids of wavelengths became increased. I’ve read the data files and operated them, and did not have any problem.
In the operational point of view, it was not easy to read the increasing text table (e.g., about 1000 columns for Rrs and 2500 columns for IOP), so I hope it will be stored by NetCDF (or other better ways) in the future version.
I just find a minor mistypo:
Figure 2: unit of rrs seems wrong: m^-1 should be sr^-1
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AC2: 'Reply on RC1', Andre Valente, 25 Aug 2022
Thank you very much for the comments. Please find below the responses to each of your comments.
Comment 1
This is an important effort because this kind of database will contribute to validate various ocean colour products and improve their interoperability. The continuous update is also meaningful.
Response
Thank you
Comment 2
In this revision, aph was especially increased and the grids of wavelengths became increased. I’ve read the data files and operated them, and did not have any problem.
In the operational point of view, it was not easy to read the increasing text table (e.g., about 1000 columns for Rrs and 2500 columns for IOP), so I hope it will be stored by NetCDF (or other better ways) in the future version.
Response
Regarding the data format, we have chosen to keep the CSV format, as it has allowed for a wider range of users to manipulate the dataset, as many users still cannot manipulate other types of files, such as NETCDF files. The recommendation of changing the data format to NETCDF in future versions will be considered.
Comment 3
I just find a minor mistypo:
Figure 2: unit of rrs seems wrong: m^-1 should be sr^-1
Response:
The typo in Figure 2 will be corrected in the revised version of the manuscript.
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RC3: 'Reply on AC2', Anonymous Referee #1, 26 Aug 2022
Thank you for your reply.
About the format issue, I understand your direction. Off course, it is good to choose by considering convenience of majority of the users.
- AC5: 'Reply on RC3', Andre Valente, 03 Nov 2022
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RC3: 'Reply on AC2', Anonymous Referee #1, 26 Aug 2022
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AC2: 'Reply on RC1', Andre Valente, 25 Aug 2022
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RC2: 'Comment on essd-2022-159', Andre Belo-Couto, 08 Aug 2022
In my opinion the paper is very well crafted an of high very quality, as it is the dataset.
The dataset is a unique and of high interest for the ocean colour community.
However,
I do have a concern,
This paper is regarding a 3rd version of the dataset, meaning that there are already 2 other papers published previously regarding the this dataset. Hence, the dataset is not new, but updated.
As such, this paper shows that the number of observations for the recent years as increased significantly when comparing with the previous version(V2).
This paper, however, is basically a copy from the V2 paper (Valente et al. 2019) with some additional paragraphs to let the reader know how much new data there is. Even the figures, 16 of them, are the same as in the previous paper (except figure 1). Which might be the intentional, as it is indeed an update on the description of a previous version of the same dataset.
I don't know the policy of the journal regarding the publication of papers that describe/discuss the updated of a dataset.
In my view, it would be more interesting, and beneficial to the reader (and public in general), to present and discuss how the new update changed the past version(s) of the dataset. Whereas there would be no need to maintain the same text/discussions/figures from previous papers. As this knowledge is already published, thus, it already has a doi to be referred to. Unless, of course these results/discussions changed due to the new update.
Further general comments below:
. it would be useful to know up front, i.e. in the introduction, how much data from which project was added in this new version of the dataset.
. the new dataset is improved by
. v3 uses AERONET-OC v3
. more observations
. the description of a few datasets do not add anything from the previous dataset paper, for e.g., ARCSSPP does not add anything to a new version as it only provides data from 1954 to 2006
. the same as above for:
. GeP&CO it ran from 1999 to 2002
. BARENTSSEA 1997 to 2013
. BIOCHEM 1997 to 2014
. ESTOC from 1994 to 2011
. Figure 1 doesn’t seem to cover the beginning of the data range wavelengths, i.e., 313 nm, it seems to start between 360 and 340 nm
. ~15% increase of data from Valente et al 2019, from previous existing stations. This information should be in the introduction, so we know up front what the update is.
. Results section (copy from the v2 paper + some paragraphs stating that there is an increase of obs. in the current version)
4th paragraph - some general results on chla (as in V2 paper)
+ a sentence on increasing n obs between V2 and V3 (+5% fluor, +16% hplc)
. question: (not that it is significant, but) why are the limits for both types of chl methods different? I.e.,
0.001 < chla_fluor < 100
0.002 < chla_hplc < 99.8
6th paragraph - relationship between rrs ratio with chla
Id it change between different versions? If so, any mechanism that could explain it? (for e.g., predominance of El Nino/La Nina phases during the new coverage?)
