Science Publications

From May 15 to October 11, 2019, six Saildrone uncrewed surface vehicles (USVs) were deployed for 150-day cruises collecting a suite of atmospheric and oceanographic measurements from Dutch Harbor, Alaska, transiting the Bering Strait into the Chukchi Sea and the Arctic Ocean. Two Saildrones funded by the National Aeronautics and Space Administration (NASA), SD-1036 and SD-1037, were equipped with infrared (IR) radiation pyrometers in a “unicorn” structure on the deck for the determination of the ocean sea surface skin temperature (SST skin ). We present an algorithm to derive SSTskin from the downward- and upward-looking radiometers and estimate the main contributions to the inaccuracy of SSTskin. After stringent quality control of data and eliminating measurements influenced by sea ice and precipitation, and restricting the acceptable tilt angles of the USV based on radiative transfer simulations, SSTskin can be derived to an accuracy of approximately 0.12 K. The error budget of the derived SSTskin is developed, and the largest component comes from the instrumental uncertainties, assuming that the viewing geometry is adequately determined. Thus, Saildrones equipped with these sensors could provide sufficiently accurate SSTskin retrievals for studying the physics of the thermal skin effect, in conjunction with accurate subsurface thermometer measurements, and for validating satellite-derived SSTskin fields at high latitudes.

C. Jia, P. J. Minnett, M. Szczodrak and M. Izaguirre, "High Latitude Sea Surface Skin Temperatures Derived From Saildrone Infrared Measurements," in IEEE Transactions on Geoscience and Remote Sensing, vol. 61, pp. 1-14, 2023, Art no. 4200214, doi: 10.1109/TGRS.2022.3231519.

Remote sensing of sea surface salinity (SSS) near land is difficult due to land contamination. In this article, we assess SSS retrieved from the soil moisture active passive (SMAP) mission in coastal region. SMAP SSS products from the Jet Propulsion Laboratory (JPL), and from the remote sensing systems (RSS) are collocated with in situ data collected by saildrones during the North American West Coast Survey. Satellite and saildrone salinity measurements reveal consistent large-scale features: the fresh water (low SSS) assocciated with the Columbia River discharge, and the relatively salty water (high SSS) near Baja California associated with regional upwelling. The standard deviation of the difference for collocations with SMAP Level 3 (eight days average) between 40 and 100 km from land is 0.51 (0.56) psu for JPL V5 (RSS V4 70 km). This is encouraging for the potential application of SMAP SSS in monitoring coastal zone freshwater particularly where there exists large freshwater variance. We analyze the different land correction approaches independently developed at JPL and RSS using SMAP level 2 matchups. We found that JPL's land correction method is more promising in pushing SMAP SSS retrieval towards land. For future improvement, we suggest implementing dynamic land correction versus the current climatology-based static land correction to reduce uncertainty in estimating land contribution. In level 2 to level 3 processing, a more rigorous quality control may help to eliminate outliers and deliver reliable level 3 products without over-smoothing, which is important in resolving coastal processes such as fronts or upwelling.

W. Tang et al., "Using Saildrones to Assess the SMAP Sea Surface Salinity Retrieval in the Coastal Regions," in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 15, pp. 7042-7051, 2022, doi: 10.1109/JSTARS.2022.3200305.

The 2020 ‘Elucidating the role of clouds-circulation coupling in climate-Ocean-Atmosphere’ (EUREC4A-OA) and the ‘Atlantic Tradewind Ocean-Atmosphere Mesoscale Interaction Campaign’ (ATOMIC) campaigns focused on improving our understanding of the interaction between clouds, convection and circulation and their function in our changing climate. The campaign utilized many data collection technologies, some of which are relatively new. In this study, we used saildrone uncrewed surface vehicles, one of the newer cutting edge technologies available for marine data collection, to validate Level 2 and Level 3 Soil Moisture Active Passive (SMAP) satellite and Hybrid Coordinate Ocean Model (HYCOM) sea surface salinity (SSS) products in the Western Tropical Atlantic. The saildrones observed fine-scale salinity variability not present in the lower-spatial resolution satellite and model products. In regions that lacked significant small-scale salinity variability, the satellite and model salinities performed well. However, SMAP Remote Sensing Systems (RSS) 70 km generally outperformed its counterparts outside of areas with submesoscale SSS variation, whereas RSS 40 km performed better within freshening events such as a fresh tongue. HYCOM failed to detect the fresh tongue. These results will allow researchers to make informed decisions regarding the most ideal product and its drawbacks for their applications in this region and aid in the improvement of mesoscale and submesoscale SSS products, which can lead to the refinement of numerical weather prediction (NWP) and climate models.

Hall, Kashawn, Alton Daley, Shanice Whitehall, Sanola Sandiford, and Chelle L. Gentemann. 2022. "Validating Salinity from SMAP and HYCOM Data with Saildrone Data during EUREC4A-OA/ATOMIC" Remote Sensing 14, no. 14: 3375. https://doi.org/10.3390/rs14143375

In 2021, a novel NOAA-Saildrone project deployed five uncrewed surface vehicle Saildrones (SDs) to monitor regions of the Atlantic Ocean and Caribbean Sea frequented by tropical cyclones. One of the SDs, SD-1045, crossed Hurricane Sam (Category 4) on September 30, providing the first-ever surface-ocean videos of conditions in the core of a major hurricane and reporting near-surface winds as high as 40 m/s. Here, we present a comprehensive analysis and interpretation of the Saildrone ocean surface wind measurements in Hurricane Sam, using the following datasets for direct and indirect comparisons: an NDBC buoy in the path of the storm, radiometer tropical cyclone (TC) winds from SMAP and AMSR2, wind retrievals from the ASCAT scatterometers and SAR (RadarSat2), and HWRF model winds. The SD winds show excellent consistency with the satellite observations and a remarkable ability to detect the strength of the winds at the SD location. We use the HWRF model and satellite data to perform cross-comparisons of the SD with the buoy, which sampled different relative locations within the storm. Finally, we review the collective consistency among these measurements by describing the uncertainty of each wind dataset and discussing potential sources of systematic errors, such as the impact of extreme conditions on the SD measurements and uncertainties in the methodology.

