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Near-surface ocean wind measurements are important for weather forecasting, determining surface transports, and estimating air-sea interactions; however, in-situ wind observations are often limited. Previous studies indicate that the equilibrium range of the surface gravity wave spectrum can be used to estimate surface wind velocity. This approach is tested using spectral wave measurements from the Coastal Data Information Program (CDIP) buoy array off Monterey, California. Quality controlled wind vectors inferred from wave spectra are statistically compared to measurements from a nearby National Data Buoy Center (NDBC) buoy, demonstrating strong agreement with the control observations with root mean square errors for speed and direction of 1.8 m/s for all wind speeds and 13.2° for wind speeds greater than 7 m/s. We expand this estimation method to account for biofouling, which causes high-frequency damping of the wave spectrum, and the effects of form factor, which impact the platform's dynamic response to high-frequency waves. The method produces wind-proxy measurements solely from wave spectra and wave-based drag parametrizations, making it useful for operational integration. This work demonstrates the ability to make robust wind velocity estimates using wave data from multiple sources, increasing the coverage of wind information over the coastal and open ocean. [ABSTRACT FROM AUTHOR]

Knowledge of the directional distribution of a wave field is crucial for a better understanding of complex air–sea interactions. However, the dynamic and unpredictable nature of ocean waves, combined with the limitations of existing measurement technologies and analysis techniques, makes it difficult to obtain precise directional information, leading to a poor understanding of this important quantity. This study investigates the potential use of a wavelet-based method applied to GPS buoy observations as an alternative approach to the conventional methods for estimating the directional distribution of ocean waves. The results indicate that the wavelet-based estimations are consistently good when compared to the framework of widely used parameterizations for the directional distribution. The wavelet-based method presents advantages in comparison with the conventional methods, including being purely data-driven and not requiring any assumptions about the shape of the distribution. In addition, it was found that the wave directional distribution is narrower at the spectral peak and broadens asymmetrically at higher and lower scales, particularly sharply for frequencies below the peak. The directional spreading appears to be independent of the wave age across the entire range of frequencies, implying that the angular width of the directional spectrum is primarily controlled by nonlinear wave–wave interactions rather than by wind forcing. These results support the use of the wavelet-based method as a practical alternative for the estimation of the wave directional distribution. In addition, this study highlights the need for continued innovation in the field of ocean wave measuring technologies and analysis techniques to improve our understanding of air–sea interactions. Significance Statement: This study presents a wavelet-based technique for obtaining the directional distribution of ocean waves applied to GPS buoy. This method serves as an alternative to conventional methods and is relatively easy to implement, making it a practical option for researchers and engineers. The study was conducted in a highly energetic environment characterized by high wind speeds and large waves, providing a valuable dataset for understanding the dynamics of marine environment in extreme conditions. This research has implications for improving our understanding of directional characteristics of ocean waves, which is crucial for navigation, offshore engineering, weather forecasting, and coastal hazard mitigation. This study also highlights the challenges associated with understanding wave directionality and emphasizes a need for further observations. [ABSTRACT FROM AUTHOR]

Peak periods estimated from finite-resolution frequency spectra are necessarily discrete. For wind-generated surface gravity waves, conflicting considerations of robust (quasi)-stationary statistics, and high spectral resolution, combined with the inverse relation between frequency and period, this typically implies that swell periods (above 10 s) are resolved at best at O (1) s intervals. Here, we consider a method to improve peak period estimates for finite-resolution spectra. Specifically, we propose to define the peak period based on continuous spectra derived from a spline-based interpolation of the discretely sampled monotone cumulative distribution function. The method may directly be applied to existing discrete spectra—the original time-domain data (which may not be available) are not required. We compare reconstructed spectra and derived peak periods to parametric shapes and field data. Peak estimates are markedly improved, allowing for better tracking of, e.g., swells. The proposed method also marginally improves spectral levels and shape for a given discretely sampled estimate. [ABSTRACT FROM AUTHOR]

Wave spectra and directional moment measurements are of scientific and engineering interest and are routinely estimated with wave buoys. Recently, both fixed-location and uncrewed aircraft system (UAS)-mounted lidar have estimated surfzone wave spectra. However, nearshore wave statistics seaward of the surfzone have not been measured with lidar due to low return number, and nearshore directional moments have not been measured at all. We use a multibeam scanning lidar mounted on a gasoline-powered UAS to estimate wave spectra, wave slope spectra, and directional moments on the inner shelf in ≈10-m water depth from an 11-min hover and compare to a collocated wave buoy. Lidar returns within circular sampling regions with varying radius R are fit to a plane and a 2D parabola, providing sea surface and slope time series. Wave spectra across the sea–swell (0.04–0.4 Hz) band are robustly estimated for R ≥ 0.8 m. Estimating slope spectra is more challenging. Large R works well in the swell band, and smaller R works well at higher frequencies, in good agreement with a wave buoy inferred slope spectrum. Directional Fourier coefficients, estimated from wave and slope spectra and cross-spectra, are compared to a wave buoy in the sea–swell band. Larger R and the 2D parabola-fit yield better comparison to the wave buoy. Mean wave angles and directional spreads, functions of the directional Fourier coefficients, are well reproduced at R = 2.4 m and the 2D parabola-fit, within the uncertainties of the wave buoy. The internal consistency of the UAS-lidar-derived results and their good comparison to the Spotter wave buoy demonstrate the effectiveness of this tool for estimating wave statistics. Significance Statement: Previously fixed-location or hovering lidar has been used to estimate wave spectra in the surf and swash zone where lidar returns are high due to the reflectance of foam. We present a methodology to accurately estimate wave spectra and directional properties on the inner shelf where waves are not breaking using a hovering uncrewed aircraft system with a mounted lidar. The estimated wave spectra and directional statistics are compared well with a Spotter wave buoy, demonstrating the method's robustness. [ABSTRACT FROM AUTHOR]

