From 96cadbf0c3236a23595a21cb53e35b3e87fa4d9d Mon Sep 17 00:00:00 2001
From: malmans2 📢 Quality assessment statementThese are the key outcomes of this assessment
The Ocean Colour dataset version 6.0:
provides a limited representation of the spatial distribution of chlorophyll-a concentrations in the oceanic region below latitude 45.5°S, based on less than 8% of valid observations.
provides an acceptable representation of the spatial distribution of chlorophyll-a concentrations off the southeast coast of South America, based on more than 35% of valid observations.
provides a limited representation of the spatial distribution of chlorophyll-a concentrations in the oceanic region below latitude 45.5°S, based on less than 8% of valid pixels.
provides an acceptable representation of the spatial distribution of chlorophyll-a concentrations off the southeast coast of South America, based on more than 35% of valid pixels.
does not reliably capture temporal chlorophyll-a patterns in the Southern Ocean, due to potential chlorophyll-a overestimation during the austral winter.
allows for the calculation of monthly chlorophyll-a trends in the Southern Ocean, although these trends should be interpreted with caution as based on less than 14% of valid observations.
allows for the calculation of monthly chlorophyll-a trends in the Southern Ocean, although these trends should be interpreted with caution as based on less than 14% of valid pixels.
This notebook provides an assessment of the ability of the Ocean Colour dataset version 6.0 to represent the spatial distribution and temporal variability of chlorophyll-a concentrations in the Indian, Pacific, and Atlantic Ocean sectors of the Permanent Open Ocean Zone in the Southern Ocean by analysing the number of valid observations available.
+This notebook provides an assessment of the ability of the Ocean Colour dataset version 6.0 to represent the spatial distribution and temporal variability of chlorophyll-a concentrations in the Indian, Pacific, and Atlantic Ocean sectors of the Permanent Open Ocean Zone in the Southern Ocean by analysing the number of valid pixels available.
The analysis and results are detailed in the sections below:
1. Choose the data to use and set up the code
The analysis performed in this notebook examines the spatial and temporal distribution of chlorophyll-a data, and corresponding valid observations, over a 26-year period (January 1998 - December 2023) in three sectors within the oceanic region in the Southern Ocean located between latitudes 47.5°S and 63.5°S (i.e., the Permanent Open Ocean Zone, POOZ) [7]. The three POOZ sectors analysed are: the Indian Ocean sector (IO_POOZ), the Pacific Ocean sector (PO_POOZ) and the Atlantic Ocean sector (AO_POOZ), which extend between longitudes 20°E and 150°E, 150°E and 70°W, and 70°W and 20°E, respectively [8].
+The analysis performed in this notebook examines the spatial and temporal distribution of chlorophyll-a data, and corresponding valid pixels, over a 21-year period (January 2003 - December 2023), which accounts for previous EQC information (https://cds.climate.copernicus.eu/datasets/satellite-ocean-colour?tab=quality_assurance_tab) and includes only complete years. The analysis is performed over three sectors within the oceanic region in the Southern Ocean located between latitudes 47.5°S and 63.5°S (i.e., the Permanent Open Ocean Zone, POOZ) [7]. The three POOZ sectors analysed are: the Indian Ocean sector (IO_POOZ), the Pacific Ocean sector (PO_POOZ) and the Atlantic Ocean sector (AO_POOZ), which extend between longitudes 20°E and 150°E, 150°E and 70°W, and 70°W and 20°E, respectively [8].
# Time period
-start = "1998-01"
+start = "2003-01"
stop = "2023-12"
# Variable
@@ -657,7 +657,7 @@ Define transform functionsdef postprocess(ds):
ds["mean"].attrs.update({"long_name": "Chl-a", "units": "mg m-3"})
- ds["valid_pixels"].attrs.update({"long_name": "valid observations", "units": "%"})
+ ds["valid_pixels"].attrs.update({"long_name": "valid pixels", "units": "%"})
return ds
The monthly_weighted_log_mean
and regionalised_spatial_weighted_mean
functions are applied to the chlorophyll-a dataset in the selected regions, and temporal and spatial averages are downloaded as two separated arrays.
