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We analyzed the temporal trends (1998–2022) of surface phytoplankton Chlorophyll (Chl) concentration in the Arctic at the local, regional, and pan‐Arctic scales. We used four empirically derived Chl satellite ocean color products: two global merged products and two MODIS products, one calibrated to the Arctic. At the local level, between 10% and 40% of the area with valid pixels showed statistically significant Chl trends, with ∼2/3${\\sim} 2/3$of those pixels showing increases, and the other third indicating a decrease. At the regional level, only the Barents and Chukchi Seas had consistent Chl increases across products. At the pan‐Arctic level, most products showed Chl increases in the months of July and September (0.3%–0.9% Chl year−1${\\text{year}}^{-1}$ ), even after removing the effect of new open water pixels. Overall, Chl is changing in the Arctic, although trends vary threefold depending on the product and spatial‐averaging assumptions used. Plain Language Summary The Arctic is undergoing critical physical changes that can affect marine ecosystems. Here we analyzed how the concentration of phytoplankton (microorganisms at the base of the marine food‐web) has changed since 1998. To do so, we investigated the temporal trends of chlorophyll (a signature of phytoplankton) as derived from satellites. We found that about 10%–40% of the area with valid satellite pixels had statistically significant phytoplankton trends, with some regions increasing and others decreasing. Over the entire Arctic, Chl has been increasing since 1998, however, the magnitude and statistical significance of the trends varied depending on the satellite product used. Key Points Depending on the month and product, 10%–40% of the area with valid pixels showed statistically significant Chl trends Chl trends in the Arctic are heterogeneous, with some regions increasing and other decreasing Magnitude and significance of Chl trends varied depending on the satellite product used

The Ocean Color Component of the Aerosol Robotic Network(AERONET-OC) supports activities related to ocean color such as validation of satellite data products, assessment of atmospheric correction schemes, and evaluation of bio-optical models through globally distributed standardized measurements of water-leaving radiance and aerosol optical depth. In view of duly assisting the AERONET-OC data user community, this work (i) summarizes the latest investigations on a number of scientific issues related to above-water radiometry, (ii) emphasizes the network expansion that from 2002 until the end of 2020 integrated 31 effective measurement sites, (iii) shows the equivalence of data product accuracy across sites and time for measurements performed with different instrument series, (iv) illustrates the variety of water types represented by the network sites ensuring validation activities across a diversity of observation conditions, and (v) documents the availability of water-leaving radiance data corrected for bidirectional effects by applying a method specifically developed for chlorophyll-a-dominated waters and an alternative one that is likely suitable for any water type.

The absorption of atmospheric carbon dioxide (CO2) in the Southern Ocean represents a critical component of the global oceanic carbon budget. Previous assessments of air‐sea carbon flux variations and long‐term trends in polar regions during winter have faced limitations due to scarce field data and the lack of ocean color satellite imagery, causing uncertainties in estimating CO2 flux estimation. This study utilized the Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation satellite to construct a continuous 16‐year (2006–2021) time series of sea surface partial pressure of CO2 (pCO2) in the Southern Ocean. Our findings revealed that the polar region in South Ocean acts as a carbon sink in winter, with CO2 flux of ∼30 TgC in high‐latitude areas (South of 50°S). This work highlights the efficacy of active remote sensing for monitoring sea surface pCO2 and contributes insights into the dynamic carbonate systems of the Southern Ocean. Plain Language Summary Climate change data from recent decades have consistently shown an increase in atmospheric CO2 concentration. The Southern Ocean, a major carbon sink, is critical in this regard. However, limitations in ocean color remote sensing and infrequent sampling hinder a complete understanding of carbon uptake in high‐latitude regions during winter. Previous reconstructions inadequately considered the biological effect on the air‐sea CO2 exchange process in winter. This study used observations from an active remote sensing satellite to represent the biological effects of CO2 and construct a long‐term time series of sea surface CO2 level for the Southern Ocean. Additionally, the study reassessed the CO2 uptake capacity of the Southern Ocean in winter. These findings suggest that previous estimates may underestimate the CO2 uptake capacity in the high‐latitude regions during winter, potentially due to underestimations of biological effects. This research underscores the value of active remote sensing for obtaining critical biogeochemical parameters in high‐latitude oceans, providing an essential tool for monitoring carbonate systems. Key Points A new method was proposed to reconstruct pressure of CO2 (pCO2) using CALIPSO‐derived bbp data A 16‐year Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation observation‐based pCO2 product was constructed The CO2 uptake capacity in the Southern Ocean during winter was estimated