Ricciardulli, Lucrezia, Gregory R. Foltz, Andrew Manaster, and Thomas Meissner. 2022. "Assessment of Saildrone Extreme Wind Measurements in Hurricane Sam Using MW Satellite Sensors" Remote Sensing 14, no. 12: 2726. https://doi.org/10.3390/rs14122726

Observations from uncrewed surface vehicles (saildrones) in the Bering, Chukchi, and Beaufort Seas during June–September 2019 were used to evaluate initial conditions and forecasts with lead times up to 10 days produced by eight operational numerical weather prediction centers. Prediction error behaviors in pressure and wind are found to be different from those in temperature and humidity. For example, errors in surface pressure were small in short-range (<6 days) forecasts, but they grew rapidly with increasing lead time beyond 6 days. Non-weighted multimodel means outperformed all individual models approaching a 10-day forecast lead time. In contrast, errors in surface air temperature and relative humidity could be large in initial conditions and remained large through 10-day forecasts without much growth, and non-weighted multimodel means did not outperform all individual models. These results following the tracks of the mobile platforms are consistent with those at a fixed location. Large errors in initial condition of sea surface temperature (SST) resulted in part from the unusual Arctic surface warming in 2019 not captured by data assimilation systems used for model initialization. These errors in SST led to large initial and prediction errors in surface air temperature. Our results suggest that improving predictions of surface conditions over the Arctic Ocean requires enhanced in situ observations and better data assimilation capability for more accurate initial conditions as well as better model physics. Numerical predictions of Arctic atmospheric conditions may continue to suffer from large errors if they do not fully capture the large SST anomalies related to Arctic warming.

Zhang, Chidong, Aaron F. Levine, Muyin Wang, Chelle Gentemann, Calvin W. Mordy, Edward D. Cokelet, Philip A. Browne, Qiong Yang, Noah Lawrence-Slavas, Christian Meinig, Gregory Smith, Andy Chiodi, Dongxiao Zhang, Phyllis Stabeno, Wanqiu Wang, Hong-Li Ren, K. Andrew Peterson, Silvio N. Figueroa, Michael Steele, Neil P. Barton, Andrew Huang, and Hyun-Cheol Shin. "Evaluation of Surface Conditions from Operational Forecasts Using In Situ Saildrone Observations in the Pacific Arctic", Monthly Weather Review 150, 6 (2022): 1437-1455, accessed Sep 13, 2022, https://doi.org/10.1175/MWR-D-20-0379.1

A scarcity of wintertime observations of surface ocean carbon dioxide partial pressure (pCO2) in and near the Gulf Stream creates uncertainty in the magnitude of the regional carbon sink and its controlling mechanisms. Recent observations from an Uncrewed Surface Vehicle (USV), outfitted with a payload to measure surface ocean and lower atmosphere pCO2, revealed sharp gradients in ocean pCO2 across the Gulf Stream. Surface ocean pCO2 was lower by ∼50 μatm relative to the atmosphere in the subtropical mode water (STMW) formation region. This undersaturation combined with strong wintertime winds allowed for rapid ocean uptake of CO2, averaging −11.5 mmol m−2 day−1 during the February 2019 USV mission. The unique timing of this mission revealed active STMW formation. The USV proved to be a useful tool for CO2 flux quantification in the poorly observed, dynamic western boundary current environment.

Nickford, S., Palter, J. B., Donohue, K., Fassbender, A. J., Gray, A. R., Long, J., et al. (2022). Autonomous wintertime observations of air-sea exchange in the Gulf Stream reveal a perfect storm for ocean CO2 uptake. Geophysical Research Letters, 49, e2021GL096805. https://doi.org/10.1029/2021GL096805

There is high demand for complete satellite SST maps (or L4 SST analyses) of the Arctic regions to monitor the rapid environmental changes occurring at high latitudes. Although there are a plethora of L4 SST products to choose from, satellite-based products evolve constantly with the advent of new satellites and frequent changes in SST algorithms, with the intent of improving absolute accuracies. The constant change of these products, as reflected by the version product, make it necessary to do periodic validations against in situ data. Eight of these L4 products are compared here against saildrone data from two 2019 campaigns in the western Arctic, as part of the MISST project. The accuracy of the different products is estimated using different statistical methods, from standard and robust statistics to Taylor diagrams. Results are also examined in terms of spatial scales of variability using auto- and cross-spectral analysis. The three products with the best performance, at this point and time, are used in a case study of the thermal features of the Yukon–Kuskokwim delta. The statistical analyses show that two L4 SST products had consistently better relative accuracy when compared to the saildrone subsurface temperatures. Those are the NOAA/NCEI DOISST and the RSS MWOI SSTs. In terms of the spectral variance and feature resolution, the UK Met Office OSTIA product appears to outperform all others at reproducing the fine scale features, especially in areas of high spatial variability, such as the Alaska coast. It is known that L4 analyses generate small-scale features that get smoothed out as the SSTs are interpolated onto spatially complete grids. However, when the high-resolution satellite coverage is sparse, which is the case in the Arctic regions, the analyses tend to produce more spurious small-scale features. The analyses here indicate that the high-resolution coverage, attainable with current satellite infrared technology, is too sparse, due to cloud cover to support very high resolution L4 SST products in high latitudinal regions. Only for grid resolutions of ~9–10 km or greater does the smoothing of the gridding process balance out the small-scale noise resulting from the lack of high-resolution infrared data. This scale, incidentally, agrees with the Rossby deformation radius in the Arctic Ocean (~10 km).

Vazquez-Cuervo, Jorge, Sandra L. Castro, Michael Steele, Chelle Gentemann, Jose Gomez-Valdes, and Wenqing Tang. 2022. "Comparison of GHRSST SST Analysis in the Arctic Ocean and Alaskan Coastal Waters Using Saildrones" Remote Sensing 14, no. 3: 692. https://doi.org/10.3390/rs14030692

The ocean and the marine parts of the cryosphere interact directly with, and are affected by, the seafloor and its primary properties of depth (bathymetry) and shape (morphology) in many ways. Bottom currents are largely constrained by undersea terrain with consequences for both regional and global heat transport. Deep ocean mixing is controlled by seafloor roughness, and the bathymetry directly influences where marine outlet glaciers are susceptible to the inflow relatively warm subsurface waters - an issue of great importance for ice-sheet discharge, i.e., the loss of mass from calving and undersea melting. Mass loss from glaciers and the Greenland and Antarctic ice sheets, is among the primary drivers of global sea-level rise, together now contributing more to sea-level rise than the thermal expansion of the ocean. Recent research suggests that the upper bounds of predicted sea-level rise by the year 2100 under the scenarios presented in IPCC’s Special Report on the Ocean and Cryosphere in a Changing Climate (SROCCC) likely are conservative because of the many unknowns regarding ice dynamics. In this paper we highlight the poorly mapped seafloor in the Polar regions as a critical knowledge gap that needs to be filled to move marine cryosphere science forward and produce improved understanding of the factors impacting ice-discharge and, with that, improved predictions of, among other things, global sea-level. We analyze the bathymetric data coverage in the Arctic Ocean specifically and use the results to discuss challenges that must be overcome to map the most remotely located areas in the Polar regions in general.