Based on data collected from 14 buoys in the Gulf Stream, this study examines how hourly air–sea turbulent heat fluxes vary on subdaily time scales under different boundary layer stability conditions. The annual mean magnitudes of the subdaily variations in latent and sensible heat fluxes at all stations are 40 and 15 W m−2, respectively. Under near-neutral conditions, hourly fluctuations in air–sea humidity and temperature differences are the major drivers of subdaily variations in latent and sensible heat fluxes, respectively. When the boundary layer is stable, on the other hand, wind anomalies play a dominant role in shaping the subdaily variations in latent and sensible heat fluxes. In the context of a convectively unstable boundary layer, wind anomalies exert a strong controlling influence on subdaily variations in latent heat fluxes, whereas subdaily variations in sensible heat fluxes are equally determined by air–sea temperature difference and wind anomalies. The relative contributions by all physical quantities that affect subdaily variations in turbulent heat fluxes are further documented. For near-neutral and unstable boundary layers, the subdaily contributions are O(2) and O(1) W m−2 for latent and sensible heat fluxes, respectively, and they are less than O(1) W m−2 for turbulent heat fluxes under stable conditions. Significance Statement: High-resolution buoy observations of air–sea variables in the Gulf Stream provide the opportunity to investigate the physical factors that determine subdaily variations in air–sea turbulent heat fluxes. This study addresses two key points. First, the observed subdaily amplitudes of heat fluxes are related to various processes, including wind fields and air–sea thermal effect differences. Second, the global sea surface heat budget is known to not be in near-zero balance and it ranges from several to tens of watts per square meter. Therefore, consideration of the relatively strong influence of subdaily variability in air–sea turbulent heat fluxes could provide a new strategy for solving the global heat budget balance problem. [ABSTRACT FROM AUTHOR]

Surface convergence in the ocean is associated with accumulation of buoyant pollutants as well as with vertical transport that is important to biological activity. Such surface convergence regions are marked by a high dilation rate, i.e., the finite time Lagrangian average divergence. Dilation-rate observations are most easily derived from the change of the area encompassed by a drifter swarm over time. The technological advances that have enabled the deployment of large numbers of drifters in a single experiment have raised new questions about optimal deployment strategies for extracting dilation-rate information with acceptable accuracy and as much spatial coverage as possible. Using a submesoscale-resolving operational model of the Mediterranean Sea, we analyze synthetic trajectories of drifter polygons to evaluate the impact of the number of drifters and their initial separation on the accuracy of the resulting dilation-rate estimates. The results confirm that estimates improve as the circumradius of the polygon decreases and as more drifters are added, but with only a marginal improvement for drifter polygons containing more than four drifters. Moreover, GPS positions obtained from drifters in the ocean are subject to uncertainty on the order of 2–50 m, and when this uncertainty is taken into account, an optimal circumradius can be identified that balances uncertainty from position measurements with that from the area approximations. Significance Statement: Locating regions of convergence over a finite time interval on the ocean surface can help in pollution mitigation, locating biological hotspots, and even search-and-rescue operations. Finite time convergence can be quantified using the dilation rate, but it is hard to measure in the ocean. Hence, we present a method to estimate the dilation rate using trajectories of drifters, which are instruments widely used by oceanographers during field experiments to understand the local flow features. We show that even though the drifter-based dilation rates are prone to error as a result of a finite number of drifters and limited GPS accuracy, the estimates locate around 90% of the strongest convergent features in our model. [ABSTRACT FROM AUTHOR]

In the equilibrium range of the wave spectrum's high-frequency tail, energy levels are proportional to the wind friction velocity. As a consequence of this intrinsic coupling, spectral tail energy levels can be used as proxy observations of surface stress and wind speed when direct observations are unavailable. Proxy observations from drifting wave-buoy networks can therefore augment existing remote sensing capabilities by providing long dwell observations of surface winds. Here we consider the skill of proxy wind estimates obtained from observations recorded by the globally distributed Sofar Spotter network (observations from 2021 to 2022) when compared with collocated observations derived from satellites (yielding over 20 000 collocations) and reanalysis data. We consider physics-motivated parameterizations (based on frequency−4 universal tail assumption), inverse modeling (estimate wind speed from spectral energy balance), and a data-driven approach (artificial neural network) as potential methods. Evaluation of trained/calibrated models on unseen test data reveals comparable performance across methods with generally of order 1 m s−1 root-mean-square difference with satellite observations. [ABSTRACT FROM AUTHOR]

The Argo array provides nearly 4000 temperature and salinity profiles of the top 2000 m of the ocean every 10 days. Still, Argo floats will never be able to measure the ocean at all times, everywhere. Optimized Argo float distributions should match the spatial and temporal variability of the many societally important ocean features that they observe. Determining these distributions is challenging because float advection is difficult to predict. Using no external models, transition matrices based on existing Argo trajectories provide statistical inferences about Argo float motion. We use the 24 years of Argo locations to construct an optimal transition matrix that minimizes estimation bias and uncertainty. The optimal array is determined to have a 2° x 2° spatial resolution with a 90-day time step. We then use the transition matrix to predict the probability of future float locations of the core Argo array, the Global Biogeochemical Array, and the Southern Ocean Carbon and Climate Observations and Modeling (SOCCOM) array. A comparison of transition matrices derived from floats using Argos system and Iridium communication methods shows the impact of surface displacements, which is most apparent near the equator. Additionally, we demonstrate the utility of transition matrices for validating models by comparing the matrix derived from Argo floats with that derived from a particle release experiment in the Southern Ocean State Estimate (SOSE). [ABSTRACT FROM AUTHOR]

