Scientific Papers

In February 2020, a 120-km-wide freshwater plume was documented by satellite and in situ observations near the Demerara Rise (7°N/54°W-56°W). It was initially stratified in the upper 10 m with a freshwater content of 2–3 m of Amazon water distributed down to 40 m. On February 2nd, ship transects indicate an inhomogeneous shelf structure with a propagating front in its midst, whereas minimum salinity close to 30 pss was observed close to the shelf break on February 5th. The salinity minimum eroded in time but was still observed 13–16 days later with 33.3 pss minimum value up to 400 km from the shelf break. At this time, the mixed layer depth was close to 20 m. The off-shelf flow lasted 10 days, contributing to a plume area extending over 100,000 km2 and associated with a 0.15 Sv (106 m3 s−1) freshwater transport. The off-shelf plume was steered northward by a North Brazil Current ring up to 12°N and then extended westward toward the Caribbean Sea. Its occurrence followed 3 days of favorable wind direction closer to the Amazon estuary, which contributed to north-westward freshwater transport on the shelf. Other such events of freshwater transport in January–March are documented since 2010 in salinity satellite products in 7 out of 10 years, and in 6 of those years, they were preceded by a change in wind direction between the Amazon estuary and the Guianas favoring the north-westward freshwater transport toward the shelf break.

Remote, harsh conditions of the Southern Ocean challenge our ability to observe the region's influence on the climate system. Southern Ocean air‐sea CO2 flux estimates have significant uncertainty due to the reliance on limited ship‐dependent observations in combination with satellite‐based and interpolated data products. We utilize a new approach, making direct measurements of air‐sea CO2, wind speed, and surface ocean properties on an Uncrewed Surface Vehicle (USV). In 2019 the USV completed the first autonomous circumnavigation of Antarctica providing hourly CO2 flux estimates. Using this unique data set to constrain potential error in different measurements and propagate those through the CO2 flux calculation, we find that different wind speed products and sampling frequencies have the largest impact on CO2 flux estimates with biases that range from ‐4% to +20%. These biases and poorly‐constrained interannual variability could account for discrepancies between different approaches to estimating Southern Ocean CO2 uptake.

Summer surveys of the Chukchi Sea indicate that high densities of age‐0 gadid fishes, historically Arctic cod (Boreogadus saida) but recently also walleye pollock (Gadus chalcogrammus), dominate the pelagic fish community. Adults are comparatively scarce, suggesting that either overwinter survivorship of age‐0 gadids is low, or that they emigrate to other areas of the Pacific Arctic. To examine population movement, we conducted repeat acoustic surveys with saildrone autonomous surface vehicles equipped with echosounders throughout summer 2018. The saildrones' range and endurance enabled two large‐scale surveys of the U.S. Chukchi shelf. Acoustic backscatter, a proxy for fish density, was highest in regions with sea surface temperatures of 6–8°C, and lowest in areas influenced by recent ice melt. A subarea of the central Chukchi was surveyed a total of four times; backscatter in this subarea increased by > 85% from late‐July to mid‐September. As summer progressed, fish developed more extensive diel vertical migrations and backscatter from individuals doubled. Both changes suggest increases in backscatter were driven primarily by increasing body size. Particle tracking simulations indicated age‐0 gadids were likely retained over the Chukchi shelf by extended periods of wind‐driven southward flow during the survey period before strong northward flow in late fall transported them to the north. These findings suggest that in summer 2018, age‐0 gadids were advected northward to the Chukchi shelf from the northern Bering Sea, where they were retained during a period of growth until late fall before being advected farther north toward the Chukchi and Beaufort shelf breaks.