Jakobsson M and Mayer LA (2022) Polar Region Bathymetry: Critical Knowledge for the Prediction of Global Sea Level Rise. Front. Mar. Sci. 8:788724. doi: 10.3389/fmars.2021.788724

In the United States alone, hurricanes have been responsible for thousands of deaths and over US$1 trillion in damages since 1980 (https://www.ncdc.noaa.gov/billions/). These impacts are significantly greater globally, particularly in regions with limited hurricane early warning systems and where large portions of the population live at or near sea level. The high socioeconomic impacts of tropical cyclones will increase with a changing climate, rising sea level, and increasing coastal populations. To mitigate these impacts, efforts are underway to improve hurricane track and intensity forecasts, which drive storm surge models and evacuation orders and guide coastal preparations. Hurricane track forecasts have improved steadily over past decades, while intensity forecasts have lagged until recently (Cangialosi et al., 2020). Hurricane intensity changes are influenced by a combination of large-scale atmospheric circulation, internal storm dynamics, and air-sea interactions (Wadler et al., 2021, and references therein). Components of the sustained ocean observing system (e.g., profiling floats, expendable bathythermographs, drifters, moorings) are useful for understanding the role of the ocean in hurricane intensity changes. However, gaps in the ocean observing system, particularly collection of data near the air-sea interface and in coastal regions, boundary currents (e.g., the Gulf Stream, Kuroshio, among others), and areas with complex currents and seafloor topography (e.g., the Caribbean Sea), have led to difficulties in accurately representing upper ocean features and processes in numerical ocean models. Employment of uncrewed ocean observing platforms has begun to fill these gaps by offering rapid relocation and adaptive sampling of regions and ocean features of interest. These platforms include autonomous underwater gliders (Figure 1; Testor et al., 2019) and surface vehicles (Meinig et al., 2019). Uncrewed surface vehicles (USVs), such as saildrones and wave gliders, are systems designed for data collection in hazardous conditions. Data collected by these platforms have improved our understanding of upper ocean temperature and salinity stratification and mixing processes and are becoming critical in improving operational ocean and coupled air-sea hurricane forecast models (Domingues et al., 2021). This paper provides a broad overview of the ongoing US hurricane glider project and details of a new effort with the Saildrone USV during the 2021 hurricane season. While this article focuses on the US East Coast, Gulf of Mexico, and Caribbean Sea, similar efforts are underway in Korea, the Philippines, Japan, and China, among other countries.

Miles, T.N., D. Zhang, G.R. Foltz, J. Zhang, C. Meinig, F. Bringas, J. Triñanes, M. Le Hénaff, M.F. Aristizabal Vargas, S. Coakley, C.R. Edwards, D. Gong, R.E. Todd, M.J. Oliver, W.D. Wilson, K. Whilden, B. Kirkpatrick, P. Chardon-Maldonado, J.M. Morell, D. Hernandez, G. Kuska, C.D. Stienbarger, K. Bailey, C. Zhang, S.M. Glenn, and G.J. Goni. 2021. Uncrewed ocean gliders and saildrones support hurricane forecasting and research. Pp. 78–81 in Frontiers in Ocean Observing: Documenting Ecosystems, Understanding Environmental Changes, Forecasting Hazards. E.S. Kappel, S.K. Juniper, S. Seeyave, E. Smith, and M. Visbeck, eds, A Supplement to Oceanography 34(4), https://doi.org/10.5670/oceanog.2021.supplement.02-28.

In 2020, the developing COVID-19 pandemic disrupted fisheries surveys to an unprecedented extent. Many surveys were cancelled, including those for walleye pollock (Gadus chalcogrammus) in the eastern Bering Sea (EBS), the largest fishery in the United States. To partially mitigate the loss of survey information, we deployed three uncrewed surface vehicles (USVs) equipped with echosounders to extend the ship-based acoustic-trawl time series of pollock abundance. Trawling was not possible from USVs, so an empirical relationship between pollock backscatter and biomass established from previous surveys was developed to convert USV backscatter observations into pollock abundance. The EBS is well suited for this approach since pollock dominate midwater fishes in the survey area. Acoustic data from the USVs were combined with historical surveys to provide a consistent fishery-independent index in 2020. This application demonstrates the unique capabilities of USVs and how they could be rapidly deployed to collect information on pollock abundance and distribution when a ship-based survey was not feasible. We note the limitations of this approach (e.g. higher uncertainty relative to previous ship-based surveys), but found the USV survey to be useful in informing the stock assessment in a situation where ship-based surveys were not possible.

Alex De Robertis, Mike Levine, Nathan Lauffenburger, Taina Honkalehto, James Ianelli, Cole C Monnahan, Rick Towler, Darin Jones, Sarah Stienessen, Denise McKelvey, Uncrewed surface vehicle (USV) survey of walleye pollock, Gadus chalcogrammus, in response to the cancellation of ship-based surveys, ICES Journal of Marine Science, 2021. https://doi.org/10.1093/icesjms/fsab155

With accelerating global warming and human activities, the North Sea is one of the marine ecosystems undergoing rapid change. The need for spatially-temporally extendable survey platforms for assisting well-established vessel-based surveys are increasing. In this thesis, short-term variation in spatial structure of plankton and lesser sandeel (Ammodytes marinus) were investigated in the North Sea by using unmanned surface vehicle (USVs) Saildrones equipped with dual-frequency (38, 200 kHz) echo sounder. The data was collected in two areas, a part of the standard Aberdeen-Hanstholm transect and English Klondyke, an important sandeel fishing ground. These areas were repeatedly covered by two Saildrones in May-June 2019. Repeated surveys witnessed high plankton density in the western part of the Aberdeen-Hanstholm transect constantly during the survey period. Salinity seemed to be one possible factor explaining the heterogeneity of plankton density in both vertical and horizontal structure. Sandeel appeared diurnally at various depths from 2 m to near the sea bottom. There was only a weak tendency that the schools were distributed deeper around midday. However, their diverse vertical distribution indicated underlying drivers of their behavior other than light. Despite the existing uncertainty of species identification due to lack of ground-truthing and limited frequency availability, this saildrone survey conveyed little but purposeful information of the dynamics in spatial utilization of plankton and sandeel over a short period of time.