This study presents observational findings of air–sea turbulent heat flux anomalies during the onset of the South China Sea summer monsoon (SCSSM) in 2021 and explains the mechanism for high-resolution heat flux variations. Turbulent heat flux discrepancies are not uniform throughout the basin but indicate a significant regional disparity in the South China Sea (SCS), which also experiences evident year-to-year variability. Based on buoy- and cruise-based air–sea measurements, high-temporal-resolution (less than hourly) anomalies in the latent heat flux during the SCSSM burst are unexpectedly determined by sea–air humidity differences instead of wind effects under near-neutral and mixed marine atmospheric boundary layer (MABL) stability conditions. However, latent heat anomalies are mainly induced by wind speed under changing MABL conditions. The sensible heat flux is much weaker, with its anomalies dominated by sea–air temperature differences regardless of the boundary layer condition. The observational results are used to examine the discrepancies in turbulent heat fluxes and associated air–sea variables in reanalysis products. The comparisons indicate that latent and sensible heat fluxes in the reanalysis are overestimated by approximately 55 and 3 W m−2, respectively. These overestimations are mainly induced by higher estimates of sea–air humidity/temperature differences. The relative humidity is underestimated by approximately 4.2% in the two high-resolution reanalysis products. The higher SST (near-surface specific humidity) and lower air temperature (specific air humidity) eventually lead to higher estimates of sea–air humidity/temperature differences (1.75 g kg−1/0.25°C), which are the dominant factors controlling the variations in the air–sea turbulent heat fluxes. Significance Statement: Air–sea interactions are significant in predicting the onset of East Asian monsoon systems, including the SCSSM. During the SCSSM in 2021, four buoys and cruise observations are used to investigate anomalies in the latent and sensible heat fluxes. The physical mechanism of the variations in turbulent heat fluxes under different MABL stability conditions is explored in this study. The humidity and wind speed anomalies play roles under mixed boundary conditions in determining the high-resolution variations in latent heat fluxes. Based on these observational results, the heat fluxes and associated air–sea variables from reanalysis products are compared to identify the differences in the operational systems. These comparison results can help improve the reanalysis to obtain better monsoon predictions. [ABSTRACT FROM AUTHOR]

Accurate measurements of ocean waves underpin efficient offshore operations and optimal offshore structure design, helping to ensure the offshore industry can operate both safely and economically. Popular instruments used by the offshore industry are the Rosemount WaveRadar (Radar) and the Waverider Buoy. The Optech Laser has been used at some locations for specific studies. Recent reports indicate systematic differences of order 10% among the wave measurements made by these instruments. This paper examines the relative performance of these instruments based upon various time-domain comparisons, including results from a quality control (QC) procedure, capabilities of measuring the wave surface profile (skewness), and crest heights for varying wind sea and swell conditions. The QC check provides good-quality data that can be further investigated with an assurance of error-free data, suggesting that the Waverider produces the bestquality data with the lowest failure rate compared to the Laser and Radar. A significant number of theWaverider surface elevation records have negative skewness, particularly at higher sea states, affecting its crest height measurements, which are lower than those from the Laser and Radar. Additionally, the significant wave height (H1/3) estimates of the Radar are lower than the Laser and Waverider, but its zero-crossing wave periods (TZ), on average, are longer than the Laser and theWaverider. The significant heights (H1/3) of Laser and Waverider are in good agreement for all three datasets, but the Waverider's zero-crossing wave period (TZ) estimates are significantly longer than the Laser. [ABSTRACT FROM AUTHOR]

Accurate ocean wave measurements are needed for the safe design and operation of offshore facilities, but despite many ocean wave measurements, the accuracy of wave measurement systems remains an ongoing issue. Of paramount importance are measurements during extreme sea states. This paper examines wave measurements made with an Optech Laser (Laser), a Rosemount WaveRadar (Radar), and a Datawell Waverider buoy at North Rankin A (NRA) platform, Australia; Ekofisk, North Sea; and several South China Sea locations. We evaluate the relative performance of these instruments based upon various frequency domain comparisons, including comparisons of their 1D frequency spectra using spectrograms, spectral moments, high-frequency tail slopes, and significant wave heights derived from their wave spectra. A spectral relationship (transfer function) in terms of mean spectral ratio of the instruments is developed, which can be used for spectral calibration. On average, Laser and Waverider spectral estimates agree well at all sea states. However, at low wind speeds, the higher-frequency spectral levels of the Laser are relatively high and noisy compared with the other two instruments. Radar higher-frequency spectral estimates are relatively low compared to the other two instruments, particularly at lower sea states. In addition, the higher-frequency tail slopes of all three instruments vary between f−4 and f−5. However, at higher sea states, the Waverider tail slopes become steeper than f−5. The Radar produces the lowest significant wave heights (Hm0) compared to the Laser and Waverider, but its second-moment period (Tm02) estimates are longer than the Laser and Waverider. [ABSTRACT FROM AUTHOR]

Abstract: Wintertime surface ocean heat loss is the key process driving the formation of Subantarctic Mode Water (SAMW), but there are few direct observations of heat fluxes, particularly during winter. The Ocean Observatories Initiative (OOI) Southern Ocean mooring in the southeast Pacific Ocean and the Southern Ocean Flux Station (SOFS) in the southeast Indian Ocean provide the first concurrent, multiyear time series of air–sea fluxes in the Southern Ocean from two key SAMW formation regions. In this work we compare drivers of wintertime heat loss and SAMW formation by comparing air–sea fluxes and mixed layers at these two mooring locations. A gridded Argo product and the ERA5 reanalysis product provide temporal and spatial context for the mooring observations. Turbulent ocean heat loss is on average 1.5 times larger in the southeast Indian (SOFS) than in the southeast Pacific (OOI), with stronger extreme heat flux events in the southeast Indian leading to larger cumulative winter ocean heat loss. Turbulent heat loss events in the southeast Indian (SOFS) occur in two atmospheric regimes (cold air from the south or dry air circulating via the north), while heat loss events in the southeast Pacific (OOI) occur in a single atmospheric regime (cold air from the south). On interannual time scales, wintertime anomalies in net heat flux and mixed layer depth (MLD) are often correlated at the two sites, particularly when wintertime MLDs are anomalously deep. This relationship is part of a larger basin-scale zonal dipole in heat flux and MLD anomalies present in both the Indian and Pacific basins, associated with anomalous meridional atmospheric circulation.

