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Reliable forecasts for the dispersion of oceanic contamination are important for coastal ecosystems, society, and the economy as evidenced by the Deepwater Horizon oil spill in the Gulf of Mexico in 2010 and the Fukushima nuclear plant incident in the Pacific Ocean in 2011. Accurate prediction of pollutant pathways and concentrations at the ocean surface requires understanding ocean dynamics over a broad range of spatial scales. Fundamental questions concerning the structure of the velocity field at the submesoscales (100 m to tens of kilometers, hours to days) remain unresolved due to a lack of synoptic measurements at these scales. Using high-frequency position data provided by the near-simultaneous release of hundreds of accurately tracked surface drifters, we study the structure of submesoscale surface velocity fluctuations in the Northern Gulf of Mexico. Observed two-point statistics confirm the accuracy of classic turbulence scaling laws at 200-m to 50-km scales and clearly indicate that dispersion at the submesoscales is local, driven predominantly by energetic submesoscale fluctuations. The results demonstrate the feasibility and utility of deploying large clusters of drifting instruments to provide synoptic observations of spatial variability of the ocean surface velocity field. Our findings allow quantification of the submesoscale-driven dispersion missing in current operational circulation models and satellite altimeter-derived velocity fields.

Strengths and weakness of remotely sensed winds are discussed, along with the current capabilities for remotely sensing winds and stress. Future missions are briefly mentioned. The observational needs for a wide range of wind and stress applications are provided. These needs strongly support a short list of desired capabilities of future missions and constellations.

Surface drifter observations from the LAgrangian Submesoscale ExpeRiment (LASER) campaign in the Gulf of Mexico are paired with Eulerian (ship-borne X-band radar) data to demonstrate that velocity structure functions from drifters differ systematically from Eulerian structure functions over scales from 0.4 to 7 km. These differences result from drifters oversampling surface convergences and regions of intense vorticity. The first-, second-, and third-order structure functions are calculated using quasi-Lagrangian (drifter) and Eulerian data from approximately the same location and time. Differences between quasi-Lagrangian and Eulerian structure functions are attributed to two forms of bias. The first bias results from the mean divergence or vorticity of the background flow creating nonzero first-order structure functions. This background bias affects both quasi-Lagrangian and Eulerian data when insufficiently time-averaged. It severely biases the drifter third-order structure functions but is smaller in Eulerian structure functions at both second and third order. This bias can be corrected for using lower-order structure functions. The second form of bias results from drifters accumulating in regions with flow statistics that differ from undersampled regions. This accumulation bias is diagnosed by identifying the dependence of the Eulerian structure functions on divergence and vorticity as well as scale. Together, both biases suggest that caution is needed when interpreting second-order drifter statistics and that linking raw third-order drifter statistics to energy fluxes is often erroneous in ocean data: Even with background correction and sufficient time-averaging, drifters overestimate the Eulerian estimate of the third-order structure function by up to a factor of 5 when signs are consistent. [ABSTRACT FROM AUTHOR]

