Near-Surface Particulate Backscattering Observations with Bio-Optical Lagrangian Drifters
1. Introduction
Particulate matter concentration is an essential ocean variable commonly used to describe biogeochemical processes over a wide range of spatial and temporal scales (Stramski et al. 1999; Chai et al. 2020). Observations of particulate matter concentration are also important to reduce the uncertainties of ocean carbon budget estimates (Brewin et al. 2023). Furthermore, measurements of particulate matter concentration improve the estimates of ocean productivity, such as net primary production (NPP) and net community production (NCP), which can be used to constrain coupled physical and biogeochemical numerical models (Johnson and Bif 2021; Stoer and Fennel 2022). In a climate change scenario, accurate estimates of NPP are important since the latter represents the material that can eventually be exported via biological pumps and hence it is a net biological sink for CO2 (Aricò et al. 2021; Brewin et al. 2023). However, accurate in situ open ocean measurements of particulate matter concentration and derived quantities (e.g., NPP) are technically challenging and often result in geographically and temporally biased datasets (Johnson and Bif 2021; Stoer and Fennel 2022; Brewin et al. 2023).
The optical particulate backscattering coefficient (bbp), defined as the fraction of incident light that is scattered by particles in the backward direction (Boss et al. 2004), is a reliable proxy of particulate matter. Several studies have demonstrated that bbp varies with the concentration, composition, size distribution, shape, and structure of particles (Stramski and Kiefer 1991). The bbp signal is dominated by particles with diameters ranging between 1 and 10 μm, which include algal (pico- and nanoplankton) and nonalgal particles (i.e., inorganic and organic detritus) (Organelli et al. 2018). It can be used to estimate changes in carbon content and abundance (Freitas et al. 2020) since it is used to quantify concentration of particulate organic and inorganic carbon (POC and PIC, respectively) and of phytoplankton biomass (Cphyto) (Bellacicco et al. 2020; Siegel et al. 2023).
The paucity of in situ measurements of bbp is particularly noticeable in the subtropical gyres, in the Southern Hemisphere, and in the Arctic Ocean (Valente et al. 2022; Brewin et al. 2023). Most in situ multispectral bbp observations have limited space/time coverage and are often ship-borne (Dall’Olmo et al. 2012), or obtained from moored installations (Antoine et al. 2011). Ship-borne observations are limited by high operating costs and are vulnerable to extreme weather conditions, resulting in sparse datasets often biased toward summer months and covering mostly coastal areas (Valente et al. 2022). Moored systems, which are also characterized by high operating costs, generate time series with high temporal resolution at fixed locations; however, they cannot provide a synoptic view of the optical properties of the ocean (Bellacicco et al. 2019b). Polar orbiting satellite ocean color sensors provide bbp estimates at synoptic scales only of ocean surface, but with a reduced temporal resolution, typically a single observation per day. Optical observations from passive sensors are also negatively affected by cloud coverage and by low light conditions at high latitudes during winter months (Bisson et al. 2019; Chai et al. 2020). Profiling floats equipped with optical sensors, such as the ones used for biogeochemical (BGC) Argo floats (Claustre et al. 2020), can provide profiles of bbp from 2000-m depth to the surface approximately every 10 days on large spatial (basin/global) and temporal scales (seasonal/interannual). Such data have been used to estimate the three-dimensional structure of bbp and its seasonal variability (Chai et al. 2020). Marine productivity estimates are improved when the diel cycle of bbp is measured at multiple wavelengths following the natural daily light cycle (Stoer and Fennel 2022), but while BGC-Argo sampling is not usually designed to resolve the diel cycle, fixed moorings are instead limited in the spatial coverage. NPP could also benefit from multiband bbp observations retrieving information on particle size distribution (PSD) from the spectral decay slope η (Pitarch et al. 2020; Brewin et al. 2023). However, the validity of PSD-slope dependence has not been confirmed in some open ocean regions (Reynolds et al. 2016; Boss et al. 2018; Organelli et al. 2020).
The use of Lagrangian (i.e., water following) Surface Velocity Programme (SVP) drifting buoys (e.g., Centurioni 2018) similar to the ones used to sustain the Global Drifter Program (Niiler 2001) in ocean color studies was pioneered over 3 decades ago (e.g., Abbott et al. 1990), but it was subsequently abandoned in favor of ship-borne and mooring methodologies. However, advances in global broadband satellite communication, low-power microprocessor technology, and the availability of self-contained backscatter sensors designed for long-term deployments have revamped the interest in this approach.