Around Hopen Island, the satellite images and experiments with drifting buoys describe the movement of the drifting ice and depict tidally generated trapped motion. An analytical solution is applied to investigate the trapping phenomenon. A general solution is achieved by the superposition of the incident and reflected (scattered) waves for an elliptically shaped island above the critical latitude. The incident wave simulates the tidal wave propagation toward the island and its prominent feature, an amphidromic point located to the southeast from Hopen Island. The analytical solution for the reflected wave is constructed in elliptic coordinates. Tide amplitudes and cophase lines are analyzed in the island's vicinity and compared to observations and numerical model results. A simulated drift of Lagrangian water particles constructed with the help of analytical solutions reproduces well the observed clockwise trapped motion of the drifting buoy near Hopen Island. Since the resonance may amplify the semidiurnal incident tide, we have also investigated the natural modes of water oscillations near the island. While this paper focuses on the details of the model used at the specific site of Hopen Island, a similar trapping analysis can be applied to circular or elliptic islands that have a small scale relative to the barotropic Rossby deformation radius. Significance Statement: This study aims to understand how the semidiurnal tide propagates and generates strong currents near Hopen Island in the Barents Sea. The trapping of the semidiurnal (M2) tide around Hopen Island leads to an organized dipole structure in sea level, which rotates clockwise. The dipole generates maximum amplitudes of water surface elevation and the strong current near the south and north tips of the island. The abrupt sea level change induced by the dipole sets up often violent currents, which, together with drifting ice, can be dangerous for navigation. The strong tidal currents generate permanent clockwise circulation around the islands, which is essential for biological life and waste disposal as material disposed of near the islands will be trapped for an extended time. Our investigation elucidates the role of dipoles in the local enhancement of tides around the islands. [ABSTRACT FROM AUTHOR]

This study presents observations of opposite fall‐to‐winter variations in the air‐sea latent heat fluxes (LHs) between the western boundary currents (WBCs) and coastal seas obtained using eight air–sea buoys in the Northern Hemisphere. Different from the WBCs, the wintertime LH along the coast is strangely reduced by approximately 60 Wm−2 compared to that in fall. The reduced sea–air humidity differences account for these opposite seasonal variations, although the sea–air temperature differences are enhanced, while the roles played by winds and the nonlinear effects are minor. The boundary layer stability also varies in terms of the air‐sea parameters from fall to winter. However, the conditions of the WBCs meet the traditional expectation: that is, the LH in winter is 60 Wm−2 higher than that in fall with near‐neutral/unstable boundary layer stability. Enhanced winds in winter determine the seasonal enhancement of the LH over the WBCs, indicating a specialized regional character. Plain Language Summary: Air‐sea turbulent heat fluxes are normally recognized to be stronger in winter due to higher sea–air thermal contrast and enhanced winds associated with cold air outbreaks. However, this study reports unexpectedly opposite fall‐to‐winter seasonal variations in the air–sea latent heat fluxes (LHs) between the western boundary currents (WBCs) and coastal seas observed using buoy observations. The LH along the coast adjacent to the WBCs is greatly reduced by 60 Wm−2 in winter, which is determined by the weakened sea–air humidity differences, although the sea–air temperature difference is enhanced. This indicates that the well‐mixed water in winter cannot support a relatively warm sea surface, as it can in fall. However, the conditions of the WBCs meet the traditional expectation. That is, the enhanced winds induce a higher LH in winter with a near‐neutral/unstable atmospheric boundary layer. Such findings remind us to focus on the optimized regional observation network when studying accurate high‐resolution air–sea heat fluxes and specialized land–atmosphere–ocean interactions along the coast. This may help provide a better understanding of regional cyclogenesis and marine meteorological forecasts, as well as the surface heat budget balance. Key Points: Opposite fall‐to‐winter variations in the air‐sea latent heat fluxes between the western boundary currents and coastal seas are shownThe reduced air‐sea humidity difference in winter dominates the weakened latent heat flux in the coastal regionsEnhanced wind speed in the boundary current systems induces a higher latent heat flux in winter with near‐neutral/unstable boundary layer [ABSTRACT FROM AUTHOR]

Global Navigation Satellite System Reflectometry (GNSS-R)-based wind retrieval techniques use the global positioning system (GPS) signals scattered from the ocean surface in the forward direction, and can potentially work in all weather conditions. An overview of recent progress made in the Cyclone Global Navigation Satellite System (CYGNSS) level-2 surface wind products is given. To this end, four publicly released CYGNSS surface wind products—Science Data Record (SDR) v2.1, SDR v3.0, Climate Data Record (CDR) v1.1, and science wind speed product NOAA v1.1—are validated quantitatively against high-quality data from tropical buoy arrays. The latest released CYGNSS wind products (e.g., CDR v1.1, SDR v3.0, NOAA v1.1), as compared with these tropical buoy data, significantly outperform the SDR v2.1. Moreover, the uncertainty among these products is found to be less than 2 m s−1 root-mean-squared difference, meeting the NASA science mission level-1 uncertainty requirement for wind speeds below 20 m s−1. The quality of the CYGNSS wind is further assessed under different precipitation conditions in low winds, and in large-scale convective regions. Results show that the presence of rain appears to cause a slightly positive wind speed bias in all CYGNSS data. Nonetheless, the outcomes are encouraging for the recently released CYGNSS wind products in general, and for CYGNSS data in regions with precipitating deep convection. The overall comparison indicates a significant improvement in wind speed quality and sample size when going from the older version to any of the newer datasets. [ABSTRACT FROM AUTHOR]

