Suspended Particulate Matter (SPM) plays a central role in coastal marine ecosystems, influencing light availability, primary production, and transport of sediments, nutrients, and pollutants. Monitoring its variability is essential for understanding the impacts of both natural and anthropogenic pressures on coastal regions. In this study, nine years (2016-2025) of data from the Ocean and Land Colour Instrument (OLCI) aboard Sentinel-3 were used to analyze SPM variability and trends across European and Mediterranean coastal waters at 300 m resolution. Monthly SPM composites were generated using a semi-analytical model, and processed using time series decomposition (Census X-11) and non-parametric trend analysis. A continental-scale climatology was generated, and high temporal variability was observed along the coasts, and in shelf seas such as the Irish Sea and the North Sea, where seasonal river discharge and resuspension events occur. Statistically significant trends were detected in several regions: declines in the Severn Estuary (-3.27%yea) and English Channel (-3.6%yea), and increases in the Northern North Sea (+3.51%yea), Gulf of Gabes (+6.52%yea), Abu Qir port, Egypt (+8.20%yea), and northwestern Black Sea (+4.01%yea). Case studies linked these trends to potential drivers including dredging and land reclamation (Abu Qir port), warfare-related disturbances (Kakhovka Dam breach), and regional hydrodynamic or anthropogenic pressures. These findings are relevant to European marine policy frameworks, supporting efforts to establish robust indicators of coastal water quality. This study highlights the value of satellite observations for environmental monitoring and coastal management across European and Mediterranean waters.

Abstract. Tropical oligotrophic surface waters are typically nutrient-limited, and internal tides have been proposed as a key mechanism supplying nutrients to the euphotic zone through two complementary physical pathways: vertical advection and turbulent mixing. However, separating and quantifying these two pathways from in situ observations, and assessing their respective ecosystem implications, remains challenging. Unlike previous studies, which have generally investigated these mechanisms separately, this study directly compares their respective contributions within a common observational framework. Here, autonomous glider observations collected during the AMAZOMIX campaign off the Amazon shelf were used to reconstruct nutrient profiles using CANYON-B neural network, identify internal-tide-driven isopycnal and nutrient-associated vertical displacements, and independently estimate turbulent dissipation rates validated against microstructure profiler (VMP) measurements. Vertical nutrient profiles revealed contrasting nutrient limitation regimes, with a nitrate deficit in the upper layer and a silicate deficit at depth. Our results demonstrate that internal-tide-induced vertical advection dominates the mean nutrient enrichment at the base of the euphotic layer (FADV = 2.3 ± 0.5 mmol NO₃ m⁻² d⁻¹ and 0.4 ± 0.1 mmol Si m⁻² d⁻¹), whereas turbulent diffusion provides smaller mean fluxes (FDIFF = 1.07 mmol NO₃ m⁻² d⁻¹ and 0.14 mmol Si m⁻² d⁻¹) but remains essential because it represents an irreversible transport pathway and can dominate during episodic high-energy mixing events. Together, these processes modify not only nutrient availability but also nutrient stoichiometry, highlighting internal tides as an important regulator of ecosystem functioning in the western tropical Atlantic. These results suggest that internal tides act both as a nutrient-supply mechanism and as a potential community-structuring process, with implications for nitrate–silicate-dependent phytoplankton groups at the base of the euphotic layer.

