Correction of Biogeochemical-Argo Radiometry for Sensor Temperature-Dependence and Drift: Protocols for a Delayed-Mode Quality Control.

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.

Quantifying the Impact of Linear Regression Model in Deriving Bio-Optical Relationships: The Implications on Ocean Carbon Estimations.

Linear regression is widely used in applied sciences and, in particular, in satellite optical oceanography, to relate dependent to independent variables. It is often adopted to establish empirical algorithms based on a finite set of measurements, which are later applied to observations on a larger scale from platforms such as autonomous profiling floats equipped with optical instruments (e.g., Biogeochemical Argo floats; BGC-Argo floats) and satellite ocean colour sensors (e.g., SeaWiFS, VIIRS, OLCI). However, different methods can be applied to a given pair of variables to determine the coefficients of the linear equation fitting the data, which are therefore not unique. In this work, we quantify the impact of the choice of "regression method" (i.e., either type-I or type-II) to derive bio-optical relationships, both from theoretical perspectives and by using specific examples. We have applied usual regression methods to an in situ data set of particulate organic carbon (POC), total chlorophyll-a (TChla), optical particulate backscattering coefficient (bbp), and 19 years of monthly TChla and bbp ocean colour data. Results of the regression analysis have been used to calculate phytoplankton carbon biomass (Cphyto) and POC from: i) BGC-Argo float observations; ii) oceanographic cruises, and iii) satellite data. These applications enable highlighting the differences in Cphyto and POC estimates relative to the choice of the method. An analysis of the statistical properties of the dataset and a detailed description of the hypothesis of the work drive the selection of the linear regression method.

Radiative Transfer Modeling With Biogeochemical-Argo Float Data in the Mediterranean Sea.

A radiative transfer model was parameterized and validated using Biogeochemical Argo float data acquired between 2012 and 2017 across the Mediterranean Sea. Fluorescence-derived chlorophyll a concentration, particulate optical backscattering at 700 nm, and fluorescence of chromophoric dissolved organic matter (CDOM) were used to parametrize the light absorption and scattering coefficients of the optically significant water constituents (such as pure water, non-algal particles, CDOM, and phytoplankton). The model was validated with in situ downwelling irradiance profiles and apparent optical properties derived both from irradiance profiles and satellite data, such as the diffuse attenuation coefficients and remote sensing reflectance. Results showed that by using regional parameterizations that are not only related to chlorophyll concentration and vertical distribution, the model was able to capture a more accurate spectral response in the examined wavelength range compared to chlorophyll-related (or Case 1) optical models. When using alternative models that incorporated also measurements of CDOM fluorescence or particulate optical backscattering, the model skill increased at all examined wavelengths. Finally, using a multi-spectral optical configuration also enabled the estimation of the relative contribution of separate water constituents in the examined spectral range. Simulations including non-algal particles and CDOM performed up to 61% and 79% better than when considering the optical properties of pure seawater alone. Moreover, a simulation including phytoplankton light absorption resulted in an error reduction of up to 42%, especially at 412 nm and with a more uniform response at the wavelengths considered.

Arctic mid-winter phytoplankton growth revealed by autonomous profilers.

It is widely believed that during winter and spring, Arctic marine phytoplankton cannot grow until sea ice and snow cover start melting and transmit sufficient irradiance, but there is little observational evidence for that paradigm. To explore the life of phytoplankton during and after the polar night, we used robotic ice-avoiding profiling floats to measure ocean optics and phytoplankton characteristics continuously through two annual cycles in Baffin Bay, an Arctic sea that is covered by ice for 7 months a year. We demonstrate that net phytoplankton growth occurred even under 100% ice cover as early as February and that it resulted at least partly from photosynthesis. This highlights the adaptation of Arctic phytoplankton to extreme low-light conditions, which may be key to their survival before seeding the spring bloom.

Abrupt warming and salinification of intermediate waters interplays with decline of deep convection in the Northwestern Mediterranean Sea.