Submesoscale oceanic fronts (SFs), which typically occur on a spatial scale of 0.1–10 km, may have a large influence on the atmospheric surface layer (ASL). However, due to their short temporal‐spatial scales, evaluating their direct impact on this layer remains challenging and characterizing the nature of SF‐ASL interaction has not been done in the field. To address this, a study of the air‐sea response to SFs was conducted using observations collected during the Lagrangian Submesoscale Experiment, which took place in the northern Gulf of Mexico. This manuscript focuses on the meteorological measurements made from a pair of masts installed on the bow of the R/V Walton Smith. This work represents one of the first observation‐based investigations into the potential influence that SFs have on the ASL. Contemporaneous measurements from an X‐band marine radar, moving vessel profiler, and Lagrangian drifters were also used to analyze the SF dynamics. Systematic surface wind velocity changes over several cross‐frontal transects were observed, a process previously associated with mesoscale fronts. A comparison between the eddy covariance and parameterized (COARE 3.5) air‐sea fluxes revealed that the directly observed heat flux was 1.5 times larger than the bulk value in the vicinity of the SFs. This suggests that the hydrodynamic processes near the front enhance the local exchange of sensible and latent heat. Given the prevalence of SF over the global upper ocean, these findings suggest that these features may have a widely distributed and cumulative impact on air‐sea interactions. Plain Language Summary: The atmosphere responds to the ocean over all scales—from microscopic to planetary scales. Previous studies showed that surface wind and even the entire atmospheric boundary layer could be affected by the relatively large‐scale (10–1,000 km) temperature variations across the open ocean, for example, the Gulf Stream. However, the impacts of relatively small‐scale (100 m to 10 km) and rapidly (hours to days) evolving fronts are largely unknown due to the difficulty in actually observing the physical processes. As part of an ongoing effort to better understand surface material dispersion across the northern Gulf of Mexico, we conducted ship‐based measurements of air‐sea fluxes across near small‐scale fronts. The observations showed that the physical mechanism used to explain the interaction between the atmosphere and large‐scale ocean temperature gradients readily downscales to these smaller fronts, which have a direct impact of wind directly above the ocean surface. These small‐scale fronts were also observed to locally enhance the air‐sea heat flux, and the conventional model used to predict this underestimates the observed value by as much as 50%. These small‐scale frontal features are common across the global ocean, and our findings suggest that they could cumulatively impact the global energy budget. Key Points: Systematic ship‐based observations of wind and fluxes across submesoscale fronts were conducted in varying wind directionsCross‐frontal wind variance depended on the airflow relative to the in‐water thermal gradientSubmesoscale fronts were observed to locally enhance air‐sea heat flux, compared to values from commonly used bulk algorithm [ABSTRACT FROM AUTHOR]

The Lagrangian Submesoscale Experiment (LASER) involved the deployment of ;1000 biodegradable GPS-tracked Consortium for Advanced Research on Transport of Hydrocarbon in the Environment (CARTHE) drifters to measure submesoscale upper-ocean currents and their potential impact on oil spills. The experiment was conducted from January to February 2016 in the Gulf of Mexico (GoM) near the mouth of the Mississippi River, an area characterized by strong submesoscale currents. A Helmholtz-Zentrum Geesthacht (HZG) marine X-band radar (MR) on board the R/V F. G. Walton Smith was used to locate fronts and eddies by their sea surface roughness signatures. The MR data were further processed to yield near-surface current maps at ~500-m resolution up to a maximum range of ~3km. This study employs the drifter measurements to perform the first comprehensive validation of MR near-surface current maps. For a total of 4130 MR--drifter pairs, the root-mean-square error for the current speed is 4 cms21 and that for the current direction is 128. The MR samples currents at a greater effective depth than the CARTHE drifters (1-5mvs~0.4m). The mean MR--drifter differences are consistent with a wave-and wind-driven vertical current profile that weakens with increasing depth and rotates clockwise from the wind direction (by 0.7% of the wind speed and 158). The technique presented here has great potential in observational oceanography, as it allows research vessels to map the horizontal flow structure, complementing the vertical profiles measured by ADCP. [ABSTRACT FROM AUTHOR]

Ocean Surface Current Radar (OSCR) HF radar measurements of ocean waves and currents were made during the Shoaling Waves Experiment (SHOWEX) in the fall of 1999. During some periods, at some locations, good quality wave measurements were obtained. Limitations in the wave measurement capability due to OSCR hardware, deployment configuration, signal-to-noise ratio, and antenna sidelobes are identified and discussed. A short period of large currents in the presence of antenna pattern distortion is identified as the source of the main errors in the wave measurements. [ABSTRACT FROM AUTHOR]

Ocean prediction systems rely on an array of assumptions to optimize their data assimilation schemes. Many of these remain untested, especially at smaller scales, because sufficiently dense observations are very rare. A set of 295 drifters deployed in July 2012 in the north-eastern Gulf of Mexico provides a unique opportunity to test these systems down to scales previously unobtainable. In this study, background error covariance assumptions in the 3DVar assimilation process are perturbed to understand the effect on the solution relative to the withheld dense drifter data. Results show that the amplitude of the background error covariance is an important factor as expected, and a proposed new formulation provides added skill. In addition, the background error covariance time correlation is important to allow satellite observations to affect the results over a period longer than one daily assimilation cycle. The results show the new background error covariance formulations provide more accurate placement of frontal positions, directions of currents and velocity magnitudes. These conclusions have implications for the implementation of 3DVar systems as well as the analysis interval of 4DVar systems. [ABSTRACT FROM AUTHOR]