Abstract. The Amazon shelf–offshore continuum is a dynamic biogeochemical hotspot of the tropical Atlantic, where riverdischarge, ocean circulation, and strong tides interact to shape nutrient and phytoplankton distributions. The Amazon plumeand regional circulation have been widely studied and are known to strongly influence nutrient availability and biologicalproductivity in this region. However, shelf-break tides remain an overlooked pathway linking physical energy to offshore fertilization, and their contribution to seasonal and intraseasonal biogeochemical variability remains unclear. Here, wequantify how tidal dynamics, including internal tides, modulate nitrate supply and chlorophyll distributions from theAmazon shelf to offshore waters. We use a high-resolution coupled physical–biogeochemical model (1/36°), evaluatedagainst climatological, satellite, and in situ observations. The model reproduces the main observed patterns of surface nitrateand chlorophyll, as well as key vertical features such as the nitracline and the deep chlorophyll maximum. We show that tides strongly enhance upward nitrate transport, increasing surface nitrate by more than 50% over the northern shelf, alongthe shelf break, and within the main internal-tide pathway. This tidally supplied nitrate fuels offshore phytoplankton growth,increasing chlorophyll by about 15–50%, while reducing surface chlorophyll near the Amazon mouth by 30–40%.Seasonally, surface chlorophyll and nitrate are higher over the Amazon shelf during April–June but lower offshore,revealing a marked cross-shelf contrast. When the tidal contribution is isolated, a similar but weaker spatial structure30 emerges, with a cone-shaped chlorophyll anomaly extending from the shelf break toward the offshore internal-tidepropagation region. Remarkably, tides account for about 63% of the total seasonal variability in surface nitrate, meaning thattidal forcing alone explains more than half of the seasonal nutrient signal. At intraseasonal timescales, tides generate a clearspring–neap rhythm of about 15 days in both nitrate and chlorophyll. This spring–neap tidal pulse propagates from the shelfbreak toward offshore waters and is especially pronounced near the deep chlorophyll maximum, where oscillations of theupper nitracline periodically modulate nitrate availability and drive a corresponding chlorophyll response., wherechlorophyll variability is nearly doubled when tides are included. The concurrent increase in nitrate variability indicates thatthis spring–neap phytoplankton response is sustained by tidally driven nutrient supply.These findings identify internal tides as a key biogeochemical driver of the Amazon shelf–offshore continuum, linking tidalenergy to nutrient injection, offshore fertilization, seasonal redistribution, and rhythmic ecosystem variability in the westerntropical Atlantic.

This study investigates the influence of tides on chlorophyll a (CHL) variability in the Brazilian Equatorial Margin using daily GlobColour and MODIS-Aqua CHL data from 2005 to 2021. The impact of the tides is assessed by comparing the spring with the neap tide signals (fortnightly signal, 14.7 d). Results show that, on the shallow Amazon shelf, significant fortnightly CHL variability is likely primarily driven by barotropic tide-induced friction on the shelf that produces significant vertical mixing. On the northwestern shelf, where the Amazon River plume prevails, CHL levels are higher during neap tides, resulting in a negative spring-neap tide CHL difference (GlobColour: -50 %; MODIS-Aqua: -84 %). Conversely, on the northeastern shelf, characterized by low-turbidity waters, CHL levels are higher during spring tides, leading to a positive spring-neap tide CHL difference (GlobColour: +30 %; MODIS-Aqua: +70 %). Offshore, baroclinic tides, also known as internal tides (ITs), seem to enhance the CHL along their pathways with a spatial structure of a wave-like pattern. The positive CHL peaks are spaced by mode-2 wavelengths (about 68 km), with peak values reaching +3.3 % (GlobColour) and +9.0 % (MODIS-Aqua). Analysis shows that the CHL wave-like pattern suggests contributions from mode-1 and mode-2 internal tides, with mode-2 components having higher spectral coherence with the original signal. A 1-3 d lag between higher CHL variability and tidal potential may indicate delayed nutrient mixing post-spring-neap tides. The effects of ITs on CHL are more pronounced than on sea surface temperature.

Oceanic N2 fixation by diazotrophic microorganisms is the primary external source of new nitrogen to the surface ocean sustaining net production of organic matter. Studying long-term trends in biomass within N2 fixation hotspots is crucial for understanding and predicting the response of N2 fixation to global climate change. Here we developed a bio-optical model based on the spectral phytoplankton absorption coefficient derived from satellite ocean color observations to estimate a proxy for particulate organic nitrogen in the western tropical South Pacific. We demonstrate the existence of a seasonal new biomass production annually over the past 20 years, likely driven by recurrent N2 fixation. Importantly, our results also reveal a gradual decline in biomass within this N2 fixation hotspot over the last two decades. This decline indicates that seasonal nitrogen inputs via N2 fixation are decreasing. This trend inevitably could lead to a decline in the efficiency of the biological carbon pump, with potential implications for global biogeochemical cycles and climate regulation.