The overarching goal of this study is to describe the integration of a commercially available, high-frequency, and multispectral optical backscatter sensor into an SVP drifter to collect bbp measurements near the ocean surface. We first describe the technology, followed by summary of the in situ near-surface bbp observations collected by drifters that were deployed in regions with widely different optical characteristics. Then, we discuss the validation of our observations using independent and nearly collocated in situ sensors and operational, satellite-derived, ocean color products. The benefits of our approach for the validation of space-borne bbp products and possible impact on backscatter-derived quantities (e.g., Cphyto, NPP; Behrenfeld et al. 2005; Graff et al. 2015; Brewin et al. 2023) are also discussed. Our methodology provides near-surface bbp (and proxy quantities) data and concurrent physical parameters (e.g., sea surface temperature and ocean currents) that can help contextualize the observed optical properties with ocean dynamical structures (e.g., fronts, tidal currents, coastal filaments, and eddies), over a wide range of spatial (submesoscale to basin scales) and temporal scales (hours to months) and could provide new insight on the physical/biological interactions which are thought to modulate productivity of the marine ecosystem (McGillicuddy 2016; Lévy et al. 2018, 2023).
2. Data and method
a. Surface bio-optical drifter
SVP drifters with drogue at 15-m depth are the primary source of in situ global observations of near-surface ocean currents and have been used for decades to study the ocean circulation and dynamics from submesoscales (∼1 km) to basin scales (1000 km) (Niiler 2001; Centurioni 2018; Essink et al. 2022). The SVP drifter is the “workhorse” of the Global Drifter Programme (GDP; https://gdp.ucsd.edu/ldl/svp/) due to its exceptional resistance to harsh environmental conditions (e.g., ice, tropical cyclones, and waves; Centurioni et al. 2019). The drogue is, in essence, a drag element centered at 15-m depth. The drogue depth is chosen to minimize the contamination from surface waves and, at the same time, to enable observations of near-surface ocean currents in the upper ocean mixed layer. The drogue size ensures that its drag is at least 40 times larger than the drag of all the other components of the drifter (tether, sensors, and surface buoy). When this condition is satisfied, the drifter-derived currents have an accuracy of 0.01 for winds up to 10 m s−1 (Niiler et al. 1995). The SVP drifter is geolocated with a Global Position System (GPS) receiver and relays data to shore in near–real-time through the Iridium Satellite communication system. Several sensors have been developed and integrated into the SVP platform, including anemometer, conductivity cells for salinity (surface and subsurface), thermometers (surface and subsurface), profiling current meters, solar radiation, barometer, and directional wave spectra (Centurioni 2010; Centurioni et al. 2015, 2017; Hormann et al. 2015; Centurioni 2018; Klenz et al. 2022). Sea surface temperature data are widely used to validate satellite-derived SST products (e.g., X. Zhang et al. 2009; Centurioni et al. 2019). The proven technology and the presence of additional sensors to measure, for example, SST and salinity, make the SVP drifter platform an excellent candidate for the integration of the optical backscatter sensor.
The SVP drifter configured with SST, backscatter, and subsurface temperature and salinity sensors is termed backscatter optical-SVP (BO-SVP). The subsurface temperature and salinity sensors are installed on the tether and as close as possible to the optical backscatter package (Fig. 1). For this study, two standard SVP drifters (IDs numbers 300534061492130 and 300534061492160) were equipped with the compact EcoTriplet (by Sea-Bird inc.; sensitivity for scattering: 0.003 m−1), which is the sensor routinely integrated on BGC-Argo floats, underwater gliders, and moorings (Chai et al. 2020) and with a SBE37 CT sensor, also manufactured by Sea-Bird inc (accuracy: 0.0003 S m2 for conductivity, or about 0.003 PSU, and 0.0028°C for temperature).
Infographic picture showing a deployed BO-SVP drifter with indicated the depths of the SST, CT, and optical sensors.
Citation: Journal of Atmospheric and Oceanic Technology 41, 11; 10.1175/JTECH-D-23-0161.1
Four independent deployments of BO-SVP drifters were used to test our methodology (Fig. 2): a 7-day-long deployment in the Tyrrhenian Sea during the COSIMO22 cruise; a 1-day-long deployment in North Sea during the JPI-OCEAN S4GES cruise; a 3-day-long deployment in the Norwegian Sea during the NORSE22 cruise; and a 5-day-long deployment in the Balearic Sea during the BIOSWOT-Med experiment. Locations were chosen to measure the optical backscattering under a wide range of oceanic conditions in coastal and open ocean waters. For the Tyrrhenian and the North Sea experiments, the optical and the SB37 CT sensors were mounted at 5-m depth. For the first two deployments, the optical sensor was configured for a single λ of 532 nm and the sampling intervals were set to 15 min, with 10 light bursts for the Tyrrhenian Sea and to 5 min with 10 light bursts for the North Sea. For the Norwegian Sea deployment, the optical and SB37 CT sensors were mounted at a depth of 9 m, and the optical sensor was configured with three bbp channels (460, 570, and 700 nm) and set to emit 20 bursts every 15 min (Fig. 2). Last, for the Balearic Sea deployment, the optical and the SB37 CT sensors were mounted at 9-m depth. The optical sensor was settled for a single λ of 532 nm, and the sampling intervals were set to 10 min with 10 light bursts.