The role of the modulational instability for rogue wave generation in the ocean is still under debate. We investigated a continuous dataset, consisting of buoy and radar wave elevation data of different frequency resolutions, from eight measurement stations in the southern North Sea. For periods with rogue waves, we evaluated the presence of conditions for the modulational instability to work, that is, a narrow-banded wave spectrum in both frequency and angular direction. We found rogue waves that exceed twice the significant wave height indeed occur at slightly lower frequency bandwidths than usual. For rogue waves that are defined only by high crests, this was, however, not the case. The results were dependent on the measurement frequency. The directional spreading of the buoy spectra yielded no information on the presence of a rogue wave. In general, all spectra estimated from the dataset were found to be broad in frequency and angular direction, while the Benjamin–Feir index yielded no indication on a high nonlinearity of the sea states. These are unfavorable conditions for the evolution of a rogue wave through modulational instability. We conclude that the modulational instability did not play a substantial role in the formation of the rogue waves identified in our dataset from the southern North Sea. Significance Statement: This work investigates whether rogue waves measured in the southern North Sea may have been generated by a modulational instability. The latter is a nonlinear mechanism of wave energy focusing that has been proven mathematically and confirmed in laboratory experiments. However, it is still unclear whether this mechanism is responsible for rogue wave generation under realistic ocean conditions. The modulational instability primarily arises when waves have similar frequencies and directions. In our data, these conditions were not satisfied. This finding leads to the insight that the modulational instability is not the most probable mechanism to generate rogue waves in our dataset. [ABSTRACT FROM AUTHOR]

Under the Atmospheric River Reconnaissance (AR Recon) Program, ocean drifting buoys (drifters) that provide surface pressure observations were deployed in the northeastern Pacific Ocean to improve forecasts of U.S. West Coast high-impact weather. We examine the impacts of both AR Recon and non-AR Recon drifter observations in the U.S. Navy's global atmospheric data assimilation (DA) and forecast system using data-denial experiments and forecast sensitivity observation impact (FSOI) analysis, which estimates the impact of each observation on the 24-h global forecast error total energy. Considering all drifters in the eastern North Pacific for the 2020 AR Recon season, FSOI indicates that most of the beneficial impacts come from observations in the lowest quartile of observed surface pressure values, particularly those taken late in the DA window. Observations in the upper quartile have near-neutral impacts on average and are slightly nonbeneficial when taken late in the DA window. This may occur because the DA configuration used here does not account for model biases, and innovation statistics show that the forecast model has a low pressure bias at high pressures. Case studies and other analyses indicate large beneficial impacts coming from observations in regions with large surface pressure gradients and integrated vapor transport, such as fronts and ARs. Data-denial experiments indicate that the assimilation of AR Recon drifter observations results in a better-constrained analysis at nearby non-AR Recon drifter locations and counteracts the NAVGEM pressure bias. Assimilating the AR Recon drifter observations improves 72- and 96-h Northern Hemisphere forecasts of winds in the lower and middle troposphere, and geopotential height in the lower, middle, and upper troposphere. Significance Statement: The purpose of this study is to understand how observations of atmospheric pressure at the ocean surface provided by drifting buoys impact weather forecasts. Some of these drifting buoys were deployed under a program to study atmospheric rivers (ARs) to improve forecasts of high-impact weather on the West Coast. We find that these observations are most effective at reducing forecast errors when taken in regions near fronts and cyclones. The additional drifting buoys deployed under the AR Reconnaissance project reduce forecast errors at 72 and 96 h over North America and the Northern Hemisphere. These results are important because they illustrate the potential for improving forecasts by increasing the number of drifting buoy surface pressure observations over the world oceans. [ABSTRACT FROM AUTHOR]

This paper describes the new International Comprehensive Ocean–Atmosphere Data Set (ICOADS) near-real-time (NRT) release (R3.0.2), with greatly enhanced completeness over the previous version (R3.0.1). R3.0.1 had been operationally produced monthly from January 2015 onward, with input data from the World Meteorological Organization (WMO) Global Telecommunication Systems (GTS) transmissions in the Traditional Alphanumeric Codes (TAC) format. Since the release of R3.0.1, however, many observing platforms have changed, or are in the process of transitioning, to the Binary Universal Form for Representation of Meteorological Data (BUFR) format. R3.0.2 combines input data from both BUFR and TAC formats. In this paper, we describe input data sources; the BUFR decoding process for observations from drifting buoys, moored buoys, and ships; and the data quality control of the TAC and BUFR data streams. We also describe how the TAC and BUFR streams were merged to upgrade R3.0.1 into R3.0.2 with duplicates removed. Finally, we compare the number of reports and spatial coverage of essential climate variables (ECVs) between R3.0.1 and R3.0.2. ICOADS NRT R3.0.2 shows both quantitative and qualitative gains from the inclusion of BUFR reports. The number of observations in R3.0.2 increased by nearly 1 million reports per month, and the coverage of buoy and ship sea surface temperatures (SSTs) on monthly 2° × 2° grids increased by 20%. The number of reported ECVs also increased in R3.0.2. For example, observations of SST and sea level pressure (SLP) increased by around 30% and 20%, respectively, as compared to R3.0.1, and salinity is a new addition to the ICOADS NRT product in R3.0.2. Significance Statement: The International Comprehensive Ocean–Atmosphere Data Set (ICOADS) is the largest collection of surface marine observations spanning from 1662 to the present. A new version, ICOADS near-real-time 3.0.2, includes data transmitted in the Binary Universal Form for Representation of Meteorological Data (BUFR) format, in combination with Traditional Alphanumeric Codes (TAC) data. Many of the organizations that report observations in near–real time have moved to BUFR, so this update brings ICOADS into alignment with collections and archives of these international data distributions. By including the BUFR reports, the number of observations in the upgraded version of ICOADS increased by nearly one million reports per month and spatial coverage of buoy and ship SSTs increased by 20% over the previous version. [ABSTRACT FROM AUTHOR]