Komiyama, Sakura. "Spatiotemporal Dynamics in the Acoustic Backscatter of Plankton and Lesser Sandeel (Ammodytes marinus) in the North Sea Measured Using a Saildrone." Master's thesis, University of Bergen, 2021. Bergen Open Research Archive, https://hdl.handle.net/11250/2759844

More high-quality, in situ observations of essential marine variables are needed over the seasonal ice zone to better understand Arctic (or Antarctic) weather, climate, and ecosystems. To better assess the potential for arrays of uncrewed surface vehicles (USVs) to provide such observations, five wind-driven and solar-powered saildrones were sailed into the Chukchi and Beaufort Seas following the 2019 seasonal retreat of sea ice. They were equipped to observe the surface oceanic and atmospheric variables required to estimate air-sea fluxes of heat, momentum and carbon dioxide. Some of these variables were made available to weather forecast centers in real time. Our objective here is to analyze the effectiveness of existing remote ice navigation products and highlight the challenges and opportunities for improving remote ice navigation strategies with USVs. We examine the sources of navigational sea-ice distribution information based on post-mission tabulation of the sea-ice conditions encountered by the vehicles. The satellite-based ice-concentration analyses consulted during the mission exhibited large disagreements when the sea ice was retreating fastest (e.g., the 10% concentration contours differed between analyses by up to ∼175 km). Attempts to use saildrone observations to detect the ice edge revealed that in situ temperature and salinity measurements varied sufficiently in ice bands and open water that it is difficult to use these variables alone as a reliable ice-edge indicator. Devising robust strategies for remote ice zone navigation may depend on developing the capability to recognize sea ice and initiate navigational maneuvers with cameras and processing capability onboard the vehicles.

Chiodi Andrew M., Zhang Chidong, Cokelet Edward D., Yang Qiong, Mordy Calvin W., Gentemann Chelle L., Cross Jessica N., Lawrence-Slavas Noah, Meinig Christian, Steele Michael, Harrison Don E., Stabeno Phyllis J., Tabisola Heather M., Zhang Dongxiao, Burger Eugene F., O’Brien Kevin M., Wang Muyin, "Exploring the Pacific Arctic Seasonal Ice Zone With Saildrone USVs," Front. Mar. Sci., May 3, 2021. https://doi.org/10.3389/fmars.2021.640697

New in situ observations collected by Saildrones, a novel uncrewed surface vehicle (USV), are used to investigate atmospheric cold pools during three 6-month missions to the central and eastern (∼140°W–125°W) tropical Pacific. Cold pool fronts in the atmospheric boundary layer are identified by a −1.5°C air temperature drop occurring in 10 min or less. While cold pool events were observed in the central Pacific as far north as 30°N and within the equatorial band, the majority of observed cold pools occurred within the convective, low-wind shear environment of the Intertropical Convergence Zone. Composite time series analysis of measurements during the 382 cold pool events reveals new insights on high-frequency variations in air temperature, wind speed, humidity, pressure, and sea surface temperature and salinity associated with cold pool fronts. The results highlight the unique capabilities of Saildrone USVs to resolve small spatial and temporal scales of variability over observationally sparse ocean regions.

Wills, S. M., Cronin, M. F., & Zhang, D. (2021). Cold pools observed by uncrewed surface vehicles in the central and eastern tropical Pacific. Geophysical Research Letters, 48, e2021GL093373. https://doi.org/10.1029/2021GL093373

The Atlantic Tradewind Ocean-Atmosphere Mesoscale Interaction Campaign (ATOMIC) took place from 7 January to 11 July 2020 in the tropical North Atlantic between the eastern edge of Barbados and 51∘ W, the longitude of the Northwest Tropical Atlantic Station (NTAS) mooring. Measurements were made to gather information on shallow atmospheric convection, the effects of aerosols and clouds on the ocean surface energy budget, and mesoscale oceanic processes. Multiple platforms were deployed during ATOMIC including the NOAA RV Ronald H. Brown (RHB) (7 January to 13 February) and WP-3D Orion (P-3) aircraft (17 January to 10 February), the University of Colorado's Robust Autonomous Aerial Vehicle-Endurant Nimble (RAAVEN) uncrewed aerial system (UAS) (24 January to 15 February), NOAA- and NASA-sponsored Saildrones (12 January to 11 July), and Surface Velocity Program Salinity (SVPS) surface ocean drifters (23 January to 29 April). The RV Ronald H. Brown conducted in situ and remote sensing measurements of oceanic and atmospheric properties with an emphasis on mesoscale oceanic–atmospheric coupling and aerosol–cloud interactions. In addition, the ship served as a launching pad for Wave Gliders, Surface Wave Instrument Floats with Tracking (SWIFTs), and radiosondes. Details of measurements made from the RV Ronald H. Brown, ship-deployed assets, and other platforms closely coordinated with the ship during ATOMIC are provided here. These platforms include Saildrone 1064 and the RAAVEN UAS as well as the Barbados Cloud Observatory (BCO) and Barbados Atmospheric Chemistry Observatory (BACO). Inter-platform comparisons are presented to assess consistency in the data sets. Data sets from the RV Ronald H. Brown and deployed assets have been quality controlled and are publicly available at NOAA's National Centers for Environmental Information (NCEI) data archive (https://www.ncei.noaa.gov/archive/accession/ATOMIC-2020, last access: 2 April 2021). Point-of-contact information and links to individual data sets with digital object identifiers (DOIs) are provided herein.