. it would be interesting to see if some descriptive relationship statistics evolution between versions, for e.g. coefficient of correlation, between the nasa algorithms and the rrs/chla ratio found in the V1, V2 and V3
7th paragraph - general results of aph, adg, bbp
+ only new data for aph (+30%)
8th paragraph - Kd didn't change (as in V2 paper, no need to repeat, already discussed)
9ht paragraph – as in V2 paper
F1 is new from V2 paper
F2 to F 16 are as in V2 paper (with some, F6, F12, F13, F16 showing statistic values slightly changed)
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AC3: 'Reply on RC2', Andre Valente, 25 Aug 2022
Thank you very much for the comments. Please find below the responses to each of your comments.
Comment 1
In my opinion the paper is very well crafted an of high very quality, as it is the dataset.
The dataset is a unique and of high interest for the ocean colour community.
Response
Thank you.
Comment 2
However,
I do have a concern,
This paper is regarding a 3rd version of the dataset, meaning that there are already 2 other papers published previously regarding the this dataset. Hence, the dataset is not new, but updated.
As such, this paper shows that the number of observations for the recent years as increased significantly when comparing with the previous version(V2).
This paper, however, is basically a copy from the V2 paper (Valente et al. 2019) with some additional paragraphs to let the reader know how much new data there is. Even the figures, 16 of them, are the same as in the previous paper (except figure 1). Which might be the intentional, as it is indeed an update on the description of a previous version of the same dataset.
I don't know the policy of the journal regarding the publication of papers that describe/discuss the updated of a dataset.
In my view, it would be more interesting, and beneficial to the reader (and public in general), to present and discuss how the new update changed the past version(s) of the dataset. Whereas there would be no need to maintain the same text/discussions/figures from previous papers. As this knowledge is already published, thus, it already has a doi to be referred to. Unless, of course these results/discussions changed due to the new update.
Response
Regarding this main concern of using a similar structure (text/figures) of previous versions, we followed the policy of ESSD, and specifically we followed the ESSD paper "Global Carbon Budget", which is updated every year (https://doi.org/10.5194/essd-12-3269-2020). In each update of that paper the text and figures remain essentially the same. This was considered to be a valid approach for an updated dataset - the updated dataset accumulates all previous co-authors and data, while maintaining its structure (text/figures) and describing the new data, and becomes the new dataset to be cited (i.e., only the last version of the dataset needs to be cited). In our specific case, the updated version 3 does not adds new data sources – it updates/adds data from the previous 27 data sources. Thus the methods, and the data sources, need to be essentially the same. It should also be noted that the present version 3, although similar, is not a copy of v2 as there has been numerous changes across the text to improve the paper and to highlight the new data and changes regarding previous version (see track-changes in https://essd.copernicus.org/preprints/essd-2022-159/essd-2022-159-supplement.pdf). It is also noted that an additional effort to further reduce the similarity of v3 compared to v2 has already been carried out during the process of submitting to ESSD.
Comment 3
Further general comments below:
. it would be useful to know up front, i.e. in the introduction, how much data from which project was added in this new version of the dataset.
Response
An upfront description of how much data from which project was added in the present version, will be added to the revised version of the manuscript. This will be added to the third paragraph of section 2.1 (where the updated data is now currently stated) and not in the introduction since the compiled variables and data sources should to be firstly introduced (currently in the first paragraph of section 2.1).
Comment 4
. the new dataset is improved by
. v3 uses AERONET-OC v3
. more observations
. the description of a few datasets do not add anything from the previous dataset paper, for e.g., ARCSSPP does not add anything to a new version as it only provides data from 1954 to 2006
. the same as above for:
. GeP&CO it ran from 1999 to 2002
. BARENTSSEA 1997 to 2013
. BIOCHEM 1997 to 2014
. ESTOC from 1994 to 2011
Response
As noted in the response to the main concern (comment 2), the followed strategy is to present all datasets, including those that were not updated, keeping a similar structure of the paper.