Understanding measurement, monitoring and verification (MM&V) needs in the environmental context of potential subsea carbon dioxide (CO2) storage projects (Carbon Capture and Storage [CCS]) is a challenging task globally. Unmanned surface vehicles (USV) equipped with acoustic sensors are an attractive option for detecting gas leaks due to their spatial and temporal coverage potential. Here, a SIMRAD Wide Band Transceiver Mini acoustic sensor is evaluated for detecting CO2 leaks in shallow coastal water (<20 m depth). Small flows of CO2 (0.34–3.90 tonnes CO2 gas yr−1) were released into the water column. The plumes were detected with the acoustic system with the results highlighting their dynamic nature. A survey simulation model showed that the probability of detecting a leak inside a 5 × 10 km survey area improved depending on the number of leaks within it, with 100 % detection probability for two leaks (>7.8 tonnes CO2 gas yr−1) achieved with a survey time of 600 h. As the number of leaks increased to 40 (> 156 tonnes CO2 gas yr−1) the survey duration reduced to ∼110 h for 100 % probability of detecting a plume. These detection flow rates are well below the upper limits proposed by IPCC (2005) for climate mitigation for a release of 1% in 1000 years for most proposed CO2 storage sites. Regulatory requirements for CCS sites are still evolving to address societal expectations and environmental monitoring needs. This work assists in determining detectable leak rate thresholds that can be detected in the marine environment using acoustic sensors.

Understanding the environmental context of potential subsea CO2 storage projects is a challenging task that requires the development of risk-based environmental monitoring to address public assurance, as well as regulatory requirements. A core need is an understanding and quantification of background environmental variability in relation to the likelihood of detection from putative release. Unmanned surface vehicle (USV) technology is rapidly evolving, with a number of USV platforms available that can meet a variety of needs in ocean observing. Advanced sensor technologies integrated on USVs promise coverage and flexibility for sustained observations at space and time scales not previously achievable. This paper describes CSIRO research with USVs in support of CCS environmental monitoring studies in Australia. CSIRO utilises a range of autonomous systems, including autonomous underwater vehicles, remotely operated vehicles and robotic profiling floats as part of its observing capabilities. For CCS studies, CSIRO is partnering with Saildrone Inc. to provide a flexible platform that houses a suite of sensors for environmental assessments at offshore CCS sites. The Saildrone platforms have been designed to accommodate sensors for detection of three important monitoring types: seawater carbon dioxide, bubble acoustics and water quality. The Saildrones can be used for long-range reconnaissance in a broad range of sea conditions and with up to 6-month deployment durations. Each Saildrone platform and its science systems can be operated remotely, with data transmitted back to shore via satellite to allow real-time monitoring of changes in the marine environment. The rapid deployment and response of the platform allows for more detailed investigation of features identified during surveys and of anomalies that exceed the known variability in measured variables. The combination of the platform with fixed measurements, such as those collected using more traditional oceanographic moorings, provides new capability to assess variability at CCS sites over a larger survey area than has been possible before. The sensor systems fitted to the Saildrone and the land based calibration and maintenance support facilities are state of the art. The carbon sensor suite delivers pH, pCO2 and dissolved oxygen. It is based on a robust system proven to work in the field over long periods and includes reference gas and transmission of multiple diagnostic parameters to ensure sensor performance and calibrations are maintained. The acoustic sensors use a two-frequency split beam system operating at 38 kHz and 2002 kHz that can detect low concentrations of bubbles in the water column. It will be possible to detect and monitor potential or reported bubble plumes over time to determine the cause. In this way reducing false alarms where under certain circumstances aggregations of fish or zooplankton can be mistakenly interpreted as a bubble plume. Sensors for sub-surface bio-optics to assess water column plankton (chlorophyll and particle backscatter), oceanographic (temperature and salinity) and meteorological data are also incorporated into the real-time data streams delivered from the Saildrone. This paper will provide an overview of the sensor configuration and performance capabilities of the USVs for use in environmental assessments to support CCS. Sea trial and other data including CCS monitoring strategies will be presented. Finally, the paper will discuss potential future uses of the platform for ongoing monitoring of CCS sites.