Quinn, P. K., Thompson, E. J., Coffman, D. J., Baidar, S., Bariteau, L., Bates, T. S., Bigorre, S., Brewer, A., de Boer, G., de Szoeke, S. P., Drushka, K., Foltz, G. R., Intrieri, J., Iyer, S., Fairall, C. W., Gaston, C. J., Jansen, F., Johnson, J. E., Krüger, O. O., Marchbanks, R. D., Moran, K. P., Noone, D., Pezoa, S., Pincus, R., Plueddemann, A. J., Pöhlker, M. L., Pöschl, U., Quinones Melendez, E., Royer, H. M., Szczodrak, M., Thomson, J., Upchurch, L. M., Zhang, C., Zhang, D., and Zuidema, P.: Measurements from the RV Ronald H. Brown and related platforms as part of the Atlantic Tradewind Ocean-Atmosphere Mesoscale Interaction Campaign (ATOMIC), Earth Syst. Sci. Data, 13, 1759–1790, https://doi.org/10.5194/essd-13-1759-2021, 2021.

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.

Reverdin, G., Olivier, L., Foltz, G. R., Speich, S., Karstensen, J., Horstmann, J., et al. (2021). Formation and evolution of a freshwater plume in the northwestern tropical Atlantic in February 2020. Journal of Geophysical Research: Oceans, 126, e2020JC016981. https://doi.org/10.1029/2020JC016981

The Arctic Ocean is one of the most important and challenging regions to observe—it experiences the largest changes from climate warming, and at the same time is one of the most difficult to sample because of sea ice and extreme cold temperatures. Two NASA-sponsored deployments of the Saildrone vehicle provided a unique opportunity for validating sea-surface salinity (SSS) derived from three separate products that use data from the Soil Moisture Active Passive (SMAP) satellite. To examine possible issues in resolving mesoscale-to-submesoscale variability, comparisons were also made with two versions of the Estimating the Circulation and Climate of the Ocean (ECCO) model (Carroll, D; Menmenlis, D; Zhang, H.). The results indicate that the three SMAP products resolve the runoff signal associated with the Yukon River, with high correlation between SMAP products and Saildrone SSS. Spectral slopes, overall, replicate the -2.0 slopes associated with mesoscale-submesoscale variability. Statistically significant spatial coherences exist for all products, with peaks close to 100 km. Based on these encouraging results, future research should focus on improving derivations of satellite-derived SSS in the Arctic Ocean and integrating model results to complement remote sensing observations.

Vazquez-Cuervo, Jorge; Gentemann, Chelle; Tang, Wenqing; Carroll, Dustin; Zhang, Hong; Menemenlis, Dimitris; Gomez-Valdes, Jose; Bouali, Marouan; Steele, Michael. 2021. "Using Saildrones to Validate Arctic Sea-Surface Salinity from the SMAP Satellite and from Ocean Models" Remote Sens. 13, no. 5: 831. https://doi.org/10.3390/rs13050831

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.

Sutton, A. J., Williams, N. L., & Tilbrook, B. (2021). Constraining Southern Ocean CO2 Flux Uncertainty Using Uncrewed Surface Vehicle Observations. Geophysical Research Letters, 48, e2020GL091748. https://doi.org/10.1029/2020GL091748

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.

Levine, R.M., De Robertis, A., Grünbaum, D., Woodgate, R., Mordy, C.W., Mueter, F., Cokelet, E., Lawrence‐Slavas, N. and Tabisola, H. (2021), Autonomous vehicle surveys indicate that flow reversals retain juvenile fishes in a highly advective high‐latitude ecosystem. Limnol Oceanogr. https://doi.org/10.1002/lno.11671

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.

Ben Scoulding, Rudy Kloser, Sven Gastauerb, "Evaluation of unmanned surface vehicle acoustics for gas seep detection in shallow coastal waters,” International Journal of Greenhouse Gas Control, Volume 102, November 2020. https://doi.org/10.1016/j.ijggc.2020.103158

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.

Whitt Christopher, Pearlman Jay, Polagye Brian, Caimi Frank, Muller-Karger Frank, Copping Andrea, Spence Heather, Madhusudhana Shyam, Kirkwood William, Grosjean Ludovic, Fiaz Bilal Muhammad, Singh Satinder, Singh Sikandra, Manalang Dana, Gupta Ananya Sen, Maguer Alain, Buck Justin J. H., Marouchos Andreas, Atmanand Malayath Aravindakshan, Venkatesan Ramasamy, Narayanaswamy Vedachalam, Testor Pierre, Douglas Elizabeth, de Halleux Sebastien, Khalsa Siri Jodha, "Future Vision for Autonomous Ocean Observations," Frontiers in Marine Science, vol. 7 (September 2020): 697, https://doi.org/10.3389/fmars.2020.00697

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.

Nagano, A., Ando, K. "Saildrone-observed atmospheric boundary layer response to winter mesoscale warm spot along the Kuroshio south of Japan," Prog Earth Planet Sci 7, 43 (2020). https://doi.org/10.1186/s40645-020-00358-8

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.

Christopher Sabine; Adrienne Sutton; Kelly McCabe; Noah Lawrence-Slavas; Simone Alin; Richard Feely; Richard Jenkins; Stacy Maenner; Christian Meinig; Jesse Thomas Erik van Ooijen; Abe Passmore; Bronte Tilbrook, "Evaluation of a New Carbon Dioxide System for Autonomous Surface Vehicles," J. Atmos. Oceanic Technol. (2020) 37 (8): 1305–1317. https://doi.org/10.1175/JTECH-D-20-0010.1

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.

Vazquez-Cuervo, J.; Gomez-Valdes, J.; Bouali, M. "Comparison of Satellite-Derived Sea Surface Temperature and Sea Surface Salinity Gradients Using the Saildrone California/Baja and North Atlantic Gulf Stream Deployments." Remote Sens. 2020, 12, 1839. https://doi.org/10.3390/rs12111839

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.

Gentemann, C. L., and Coauthors, 2020: "Saildrone: Adaptively Sampling the Marine Environment." Bull. Amer. Meteor. Soc., 101, E744–E762, https://doi.org/10.1175/BAMS-D-19-0015.1.

We tested the feasibility of using Saildrone unmanned wind- and solar-powered surface vehicles to conduct remote focal follow studies of northern fur seals Callorhinus ursinus. Using Argos satellite and transmitted GPS locations, the Saildrones followed a fur seal while recording oceanographic conditions and mapping prey abundance and depth distribution using a scientific echosounder. The Saildrones successfully followed 6 fur seals over 2.4 ± 0.2 d (mean ± SE) and 149.7 ± 16.3 km of the foraging path. Median separation distance between the Saildrone and fur seal path was 0.65 ± 0.1 km and average time separation was 9.9 ± 1.4 h, with minimum time separations ranging from 1.9-4.9 h. Time and distance separation were a function of both animal behavior and study design. Our results show that Saildrones can approach satellite tracked marine predators from long distances and follow them over extended periods while collecting oceanographic and prey data. These successful focal follows demonstrate that unmanned surface vehicles are a valuable tool for collecting data on fine-scale relationships between marine predators, their prey, and the environment.