Tracks of BO-SVP drifter in the Norwegian Sea [(A1); 300534061492130], in the North Sea [(A2); 300534061492160], along coastal Tyrrhenian Sea [(A3); 300534061492160], and in the Balearic Sea [(A4); 300534061492130]. Track color represents the bbp magnitude (note different scales). Independent in situ sampling point is indicated as yellow stars.
Citation: Journal of Atmospheric and Oceanic Technology 41, 11; 10.1175/JTECH-D-23-0161.1
b. Reference datasets
In this section, we describe the independent datasets used to validate the bbp measurements obtained from the BO-SVP drifter:
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Cruise data: During the experiments in the Tyrrhenian Sea and in the North Sea, bbp profiles were collected from research vessels (Fig. 2). Data from the closest stations (within 5 km and 24 h and the median between 4- and 6-m depth) were used for the comparisons. The reference probe for the Tyrrhenian Sea cruise was the SC6 (by In situ Marine Optics, WA, Australia). The SC6 (SN 0001) measures the VSF at the wavelengths 365, 440, 510, 560, 660, and 730 nm, with an angular field of view centered at around 124°. In the North Sea, we used an ECO-VSF3 by Wetlabs Inc. (now Sea-Bird Inc.) that measures the VSF at the wavelengths 470, 532, and 660 nm and at three angular geometries, with fields of view centered at about 104°, 131°, and 151°. In both cases, the dark counts were subtracted from the raw data and scaling factors (calibrations) were applied to obtain the total VSF at the given angles. Then, the water VSF at the same angles and wavelengths was subtracted (X. Zhang et al. 2009). The total VSF of particles was then converted to bbp using χ = 1.113 for the SC6 and χ = 1.104 for the ECO-VSF at 131° (Sullivan et al. 2013). Since the SC6 instrument does not provide data at 532-nm band, we interpolated the bbp observations obtained at 510 and 560 nm by applying a power-law fit.
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BGC-Argo floats data: In the Norwegian Sea, data from three BGC Argo profiling floats with WMO numbers 6902548, 6903575, and 6903577 (available at ftp://ftp.ifremer.fr/ifremer/argo) were used (Fig. 2). Here, these three BGC-Argo floats were also equipped with an EcoTriplet by Sea-Bird inc. Following Schmechtig et al. (2018) and Carval et al. (2018), the bbp at 700 nm was obtained by removing the contribution of pure seawater (H.-M. Zhang et al. 2009) from β (124°, 700 nm), using the method described also in Organelli et al. (2017) and Bellacicco et al. (2019a). The bbp(700) was averaged between 7- and 11-m depth for all the available observations in October (N = 17) during the period 2015–22 to obtain a mean regional reference value for the month of October.
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Ocean color data: Daily merged satellite remote sensing reflectance Rrs (sr−1) data time series at 1-km resolution (dataset OCEANCOLOUR_MED_BGC_L3_MY_009_143) was obtained from the Copernicus Marine Service over the Tyrrhenian and Balearic seas for the duration of the BO-SVP drifter deployment (see Table 1). The Rrs datasets were then used to compute daily bbp after the application of the Quasi-Analytical Algorithm (QAA) with Raman correction included (Lee et al. 2002; Pitarch et al. 2020). The QAA is a multilevel algorithm that concatenates a sequence of empirical, analytical, and semianalytical steps to retrieve at different wavelengths. The high accuracy of the QAA for bbp retrieval in open and coastal waters, especially for Mediterranean Sea, was recently demonstrated (Pitarch et al. 2016, 2020).
Details of experiments and statistics for bbp measurements collected.