Comment 5:
. Figure 1 doesn’t seem to cover the beginning of the data range wavelengths, i.e., 313 nm, it seems to start between 360 and 340 nm
Response
This will be corrected in the revised version of the manuscript.
Comment 6
. ~15% increase of data from Valente et al 2019, from previous existing stations. This information should be in the introduction, so we know up front what the update is.
Response
We will add this information to the third paragraph of section 2.1 (please see also response to comment 3).
Comment 7
. Results section (copy from the v2 paper + some paragraphs stating that there is an increase of obs. in the current version)
As it can be seen in the
4th paragraph - some general results on chla (as in V2 paper)
+ a sentence on increasing n obs between V2 and V3 (+5% fluor, +16% hplc)
Response
As noted in the response to the main concern (comment 2), the followed strategy is to present all datasets, including those that were not updated, keeping a similar structure of the paper.
Comment 8
. question: (not that it is significant, but) why are the limits for both types of chl methods different? I.e.,
0.001 < chla_fluor < 100
0.002 < chla_hplc < 99.8
Response
The limits are different because the lowest and highest values of the compiled chla_fluor and chla_hplc are different (these two variables are measured with different protocols thus they do not need to have the same range).
Comment 9
6th paragraph - relationship between rrs ratio with chla
Id it change between different versions? If so, any mechanism that could explain it? (for e.g., predominance of El Nino/La Nina phases during the new coverage?)
. it would be interesting to see if some descriptive relationship statistics evolution between versions, for e.g. coefficient of correlation, between the nasa algorithms and the rrs/chla ratio found in the V1, V2 and V3
Response
Compared to the previous version, only a few concurrent Rrs_ratio VS Chl data points were added (N=13), which corresponds to a quite small 0.13 % increase. As already stated in the text: “Compared to the previous version (Valente et al., 2019), the relations between maximum band ratio and chlorophyll are not altered by the additional number of concurrent observations (N=13).”
Comment 8
7th paragraph - general results of aph, adg, bbp
+ only new data for aph (+30%)
8th paragraph - Kd didn't change (as in V2 paper, no need to repeat, already discussed)
9ht paragraph – as in V2 paper
F1 is new from V2 paper
F2 to F 16 are as in V2 paper (with some, F6, F12, F13, F16 showing statistic values slightly changed)
Response
As noted in the response to the main concern (comment 2), the followed strategy is to present all datasets, including those that were not updated, keeping a similar structure of the paper.
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RC4: 'Reply on AC3', Andre Belo-Couto, 26 Aug 2022
Very well then. If, within this manuscript, you are following journal's policy on how to describe dataset update. And, given that you do provide a specific example of a previous published paper of this ame journal that does so, with the same structure and ideology. I believe that this paper is in very good shape to be published, as it is of high quality standards and most wanted by the Ocean Colour comunity to refere to the most updated version of this unique dataset (assuming that the small typos/errors are corrected).
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RC4: 'Reply on AC3', Andre Belo-Couto, 26 Aug 2022
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AC3: 'Reply on RC2', Andre Valente, 25 Aug 2022
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RC5: 'Comment on essd-2022-159', Anonymous Referee #3, 09 Sep 2022
The paper describes a compilation of bio-optical in situ data with global coverage, which spans from 1997, now to 2021 (i.e. extended from 2018 to 2021). As this period corresponds to a period of a continuous satellite ocean-colour data record, this is a valuable contribution for validation of satellite data from various missions, including the new ESA’s Sentinel-3 OLCI and NOAA-20 VIIRS. The work is an update to data originally published in Valente et al., 2019.
Measurements of the following variables were considered: remote sensing reflectance, chlorophyll-a concentration, algal pigment absorption coefficient, detrital and coloured dissolved organic matter absorption coefficient, particle backscattering coefficient, diffuse attenuation coefficient for downward irradiance and total suspended matter.
As one of the largest data set collections of chlorophyll-a concentrations ever made public, it becomes a reference for the climate and biological scientific communities concerned with Ocean Colour. The primary objective is thus to make the measurements easily accessible by the broader scientific community.
As mentioned by another reviewer, the data set could benefit from being available in NETCDF format, these days accessable to wider audience. In addition, this reviewer suggest to make use of modern document file tools to generate a map with the measurement values available by interactive cursor pointing (over the map). Alternatively, the authors could consider making the data set available in tools such as “NASA WORLDVIEW” and/or the European “Ocean Virtual Laboratory”. This would make a nice addition to the publication.