The monthly_weighted_log_mean
and weighted_log_map
functions are applied to the chlorophyll-a dataset in the selected regions, and temporal and spatial averages are downloaded as two separated arrays.
The plot_map
function is defined to visualise the maps of average chlorophyll-a concentrations and corresponding valid observations percentages across the POOZ.
The plot_map
function is defined to visualise the maps of average chlorophyll-a concentrations and corresponding percentages of valid pixels across the POOZ.
The calculate_mk_trends
function is defined to calculate chlorophyll-a trends and their statistical significance for each individual month over the 26-year period analysed here in the three POOZ sectors.
The calculate_mk_trends
function is defined to calculate chlorophyll-a trends and their statistical significance for each individual month over the 21-year period analysed here in the three POOZ sectors.
Maps showing the spatial distribution of the percentage of valid observations and the derived chlorophyll-a concentration in the POOZ are provided. Additionally, two sets of heatmaps are generated: the first series shows the monthly chlorophyll-a time series for each POOZ sector by month and year, while the second series displays the corresponding percentage of valid observations. White grid cells in the chlorophyll-a heatmaps indicate missing data. Monthly climatology of valid observations and chlorophyll-a concentrations are also shown. Chlorophyll-a trends and their statistical significance, calculated for each individual month over the 26-year period analysed, are summarized in a table, where statistically significant trends are highlighted in bold.
+Maps showing the spatial distribution of the percentage of valid pixels and the derived chlorophyll-a concentration in the POOZ are provided. Additionally, two sets of heatmaps are generated: the first series shows the monthly chlorophyll-a time series for each POOZ sector by month and year, while the second series displays the corresponding percentage of valid pixels. White grid cells in the chlorophyll-a heatmaps indicate missing data. Monthly climatology of valid pixels and chlorophyll-a concentrations are also shown. Chlorophyll-a trends and their statistical significance, calculated for each individual month over the 21-year period analysed, are summarized in a table, where statistically significant trends are highlighted in bold.
- | 1 | -2 | -3 | -4 | -5 | -6 | -7 | -8 | -9 | -10 | -11 | -12 | +Jan | +Feb | +Mar | +Apr | +May | +Jun | +Jul | +Aug | +Sep | +Oct | +Nov | +Dec | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
IO_POOZ | -0.0012 (0.0473) | -0.0011 (0.0002) | -0.0009 (0.0003) | -0.0006 (0.0003) | -0.0008 (0.0001) | -0.0023 (0.0208) | -0.0015 (0.0000) | -0.0011 (0.0000) | -0.0006 (0.0001) | -0.0004 (0.0153) | -0.0008 (0.0343) | -0.0009 (0.1457) | +IO_POOZ | +1.7790 (0.0235) | +1.3479 (0.0003) | +1.0629 (0.0041) | +0.7690 (0.0034) | +0.7683 (0.0086) | +0.5300 (0.6505) | +1.2719 (0.0023) | +1.2598 (0.0002) | +0.9638 (0.0001) | +0.6180 (0.0320) | +0.4780 (0.3812) | +1.3382 (0.1095) |
PO_POOZ | -0.0003 (0.5968) | -0.0003 (0.3321) | -0.0005 (0.0473) | -0.0011 (0.0000) | -0.0017 (0.0001) | -0.0024 (0.0122) | -0.0020 (0.0024) | -0.0012 (0.0000) | -0.0003 (0.0641) | -0.0003 (0.0524) | -0.0007 (0.0641) | -0.0008 (0.4275) | +PO_POOZ | +0.7043 (0.5661) | +-0.2822 (0.4874) | +0.1760 (0.5260) | +1.0227 (0.0019) | +1.1610 (0.0235) | +1.5488 (0.4995) | +1.5226 (0.1235) | +1.1339 (0.0001) | +0.5096 (0.0201) | +0.2187 (0.3812) | +0.8796 (0.0852) | +0.7861 (0.6077) |