c. Statistical metrics
3. Results and discussion
a. Overview of bbp observations and comparison to reference data
During the four experiments, the BO-SVP drifters acquired over 1200 bbp observations while drifting approximately 240 km (Table 1), from a coastal region to open ocean waters. In the Tyrrhenian Sea, bbp (532) values ranged from 2.5 × 10−3 to 1.7 × 10−2 m−1, consistent with values observed in similar coastal waters from both in situ and satellite data (Pitarch et al. 2016) (Table 1). In the North Sea, which is an area characterized by a strong tidal regime, as shown by the trajectory of the BO-SVP, bbp (532) showed a low variability ranging from 4.9 × 10−3 to 9.9 × 10−3 m−1. Instead, in the Norwegian Sea, which is an oligotrophic region of the ocean (Dall’Olmo and Mork 2014), bbp values were about an order of magnitude lower than the values observed in more coastal waters and showed a reduced temporal variability (Table 1). Indeed, bbp ranged from 1.1 × 10−3 to 1.3 × 10−3 m−1 at 460 nm, from 1.1 × 10−3 to 1.4 × 10−3 m−1 at 532 nm, and from 8.0 × 10−4 to 1.1 × 10−3 at 700 nm. The bbp (700) showed consistency with the near-surface bbp measurements collected by two BGC-Argo floats in the Lofoten basin during winter (see Fig. 2 in Dall’Olmo and Mork 2014). The observed small bbp values within the Norwegian Sea at ∼70°–72° N are a consequence of low-light low-nutrients conditions that limit the growth of phytoplankton, bacteria, and viruses, which is usually interpreted as a footprint of a reduced particle concentration and biological activity (e.g., particle growth and losses and phytoplankton stocks) (Dall’Olmo and Mork 2014). In this area, the observed oligotrophic condition is also linked to the surface ocean circulation where cold and less saline Arctic water flows both southward with the East Greenland Current (EGC) and eastward in correspondence with Jan Mayen and the Mohns Ridge (see blue line in Fig. 1 of Mork et al. 2019). In the Balearic Sea, the BO-SVP drifter moved along an anticyclonic mesoscale structure with bbp (532) values between 1.1 × 10−3 and 1.5 × 10−3, typical for oligotrophic condition. Along the entire track, bbp remained stable without any marked diel cycle. Such pattern is consistent with the conditions for the northwestern Mediterranean Sea which occurs typically during summer season with similar range of magnitude and variations (Bellacicco et al. 2019b).
Figure 3 shows the bbp data for the Tyrrhenian Sea, consisting of rapid data burst every 15-min intervals. From each burst, the median values are computed. The interquartile range for each burst is also shown. The higher bbp values at the beginning of the record (4–7 October 2022) are probably due to the fact that the BO-SVP drifter remained near the coast where organic and inorganic inputs from river outflows increase the concentration of particles (Pitarch et al. 2020). The second part of the record (8–11 October 2022) corresponds to a time when the drifter was sampling less productive waters.
Original (bursts) and 15-min median bbp (532) time series collected by the BO-SVP drifter in the Tyrrhenian Sea with overlaid corresponding independent in situ cruise data and the median satellite value of a 3 × 3 box for each drifter position obtained from daily ocean color product. IQR stands for interquartile range defined as the difference between the 75th and 25th percentiles of the data. Here, IQR is small compared to the total range of values except briefly around noon on 6 Oct. From 7 to 8 Oct 2022, the drifter was recovered and then redeployed. Details are in the legend.
Citation: Journal of Atmospheric and Oceanic Technology 41, 11; 10.1175/JTECH-D-23-0161.1
The bbp (532) values measured by the BO-SVP drifter were compared with concurrent and independent in situ data collected from vertical profiles during the COSIMO22 cruise (red squares; SC6 and ECO-VSF3 stations in Fig. 3), and a general good agreement was found, except for one station (i.e., marked with red and orange squares where bbp was less than 0.0025 m−1) which was located around 5 km from the BO-SVP location in more open ocean waters. Space-borne bbp (532) was in agreement with those collected by the BO-SVP drifter and similar minima, maxima, and temporal evolution. The overall average value of the difference between satellite and drifter data, the bias, was of 8.0 × 10−4 m−1 with a standard deviation of difference of 2.8 × 10−3 m−1. Such variability should be expected due to the dynamical nature of the marine ecosystem and its fast response to environmental conditions that can change quickly in coastal areas. During the COSIMO22 cruise, the relative bias in percentage between the drifter and satellite bbp observations was of 10%. The reader should note that the satellite data correspond to the merging of images taken at different times, while the drifter moves in space and time continuously collecting bbp.
During the experiment in the North Sea, there was a good agreement in the data acquired by the drifter and vertical profiles obtained by SC6 and ECO-VSF3 instruments, in two different periods of the same day, in the early morning and at noon (Fig. 4, red and orange squares and shaded area). During the NORSE22 experiment performed in the Norwegian Sea, neither cruise and nor ocean color data were available for a comparison analysis with drifter bbp measurements. For such a comparison, we used the surface climatological bbp (700) computed from data obtained by the BGC-Argo floats. The relative anomalies between bbp from drifter and BGC-Argo floats climatological single value were of +2.3% (Fig. 5). The accordance was also confirmed since the climatological value is within the IQR range.
Original and 5-min median bbp (532) time series collected by the BO-SVP in the North Sea with the corresponding independent in situ observations obtained by SC6 and ECO-VSF3 vertical profiles. IQR stands for interquartile range as defined in Fig. 3. Details are given in the legend.
