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Phytoplankton photoacclimation is a well‐documented response to changes in light and nutrient availability, with the Chlorophyll a to phytoplankton Carbon ratio (θ $\\theta $ = Chl: Cphyto ${\\mathrm{C}}_{\\text{phyto}}$) increasing at low light and decreasing under high light to optimize growth rate. Accurate estimation of phytoplankton growth rates and Net Primary Production (NPP) from space requires knowledge of θ $\\theta $, but cloud cover creates gaps. Current NPP models fill in the gaps by interpolating Chl (and other inputs) from clear‐sky pixels, ignoring the possibility of photoacclimation underneath clouds. Using data from ≈ ${\\approx} $9,000 matchups between BioGeoChemical‐Argo floats and cloud cover from the Moderate Resolution Imaging Spectroradiometer, we compared the response of θ $\\theta $ to irradiances under cloudy and clear skies. We found that phytoplankton photoacclimate similarly regardless of sky conditions at the global scale. This study highlights an incorrect assumption in current NPP estimates and suggests ways to improve global assessments of both chlorophyll and NPP.

We use observations from the Southern Ocean (SO) biogeochemical profiling float array to quantify the meridional pattern of particle export efficiency (PEeff) during the austral productive season. Float estimates reveal a pronounced latitudinal gradient of PEeff, which is quantitatively supported by a compilation of existing ship‐based measurements. Relying on complementary float‐based estimates of distinct carbon pools produced through biological activity, we find that PEeff peaks near the region of maximum particulate inorganic carbon sinking flux in the polar antarctic zone, where net primary production (NPP) is the lowest. Regions characterized by intermediate NPP and low PEeff, primarily in the subtropical and seasonal ice zones, are generally associated with a higher fraction of dissolved organic carbon production. Our study reveals the critical role of distinct biogenic carbon pool production in driving the latitudinal pattern of PEeff in the SO. Plain Language Summary Microbial organisms in seawater transform carbon dioxide into different types of carbon through photosynthesis and food web cycling. These carbon types include particulate and dissolved phases, with particles being more efficiently transferred out of the sunlit ocean via gravitational sinking. The ratio of sinking particulate organic carbon to total organic carbon production, commonly referred to as the particle export efficiency, is a metric used to describe how efficiently carbon moves from the surface to the deep ocean. Using observations from a large array of robots in the Southern Ocean, we find that the different types of biogenic carbon produced control the latitudinal gradient in particle export efficiency, which is highest in regions where particulate inorganic carbon export is greatest, even when photosynthetically fixed carbon is minimal. In other areas where phytoplankton carbon production is moderate but largely comprised of dissolved organic carbon, the particle export efficiency is lower. Key Points Meridional pattern of particle export efficiency (PEeff) estimated from BGC‐Argo aligns with ship‐based observations in the Southern Ocean Low PEeff in subtropical and ice‐covered regions and high PEeff in subpolar regions is linked to the biogenic carbon pools produced Most global models struggle to reproduce the meridional pattern of PEeff in the Southern Ocean

The seasonal variability of phytoplankton vertical distribution is investigated in the South Pacific where observations are scarce and scattered. We used 13 BioGeoChemical‐Argo floats deployed across diverse oceanic environments. The seasonal latitudinal displacement of the Tasman front induces transitions from mesotrophic to oligotrophic conditions. This shift results in Chlorophyll‐a concentration vertical distribution changing from bloom types to Subsurface Chlorophyll Maxima (SCM) types, with intermediate hybrid types between these extremes. Such hybrid profiles frequently occur in the equatorial Pacific, highlighting a large‐scale pattern rather than local island mass effect. In oligotrophic regions, seasonal variations of light availability and stratification dynamics below the mixed layer likely relate SCM to an increase in carbon biomass or photoacclimation. A biomass increase is frequently observed, contrary to previous studies, suggesting that subsurface phytoplankton biomass may have been largely underestimated. This calls for further observations of the water column in these remote undersampled open ocean areas.