Daily rainfall accumulation estimates have been derived from 1-min volume data collected via self-syphon rain gauges deployed in the Tropical Atmosphere–Ocean (TAO) array of oceanographic buoys. The underlying high-resolution volume data were obtained directly from the Global Tropical Moored Buoy Array (GTMBA) Project Office of NOAA/Pacific Marine Environmental Laboratory. The derived accumulations have been incorporated into the Pacific Rainfall (PACRAIN) database as estimated daily values to augment existing sea level oceanic rainfall records gathered using traditional rain gauges. They have also been included in the PACRAIN historical, monthly gridded rainfall product. The methodology presented, which employs differencing of least squares–regressed sensor levels about 0000 UTC and rain gauge syphon events, is shown to offer improved error characteristics over the methodology used to compute previously published GTMBA rain rates. In particular, the PACRAIN method yields larger coefficients of determination and smaller standard errors than the duplicated GTMBA method when applied to synthetic rainfall data with noise magnitude and decorrelation times encompassing those observed in the real 1-min data. These results are shown to be consistent with mathematical expectations. Sources of instrument and catchment errors, as well as evaporation, are discussed in the context of their potential effects on accumulation estimates for periods of a day or longer. Significance Statement: In this paper, we describe the derivation of daily rainfall amounts from raw rain gauge data obtained from buoy-mounted rain gauges. These new accumulation estimates expand the store of rainfall estimates from locations approximating the open-ocean conditions of the tropical Pacific Ocean. The derivation technique we describe exhibits better performance than the method used to generate previously published estimates using the same dataset. [ABSTRACT FROM AUTHOR]

Prediction of rapid intensification in tropical cyclones prior to landfall is a major societal issue. While air–sea interactions are clearly linked to storm intensity, the connections between the underlying thermal conditions over continental shelves and rapid intensification are limited. Here, an exceptional set of in situ and satellite data are used to identify spatial heterogeneity in sea surface temperatures across the inner core of Hurricane Sally (2020), a storm that rapidly intensified over the shelf. A leftward shift in the region of maximum cooling was observed as the hurricane transited from the open gulf to the shelf. This shift was generated, in part, by the surface heat flux in conjunction with the along- and across-shelf transport of heat from storm-generated coastal circulation. The spatial differences in the sea surface temperatures were large enough to potentially influence rapid intensification processes suggesting that coastal thermal features need to be accounted for to improve storm forecasting as well as to better understand how climate change will modify interactions between tropical cyclones and the coastal ocean. Significance Statement: The connections between the underlying thermal energy in the ocean that powers tropical cyclones and rapid intensification of storms over continental shelves are limited. An exceptional set of data collected in the field as well as from space with satellites was used to identify spatial variations in sea surface temperatures across the inner core of Hurricane Sally (2020), a storm that rapidly intensified over the shelf. The spatial differences were due to the heat loss from the surface of the ocean as well as heat transport by shelf currents. The spatial differences were large enough to potentially influence how quickly storms can intensify, suggesting that coastal thermal features need to be accounted for to improve storm forecasting. [ABSTRACT FROM AUTHOR]

Abstract This study presents observations of opposite fall‐to‐winter variations in the air‐sea latent heat fluxes (LHs) between the western boundary currents (WBCs) and coastal seas obtained using eight air–sea buoys in the Northern Hemisphere. Different from the WBCs, the wintertime LH along the coast is strangely reduced by approximately 60 Wm−2 compared to that in fall. The reduced sea–air humidity differences account for these opposite seasonal variations, although the sea–air temperature differences are enhanced, while the roles played by winds and the nonlinear effects are minor. The boundary layer stability also varies in terms of the air‐sea parameters from fall to winter. However, the conditions of the WBCs meet the traditional expectation: that is, the LH in winter is 60 Wm−2 higher than that in fall with near‐neutral/unstable boundary layer stability. Enhanced winds in winter determine the seasonal enhancement of the LH over the WBCs, indicating a specialized regional character.

Horizontal velocity gradients of a flow field and the related kinematic properties (KPs) of divergence, vorticity, and strain rate can be estimated from dense drifter deployments, e.g., the spatiotemporal average divergence (and other KPs) over a triangular area defined by three drifters and over a given time interval can be computed from the initial and final areas of said triangle. Unfortunately, this computation can be subject to large errors, especially when the triangle shape is far from equilateral. Therefore, samples with small aspect ratios are generally discarded. Here we derive the thresholds on two shape metrics that optimize the balance between retention of good and removal of bad divergence estimates. The primary tool is a high-resolution regional ocean model simulation, where a baseline for the average divergence can be established, so that actual errors are available. A value of 0.2 for the scaled aspect ratio Λ and a value of 0.86π for the largest interior angle θ are found to be equally effective thresholds, especially at scales of 5 km and below. While discarding samples with low Λ or high θ values necessarily biases the distribution of divergence estimates slightly toward positive values, this bias is small compared to (and in the opposite direction of) the Lagrangian sampling bias due to drifters preferably sampling convergence regions. Errors due to position uncertainty are suppressed by the shape-based subsampling. The subsampling also improves the identification of the areas of extreme divergence or convergence. An application to an observational dataset demonstrates that these model-derived thresholds can be effectively used on actual drifter data. Significance Statement: Divergence in the ocean indicates how fast floating objects in the ocean spread apart, while convergence (negative divergence) captures how fast they accumulate. Measuring divergence in the ocean, however, remains challenging. One method is to estimate divergence from the trajectories of drifting buoys. This study provides guidance under what circumstances these estimates should be discarded because they are too likely to have large errors. The criteria proposed here are less stringent than some of the ad hoc criteria previously used. This will allow users to retain more of their estimates. We consider how position uncertainty affects the reliability of the divergence estimates. An observational dataset collected in the Mediterranean is used to illustrate an application of these reliability criteria. [ABSTRACT FROM AUTHOR]