Citation: Journal of Atmospheric and Oceanic Technology 41, 11; 10.1175/JTECH-D-23-0161.1
Original and 15-min median bbp (λ) time series collected by the BO-SVP drifter in the Norwegian Sea. Median climatological value obtained by BGC-Argo is indicated by the red dotted line. IQR stands for interquartile range as defined in Fig. 3. More details are given in the legend.
Citation: Journal of Atmospheric and Oceanic Technology 41, 11; 10.1175/JTECH-D-23-0161.1
Finally, bbp data collected at 10-min intervals (bursts) and their median values (for each burst) during the BIOSWOT-Med experiment in the Balearic Sea show a moderate spread in respect to the daily ocean color data. In this experiment, the drifter moves along an anticyclonic structure. For the water masses followed, conditions seemed very stationary. Instead, the track in the satellite image fails to consider the water masses movements and thus it could probably explain most of the differences observed. Even so, the relative average and standard deviation of the difference between datasets are less than 1% and 4.5%, respectively. This result is particularly relevant considering the extremely low dynamic range of variations typical of oligotrophic conditions which spans from 0.8 × 10−3 to 1.7 × 10−3.
b. Can BO-SVP drifter be used to validate satellite estimates of bbp?
One priority in ocean biology from space is the collection of more in situ multispectral bbp data to enhance the quality of satellite-based bbp products. Satellite bbp serves as an input for deriving biogeochemical quantities, such as POC, Cphyto, and NPP (Brewin et al. 2021, 2023), which are used, in turn, to estimate the ocean carbon budget (Siegel et al. 2023; Brewin et al. 2023). Moreover, the benefit of SVP data for validating satellite-based SST and sea surface salinity products has been demonstrated (Hormann et al. 2015; Centurioni et al. 2015), and thus, here, BO-SVP Lagrangian drifters can contribute to solve the paucity of in situ bbp observations necessary for the validation of satellite bbp product and a reliable quantification of its uncertainty on a global scale (Valente et al. 2022). To this aim, the combination of a high temporal resolution of bbp data and the water-following platform’s capabilities has enabled two key advantages: 1) the ability to capture and characterize intrapixel variability and 2) the validation of a single pixel crossed by the drifter through multiple in situ measurements, thereby enhancing the quality of daily satellite product. Regarding the former point, Fig. 7 demonstrates the BO-SVP drifter’s capacity to detect intrapixel variations and highlights the significance of incorporating such variability into pixel-scale satellite validation. During the COSIMO22 cruise, the BO-SVP drifter crossed more than 30 pixels in coastal and open ocean waters. In most cases, the intrapixel variations significantly diverge from the sensitivity of the optical sensor. The capacity to capture intrapixel variations proves beneficial for satellite validation activities, particularly if an extensive array of drifting buoys will be deployed across various trophic conditions, spanning from oligotrophic to mesotrophic waters, and thus encompassing a wide range of bbp variations.
Previous specific validation analyses performed over global (Brewin et al. 2015; Bisson et al. 2019, 2021a,b) and regional areas (Bellacicco et al. 2016; Pitarch et al. 2016, 2020) showed a generally acceptable agreement between satellite data and coincident in situ observations collected by vertical profiles. Despite the limited available dataset (N = 36 in COSIMO22 and N = 78 during BIOSWOT-Med), in situ and merged-sensor coincident bbp measurements showed an excellent agreement with satellite observations that slightly overestimate (+7.49%) the in situ counterpart (Fig. 8). This finding is of particular relevance in respect to the higher biases and spread found between satellite and BGC-Argo floats observations in the Mediterranean and Black Seas (Table 1 and Fig. 4 in Bisson et al. 2019) and in the South Pacific Gyre (Bisson et al. 2021b). Such differences could be linked to the selected algorithm [e.g., QAA or Global Ice Ocean Prediction (GIOP)], sensor considered [e.g., Ocean and Land Color Instrument (OLCI)/VIIRS/MODIS], the use of bbp spectral band (Bisson et al. 2019), atmospheric correction issues, and the discrepancy in sensor response to differing environmental conditions. Here, drifter bbp values are within the range of known variability (10−4–10−2 m−1) expected for oligo- to mesotrophic waters of the Mediterranean Sea (Antoine et al. 2011). Figure 8 also shows the matchups between daytime drifter data (N = 60; from approximately 0800 to 1800 local time) and concurrent satellite observations at pixel scale. In the same scatterplot, the drifter bbp observations (N = 36) collected ±2.5 h (i.e., from 1000 to 1500 local time) are also overplotted onto the satellite passage which is usually between 1200 and 1300 local time. Such time intervals include the typical polar satellite passes (i.e., 2 times per day in the case of a two-satellite configuration; see also https://sentinel.esa.int/web/sentinel/user-guides/sentinel-3-olci/coverage). In both cases, satellite data show a negligible bias in respect to in situ data. Note that satellite bbp is derived from Rrs and the observed differences with in situ data could be also affected by the selected algorithm and atmospheric interferences.