Previous satellite‐based studies have suggested an expansion of subtropical gyres concomitant with decreasing chlorophyll concentrations over time due to ocean warming, raising major concerns about a potential increase in the ocean desertification and its effect on the global climate. However, these studies have relied on the analysis of limited period and/or single gyre and do not provide a comprehensive overview of the temporal evolution of phytoplankton biomass in these systems. Here, 25‐year (1998–2022) time series of satellite ocean color and sea surface temperature data and mixed layer depth are examined to investigate long‐term trends in phytoplankton chlorophyll and carbon biomass in the five major subtropical gyres on Earth. Main results show that, despite the chlorophyll decrease observed in the most oligotrophic zone of all gyres, phytoplankton biomass is rather constant over time, suggesting that chlorophyll changes in these systems are mainly driven by phytoplankton physiological adaptation to the ongoing warming.

Chlorophyll-a concentration (Chl-a) is a crucial parameter for monitoring the water quality in coastal waters. The principal aim of this study is to evaluate the performance of existing Chl-a band ratio inversion models for estimating Chl-a from Sentinel2-MSI and Sentinel3-OLCI observation. This was performed using an extensive in situ Rrs-Chl-a dataset covering contrasted coastal waters (N = 1244, Chl-a (0.03–555.99) µg/L), which has been clustered into five optical water types (OWTs). Our results show that the blue/green inversion models are suitable to derive Chl-a over clear to medium turbid waters (OWTs 1, 2, and 3) while red/NIR models are adapted to retrieve Chl-a in turbid/high-Chl-a environments. As they exhibited the optimal performance considering these two groups of OWTs, MuBR (multiple band ratio) and NDCI (Normalized Difference Chlorophyll-a Index)-based models were merged using the probability values of the defined OWTs as the blending coefficients. Such a combination provides a reliable Chl-a prediction over the vast majority of the global coastal turbid waters (94%), as evidenced by a good performance on the validation dataset (e.g., MAPD = 21.64%). However, our study further illustrated that none of the evaluated algorithms yield satisfying Chl-a estimates in ultra-turbid waters, which are mainly associated with turbid river plumes (OWT 5). This finding highlights the limitation of multispectral ocean color observation in such optically extreme environments and also implies the interest to better explore hyperspectral Rrs information to predict Chl-a.

A Global Ocean Carbon Algorithm Database (GOCAD) has been developed from over 500 oceanographic field campaigns conducted worldwide over the past 30 years including in situ reflectances and coincident satellite imagery, multi- and hyperspectral Chromophoric Dissolved Organic Matter (CDOM) absorption coefficients from 245–715 nm, CDOM spectral slopes in eight visible and ultraviolet wavebands, dissolved and particulate organic carbon (DOC and POC, respectively), and inherent optical, physical, and biogeochemical properties. From field optical and radiometric data and satellite measurements, several semi-analytical, empirical, and machine learning algorithms for retrieving global DOC, CDOM, and CDOM slope were developed, optimized for global retrieval, and validated. Global climatologies of satellite-retrieved CDOM absorption coefficient and spectral slope based on the most robust of these algorithms lag seasonal patterns of phytoplankton biomass belying Case 1 assumptions, and track terrestrial runoff on ocean basin scales. Variability in satellite retrievals of CDOM absorption and spectral slope anomalies are tightly coupled to changes in atmospheric and oceanographic conditions associated with El Niño Southern Oscillation (ENSO), strongly covary with the multivariate ENSO index in a large region of the tropical Pacific, and provide insights into the potential evolution and feedbacks related to sea surface dissolved carbon in a warming climate. Further validation of the DOC algorithm developed here is warranted to better characterize its limitations, particularly in mid-ocean gyres and the southern oceans.