Autonomous platforms already make observations over a wide range of temporal and spatial scales, measuring salinity, temperature, nitrate, pressure, oxygen, biomass, and many other parameters. However, the observations are not comprehensive. Future autonomous systems need to be more affordable, more modular, more capable and easier to operate. Creative new types of platforms and new compact, low power, calibrated and stable sensors are under development to expand autonomous observations. Communications and recharging need bandwidth and power which can be supplied by standardized docking stations. In situ power generation will also extend endurance for many types of autonomous platforms, particularly autonomous surface vehicles. Standardized communications will improve ease of use, interoperability, and enable coordinated behaviors. Improved autonomy and communications will enable adaptive networks of autonomous platforms. Improvements in autonomy will have three aspects: hardware, control, and operations. As sensors and platforms have more onboard processing capability and energy capacity, more measurements become possible. Control systems and software will have the capability to address more complex states and sophisticated reactions to sensor inputs, which allows the platform to handle a wider variety of circumstances without direct operator control. Operational autonomy is increased by reducing operating costs. To maximize the potential of autonomous observations, new standards and best practices are needed. In some applications, focus on common platforms and volume purchases could lead to significant cost reductions. Cost reductions could enable order-of-magnitude increases in platform operations and increase sampling resolution for a given level of investment. Energy harvesting technologies should be integral to the system design, for sensors, platforms, vehicles, and docking stations. Connections are needed between the marine energy and ocean observing communities to coordinate among funding sources, researchers, and end users. Regional teams should work with global organizations such as IOC/GOOS in governance development. International networks such as emerging glider operations (EGO) should also provide a forum for addressing governance. Networks of multiple vehicles can improve operational efficiencies and transform operational patterns. There is a need to develop operational architectures at regional and global scales to provide a backbone for active networking of autonomous platforms.

Using an unmanned sailing vehicle, known as a Saildrone, we observed mesoscale and smaller scale structures of oceanic and atmospheric variables across the Kuroshio south of Japan during the winter of 2018/2019. From December 28 to December 29, 2018, the Saildrone crossed just north of the center of a very warm (∼23∘C) mesoscale spot in the Kuroshio centered around 31.5∘ N, 135.8∘ E. The northerly winter monsoon wind was intensified by ∼2 m s−1 over the mesoscale warm spot (MWS) and accompanied by a submesoscale sea level pressure undulation of ∼1 hPa possibly due to two oppositely rotating ageostrophic vortices. At this time, the wind reached a maximum speed of greater than 12 m s−1 and removed heat from the ocean at a rate of 1141 W m−2. Subsequently (January 3–5, 2019), the Saildrone observed weakening of wind and heat release to the atmosphere on the southern edge of the MWS, which was associated with the approaching low-pressure system over the Kuroshio. The observed submesoscale structures of atmospheric and oceanic variables near the center of the MWS suggest that the atmospheric boundary layer responded to the MWS through the pressure adjustment mechanism in the Kuroshio, where in situ high-resolution measurements have not been performed before.

Current carbon measurement strategies leave spatiotemporal gaps that hinder the scientific understanding of the oceanic carbon biogeochemical cycle. Data products and models are subject to bias because they rely on data that inadequately capture mesoscale spatiotemporal (kilometers and days to weeks) changes. High-resolution measurement strategies need to be implemented to adequately evaluate the global ocean carbon cycle. To augment the spatial and temporal coverage of ocean–atmosphere carbon measurements, an Autonomous Surface Vehicle CO2 (ASVCO2) system was developed. From 2011 to 2018, ASVCO2 systems were deployed on seven Wave Glider and Saildrone missions along the U.S. Pacific and Australia’s Tasmanian coastlines and in the tropical Pacific Ocean to evaluate the viability of the sensors and their applicability to carbon cycle research. Here we illustrate that the ASVCO2 systems are capable of long-term oceanic deployment and robust collection of air and seawater pCO2 within ±2 μatm based on comparisons with established shipboard underway systems, with previously described Moored Autonomous pCO2 (MAPCO2) systems, and with companion ASVCO2 systems deployed side by side.