Estimation of Chlorophyll-a concentration (Chl-a) across diverse aquatic systems using Moderate Resolution Imaging Spectroradiometer-Aqua (MODIS-A) data has posed challenges, particularly the inability of existing algorithms to maintain consistent accuracy across varying optical water conditions, from oligotrophic clear waters to highly turbid productive systems. Traditional Blue/Green ratio approaches often show limitations over optically complex waters where colored dissolved organic matter and suspended sediments interfere with phytoplankton signal detection. In contrast, Red/NIR (Near-Infrared) models perform relatively well in productive coastal domains but are less effective in open ocean waters where phytoplankton absorption is too weak to produce detectable signals in these longer wavelengths. To address these challenges, we developed a Combination Of Neural Network models for Estimating Chlorophyll-a over Turbid and clear waters (CONNECT model) based on the principle that different Optical Water Types (OWTs) require specialized bio-optical algorithms. The methodology involves the development of two Multi-Layer Perceptron (MLP) models (NN-Clear & NN-Turbid) that are trained and evaluated on a comprehensive in-situ dataset with simultaneous measurements of Remote Sensing Reflectance (Rrs) and Chl-a gathered in various environments from clear to ultra-turbid waters (N = 5,358) with Chl-a ranging between 0.017 and 838.24 µg.L-1. These specialized models are then combined through a weighted blending approach to produce unified Chl-a estimates that adapts to the optical conditions of various water types. In particular, the algorithm merging process involves the use of probability values corresponding to 2 groups of Optical Water Types as the blending coefficients. Accuracy evaluations performed on both in-situ and matchup datasets indicate a remarkable advancement of the CONNECT model compared to the traditional Blue/Green approaches over different trophic conditions with an improvement of 49.65% on the matchup validation considering the Symmetric Signed Percentage Bias (SSPB) metric.

Internal tides (ITs) in the Indonesian Seas were largely investigated and held responsible for strong water mass transformation and intense surface cooling. Here, we evaluate the ITs' impact on chlorophyll-a through a coupled INDESO ocean-biogeochemical model which is compared with in situ data and satellite products. The results show that explicit tides' inclusion within the model improves the representation of chlorophyll-a and nutrients. Previous studies highlighted that tides at spring-neap cycle cool the surface water by 0.2 degrees C. Our current results show increases of chlorophyll-a by 0.2 up to 5 x 10-7 mg Chl m-3 (in log10) at ITs' generation sites (Sangihe, Ombai, Banda, and Halmahera Straits) and over the shallow Australian plateau and Java Sea, where barotropic tidal friction is high (Zaron et al., 2023, ). In addition, maxima of chlorophyll-a concentration have a spring-neap tides pulse in good agreement with ocean color images. We use INDOMIX in situ vertical diffusivities in a 1D diffusion model to explain the biogeochemical tracers' transformation within the Halmahera Sea and to estimate the nutrients' turbulent flux. We find an associated increase in new production of similar to 25% of the total and an increase in mean chlorophyll-a of similar to 30%. These findings support the idea of enhanced surface mixing capable of providing cold and nutrient-rich water favorable for the phytoplankton growth. Hence, we confirm the key role of ITs in shaping vertical distribution and variability of chlorophyll-a, along with nutrients and oxygen, in the Indonesian archipelago at the hotspots of intensified mixing where strong ITs are found.

Plankton are highly sensitive to climate change, and understanding their shifts in behaviour, physiology, phenology, and biogeography is important for anticipating changes in ecosystem services. This study used a recently developed ecological niche model to reanalyze data from the Continuous Plankton Recorder (CPR) survey using 8 environmental variables to build, for the first time, a CPR-based 4D data set (longitude x latitude x depth x day) of plankton abundance. First, we analyzed spatio-temporal changes in the abundance of 4 plankton species daily from 1958 to 2022: 2 diatoms (Ephemera planamembranacea and Odontella sinensis) and 2 calanoid copepods (Calanus finmarchicus and C. helgolandicus). We validated our new CPR-based 4D data set with existing in situ data and found that modeled spatio-temporal changes in abundance reproduced observations well. Then, we showed pronounced phenological and biogeographical shifts for the 4 species. Long-term latitudinal shifts in C. finmarchicus and E. planamembranacea were observed and correlated with the Atlantic subarctic gyre state, the North Atlantic Oscillation, and the Atlantic Multidecadal Oscillation. Our results also revealed a prominent positive influence of temperature on long-term changes in the abundance of E. planamembranacea, O. sinensis and C. helgolandicus, whereas they identified a negative influence of temperature on C. finmarchicus. Interestingly, our modeled data suggest a rise in the abundance of C. finmarchicus at greater depths during peak seasons, although this depth adjustment in response to changing conditions is unlikely to overcome the overall surface decline of the species.