The definition of an adequate frequency of time sampling means to take into account the geophysical variability that therefore is incorporated into the resulting geophysical signal considering both spatial (e.g., pixel scale) and temporal dimension (e.g., h to day). Recently, Stoer and Fennel (2022) demonstrated the importance, and necessity, in reconstructing the diel cycle of bbp (as a proxy of carbon biomass) to improve satellite NPP estimations which are key quantities in the global carbon cycle budget computation and for biological carbon pump studies. In their work, they have modeled a diel cycle of bbp by using a large bbp database of BGC-Argo floats in the Southern Ocean, which has been hourly aggregated to simulate a mean daily cycle following what has been applied for the oxygen measurements (Johnson and Bif 2021). In the near future, the deployment of a large array of BO-SVP drifting buoys over the global ocean, with multispectral high-frequency temporal resolution, could allow to reconstruct a more robust diel bbp cycle and improve satellite NPP estimations.
c. Can BO-SVP drifter be used to link ocean productivity to kinematical properties?
Enhanced observations of biological-physical coupling are crucial, as our understanding of the impact of ocean circulation changes on marine productivity and organic carbon export is currently limited, mainly relying on theoretical considerations and numerical simulations (Lévy et al. 2018, 2023). Up to now, only a few and sparse regional investigations have been conducted in which biological properties have been simultaneously coupled with ocean dynamics (i.e., surface) by using Lagrangian platforms off Northern California Current (Abbott et al. 1990, 1995; Abbott and Letelier 1998) and in the Southern Ocean (Letelier et al. 1997; Abbott et al. 2001. In these studies, a device was used to record transmissometer and fluorimeter data together with a spectroradiometer which measured both upwelling radiance and downwelling irradiance at different wavelengths (Abbott et al. 1990, 1995; Abbott and Letelier 1998; Abbott et al. 2001; Letelier et al. 1997). An increase of chlorophyll-a concentration corresponding to oceanic structures (e.g., fronts, jets, and filaments) was observed due to the nutrient upwelling, while low chlorophyll-a concentration was observed in the surrounding areas. The combination of high sampling frequency and surface water following capabilities is also important to capture complex optical and biogeochemical features to be linked to ocean dynamics. Indeed, high temporal resolution can support the detection of diel cycles of bbp (Fig. 3) which is linked to organic carbon biomass changes, particle growth rate, and losses. Several studies report that diurnal bbp increase may have been caused by the life cycle of phytoplankton (in terms of growth, cell division, and losses), while the decrease usually occurred during the nighttime mainly due to the net losses related respiration processes and zooplankton grazing (Kheireddine and Antoine 2014; Freitas et al. 2020; Baetge et al. 2024). Furthermore, the use of SVP drifters is widespread for describing and characterizing ocean kinematics and dynamic properties (e.g., vorticity, strain, and relative divergence) ranging from submesoscale to large circulation scales spanning 0.1–1000 km (Centurioni 2018; Essink et al. 2022). The abovementioned configuration, combined with hydrological and bio-optical sensors (e.g., for SST, temperature, conductivity, and bio-optical measurements), offers new insights into the complex interactions between biological and physical components that underpin oceanic production (McGillicuddy 2016; Lévy et al. 2018, 2023), for instance, a deeper understanding of the decorrelation time and length scales of biological responses and ocean dynamics (Abbott and Letelier 1998; McKee et al. 2022, 2023).
d. Next steps
There are three specific items to be addressed in future versions of BO-SVP drifter and related data processing:
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Evaluate the biofouling impact in long-term deployment. Previous works reported the occurrence of biofouling on optical devices during long experiments (>73 days; Letelier et al. 1997). The current BO-SVP drifter is based on the use of the Ecotriplet-wB sensor which has a copper faceplate and a wiper to discourage and remove the biofouling occurrence. There is ongoing work to minimize the impact of biofouling on long-term optical measurements: specifically, to identify when biofouling starts to compromise the optical signal and thus evaluate the life cycle of the sensor and the concurrent high quality optical observations obtained with the BO-SVP drifter across various water types (e.g., from coastal to open ocean waters). To support extended deployments, an alternative option under consideration is the integration of an additional antifouling system on the optical device (e.g., seawater electrolysis method and UV irradiation) along with the existing one (Delauney et al. 2018). The impact of this additional system on the battery consumption will be assessed.