Kuhn CE, De Robertis A, Sterling J, Mordy CW et al. (2020) "Test of unmanned surface vehicles to conduct remote focal follow studies of a marine predator." Mar Ecol Prog Ser 635:1-7. https://doi.org/10.3354/meps13224

Abstract: In vivo chlorophyll fluorescence (ChlF) can serve as a reasonable estimator of in situ phytoplankton biomass with the benefits of efficiently and affordably extending the global chlorophyll (Chl) data set in time and space to remote oceanic regions where routine sampling by other vessels is uncommon. However, in vivo ChlF measurements require correction for known, spurious biases relative to other measures of Chl concentration, including satellite ocean color retrievals. Spurious biases affecting in vivo ChlF measurements include biofouling, colored dissolved organic matter (CDOM) fluorescence, calibration offsets, and non-photochemical quenching (NPQ). A more evenly distributed global sampling of in vivo ChlF would provide additional confidence in estimates of uncertainty for satellite ocean color retrievals. A Saildrone semi-autonomous, ocean-going, solar- and wind-powered surface drone recently measured a variety of ocean and atmospheric parameters, including ChlF, during a 60-day deployment in mid-2018 in the California Current region. Correcting the Saildrone ChlF data for known biases, including deriving an NPQ-correction, greatly improved the agreement between the drone measurements and satellite ocean color retrievals from MODIS-Aqua and VIIRS-SNPP, highlighting that once these considerations are made, Saildrone semi-autonomous surface vehicles are a valuable, emerging data source for ocean and ecosystem monitoring.

Joel P. Scott, Scout Crooke, Ivona Cetinić, Carlos E. Del Castillo, and Chelle L. Gentemann, "Correcting non-photochemical quenching of Saildrone chlorophyll-a fluorescence for evaluation of satellite ocean color retrievals," Opt. Express 28, 4274-4285 (2020) https://doi.org/10.1364/OE.382029

Abstract: Traditional ways of validating satellite-derived sea surface temperature (SST) and sea surface salinity (SSS) products by comparing with buoy measurements, do not allow for evaluating the impact of mesoscale-to-submesoscale variability. We present the validation of remotely sensed SST and SSS data against the unmanned surface vehicle (USV)—called Saildrone—measurements from the 60 day 2018 Baja California campaign. More specifically, biases and root mean square differences (RMSDs) were calculated between USV-derived SST and SSS values, and six satellite-derived SST (MUR, OSTIA, CMC, K10, REMSS, and DMI) and three SSS (JPLSMAP, RSS40, RSS70) products. Biases between the USV SST and OSTIA/CMC/DMI were approximately zero, while MUR showed a bias of 0.3 ◦C. The OSTIA showed the smallest RMSD of 0.39 ◦C, while DMI had the largest RMSD of 0.5 ◦C. An RMSD of 0.4 ◦C between Saildrone SST and the satellite-derived products could be explained by the diurnal and sub-daily variability in USV SST, which currently cannot be resolved by remote sensing measurements. SSS showed fresh biases of 0.1 PSU for JPLSMAP and 0.2 PSU and 0.3 PSU for RMSS40 and RSS70 respectively. SST and SSS showed peaks in coherence at 100 km, most likely associated with the variability of the California Current System.

Vazquez-Cuervo, J.; Gomez-Valdes, J.; Bouali, M.; Miranda, L.E.; Van der Stocken, T.; Tang, W.; Gentemann, C. "Using Saildrones to Validate Satellite-Derived Sea Surface Salinity and Sea Surface Temperature along the California/Baja Coast." Remote Sens. 2019, 11, 1964. https://doi.org/10.3390/rs11171964

Partnership between the private sector and the ocean observing community brings exciting opportunities to address observing challenges through leveraging the unique strengths of each sector. Here, we discuss a case study of a successful relationship between the National Oceanic and Atmospheric Administration (NOAA) Pacific Marine Environmental Laboratory (PMEL) and Saildrone to instrument an Unmanned Surface Vehicle (USV) in order to serve shared goals. This case study demonstrates that a private company working with a federal laboratory has provided innovative ocean observing solutions deployed at regional scale in only a few years, and we project that this model will be sustainable over the long-term. An alignment of long-term goals with practical deliverables during the development process and integrating group cultures were key to success. To date, this effort has expanded NOAA’s interdisciplinary observing capabilities, improved public access to ocean data, and paved the way for a growing range of USV applications in every ocean. By emphasizing shared needs, complementary strengths, and a clear vision for a sustainable future observing system, we believe that this case study can serve as a blueprint for public and private partners who wish to improve observational capacity. We recommend that the international scientific community continue to foster collaborations between the private sector and regional ocean observing networks. This effort could include regional workshops that build community confidence through independent oversight of data quality. We also recommend that an international framework should be created to organize public and private partners in the atmospheric and oceanographic fields. This body would coordinate development of observational technologies that adhere to best practices and standards for sensor integration, verification, data quality control and delivery, and provide guidance for unmanned vehicle providers. Last, we also recommend building bridges between the private sector, ocean observing community, and the operational forecast community to consider the future of this new private sector, with goals to determine targeted ocean observing needs; assess the appropriateness of USVs as science platforms, sensors, and data format standards; and establish usage and data quality control and distribution protocols for ocean observing and operational forecasting.

Meinig, C., E.F. Burger, N. Cohen, E.D. Cokelet, M.F. Cronin, J.N. Cross, S. de Halleux, R. Jenkins, A.T. Jessup, C.W. Mordy, N. Lawrence-Slavas, A.J. Sutton, D. Zhang, and C. Zhang. "Public private partnerships to advance regional ocean observing capabilities: A Saildrone and NOAA-PMEL case study and future considerations to expand to global scale observing." OceanObs'19, Front. Mar. Sci., doi: 10.3389/fmars.2019.00448, 2019.