The lack of in situ observations and the uncertainties of the drag coefficient at high wind speeds result in limited understanding of heat flux through the air-sea interface and thus inaccurate estimation of typhoon intensity in numerical models. In this study, buoy observations and numerical simulations from an air-sea coupled model are used to assess the surface heat flux changes and impacts of the drag coefficient parameterization schemes on its simulations during the passage of Typhoon Kalmaegi (2014). Three drag coefficient schemes, which make the drag coefficient increase, level off, and decrease, respectively, are considered. The air-sea coupled model captured both trajectory and intensity changes better than the atmosphere-only model, though with relatively weaker sea surface cooling (SSC) compared to that captured by buoy observations, which led to relatively higher heat flux and thus a stronger typhoon. Different from previous studies, for a moderate typhoon, the coupled simulation with the increasing drag coefficient scheme outputted an intensity most consistent with the observation because of the strongest SSC, reasonable ratio of latent and sensible heat exchange coefficients, and an obvious reduction in the overestimated surface heat flux among all experiments. Results from sensitivity experiments showed that surface heat flux was significantly determined by the drag coefficient-induced SSC rather than the resulting wind speed changes. Only when SSC differs indistinctively (<0.4°C) between the coupled simulations, heat flux showed a weak positive correlation with the drag coefficient-impacted 10-m wind speed. The drag coefficient also played an important role in decreasing heat flux even a long time after the passage of Kalmaegi because of the continuous upwelling from deeper ocean layers driven by the impacted momentum flux through the air-sea interface. [ABSTRACT FROM AUTHOR]

An apparent giant wave event having a maximum trough-to-crest height of 21 m and a maximum zero-upcrossing period of 27 s was recorded by a wave buoy at a nearshore location off the southwestern coast of Australia. It appears as a group of waves that are significantly larger both in height and in period than the waves preceding and following them. This paper reports a multifaceted analysis into the plausibility of the event. We first examine the statistics of the event in relation to the rest of the record, where we look at quantities such as maximum-to-significant wave height ratios, ordered crest–trough statistics, and average wave profiles. We then investigate the kinematics of the buoy, where we look at the relationship between the horizontal and vertical displacements of the buoy, and also attempt to numerically reconstruct the giant event using Boussinesq and nonlinear shallow water equations. Additional analyses are performed on other sea states where at least one of the buoy's accelerometers reached its maximum limit. Our analysis reveals incompatibilities of the event with known behavior of real waves, leading us to conclude that it was not a real wave event. Wave events similar to the one reported in our study have been reported elsewhere and have sometimes been accepted as real occurrences. Our methods of forensically analyzing the giant wave event should be potentially useful for identifying false rogue wave events in these cases. [ABSTRACT FROM AUTHOR]

This paper describes a remotely monitored buoy that, when deployed in open water prior to freeze up, permits scientists to monitor not only temperature with depth, and hence freeze up and sea ice thickness, but also the progression of sea ice development—e.g., the extent of cover at a given depth as it grows (solid fraction), the brine volume of the ice, and the salinity of the water just below, which is driven by brine expulsion. Microstructure and In situ Salinity and Temperature (MIST) buoys use sensor "ladders" that, in our prototypes, extend to 88 cm below the surface. We collected hourly measurements of surface air temperature and water temperature and electrical impedance every 3 cm to track the seasonal progression of sea ice growth in Elson Lagoon (Utqiaġvik, Alaska) over the 2017/18 ice growth season. The MIST buoy has the potential to collect detailed sea ice microstructural information over time and help scientists monitor all parts of the growth/melt cycle, including not only the freezing process but the effects of meteorological changes, changing snow cover, the interaction of meltwater, and drainage. Significance Statement: There is a need to better understand how an increasing influx of freshwater, one part of a changing Arctic climate, will affect the development of sea ice. Current instruments can provide information on the growth rate, extent, and thickness of sea ice, but not direct observations of the structure of the ice during freeze up, something that is tied to salinity and local air and water temperature. A first deployment in Elson Lagoon in Utqiaġvik, Alaska, showed promising results; we observed fluctuations in ice temperatures in response to brief warmings in air temperature that resulted in changes in the conductivity, liquid fraction, and brine volume fraction within the ice. [ABSTRACT FROM AUTHOR]

The Marine Institute of Ireland operates a network of weather buoys around Ireland. A wave of 32.3 m height (crest–trough) was recorded by one of these buoys, the M6 buoy, off the coast of Ireland in October 2020. In this paper, the technological evolution of this network is explored, with a particular emphasis on this extremely high wave. Raw data and bulk parameters collected during the event are presented, and the wider met-ocean context is outlined. In addition, wave data across the buoy deployment period from dual wave sensors installed on the buoy are analysed. Differences in calculation methods are discussed, rogue incidence rates are calculated, and the sensors are found to be generally in good agreement for key sea state parameters. Considerations specific to this network of buoys are described, including recent advances in technology that may affect continuity of historic records. Wave data from the buoys are found to be robust; the importance of keeping technological changes in mind and using the full raw dataset for analysis purposes are highlighted. [ABSTRACT FROM AUTHOR]