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AC4: 'Reply on RC5', Andre Valente, 03 Nov 2022
Comment 1
The paper describes a compilation of bio-optical in situ data with global coverage, which spans from 1997, now to 2021 (i.e. extended from 2018 to 2021). As this period corresponds to a period of a continuous satellite ocean-colour data record, this is a valuable contribution for validation of satellite data from various missions, including the new ESA’s Sentinel-3 OLCI and NOAA-20 VIIRS. The work is an update to data originally published in Valente et al., 2019.
Measurements of the following variables were considered: remote sensing reflectance, chlorophyll-a concentration, algal pigment absorption coefficient, detrital and coloured dissolved organic matter absorption coefficient, particle backscattering coefficient, diffuse attenuation coefficient for downward irradiance and total suspended matter.
As one of the largest data set collections of chlorophyll-a concentrations ever made public, it becomes a reference for the climate and biological scientific communities concerned with Ocean Colour. The primary objective is thus to make the measurements easily accessible by the broader scientific community.
Response
Thank you for the comment
Comment 2
As mentioned by another reviewer, the data set could benefit from being available in NETCDF format, these days accessable to wider audience.
Response
The original CSV text tables were converted to the NETCDF format and supplied as auxiliary files. The data files in netCDF format are now available from PANGAEA.
Comment 3
In addition, this reviewer suggest to make use of modern document file tools to generate a map with the measurement values available by interactive cursor pointing (over the map). Alternatively, the authors could consider making the data set available in tools such as “NASA WORLDVIEW” and/or the European “Ocean Virtual Laboratory”. This would make a nice addition to the publication.
Response
We were unable to provide a bespoke visualisation due to completion of this part of the project; however, by providing NETCDFs researchers may perform what the reviewer suggests by ingesting the data into a visualisation system of their choice, using subsets where appropriate, relevant to their own applications.
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AC4: 'Reply on RC5', Andre Valente, 03 Nov 2022
André Valente et al.
Data sets
A compilation of global bio-optical in situ data for ocean-colour satellite applications - version 3 Valente, André; Sathyendranath, Shubha; Brotas, Vanda; Groom, Steve; Grant, Michael; Jackson, Thomas; Chuprin, Andrei; Taberner, Malcolm; Airs, Ruth; Antoine, David; Arnone, Robert; Balch, William M; Barker, Kathryn; Barlow, Ray; Bélanger, Simon; Berthon, Jean-François; Besiktepe, Sukru; Borsheim, Yngve; Bracher, Astrid; Brando, Vittorio E; Brewin, Robert J W; Canuti, Elisabetta; Chavez, Francisco P; Cianca, Andres; Claustre, Hervé; Clementson, Lesley; Crout, Richard; Ferreira, Afonso; Freeman, Scott; Frouin, Robert; García-Soto, Carlos; Gibb, Stuart W; Goericke, Ralf; Gould, Richard; Guillocheau, Nathalie; Hooker, Stanford B; Hu, Chuamin; Kahru, Mati; Kampel, Milton; Klein, Holger; Kratzer, Susanne; Kudela, Raphael M; Ledesma, Jesus; Lohrenz, Steven; Loisel, Hubert; Mannino, Antonio; Martinez-Vicente, Victor; Matrai, Patricia A; McKee, David; Mitchell, Brian G; Moisan, Tiffany; Montes, Enrique; Muller-Karger, Frank E; Neeley, Aimee; Novak, Michael G; O'Dowd, Leonie; Ondrusek, Michael; Platt, Trevor; Poulton, Alex J; Repecaud, Michel; Röttgers, Rüdiger; Schroeder, Thomas; Smyth, Timothy J; Smythe-Wright, Denise; Sosik, Heidi; Thomas, Crystal S; Thomas, Rob; Tilstone, Gavin H; Tracana, Andreia; Twardowski, Michael S; Vellucci, Vincenzo; Voss, Kenneth; Werdell, Jeremy; Wernand, Marcel Robert; Wojtasiewicz, Bozena; Wright, Simon; Zibordi, Giuseppe https://doi.pangaea.de/10.1594/PANGAEA.941318
André Valente et al.
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