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Real-time data transmission of data: BO-SVP drifter will be configured with real-time data transmission of bio-optical data along with existing capabilities for SST, temperature, and conductivity. This will enable drifters to be deployed for longer periods minimizing the risks of loss of bio-optical data associated with the drifter loss.
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Development of a fit-to-purpose data quality control (QC): The development of a specific QC data analysis is of a fundamental importance to release ready fit to purpose data to the oceanographic community, following the scheme already in use in the GDP SVP drifters or in the case of BGC-Argo profilers.
4. Conclusions and future perspectives
In this study, we present and evaluate the near-surface optical particulate backscatter (bbp) measurements collected from an upgraded water-following Lagrangian drifter platform drogued at 15-m depth, here named the backscatter-optical SVP drifter (BO-SVP), during four experiments conducted in different areas and across a wide range of oceanic environmental conditions. The bbp measurements obtained by the BO-SVP drifter buoy were compared with independent ship-borne, satellite, and BGC-Argo data. The main findings are as follows:
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Near-surface bbp measurements obtained by the BO-SVP drifter are reliable over a wide range of environmental conditions and with acceptable differences with respect to independent datasets (Figs. 3–6; relative bias less than 10%).
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BO-SVP drifter captures the satellite intrapixel-scale variability by exploiting water-following capabilities and a high-frequency time sampling. This configuration allows sampling several pixels in the same day (Fig. 7) with benefit for validation of ongoing satellite missions (e.g., Sentinel-3/OLCI, OCI/PACE) and for the quantification of related uncertainties (Fig. 7).
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Space-borne bbp obtained by the application of the QAA to satellite Rrs displays a negligible bias with respect to in situ drifter-based data collected in two different experiments across oligotrophic to mesotrophic waters (Fig. 8).
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BO-SVP drifters, like the standard SVP drifter, can describe the kinematical and dynamical properties near the ocean surface thereby providing the physical context to characterize and explain the changes in bio-optical signal and derived biogeochemical quantities.
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BO-SVP drifters could potentially provide high-frequency information at the sea surface otherwise unobtainable in hostile regions of the oceans such as the polar region, in particular during the polar night.
Original and 10-min median bbp (532) time series collected by the BO-SVP drifter in the Balearic Sea during the BIOSWOT-Med cruise with corresponding median satellite value of 3 × 3 box for each drifter position obtained by daily ocean color product. IQR stands for interquartile range defined as the difference between the 75th and 25th percentiles of the data. Since the original burst data were stable along the entire time series, the IQR bars overlapped with the median value dots. Details are in the legend.
Citation: Journal of Atmospheric and Oceanic Technology 41, 11; 10.1175/JTECH-D-23-0161.1
Example of intrapixel variability. Green dots represent the standard deviation of bbp at pixel-scale obtained by the BO-SVP drifter during the COSIMO22 cruise. Dashed blue line represents the sensitivity of the bio-optical sensor. In red, the number of measurements collected by BO-SVP drifter for each single pixel is also superimposed. Pixels with one observation are masked out since the standard deviation cannot be computed.
Citation: Journal of Atmospheric and Oceanic Technology 41, 11; 10.1175/JTECH-D-23-0161.1
Matchups between space-borne bbp observations and all in situ bbp collected by BO-SVP drifter during the COSIMO22 oceanographic cruise held during November 2022 in the Tyrrhenian Sea and BIOSWOT-Med cruise held in May 2023 (left). In the right panel, gold squares are matchups obtained by using all daytime drifter observations; blue triangles are matchups using observations across satellite passage. Statistics are superimposed on both plots. Pearson coefficient r was calculated after a log-transformation of datasets. Dots at the lower bound (around 0.001) are those related to the BIOSWOT-Med cruise along the anticyclonic eddy. Black dashed line is the 1:1 line.