The ocean region off the Amazon shelf including the shelf break presents a hotspot for internal tide (IT) generation, yet its impact on phytoplankton distribution remains poorly understood. While previous studies have extensively examined the physical characteristics and dynamics of ITs, their biological implications – particularly in nutrient-limited environments – remain underexplored. To address this question, we analyzed a 26 d glider mission deployed over September–October 2021 sampling hydrographic and optical properties (chlorophyll a) at high resolution along an IT pathway as well as satellite chlorophyll a and altimetry data to assess mesoscale interactions. Chlorophyll a dynamics were analyzed under varying IT intensities, comparing strong (HT) and weak (LT) internal tide conditions. Results reveal that ITs drive vertical displacements of the deep chlorophyll maximum (DCM) from 15 to 45 m, accompanied by 50 % expansion in its thickness during HT events. This expansion is observed with a dilution of the chlorophyll a maximum concentration within the DCM depth. While direct turbulence measurements were not collected, the observed vertical redistribution of chlorophyll a is indicative of tidally driven cross-isopycnal exchanges, the only physical mechanism explaining the transfer of biomass above and below the DCM. At the surface, turbulent fluxes provide 38 % of the chlorophyll a input, while the remainder is supplied by in situ biological activity. Notably, total chlorophyll a in the water column increases by 14 %–29 % during high internal tide phases, indicating a net enhancement of primary productivity driven by the combined effects of vertical mixing and stimulated surface-layer biological activity. These findings indicate that internal tides can be an important driver of chlorophyll a distribution and short-term biological variability in our study region. By reshaping the vertical chlorophyll a profile through vertical mixing, active internal tides influence primary productivity and may contribute to carbon cycling, particularly in oligotrophic oceanic environments where both a deep chlorophyll maximum and strong internal tides are present.

Chlorophyll-a (Chl-a) concentration is a key climate variable, as its variability is associated with meteorological and oceanographic processes. This study analyzed 25 years (1998–2022) of Chl-a data from the European Space Agency (ESA) Ocean Colour Climate Change Initiative (OC-CCI) multisensor archive for the South Brazil Bight, Southwestern Atlantic. Temporal variability and trends were assessed using the Census X11 method, Mann-Kendall, and Sens’ slope tests. The ESA OC-CCI data highlight reliable regional performance, although Chl-a concentrations above 10 mg.m−3 were underestimated. Temporal analyses showed the lowest Chl-a variability (29%) in open ocean waters, with 81% of the variability attributed to seasonal dynamics influenced by the South Atlantic Subtropical Gyre (SASG). A negative Chl-a trend of −11.0% was observed over the 25-year period, attributed to the expansion of the oligotrophic area of the SASG. In the shelf areas southwest of São Sebastião Island, Chl-a variability was moderate (34%–39%), with no discernible long-term trend, but significant interannual variability (44%). The Cape Frio upwelling region shows an increasing Chl-a trend (14.5% in the last 25 years), driven by atmospheric circulation affecting local winds. The highest Chl-a variability (74%) occurred along the southern continental shelf, associated with seasonal nutrient inputs from the Subtropical Shelf Front, with a Chla-a trend increase of 7.5% in 25 years. These results highlight the dynamic and variable Chl-a responses to environmental forcing across the South Brazil Bight.

In this paper, we address the multi-sharpening problem by simultaneously fusing multiple multispectral images with a single hyperspectral image. We propose two variants of a novel strategy named G-STEREO-1 and G-STEREO-2. Both methods extend the tensor-based multi-sharpening framework named STEREO, by leveraging the complementarity of several multispectral sources to enhance fusion quality. G-STEREO-1 and G-STEREO-2 are based on a joint tensor decomposition model that incorporates a generalized Sylvester equation within a Canonical Polyadic (CP) tensor decomposition scheme. Our approaches overcome the limitations of existing joint tensor-based fusion techniques, which are restricted to fusing only a single multispectral image with a hyperspectral one. Experimental results show that both G-STEREO-1 and G-STEREO-2 consistently outperform these existing methods.

The present study evaluates the influence of industrialization on suspended particulate matter (SPM) dynamics along the northern coast of Rio de Janeiro, focusing specifically on the Açu Port Industrial Complex (APIC). A 20-year MODIS-Aqua (1 km) dataset (2002–2022) was processed using the OC-SMART atmospheric correction. For SPM estimation, a retrieval approach for coastal turbid waters that integrates two optimized bio-optical algorithms based on Optical Water Types (OWTs) was developed. The validity of this approach was substantiated through the utilization of the GLORIA in situ dataset and satellite matchups, which demonstrated its robust performance across a range of turbidity conditions. Its main innovation lies in the OWT-based fusion of two optimized SPM models, enabling robust retrievals across diverse coastal optical conditions. Statistical analyses based on Census X11 decomposition and the Seasonal Mann–Kendall test revealed strong spatial and temporal variability, with SPM concentrations increasing by up to 60% near the APIC during the study period, coinciding with dredging, port expansion, and sediment disposal. These findings indicate a pronounced anthropogenic signal, while spatial and temporal correlation analyses demonstrated that sediment dispersion is consistently directed northward, primarily controlled by currents and wind forcing. The results indicate that industrial activities augment the supply of sediments, while natural hydrodynamic processes govern their dispersion and transport, emphasizing the impact of human pressures and physical drivers on coastal sediments.