Carbon export driven by submesoscale, eddy‐associated vertical velocities (“eddy subduction”), and particularly its seasonality, remains understudied, leaving a gap in our understanding of ocean carbon sequestration. Here, we assess mechanisms controlling eddy subduction's spatial and seasonal patterns using 15 years of observations from BGC‐Argo floats in the Southern Ocean. We identify signatures of eddy subduction as subsurface anomalies in temperature‐salinity and oxygen. The anomalies are spatially concentrated near weakly stratified areas and regions with strong lateral buoyancy gradients diagnosed from satellite altimetry, particularly in the Antarctic Circumpolar Current's standing meanders. We use bio‐optical ratios, specifically the chlorophyll a to particulate backscatter ratio (Chl/bbp) to find that eddy subduction is most active in the spring and early summer, with freshly exported material associated with seasonally weak vertical stratification and increasing surface biomass. Climate change is increasing ocean stratification globally, which may weaken eddy subduction's carbon export potential. Plain Language Summary Oceans play an important role in global climate by soaking up and sequestering atmospheric carbon dioxide. Photosynthetic activity at the surface turns carbon dioxide into organic carbon, and if this carbon leaves the surface to the deep ocean, it can be locked away from the atmosphere. One way this occurs is through the physical circulation associated with swirling eddies, which can rapidly transport organic carbon‐rich surface waters and “inject” them into deep waters. However, we still don't fully understand the seasonal timing of this process, or what drives its spatial distribution. We investigated this in the Southern Ocean, which is very important to global climate, using data collected by drifting robots. We find that this process is the most active in regions where eddies drive strong surface stirring, and during the spring, when weak stratification allows injections to penetrate deep into the ocean. Because this process is poorly represented in climate models, these findings will improve our understanding of how the ocean absorbs carbon. Key Points Eddy subduction in the Southern Ocean is observed as subsurface anomalies in spice and oxygen measured by autonomous profiling floats Spatial distribution is controlled by weak stratification and strong lateral buoyancy gradients, diagnosed using satellite altimetry Bio‐optical proxies suggest that eddy subduction is most active in spring/early summer, driven by weak vertical stratification

Model parameterizations of particulate organic carbon (POC) flux are critical for simulating the strength and future evolution of the biological carbon pump (BCP) but remain poorly constrained because direct observations are sparse. Here, we ask whether the Biogeochemical (BGC)‐Argo proxy observations of POC can help distinguish between these parameterizations by objectively comparing two common parameterizations, which reproduce the observed slowdown of flux attenuation with depth by either decreasing the remineralization rate or increasing the sinking velocity. Both can well reproduce the BGC‐Argo observations in top 1,000 m but predict different POC concentration below, making them possible to be distinguished if BGC‐Argo observations were available there. Therefore, an integration of backscatter sensors into the Deep Argo program is recommended to provide full depth proxy measurements. If the parameterization is known, POC flux can be determined from POC concentration. Thus, the BGC‐Argo proxy observations of POC concentration provide new insights into the BCP. Plain Language Summary Photosynthesis produces organic particles at the ocean's surface. A fraction of these particles sinks to the deep ocean where they are decomposed into inorganic forms. This process, referred to as the biological carbon pump, leads to the storage of inorganic carbon in the deep ocean for hundreds to thousands of years and influences atmospheric CO2 levels. The fraction of organic particles reaching the deep ocean is determined by their remineralization rate and sinking velocity. Both parameters are only poorly constrained by sparse in situ observations of particle flux and climatological data sets of nutrients but are critically important for model projections of future climate. Observation of organic particle concentration throughout the ocean interior is now possible with bio‐optical sensors on Biogeochemical (BGC)‐Argo floats. Particle concentration is dynamically related to vertical particle flux, but has received little attention so far as an observable for calibrating vertical carbon flux in biogeochemical models. This study investigates to what extent the bio‐optical proxy observations of organic carbon concentration can help in calibrating biogeochemical models. Our results suggest that observations of organic carbon concentration can inform us on the appropriate choice of parameterization for particle sinking and provide useful constraints in the calibration of flux‐related parameters. Key Points Two widely used parameterizations of vertical carbon flux are compared objectively in the same model environment The value of Biogeochemical‐Argo observations of backscatter for distinguishing between vertical flux parameterizations is assessed An integration of backscatter sensors into the Deep Argo program will help distinguish between the two parameterizations