AO_POOZ | -0.0015 (0.2704) | -0.0014 (0.2011) | -0.0010 (0.0308) | -0.0012 (0.0136) | -0.0021 (0.0004) | -0.0017 (0.4503) | -0.0028 (0.0000) | -0.0015 (0.0000) | -0.0006 (0.1029) | -0.0007 (0.5371) | -0.0018 (0.1457) | -0.0015 (0.2171) | +AO_POOZ | +-0.1337 (1.0000) | +1.2132 (0.6077) | +0.5293 (0.4503) | +1.3570 (0.0372) | +1.2037 (0.0497) | +0.8919 (0.8219) | +2.1216 (0.0086) | +1.3946 (0.0008) | +0.1215 (0.7398) | +-1.2910 (0.2906) | +1.0990 (0.4874) | +-0.3304 (0.9759) |
Chlorophyll-a spatial distribution:
-The mean availability of chlorophyll-a data over the 26-year period analysed is approximately 7% across the entire POOZ, indicating limited dataset coverage that may not fully capture the spatial variability of chlorophyll-a distribution in this region. A small difference in the number of valid observations is observed across the three POOZ sectors: the PO_POOZ exhibits the greatest availability (8.8%), followed by the AO_POOZ (7.7%) and the IO_POOZ (6.8%). A significant number of valid observations (above 35%) are detected off the southeastern coasts of South America. Therefore, the representation of the spatial distribution of chlorophyll-a in this area can be assumed to be more reliable than elsewhere in the POOZ.
-Different average chlorophyll-a concentrations are observed in the three POOZ sectors: the AO_POOZ sector is the less oligotrophic with an average value of about 0.2 mg m-3, whereas the IO_POOZ and PO_POOZ are characterized by lower, but comparable averages (0.12 and 0.13 mg m-3 in the IO_POOZ and PO_POOZ, respectively), confirming what reported in previous studies (e.g., [8]). While the subregional variability in terms of valid observations likely depends on differences in sea ice extent and cloud coverage across the three POOZ sectors, differences in their average chlorophyll-a concentration are influenced by several key factors, such as nutrient supply through Patagonian dust deposition and/or upwelling (e.g., [11] [12] [13]).
The mean availability of chlorophyll-a valid pixels over the 21-year period analysed is approximately 8% across the entire POOZ, indicating limited dataset coverage that may not fully capture the spatial variability of chlorophyll-a distribution in this region. A small difference in the number of valid pixels is observed across the three POOZ sectors: the PO_POOZ exhibits the greatest availability (9.5%), followed by the AO_POOZ (8.3%) and the IO_POOZ (7.3%). A significant number of valid pixels (above 30%) are detected off the southeastern coasts of South America. Therefore, the representation of the spatial distribution of chlorophyll-a in this area can be assumed to be more reliable than elsewhere in the POOZ.
+Different average chlorophyll-a concentrations are observed in the three POOZ sectors: the AO_POOZ sector is the less oligotrophic with an average value of about 0.2 mg m-3, whereas the IO_POOZ and PO_POOZ are characterized by lower averages (0.12 and 0.14 mg m-3, respectively), confirming what reported in previous studies (e.g., [8]). While the subregional variability in terms of valid pixels likely depends on differences in sea ice extent and cloud coverage across the three POOZ sectors, differences in their average chlorophyll-a concentration are influenced by several key factors, such as nutrient supply through Patagonian dust deposition and/or upwelling (e.g., [11] [12] [13]).