From 11 April to 11 June 2018 a new type of ocean observing platform, the Saildrone surface vehicle, collected data on a round-trip, 60-day cruise from San Francisco Bay, down the U.S. and Mexican coast to Guadalupe Island. The cruise track was selected to optimize the science team’s validation and science objectives. The validation objectives include establishing the accuracy of these new measurements. The scientific objectives include validation of satellite-derived fluxes, sea surface temperatures, and wind vectors and studies of upwelling dynamics, river plumes, air–sea interactions including frontal regions, and diurnal warming regions. On this deployment, the Saildrone carried 16 atmospheric and oceanographic sensors. Future planned cruises (with open data policies) are focused on improving our understanding of air–sea fluxes in the Arctic Ocean and around North Brazil Current rings. The California coastal waters are important for the economy, society (this is the coast of the most populous state in the union), national security (they are the home waters of the Navy’s Pacific fleet), and environment (it is along an eastern boundary current with biologically important upwelling). In the California Current region, the air–land–sea interface is complex, characterized by coastal promontories, upwelling jets and shadows, river plumes, and a narrow continental shelf that affects coastal dynamics producing highly variable sea surface temperature (SST) and concentration of the photosynthetic pigment chlorophyll a (Chl) (Checkley and Barth 2009; Strub and James 1995; Kelly et al. 1998; Brink et al. 2000). Along the U.S. and Mexican west coast, upwelling induces a flux of cold, nutrient-rich, dense, low-in-oxygen, and acidic waters to the surface ocean layers, leading to important air–sea and coastal–open ocean interactions (Sverdrup et al. 1942). Due to its economic importance, the California Current System is one of the most studied and well-monitored upwelling systems in the world, including high-frequency (HF) radar for surface currents, regular oceanographic research cruises, and moored buoys for near-surface meteorological measurements and ocean temperature. Yet, even in this heavily sampled region, there are substantial gaps not filled by the current sampling strategy. Geostationary and polar-orbiting satellites provide discrete glimpses of the spatial structuring at the air–sea interface for a limited subset of environmental parameters. Temporal evolution of features can be provided by moored buoys but the fixed locations limit their use in understanding spatiotemporal structures and spatial scales of dynamical interactions. Other in situ platforms, such as subsurface gliders, floats, and drifters, provide valuable vertical and subsurface oceanographic measurements critical for measuring ocean heat content and transport, ocean velocities, thermohaline circulation, and other oceanographic applications. Wave Gliders provide both surface atmospheric (wind speed and direction, atmospheric pressure, and air temperature) and subsurface oceanographic observations and are able to travel at velocities of typically 0.8 m s‒1. The Saildrone measurements provide significant value to certain types of scientific studies through their design as a solar-powered, movable, steerable platform that samples a wide variety of air–sea-interface and upper-ocean parameters, especially in regions where it is difficult to deploy and maintain other types of assets. Wave Gliders and Saildrones both provide air–sea measurements that address the need for flexible, deployable, movable in situ observational assets, with each vehicle providing different capabilities for different types of scientific investigations. Wave Gliders can provide subsurface observations while Saildrones provide interfacial observations. The Saildrone vehicle’s advantage is for science applications needing rapid spatial sampling (it can travel at up to 4 m s‒1), with additional atmospheric and oceanographic measurements needed to advance research into upwelling dynamics, submesoscale variability, and air–sea fluxes in the vicinity of ocean fronts, diurnal warming modeling, carbon cycling, and biophysical interactions and coupled atmosphere–ocean modeling and data assimilation. It is important to assess the accuracy of Saildrone observations for science. We believe that such an assessment is important for two reasons: first, the Saildrone business model is different from the way research has been previously accomplished. Instead of purchasing equipment, which scientists then maintain, calibrate, and deploy, Saildrone owns and operates the vehicles and sensors, it is the data that are purchased. Second, there may be deployment issues associated with some of the instruments because of the nature of the vehicle. In the following we touch briefly on the former with a bit more discussion devoted to the latter.

Validation of satellite-based retrieval of ocean parameters like Sea Surface Temperature (SST) and Sea Surface Salinity (SSS) is commonly done via statistical comparison with in situ measurements. Because in situ observations derived from coastal/tropical moored buoys and Argo floats are only representatives of one specific geographical point, they cannot be used to measure spatial gradients of ocean parameters (i.e., two-dimensional vectors). In this study, we exploit the high temporal sampling of the unmanned surface vehicle (USV) Saildrone (i.e., one measurement per minute) and describe a methodology to compare the magnitude of SST and SSS gradients derived from satellite-based products with those captured by Saildrone. Using two Saildrone campaigns conducted in the California/Baja region in 2018 and in the North Atlantic Gulf Stream in 2019, we compare the magnitude of gradients derived from six different GHRSST Level 4 SST (MUR, OSTIA, CMC, K10, REMSS, and DMI) and two SSS (JPLSMAP, RSS40km) datasets. While results indicate strong consistency between Saildrone- and satellite-based observations of SST and SSS, this is not the case for derived gradients with correlations lower than 0.4 for SST and 0.1 for SSS products.