Scientific Papers

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.

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.

Acoustic surveys to estimate fish biomass and abundance are a major component of many fisheries monitoring programs. An important bias in acoustic surveys is that fish may avoid the survey vessel. Here, we utilized quiet uncrewed surface vessels (USVs) equipped with 120 kHz split beam echosounders to evaluate fish responses to motorized survey vessels. Two of these USVs were deployed in Lakes Michigan and Huron in summer 2021 and compared against three motorized vessels used in conventional fisheries acoustic surveys. Paired comparisons employed vessel-drone passes that provided the opportunity to observe fish response as vessels approached and then overtook their quiet USV counterparts. Sound originating from the vessels was primarily in the 10–1000 Hz range. Overall received sound pressure levels for ships at the closest pass were 100 dB (re 1 µPa @ 1 m) for one and 133–134 dB for the other two vessels. In contrast, sound originating from the USV was not detectable over ambient noise. We examined acoustic data from the USVs for potential changes in total acoustic backscatter, average target depth, and average in situ target strength as vessels approached. We observed weak evidence of an avoidance response by fish to the vessel with the loudest noise profile and highest survey speed but not for the other two vessels. We also compared acoustic data from 33 2-km transects surveyed by both vessels and the USVs, finding few differences between vessel and USV data for water depths between 5 and 80 m. Results from this work suggest that acoustics estimates of fishes in Lakes Michigan and Huron (primarily alewife, rainbow smelt, and bloater) are largely consistent among the vessels used in these two lakes for standard acoustic surveys and that fish avoidance is minimal in water depths > 5 meters.

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.

On 30 September 2021, a saildrone uncrewed surface vehicle (USV) was steered into Category 4 Hurricane Sam, the most intense storm of the 2021 Atlantic hurricane season. It measured significant wave heights up to 14 m (maximum wave height 27 m) and near-surface winds exceeding 55 m s−1. This was the first time in more than seven decades of hurricane observations that in real time a USV transmitted scientific data, images, and videos of the dynamic ocean surface near a hurricane’s eyewall. The saildrone was part of a five-saildrone deployment of the NOAA 2021 Atlantic Hurricane Observations Mission. These saildrones observed the atmospheric and oceanic near-surface conditions of five other tropical storms, of which two became hurricanes. Such observations inside tropical cyclones help to advance the understanding and prediction of hurricanes, with the ultimate goal of saving lives and protecting property. The 2021 deployment pioneered a new practice of coordinating measurements by saildrones, underwater gliders, and airborne dropsondes to make simultaneous and near-collocated observations of the air-sea interface, the ocean immediately below, and the atmosphere immediately above. This experimental deployment opened the door to a new era of using remotely piloted uncrewed systems to observe one of the most extreme phenomena on Earth in a way previously impossible. This article provides an overview of this saildrone hurricane observations mission, describes how the saildrones were coordinated with other observing platforms, presents preliminary scientific results from these observations to demonstrate their potential utility and motivate further data analysis, and offers a vision of future hurricane observations using combined uncrewed platforms.

The collection of environmental DNA (eDNA) samples is often laborious, costly, and logistically difficult to accomplish at high frequency in remote locations and over large geographic areas. Here, we addressed those challenges by combining two robotic technologies: an uncrewed surface vessel (USV) fitted with an automated eDNA sample collection device to survey surface waters in the eastern North Pacific Ocean from Alameda, CA to Honolulu, HI. USV Surveyor SD 1200 (Saildrone) carrying the Environmental Sample Processor (ESP) collected 2-L water samples by filtration followed by RNAlater preservation at regular intervals over a 4200-km, 29-day transit. Sixty samples (52 field and 8 controls) were acquired and used to estimate the concentration of specific genes and assess eukaryotic diversity via targeted qPCR and metabarcoding of the cytochrome oxidase subunit I (COI) gene, respectively. Comparisons of control samples revealed important considerations for interpreting results. Samples stored at ambient temperatures onboard Surveyor over the length of the voyage had less total recoverable DNA and specific target gene concentrations compared to the same material immediately flash-frozen after collection and stored in a laboratory. In contrast, the biodiversity of the COI genes in those samples was similar regardless of sample age and storage condition. COI genes affiliated with 40 eukaryotic phyla were found in native samples collected during the voyage. The distribution and dominance of those phyla varied across different regions, with some taxa spanning large continuous stretches >2000 km, while others were only detected in a single sample. This work highlights the utility and potential of using USVs fitted with autonomous eDNA sample collection devices to improve ocean exploration and support large, basin-scale, systematic biodiversity surveys. Results of this study also inform future technical considerations for using automated eDNA samplers to acquire material and store it over prolonged periods under prevailing environmental conditions.