The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission represents the National Aeronautics and Space Administration’s (NASA) next investment in satellite ocean color and the study of Earth’s ocean–atmosphere system, enabling new insights into oceanographic and atmospheric responses to Earth’s changing climate. PACE objectives include extending systematic cloud, aerosol, and ocean biological and biogeochemical data records, making essential ocean color measurements to further understand marine carbon cycles, food-web processes, and ecosystem responses to a changing climate, and improving knowledge of how aerosols influence ocean ecosystems and, conversely, how ocean ecosystems and photochemical processes affect the atmosphere. PACE objectives also encompass management of fisheries, large freshwater bodies, and air and water quality and reducing uncertainties in climate and radiative forcing models of the Earth system. PACE observations will provide information on radiative properties of land surfaces and characterization of the vegetation and soils that dominate their ref lectance. The primary PACE instrument is a spectrometer that spans the ultraviolet to shortwave-infrared wavelengths, with a ground sample distance of 1 km at nadir. This payload is complemented by two multiangle polarimeters with spectral ranges that span the visible to near-infrared region. Scheduled for launch in late 2022 to early 2023, the PACE observatory will enable significant advances in the study of Earth’s biogeochemistry, carbon cycle, clouds, hydrosols, and aerosols in the ocean–atmosphere–land system. Here, we present an overview of the PACE mission, including its developmental history, science objectives, instrument payload, observatory characteristics, and data products.

Since 2002, China has launched four Haiyang-1 (HY-1) satellites equipped with the Chinese Ocean Color and Temperature Scanner (COCTS), which can observe the sea surface temperature (SST). The planned new generation ocean color observation satellites also carry a sensor for observing the SST represented by the payload in this paper. We analyze the spectral brightness temperature (BT) difference between the payload and the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Terra for the thermal infrared channels (11 and 12 µm) based on atmospheric radiative transfer simulation. The bias and standard deviation (SD) of spectral BT difference for the 11 µm channel are −0.12 K and 0.15 K, respectively, and those for the 12 µm channel are −0.10 K and 0.03 K, respectively. When the total column water vapor (TCWV) decreases from the oceans near the equator to high-latitude oceans, the spectral BT difference of the 11 µm channel varies from a positive deviation to a negative deviation, and that of the 12 µm channel basically remains stable. By correcting the MODIS BT observation using the spectral BT differences, we produce the simulated BT data for the thermal infrared channels of the payload, and then validate it using the Infrared Atmospheric Sounding Interferometer (IASI) carried on METOP-B. The validation results show that the bias of BT difference between the payload and IASI is −0.22 K for the 11 µm channel, while it is −0.05 K for the 12 µm channel. The SD of both channels is 0.13 K. In this study, we provide the simulated BT dataset for the 11 and 12 µm channels of a payload for the retrieval of SST. The simulated BT dataset corrected may be used to develop SST-retrieval algorithms.

The currents and water mass properties at the Pacific entrance of the Indonesian seas are studied using measurements of three subsurface moorings deployed between the Talaud and Halmahera Islands. The moored current meter data show northeastward mean currents toward the Pacific Ocean in the upper 400 m during the nearly 2-yr mooring period, with the maximum velocity in the northern part of the channel. The mean transport between 60- and 300-m depths is estimated to be 10.1–13.2 Sv (1 Sv ≡ 10 6 m 3 s −1 ) during 2016–17, when all three moorings have measurements. The variability of the along-channel velocity is dominated by low-frequency signals (periods > 150 days), with northeastward variations in boreal winter and southwestward variations in summer in the superposition of the annual and semiannual harmonics. The current variations evidence the seasonal movement of the Mindanao Current retroflection, which is supported by satellite sea level and ocean color data, showing a cyclonic intrusion into the northern Maluku Sea in boreal winter whereas a leaping path occurs north of the Talaud Islands in summer. During Apri–July, the moored CTDs near 200 m show southwestward currents carrying the salty South Pacific Tropical Water into the Maluku Sea.

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 homogenization, 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 148 432 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.