Satellite observations can reveal chlorophyll blooms in the wake of hurricane disturbances but their subsurface biogeochemical anomalies remain poorly described due to limited in situ observations. Here, we quantify the biogeochemical response across the ocean water column to Hurricane Idalia (2023) in the Gulf of America (also known as the Gulf of Mexico). We compile observations across the eastern Gulf using satellite data and two autonomous platforms: a profiling Biogeochemical-Argo (BGC-Argo) float and saildrone. Prior to the formation of Hurricane Idalia, an anomalously large extension of the Mississippi River plume spanned much of the eastern Gulf, contributing low-salinity and high-chlorophyll conditions. Following Idalia’s passage, the saildrone observed surface chlorophyll increases in the river plume extension, while the BGC-Argo float observed subsurface nitrate depletion and oxygen enrichment. These changes occurred as the float measured background ocean conditions evolving from the edge of the Loop Current to a cyclonic eddy, influenced by the river plume extension. Increases in chlorophyll concentration, decreases in nitrate, and elevated dissolved oxygen levels suggested increased primary production. BGC-Argo float observations revealed enhanced upwelling below the surface layer (~22 m) that shoaled the nitracline, fueling the increase in subsurface primary production (20–50 m depth). Our study provides a glimpse on the surface and subsurface ocean-biogeochemical changes associated with the Hurricane Idalia passage, highlighting the importance of the background mesoscale seascape on shaping the phytoplankton response to hurricane-induced disturbances. The combination of observations underscores the value of continuous in situ monitoring to better understand hurricane-driven impacts on the full ocean water column and the impacts these dynamics have on the base of the marine food web.

Measuring the underwater light field is a key mission of the international Biogeochemical-Argo program. Since 2012, 0–250 dbar profiles of downwelling irradiance at 380, 412 and 490 nm besides photosynthetically available radiation (PAR) have been acquired across the globe every 1 to 10 days. The resulting unprecedented amount of radiometric data has been previously quality-controlled for real-time distribution and ocean optics applications, yet some issues affecting the accuracy of measurements at depth have been identified such as changes in sensor dark responsiveness to ambient temperature, with time and according to the material used to build the instrument components. Here, we propose a quality-control procedure to solve these sensor issues to make Argo radiometry data available for delayed-mode distribution, with associated error estimation. The presented protocol requires the acquisition of ancillary radiometric measurements at the 1000 dbar parking depth and night-time profiles. A test on >10,000 profiles from across the world revealed a quality-control success rate >90% for each band. The procedure shows similar performance in re-qualifying low radiometry values across diverse oceanic regions. We finally recommend, for future deployments, acquiring daily 1000 dbar measurements and one night profile per year, preferably during moonless nights and when the temperature range between the surface and 1000 dbar is the largest.