The impact of internal and barotropic tides on the vertical and horizontal temperature structure off the Amazon River was investigated during two highly contrasted seasons (AMJ: April–May–June; ASO: August–September–October) over a 3-year period from 2013 to 2015. Twin regional simulations, with and without tides, were used to highlight the general effect of tides. The findings reveal that tides have a cooling effect on the ocean from the surface (∼ 0.3 ∘C) to above the thermocline (∼ 1.2 ∘C), while warming it up below the thermocline (∼ 1.2 ∘C). The heat budget analysis indicates that the vertical mixing is the dominant process driving temperature variations within the mixed layer, while it is associated with both horizontal and vertical advection to explain temperature variations below. The increased mixing in the simulations including tides is attributed to breaking of internal tides (ITs) on their generation sites over the shelf break and offshore along their propagation pathways. Over the shelf, mixing is driven by the dissipation of the barotropic tides. In addition, the vertical terms of the heat budget equation exhibit wavelength patterns typical of mode-1 IT. The study highlights the key role of tides and particularly how IT-related vertical mixing shapes the ocean temperature off the Amazon. Furthermore, we found that tides impact the interactions between the upper ocean interface and the overlying atmosphere. They contribute significantly to increasing the net heat flux between the atmosphere and the ocean, with a notable seasonal variation from 33.2 % in AMJ to 7.4 % in ASO seasons. This emphasizes the critical role of tidal dynamics in understanding regional-scale climate.

Sentinel-2/MSI and Landsat-8/OLI sensors enable the mapping of ocean color-related bio-optical parameters of surface coastal and inland waters. While many algorithms have been developed to estimate the Chlorophyll-a concentration, Chl-a, and the suspended particulate matter, SPM, from OLI and MSI data, the absorption by colored dissolved organic matter, acdom, a key parameter to monitor the concentration of dissolved organic matter, has received less attention. Herein we present an inverse model (hereafter referred to as AquaCDOM) for estimating acdom at the wavelength 412 nm (acdom (412)), within the surface layer of coastal waters, from measurements of ocean remote sensing reflectance, Rrs (λ), for these two high spatial resolution (around 20 m) sensors. Combined with a water class-based approach, several empirical algorithms were tested on a mixed dataset of synthetic and in situ data collected from global coastal waters. The selection of the final algorithms was performed with an independent validation dataset, using in situ, synthetic, and satellite Rrs (λ) measurements, but also by testing their respective sensitivity to typical noise introduced by atmospheric correction algorithms. It was found that the proposed algorithms could estimate acdom (412) with a median absolute percentage difference of ~30% and a median bias of 0.002 m−1 from the in situ and synthetic datasets. While similar performances have been shown with two other algorithms based on different methodological developments, we have shown that AquaCDOM is much less sensitive to atmospheric correction uncertainties, mainly due to the use of band ratios in its formulation. After the application of the top-of-atmosphere gains and of the same atmospheric correction algorithm, excellent agreement has been found between the OLI- and MSI-derived acdom (412) values for various coastal areas, enabling the application of these algorithms for time series analysis. An example application of our algorithms for the time series analysis of acdom (412) is provided for a coastal transect in the south of Vietnam.

Water resources play a crucial role in the global water cycle and are affected by human activities and climate change. However, the impacts of hydropower infrastructures on the surface water extent and volume cycle are not well known. We used a multi-satellite approach to quantify the surface water storage variations over the 2000-2020 period and relate these variations to climate-induced and anthropogenic factors over the whole basin. Our results highlight that dam operations have strongly modified the water regime of the Mekong River, exhibiting a 55 % decrease in the seasonal cycle amplitude of inundation extent (from 3178 km2 to 1414 km2) and a 70 % decrease in surface water volume (from 1109 km3 to 327 km3) over 2000-2020. In the floodplains of the Lower Mekong Basin, where rice is cultivated, there has been a decline in water residence time by 30 to 50 days. The recent commissioning of big dams (2010 and 2014) has allowed us to choose 2015 as a turning point year. Results show a trend inversion in rice production, from a rise of 40 % between 2000 and 2014 to a decline of 10 % between 2015 and 2020, and a strong reduction in aquaculture growth, from +730 % between 2000 and 2014, to +53 % between 2015 and 2020. All these results show the negative impact of dams on the Mekong basin, causing a 70 % decline in surface water volumes, with major repercussions for agriculture and fisheries over the period 2000-2020. Therefore, new future projects such as the Funan Techo canal in Cambodia, scheduled to start construction at the end of 2024, will particularly affect 1300 km2 of floodplains in the lower Mekong basin, with a reduction in the amount of water received, and other areas will be subjected to flooding. The human, material and economic damage could be catastrophic.