Chlorophyll-a temporal distribution:
-Besides missing data (i.e., white grid cells in the chlorophyll-a heatmap), the average chlorophyll-a concentrations calculated for each individual month over the 26-year period analysed here show surprisingly high isolated values (up to 1.0 mg m-3) during the polar night months (i.e., May–July) in all three POOZ sectors. This pattern, which is also observed when analysing the chlorophyll-a monthly climatology, is in contrast to what is typically observed in the Southern Ocean, where the lowest chlorophyll-a concentrations are generally found during the austral winter (e.g., [14]). This suggests the presence of a suspicious artefact in the dataset, leading to an overestimation of chlorophyll-a during this period. -Conversely, the monthly climatological distribution of valid chlorophyll-a observations is in line with expectations based on their dependence on the solar zenith angle: the highest percentage (up to about 14%) is observed between November and February, when the solar zenith angle is low, then it decreases to reach its minimum (almost 0%) during the polar night months (i.e. May-July) and gradually increases again towards the end of the year. -It is interesting to note that, as shown in the valid observation heatmap, the valid percentages reveal an initial increase starting in 2002, when MERIS and MODIS-Aqua satellites joined the SeaWiFS mission, and between 2016 and 2020, when the highest number of observation systems were operational (i.e., MODIS-Aqua, VIIRS, OLCI-3A, and OLCI-3B) +
Besides missing data (i.e., white grid cells in the chlorophyll-a heatmap), the average chlorophyll-a concentrations calculated for each individual month over the 21-year period analysed here show surprisingly high isolated values (up to 1.0 mg m-3) during the polar night months (i.e., May–July) in all three POOZ sectors. This pattern, which is also observed when analysing the chlorophyll-a monthly climatology and was previously described in [14], is in contrast to what is typically observed in the Southern Ocean, where the lowest chlorophyll-a concentrations are generally found during the austral winter (e.g., [15]). This suggests the presence of a suspicious artefact in the dataset, leading to an overestimation of chlorophyll-a during this period.
+Conversely, the monthly climatological distribution of valid chlorophyll-a pixels is in line with expectations based on their dependence on the solar zenith angle: the highest percentage (up to about 15%) is observed between November and February, when the solar zenith angle is low, then it decreases to reach its minimum (almost 0%) during the polar night months (i.e. May-July) and gradually increases again towards the end of the year.
+It is interesting to note that, as shown in the valid pixels heatmap, the valid percentages increased between 2017 and 2019, reaching a maximum in 2018 (up to about 24%), when the highest number of observing systems were operational (i.e., MODIS-Aqua, VIIRS, OLCI-3A, and OLCI-3B)
([1]).
-Despite varying statistical significance, the linear trends calculated for each individual month between 1998 and 2023 indicate an overall chlorophyll-a increase across all POOZ sectors examined, consistent with the results of previous studies (e.g., [8]). However, these trends should be interpreted with caution as they are based on a percentage of valid observations always below 14%.
-Particular attention should be paid to chlorophyll-a data and trends during the polar night months in the POOZ due to the scarcity of valid observations and the potential chlorophyll-a overestimation.
[12] Paparazzo, F.E., Crespi-Abril, A.C., Gonçalves, R.J., Barbieri, E.S., Gracia Villalobos, L.L., SolÃs, M.E., & Soria, G. (2018). Patagonian dust as a source of macronutrients in the Southwest Atlantic Ocean. Oceanography, 31(4), 33-39.
[13] Demasy, C., Boye, M., Lai, B., Burckel, P., Feng, Y., Losno, R., Borensztajn, S., & Besson, P. (2024). Iron dissolution from Patagonian dust in the Southern Ocean: under present and future conditions. Frontiers in Marine Science, 11, 1363088.
-[14] Arteaga, L.A., Boss, E., Behrenfeld, M.J., Westberr, T.K., & Sarmiento, J.L. (2020). Seasonal modulation of phytoplankton biomass in the Southern Ocean. Nature Communications, 11, 5364.
+[14] Gregg, W.W., & Casey, N.W. (2007). +Sampling biases in MODIS and SeaWiFS ocean chlorophyll data. Remote Sensing of Environment, 111(1), 25-35.
+[15] Arteaga, L.A., Boss, E., Behrenfeld, M.J., Westberry, T.K., & Sarmiento, J.L. (2020). Seasonal modulation of phytoplankton biomass in the Southern Ocean. Nature Communications, 11, 5364.
+[16] Venegas, R.M., Rivas, D., & Treml, E. (2025). Global climate-driven sea surface temperature and chlorophyll dynamics. Marine Environmental Research, 204, 106856
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