Citation: Journal of Atmospheric and Oceanic Technology 41, 11; 10.1175/JTECH-D-23-0161.1
This work highlights how BO-SVP drifters could complement other existing autonomous platforms (e.g., BGC-Argo, gliders) also to improve the 4D ocean ecosystem reconstruction and description (Boyd et al. 2019; Chai et al. 2020) that is necessary for a full comprehension of ocean warming impacts on ocean biology and biogeochemistry. BO-SVP drifters can contribute to the enhancement and expansion of existing ocean observing systems of biological and ecological parameters, across all ocean basins, as prescribed in the Implementation plan of the United Nations Decade of Ocean Science for Sustainable Development (https://unesdoc.unesco.org/ark:/48223/pf0000377082). Last, high-frequency physical/biological observations obtained from BO-SVP drifters could be impactful in relation to the next generation of altimetry (e.g., NASA SWOT), hyperspectral ocean color satellite missions (e.g., NASA GLIMR, ESA Sentinel Next Generation (NG), and ESA CHIME), and future lidar mission (e.g., ASI CALIGOLA) for the detection of ocean processes from larger to finer scales (i.e., space and time). In the future, a coordinated array of BO-SVP drifters, BGC-Argo floats, and other autonomous platforms working in synergy could provide the required surface and subsurface data at the temporal, spatial, and spectral (e.g., multi- or hyperspectral resolution) scales of interest to future satellite missions. Future research will aim to (i) develop an observing simulation system experiment to define optimal deployment locations, periods, and amount of drifters for robust ocean color product validation, reducing the uncertainties on the retrievals and improving ocean productivity from space (e.g., NPP and NCP); (ii) link the biological responses (e.g., particle growth and losses) to physical processes (e.g., ocean circulation, divergence and convergence zones, fronts, and eddies) with a Lagrangian approach; (iii) investigate spikes in bbp time series to determine particle size or air bubbles at the sea surface (Briggs et al. 2011, 2013); and (iv) focus on night and day differences in relation to the diel vertical migration of zooplankton following Bianchi and Mislan (2016), Burt and Tortell (2018), and recently Behrenfeld et al. (2019).
Acknowledgments.
We thank Global Drifter Programme, Copernicus Marine Service and the International Argo and Biogeochemical-Argo programs for providing state of arts data. Dr. Marco Bellacicco would like to thank the European Space Agency (ESA) and especially Dr. Diego Fernandez Prieto for the productive visiting period at the Science Hub in ESA-ESRIN. Dr. Marco Bellacicco would like to thank the staff of the Earth Observation Graphic Bureau (EOGB) of ESA for the help on Fig. 1. Dr. Luca Centurioni was supported by ONR Grant N00014-21-1-2742 and NOAA Grant NA20OAR4320278 “the Global Drifter Program.” This work has been funded by EU -Next Generation EU Mission 4 “Education and Research” - Component 2: “From research to business” - Investment 3.1: “Fund for the realisation of an integrated system of research and innovation infrastructures” - Project IR0000032 – ITINERIS - Italian Integrated Environmental Research Infrastructures System - CUP B53C22002150006. The authors acknowledge the Research Infrastructures participating in the ITINERIS project with their Italian nodes: Euro-Argo and JERICO. The authors would like also to thank the crew of R/V Dallaporta, R/V Alliance, R/V Belgica, R/V Porquoi Pas! and colleagues (e.g., Gianluca Volpe, Simone Colella, Marina Ampolo Rella, Pierre-Marie Poulin, Mattia Pecci, Salvatore Mangano, Vittorio Brando, Federica Braga, Maristella Berta, Andrea Doglioli, Francesco d’Ovidio, and others) that helped in drifter deployment and recovery activities during the oceanographic cruises. The BioSWOT cruise was part of the TOSCA/CNES project BioSWOT-AdAC (https://www.swot-adac.org) and was supported by the FOF-French Oceanographic Fleet (https://campagnes.flotteoceanographique.fr/campagnes/18002392/). We would like also to thank Dr. Giorgio Dall’Olmo, Dr. Vincenzo Vellucci, Dr. Daniele Iudicone, and Dr. Bruno Buongiorno Nardelli for fruitful discussions on the BO-SVP drifter definition. PhD candidate Mengyu Li is supported by a fellowship (CSC No. 202206140082) during visiting period at ISMAR-CNR in Rome. We wish to thank the anonymous reviewers for their criticisms and suggestions that helped the manuscript to be improved. Conceptualization: Marco Bellacicco, Luca Centurioni, Salvatore Marullo; Methodology: Marco Bellacicco, Jaime Pitarch, Maria Laura Zoffoli, Salvatore Marullo, Luca Centurioni; Data acquisition: Federico Falcini, Jaime Pitarch, Luca Centurioni, Marco Bellacicco, Maria Laura Zoffoli, Mengyu Li; Investigation: All; Visualization: Marco Bellacicco, Jaime Pitarch, Maria Laura Zoffoli, Salvatore Marullo; Funding acquisition: Rosalia Santoleri, Luca Centurioni; Supervision: All; Writing—original draft: Marco Bellacicco, Jaime Pitarch, Maria Laura Zoffoli; Writing—review and editing: All.
Data availability statement.
The data that support the main findings of this study are openly available: Daily merged satellite remote sensing reflectance (Rrs; in sr−1) data time series at 1-km resolution (OCEANCOLOUR_MED_BGC_L3_MY_009_143) can be downloaded from the Copernicus Marine Service website (https://data.marine.copernicus.eu/products). BGC-Argo float data can be downloaded at ftp://ftp.ifremer.fr/ifremer/argo. The BO-SVP drifter datasets collected in the four deployments are available at the following open access repository https://doi.org/10.5281/zenodo.10213792.
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