Turbulent and radiative exchanges of heat between the ocean and atmosphere (hereafter heat fluxes), ocean surface wind stress, and state variables used to estimate them, are Essential Ocean Variables (EOVs) and Essential Climate Variables (ECVs) influencing weather and climate. This paper describes an observational strategy for producing 3-hourly, 25-km (and an aspirational goal of hourly at 10-km) heat flux and wind stress fields over the global, ice-free ocean with breakthrough 1-day random uncertainty of 15 W m–2 and a bias of less than 5 W m–2. At present this accuracy target is met only for OceanSITES reference station moorings and research vessels (RVs) that follow best practices. To meet these targets globally, in the next decade, satellite-based observations must be optimized for boundary layer measurements of air temperature, humidity, sea surface temperature, and ocean wind stress. In order to tune and validate these satellite measurements, a complementary global in situ flux array, built around an expanded OceanSITES network of time series reference station moorings, is also needed. The array would include 500–1000 measurement platforms, including autonomous surface vehicles, moored and drifting buoys, RVs, the existing OceanSITES network of 22 flux sites, and new OceanSITES expanded in 19 key regions. This array would be globally distributed, with 1–3 measurement platforms in each nominal 10° by 10° box. These improved moisture and temperature profiles and surface data, if assimilated into Numerical Weather Prediction (NWP) models, would lead to better representation of cloud formation processes, improving state variables and surface radiative and turbulent fluxes from these models. The in situ flux array provides globally distributed measurements and metrics for satellite algorithm development, product validation, and for improving satellite-based, NWP and blended flux products. In addition, some of these flux platforms will also measure direct turbulent fluxes, which can be used to improve algorithms for computation of air-sea exchange of heat and momentum in flux products and models. With these improved air-sea fluxes, the ocean’s influence on the atmosphere will be better quantified and lead to improved long-term weather forecasts, seasonal-interannual-decadal climate predictions, and regional climate projections.

Cronin Meghan F., Gentemann Chelle L., Edson James, Ueki Iwao, Bourassa Mark, Brown Shannon, Clayson Carol Anne, Fairall Chris W., Farrar J. Thomas, Gille Sarah T., Gulev Sergey, Josey Simon A., Kato Seiji, Katsumata Masaki, Kent Elizabeth, Krug Marjolaine, Minnett Peter J., Parfitt Rhys, Pinker Rachel T., Stackhouse Paul W., Swart Sebastiaan, Tomita Hiroyuki, Vandemark Douglas, Weller A. Robert, Yoneyama Kunio, Yu Lisan, Zhang Dongxiao. "Air-Sea Fluxes With a Focus on Heat and Momentum," Frontiers in Marine Science, Vol. 5, 2019, p. 430. https://doi.org/10.3389/fmars.2019.00430

Two Saildrone unmanned surface vehicles (USVs) were instrumented with echosounders and deployed in the Bering Sea to make acoustic observations of walleye pollock for 103 days. The Saildrones proved to be a suitable platform for measurement of fish backscatter: they produced high-quality measurements at wind speeds of <10 m s−1. Pollock backscatter measured from the Saildrones was compared to backscatter measured by a noise-reduced research vessel during two “follow-the-leader” comparisons. In a location where pollock were shallowly distributed (30–100 m), there was evidence of depth-dependent avoidance reactions to the ship. This behaviour was not evident in a second comparison, where the fish were primarily deeper than 90 m. Opportunistic comparisons indicate that backscatter where the ship and USVs crossed paths was similar. However, the Saildrones observed higher densities of shallow fish, which is consistent with the diving response inferred in the first follow-the-leader comparison. USVs equipped with echosounders, like all platforms, have inherent strengths (endurance) and limitations (species identification) that should be carefully considered for a given application. USVs can complement traditional ship-based surveys by increasing the spatial and temporal extent of acoustic observations, and their use is likely to become more widespread.

Alex De Robertis, Noah Lawrence-Slavas, Richard Jenkins, Ivar Wangen, Calvin W Mordy, Christian Meinig, Mike Levine, Dave Peacock, Heather Tabisola, "Long-term measurements of fish backscatter from Saildrone unmanned surface vehicles and comparison with observations from a noise-reduced research vessel," ICES Journal of Marine Science, , fsz124, https://doi.org/10.1093/icesjms/fsz124

A successful integrated ocean acidification (OA) observing network must include (1) scientists and technicians from a range of disciplines from physics to chemistry to biology to technology development; (2) government, private, and intergovernmental support; (3) regional cohorts working together on regionally specific issues; (4) publicly accessible data from the open ocean to coastal to estuarine systems; (5) close integration with other networks focusing on related measurements or issues including the social and economic consequences of OA; and (6) observation-based informational products useful for decision making such as management of fisheries and aquaculture. The Global Ocean Acidification Observing Network (GOA-ON), a key player in this vision, seeks to expand and enhance geographic extent and availability of coastal and open ocean observing data to ultimately inform adaptive measures and policy action, especially in support of the United Nations 2030 Agenda for Sustainable Development. GOA-ON works to empower and support regional collaborative networks such as the Latin American Ocean Acidification Network, supports new scientists entering the field with training, mentorship, and equipment, refines approaches for tracking biological impacts, and stimulates development of lower-cost methodology and technologies allowing for wider participation of scientists. GOA-ON seeks to collaborate with and complement work done by other observing networks such as those focused on carbon flux into the ocean, tracking of carbon and oxygen in the ocean, observing biological diversity, and determining short- and long-term variability in these and other ocean parameters through space and time.

Tilbrook Bronte, Jewett Elizabeth B., DeGrandpre Michael D., Hernandez-Ayon Jose Martin, Feely Richard A., Gledhill Dwight K., Hansson Lina, Isensee Kirsten, Kurz Meredith L., Newton Janet A., Siedlecki Samantha A., Chai Fei, Dupont Sam, Graco Michelle, Calvo Eva, Greeley Dana, Kapsenberg Lydia, Lebrec Marine, Pelejero Carles, Schoo Katherina L., Telszewski Maciej, "An Enhanced Ocean Acidification Observing Network: From People to Technology to Data Synthesis and Information Exchange," Frontiers in Marine Science, vol. 6. (2019):337. https://doi.org/10.3389/fmars.2019.00337

Two saildrones participated in the Salinity Processes in the Upper-ocean Regional Study 2 (SPURS-2) field campaign at 10°N, 125°W, as part of their more than six-month Tropical Pacific Observing System (TPOS)-2020 pilot study in the eastern tropical Pacific. The two saildrones were launched from San Francisco, California, on September 1, 2017, and arrived at the SPURS-2 region on October 15, one week before R/V Revelle. Upon arrival at the SPURS-2 site, they each began a two-week repeat pattern, sailing around the program’s central moored surface buoy. The heavily instrumented Woods Hole Oceanographic Institution (WHOI) SPURS-2 buoy serves as a benchmark for validating the saildrone measurements for air-sea fluxes. The data collected by the WHOI buoy and the saildrones were found to be in reasonably good agreement. Although of short duration, these ship-saildrone-buoy comparisons are encouraging as they provide enhanced understanding of measurements by various platforms in a rapidly changing subsynoptic weather system. The saildrones were generally able to navigate the challenging Intertropical Convergence Zone, where winds are low and currents can be strong, demonstrating that the saildrone is an effective platform for observing a wide range of oceanographic variables important to airsea interaction studies.