Estimates of the diffuse attenuation coefficient (Kd) at two different wavelengths and band-integrated (PAR) were obtained using different published algorithms developed for open ocean waters spanning in type from explicit-empirical, semi-analytical and implicit-empirical and applied to data from spectral radiometers on board six different satellites (MODIS-Aqua, MODIS-Terra, VIIRS–SNPP, VIIRS-JPSS, OLCI-Sentinel 3A and OLCI-Sentinel 3B). The resultant Kds were compared to those inferred from measurements of radiometry from sensors on board autonomous profiling floats (BGC-Argo). Advantages of BGC-Argo measurements compared to ship-based ones include: 1. uniform sampling in time throughout the year, 2. large spatial coverage, and 3. lack of shading by platform. Over 5000 quality-controlled matchups between Kds derived from float and from satellite sensors were found with values ranging from 0.01 to 0.67 m−1. Our results show that although all three algorithm types provided similarly ranging values of Kd to those of the floats, for most sensors, a given algorithm produced statistically different Kd distributions from the two others. Algorithm results diverged the most for low Kd (clearest waters). Algorithm biases were traced to the limitations of the datasets the algorithms were developed and trained with, as well as the neglect of sun angle in some algorithms. This study highlights: 1. the importance of using comprehensive field-based datasets (such as BGC-Argo) for algorithm development, 2. the limitation of using radiative-transfer model simulations only for algorithm development, and 3. the potential for improvement if sun angle is taken into account explicitly to improve empirical Kd algorithms. Recent augmentation of profiling floats with hyper-spectral radiometers should be encouraged as they will provide additional constraints to develop algorithms for upcoming missions such as NASA’s PACE and SBG and ESA’s CHIME, all of which will include a hyper-spectral radiometer.

Oceanic submesoscales can significantly influence phytoplankton production and export owing to their similar timescales of days. Based on two-year Biogeochemical Argo (BGC-Argo) observations, this study investigated the development of submesoscale instabilities, particularly symmetric and mixed-layer baroclinic instabilities, and their impacts on biological production and export in the oligotrophic South China Sea basin. In the northern basin, near-surface winter blooms consistently cooccurred with seasonally deepened mixed layers. However, significantly stronger and weaker winter blooms were observed over two consecutive winters within the BGC-Argo observation period. During the first winter, symmetric-instability-induced upward nutrient entrainment played a crucial role in initiating the strong winter bloom in early December, when the mixed layer was approximately 20–30 m shallower than the nutricline. This bloom occurred approximately 20–30 days earlier than that anticipated owing to the contact between the seasonally deepened mixed layer and mesoscale-cyclone-induced uplifted nutricline. The symmetric instability also facilitated the export of fixed phytoplankton carbon from the surface to deeper layers. Conversely, during the second winter, remarkably intense mixed-layer baroclinic instability associated with an intense mesoscale anticyclone led to more significant shoaling of the mixed layer compared to the nutricline, thus increasing the vertical distance between the two layers. Under this condition, upward nutrient injection, phytoplankton bloom, and carbon export were suppressed. In contrast, the BGC-Argo float in the central basin revealed significantly inhibited seasonality of phytoplankton biomass and submesoscale instabilities compared to those in the northern basin, primarily owing to the significantly shallower winter mixed layer.

Dissolved oxygen (DO) is essential for assessing and monitoring the health of marine ecosystems. The phenomenon of ocean deoxygenation is widely recognized. Nevertheless, the limited availability of observations poses a challenge in achieving a comprehensive understanding of global ocean DO dynamics and trends. The study addresses the challenge of unevenly distributed Argo DO data by developing time–space–depth machine learning (TSD-ML), a novel machine learning-based model designed to enhance reconstruction accuracy in data-sparse regions. TSD-ML partitions Argo data into segments based on time, depth, and spatial dimensions, and conducts model training for each segment. This research contrasts the effectiveness of partitioned and non-partitioned modeling approaches using three distinct ML regression methods. The results reveal that TSD-ML significantly enhances reconstruction accuracy in areas with uneven DO data distribution, achieving a 30% reduction in root mean square error (RMSE) and a 20% decrease in mean absolute error (MAE). In addition, a comparison with WOA18 and GLODAPv2 ship survey data confirms the high accuracy of the reconstructions. Analysis of the reconstructed global ocean DO trends over the past two decades indicates an alarming expansion of anoxic zones.