There is growing recognition that key to addressing critical issues like climate change, global sea level rise, and the long-term sustainability of humankind is a more complete understanding of our oceans and processes within them that account for the distribution of global heat, CO, and provide sustenance to so many. Yet, despite years of effort, less than 25% of the global ocean seafloor has been mapped, and less than 5% of the ocean volume explored, likely due to the cost and inefficiency of traditional ocean mapping and exploration techniques using large, very expensive, crewed research vessels. Recent advances in the development of uncrewed surface vessels offer the possibility to reduce costs and increase efficiency of ocean mapping and exploration. Such efficiencies can be gained by using small mother ship-deployed uncrewed vessels acting as relatively inexpensive mapping and sampling force multipliers or the use of small uncrewed vessels launched to from a mother ship to monitor and control autonomous underwater vehicles, allowing multiple operations simultaneously and “verified, directed sampling,” all while freeing the mother ship for independent operations. We are also seeing the development of larger uncrewed vessels launched from shore with long endurance and range, capable of carrying a full suite of deep ocean mapping and exploration tools. All of these systems and approaches offer great hope, but it is very early in our understanding of their full capabilities, costs, and limitations, and we must be careful not to overpromise, leading to disappointments and early abandonment of a potentially innovative approach, while at the same time maintaining the patience required to continue the research, investment, and innovation that will hopefully bring us to a new world of efficient and effective ocean mapping and exploration that will allow us to meet our goal of complete coverage of the ocean.

High-frequency wind measurements from Saildrone autonomous surface vehicles are used to calculate wind stress in the tropical east Pacific. Comparison between direct covariance (DC) and bulk wind stress estimates demonstrates very good agreement. Building on previous work that showed the bulk input data were reliable, our results lend credibility to the DC estimates. Wind flow distortion by Saildrones is comparable to or smaller than other platforms. Motion correction results in realistic wind spectra, albeit with signatures of swell-coherent wind fluctuations that may be unrealistically strong. Fractional differences between DC and bulk wind stress magnitude are largest at wind speeds below 4 m s−1. The size of this effect, however, depends on choice of stress direction assumptions. Past work has shown the importance of using current-relative (instead of Earth-relative) winds to achieve accurate wind stress magnitude. We show that it is also important for wind stress direction.

High-frequency wind measurements from Saildrone autonomous surface vehicles are used to calculate wind stress in the tropical east Pacific. Comparison between direct covariance (DC) and bulk wind stress estimates demonstrates very good agreement. Building on previous work that showed the bulk input data were reliable, our results lend credibility to the DC estimates. Wind flow distortion by Saildrones is comparable to or smaller than other platforms. Motion correction results in realistic wind spectra, albeit with signatures of swell-coherent wind fluctuations that may be unrealistically strong. Fractional differences between DC and bulk wind stress magnitude are largest at wind speeds below 4 m s−1. The size of this effect, however, depends on choice of stress direction assumptions. Past work has shown the importance of using current-relative (instead of Earth-relative) winds to achieve accurate wind stress magnitude. We show that it is also important for wind stress direction.

The sea surface temperature (SST) is one of the essential parameters needed to understand the climate change in the Arctic. Saildrone, an advanced autonomous surface vehicle, has proven to be a useful tool for providing accurate SST data at high latitudes. Here, data from two Saildrones, deployed in the Arctic in the summer of 2019, are used to investigate the diurnal variability of upper ocean thermal structure. An empirical cool skin effect model with dependence on the wind speed with new coefficients was generated. Several local large diurnal warming events were observed, the amplitudes of warming in the skin layer >5 K, rarely reported in previous studies. Furthermore, the warming signals could persist beyond 1 day. For those cases, it was found surface warm air suppressed the surface turbulent heat loss to maintain the persistence of diurnal warming under low wind conditions. Salinity also plays an important role in the formation of upper ocean density stratification during diurnal warming at high latitudes. A less salty and hence less dense surface layer was likely created by precipitation or melting sea ice, providing favorable conditions for the formation of upper ocean stratification. Comparisons with two prognostic diurnal warming models showed the simulations match reasonably well with Saildrone measurements for moderate wind speeds but exhibit large differences at low winds. Both schemes show significant negative biases in the early morning and late afternoon. It is necessary to improve the model schemes when applied at high latitudes.