Zhang, D., M.F. Cronin, C. Meinig, J.T. Farrar, R. Jenkins, D. Peacock, J. Keene, A. Sutton, and Q. Yang. 2019. Comparing air-sea flux measurements from a new unmanned surface vehicle and proven platforms during the SPURS-2 field campaign. Oceanography 32(2):122–133, https://doi.org/10.5670/oceanog.2019.220

This report provides: 1) a detailed description of the acoustic-trawl method (ATM) used by NOAA’s Southwest Fisheries Science Center (SWFSC) for direct assessments of the dominant species of coastal pelagic species (CPS; i.e., Pacifc Sardine Sardinops sagax, Northern Anchovy Engraulis mordax, Pacifc Mackerel Scomber japonicus, Jack Mackerel Trachurus symmetricus, and Pacifc Herring Clupea pallasii) in the California Current Ecosystem (CCE) o ̇ the west coast of North America; and 2) estimates of the biomasses, distributions, and demographies of those CPS in the survey area between 26 June and 23 September 2018. The survey area spanned most of the continental shelf between the northern tip of Vancouver Island, British Columbia (BC) and San Diego, CA. Throughout the survey area, NOAA Ship Reuben Lasker (hereafter, Lasker) sampled along transects oriented approximately perpendicular to the coast, from the shallowest navigable depth (~30 m depth) to either a distance of 35 nmi or to the 1,000 fathom (~1830 m) isobath, whichever is farthest. Between approximately San Francisco and Pt. Conception, additional acoustic sampling was conducted along 4 nmi-long transects spaced 5-nmi apart using a wind- and solar-powered unmanned surface vehicle (USV; Saildrone, Inc.) in the nearshore where Lasker could not safely navigate.

Kevin L. Stierhoff, Juan P. Zwolinski, and David A. Demer. 2019. "Distribution,biomass, and demography of coastal pelagic fishes in the California Current Ecosystem during summer 2018 based on acoustic-trawl sampling." U.S. Department of Commerce, NOAA Technical Memorandum NMFS-SWFSC-613. https://doi.org/10.25923/nghv-7c40

Abstract: Saildrones are unmanned surface vehicles engineered for oceanographic research and powered by wind and solar energy. In the summer of 2016, two Saildrones surveyed the southeastern Bering Sea using passive acoustics to listen for vocalizations of marine mammals and active acoustics to quantify the spatial distribution of small and large fishes. Fish distributions were examined during foraging trips of northern fur seals (Callorhinus ursinus), and initial results suggest these prey distributions may influence the diving behavior of fur seals. The Saildrone is faster, has greater instrument capacity, and requires less support services than its counterparts. This innovative platform performed well in stormy conditions, and it demonstrated the potential to augment fishery surveys and advance ecosystem research.

Mordy, C.W., E.D. Cokelet, A. De Robertis, R. Jenkins, C.E. Kuhn, N. LawrenceSlavas, C.L. Berchok, J.L. Crance, J.T. Sterling, J.N. Cross, P.J. Stabeno, C. Meinig, H.M. Tabisola, W. Burgess, and I. Wangen. 2017. "Advances in ecosystem research: Saildrone surveys of oceanography, fish, and marine mammals in the Bering Sea." Oceanography 30(2):113–115. https://doi.org/10.5670/oceanog.2017.230

Abstract: Persistence of oil floating in the ocean is an important factor for evaluating hydrocarbon fluxes from natural seeps and anthropogenic releases into the environment. The objective of this work is to estimate the surface residence-time of the oil slick and to determine the importance of wind and surface currents on the trajectory and fate of the released oil. Oil slicks released from natural hydrocarbon seeps located in Green Canyon 600 lease block and its surrounding region in the Gulf of Mexico were analyzed. A Texture Classifying Neural Network Algorithm was used to delineate georectified polygons for oil slicks from 41 synthetic aperture radar images. Trajectories of the oil slicks were investigated by employing a Lagrangian particle-tracking surface oil drift model. A set of numerical simulations was performed by increasing hindcast interval in reverse time order from the image collection time in order to obtain the closest resemblance between the simulated oil pathways and the length and shape of the oil slicks observed in SAR images. The average surface residence-time predicted from the hindcast modeling was 6.4 h (± 5.7 h). Analysis of a linear regression model, including observed oil slick lengths and variables of wind, surface current, and their relative direction, indicated a statistically significant negative effect of wind speed on the surface oil drift. Higher wind speed (> 7 m s-1) reduced length of the oil slicks. When wind and surface currents were driving forces of the surface oil drift model, a good agreement between simulated trajectories and subsequent satellite observations (R2 = 0.9) suggested that a wind scaling coefficient of 0.035 and a wind deflection angle of 20º to the right of the wind direction were acceptable approximations for modeling wind effects in this study. Results from the numerical experimentation were supported by in situ observations conducted by a wind-powered autonomous surface vehicle (Saildrone). Results indicated that the surface currents are, indeed, responsible for stretching oil slicks and that surface winds are largely responsible for the disappearance of the oil slicks from the sea surface. Under conditions of low wind and strong current, natural seeps can produce oil slicks that are longer than 20 km and persist for up to 48 h.

Daneshgar, Samira & Dukhovskoy, Dmitry & Bourassa, Mark & Macdonald, Ian. (2016). "Hindcast modeling of oil slick persistence from natural seeps." Remote Sensing of Environment. 189. http://dx.doi.org/10.1016/j.rse.2016.11.003