The Sepetiba Bay (Rio de Janeiro, SE Brazil) is an important coastal environment due to its ecological characteristics, extensive biodiversity, vast green area and connection to the sea, and vast socio-economic impact due to its importance to the surrounding communities and for the country. The bay receives a considerable amount of sediments through several small rivers and artificial channels along its coast, creating a “river plume” dynamic that influences its biogeochemical processes within the bay. This study analyzes a 20-year remote sensing temporal series from MODIS-Terra, combined with a semi-analytical algorithm based on wellestablished literature, to retrieve surface sediment concentration. The results reveal an inhomogeneous spatio-temporal pattern of the plume, which varies with climatological seasons. Summer and Spring present higher sediment concentrations and range, compared to Autumn and Winter. The observed patterns in the plume suggests a heterogeneous specialization that depends on the riverine inflow, which agrees with previous literature studies. Future studies should tackle both, the increase of remote sensing algorithms’ accuracy to retrieve sediment concentration and focus on plume change detection events to better understand the impact of land cover changes within the drainage basins surrounding Sepetiba Bay.

Photosynthetically Active Radiation (PAR) plays a crucial role in shaping marine ecosystems, influencing primary production, species interaction, and phytoplankton seasonal dynamics. However, comprehensive long-term (gap-free) datasets for both surface PAR and the diffuse Attenuation Coefficient of Photosynthetically Active Radiation (KdPAR) are currently lacking. In this study, we introduce two new extensive global 4D PAR gap-free datasets (Longitude x Latitude x Day x Depth) at a resolution of 0.25o latitude x 0.25o longitude from surface to 250 m covering the periods 1998-2022 and 1958-2022. The first dataset (1998-2022) is primarily derived from Globcolour (surface PAR and Chlorophyll-a), supplemented with missing surface PAR data estimated using the Environmental String Model (ESM) with key climatic ERA5 variables. Missing Chlorophyll-a data are interpolated by applying the DINEOF method (Data Interpolating Empirical Orthogonal Functions) and transformed into KdPAR. Visual and numerical evaluations closely approximate observations, demonstrating the accuracy of our approach. Subsequently, we extend our dataset back to 1958 using exclusively the ESM based on key climatic ERA5 variables. The ESM outperforms the Generalized Regression on Neural Network (GRNN) in computational efficiency while yielding similar results. Validation against in-situ measurements confirms the reliability of PAR and KdPAR surface products. Although the 1958-2022 dataset exhibits limited daily variability in PAR compared to the 1998-2022 dataset, it effectively captures critical spatial-temporal patterns, as demonstrated by correlative and comparative studies with El Nino indices. Furthermore, the similarity observed between euphotic depth (Zeu) derived from our ESM-based 4D PAR dataset (1958-2022), and the Mercator-Ocean hindcast model, along with in-situ data, underscores the robustness of our approach in capturing light availability at depth.

Water colour remote sensing is a valuable tool for assessing bio-optical and biogeochemical parameters across the vast extent of the Amazon River Continuum (ARC). However, accurate retrieval depends on selecting the best atmospheric correction (AC). Four AC processors (Acolite, Polymer, C2RCC, OC-SMART) were evaluated against in situ remote sensing reflectance (Rrs) measurements. K-means classification identified four optical water types (OWTs) that are affected by the ARC. Two OWTs showed seasonal differences in the Lower Amazon River, influenced by the increase in suspended sediment concentration with river discharge. The other OWTs in the Amazon River Plume are dominated by phytoplankton or by a mixture of optically significant constituents. The Quality Water Index Polynomial method used to assess the quality of in situ and orbital Rrs had a high failure rate when the Apparent Visible Wavelength was >580 nm for in situ Rrs. OC-SMART Rrs products showed better spectral quality compared to Rrs derived from other AC processors evaluated in this study. These results improve our understanding of remotely sensing very turbid waters, such as those in the Amazon River Continuum.