The Mediterranean Sea is a hotspot for climate change, and recent studies have reported its intense warming and salinification. In this study, we use an outstanding dataset relying mostly on glider endurance lines but also on other platforms to track these trends in the northwestern Mediterranean where deep convection occurs. Thanks to a high spatial coverage and a high temporal resolution over the period 2007-2017, we observed the warming (+0.06 [Formula: see text]C year[Formula: see text]) and salinification (+0.012 year[Formula: see text]) of Levantine Intermediate Water (LIW) in the Ligurian Sea. These rates are similar to those reported closer to its formation area in the Eastern Mediterranean Sea. Further downstream, in the Gulf of Lion, the intermediate heat and salt content were exported to the deep layers from 2009 to 2013 thanks to deep convection processes. In 2014, a LIW step of +0.3 [Formula: see text]C and +0.08 in salinity could be observed concomitant with a weak winter convection. Warmer and more saline LIW subsequently accumulated in the northwestern basin in the absence of intense deep convective winters until 2018. Deep stratification below the LIW thus increased, which, together with the air-sea heat fluxes intensity, constrained the depth of convection. A key prognostic indicator of the intensity of deep convective events appears to be the convection depth of the previous year.

Ocean plankton. Environmental characteristics of Agulhas rings affect interocean plankton transport.

Agulhas rings provide the principal route for ocean waters to circulate from the Indo-Pacific to the Atlantic basin. Their influence on global ocean circulation is well known, but their role in plankton transport is largely unexplored. We show that, although the coarse taxonomic structure of plankton communities is continuous across the Agulhas choke point, South Atlantic plankton diversity is altered compared with Indian Ocean source populations. Modeling and in situ sampling of a young Agulhas ring indicate that strong vertical mixing drives complex nitrogen cycling, shaping community metabolism and biogeochemical signatures as the ring and associated plankton transit westward. The peculiar local environment inside Agulhas rings may provide a selective mechanism contributing to the limited dispersal of Indian Ocean plankton populations into the Atlantic.

Deep-sea bioluminescence blooms after dense water formation at the ocean surface.

The deep ocean is the largest and least known ecosystem on Earth. It hosts numerous pelagic organisms, most of which are able to emit light. Here we present a unique data set consisting of a 2.5-year long record of light emission by deep-sea pelagic organisms, measured from December 2007 to June 2010 at the ANTARES underwater neutrino telescope in the deep NW Mediterranean Sea, jointly with synchronous hydrological records. This is the longest continuous time-series of deep-sea bioluminescence ever recorded. Our record reveals several weeks long, seasonal bioluminescence blooms with light intensity up to two orders of magnitude higher than background values, which correlate to changes in the properties of deep waters. Such changes are triggered by the winter cooling and evaporation experienced by the upper ocean layer in the Gulf of Lion that leads to the formation and subsequent sinking of dense water through a process known as "open-sea convection". It episodically renews the deep water of the study area and conveys fresh organic matter that fuels the deep ecosystems. Luminous bacteria most likely are the main contributors to the observed deep-sea bioluminescence blooms. Our observations demonstrate a consistent and rapid connection between deep open-sea convection and bathypelagic biological activity, as expressed by bioluminescence. In a setting where dense water formation events are likely to decline under global warming scenarios enhancing ocean stratification, in situ observatories become essential as environmental sentinels for the monitoring and understanding of deep-sea ecosystem shifts.

Climate-driven basin-scale decadal oscillations of oceanic phytoplankton.

Phytoplankton--the microalgae that populate the upper lit layers of the ocean--fuel the oceanic food web and affect oceanic and atmospheric carbon dioxide levels through photosynthetic carbon fixation. Here, we show that multidecadal changes in global phytoplankton abundances are related to basin-scale oscillations of the physical ocean, specifically the Pacific Decadal Oscillation and the Atlantic Multidecadal Oscillation. This relationship is revealed in approximately 20 years of satellite observations of chlorophyll and sea surface temperature. Interaction between the main pycnocline and the upper ocean seasonal mixed layer is one mechanism behind this correlation. Our findings provide a context for the interpretation of contemporary changes in global phytoplankton and should improve predictions of their future evolution with climate change.