A yearlong wind and wave dataset derived from a cost-effective GPS wave buoy (Spotter) is compared to waves obtained from an accelerometer wave buoy (Datawell) and winds obtained from a collocated meteorological buoy. Overall, there was a strong correlation in bulk wave parameters obtained from the Spotter buoy and the Datawell buoy (RMSE of 0.06 m, 0.27 s, and 21.89° for significant wave height, mean wave period, and peak wave direction, respectively). Similarly, the bulk characteristics compared well when separating the directional wave spectra into sea and swell components with more scatter in mean wave periods for lower frequencies. Measurements of mean directional spread from the Spotter buoy were 7.51° larger than the Datawell, spreading more wave energy across different directions outside the peak direction. Additional analysis indicates that the increased directional spreading arises from a bias in the a1 and b1 spectral moments. Using the equilibrium frequency range of the wave energy spectrum, the Spotter buoy can derive wind speed and direction. This study found the Spotter buoy can report wind speed and direction with reasonable accuracy but underestimates wind speeds less than 4 m/s and greater than 8 m/s and was less accurate reporting wind directions oriented offshore. A comparison with a Spotter buoy in deeper water revealed the Spotter buoy further offshore was most accurate in reporting wind directions indicating this proxy-based measurement of wind speed and wind direction may be significantly influenced by fetch and local geography (e.g., large-scale cuspate coastlines).

This study uses the ECMWF ERA5 reanalysis and observationally constrained top-of-the-atmosphere radiative fluxes to infer net surface energy fluxes covering 1985–2018, which can be further adjusted to match the observed mean land heat uptake. Various diagnostics are applied to provide error estimates of inferred fluxes on different spatial scales. For this purpose, adjusted as well as unadjusted inferred surface fluxes are compared with other commonly used flux products. On a regional scale, the oceanic energy budget of the North Atlantic between the RAPID array at 26.5°N and moorings located farther north (e.g., at the Greenland–Scotland Ridge) is evaluated. On the station scale, a comprehensive comparison of inferred and buoy-based fluxes is presented. Results indicate that global land and ocean averages of unadjusted inferred surface fluxes agree with the observed heat uptake to within 1 W m−2, while satellite-derived and model-based fluxes show large global mean biases. Furthermore, the oceanic energy budget of the North Atlantic is closed to within 2.7 (−0.2) W m−2 for the period 2005–09 when unadjusted (adjusted) inferred surface fluxes are employed. Indirect estimates of the 2004–16 mean oceanic heat transport at 26.5°N are 1.09 PW (1.17 PW with adjusted fluxes), which agrees well with observed RAPID transports. On the station scale, inferred fluxes exhibit a mean bias of −20.1 W m−2 when using buoy-based fluxes as reference, which confirms expectations that biases increase from global to local scales. However, buoy-based fluxes as reference are debatable, and are likely positively biased, suggesting that the station-scale bias of inferred fluxes is more likely on the order of −10 W m−2. [ABSTRACT FROM AUTHOR]

Recently introduced in oceanography to interpret the near-surface circulation, transition path theory (TPT) is a methodology that rigorously characterizes ensembles of trajectory pieces flowing out from a source last and into a target next, i.e., those that most productively contribute to transport. Here we use TPT to frame, in a statistically more robust fashion than earlier analysis, equatorward routes of North Atlantic Deep Water (NADW) in the subpolar North Atlantic. TPT is applied on all available RAFOS and Argo floats in the area by means of a discretization of the Lagrangian dynamics described by their trajectories. By considering floats at different depths, we investigate transition paths of NADW in its upper (UNADW) and lower (LNADW) layers. We find that the majority of UNADW transition paths sourced in the Labrador and southwestern Irminger Seas reach the western side of a target arranged zonally along the southern edge of the subpolar North Atlantic domain visited by the floats. This is accomplished in the form of a well-organized deep boundary current (DBC). LNADW transition paths sourced west of the Reykjanes Ridge reveal a similar pattern, while those sourced east of the ridge are found to hit the western side of the target via a DBC and also several other places along it in a less organized fashion, indicating southward flow along the eastern and western flanks of the Mid-Atlantic Ridge. Naked-eye inspection of trajectories suggest generally more diffused equatorward NADW routes. A source-independent dynamical decomposition of the flow domain into analogous backward-time basins of attraction, beyond the reach of direct inspection of trajectories, reveals a much wider influence of the western side of the target for UNADW than for LNADW. For UNADW, the average expected duration of the pathways from the Labrador and Irminger Seas was found to be of 2–3 years. For LNADW, the duration was found to be influenced by the Reykjanes Ridge, being as long as 8 years from the western side of the ridge and of about 3 years on average from its eastern side. [ABSTRACT FROM AUTHOR]

Ocean wave measurements are of major importance for a number of applications including climate studies, ship routing, marine engineering, safety at sea, and coastal risk management. Depending on the scales and regions of interest, a variety of data sources may be considered (e.g., in situ data, Voluntary Observing Ship observations, altimeter records, numerical wave models), each one with its own characteristics in terms of sampling frequency, spatial coverage, accuracy, and cost. To combine multiple source of wave information (e.g., for data assimilation scheme in numerical weather prediction models), the error characteristics of each measurement system need to be defined. In this study, we use the triple collocation technique to estimate the random error variance of significant wave heights from a comprehensive collection of collocated in situ, altimeter, and model data. The in situ dataset is a selection of 122 platforms provided by the Copernicus Marine Service In Situ Thematic Center. The altimeter dataset is the ESA Sea State CCI version1 L2P product. The model dataset is the WW3-LOPS hindcast forced with bias-corrected ERA5 winds and an adjusted T475 parameterization of wave generation and dissipation. Compared to previous similar analyses, the extensive (∼250 000 entries) triple collocation dataset generated for this study provides some new insights on the error variability associated to differences in in situ platforms, satellite missions, sea state conditions, and seasonal variability. [ABSTRACT FROM AUTHOR]

We identify and characterize an error in the National Data Buoy Center (NDBC) wave records due to the sustained tilt of a buoy under high winds. We use a standard, operational 3-m aluminum discus buoy from NDBC with two wave systems, one gimballed, and the other strapped down but uncorrected. By comparing the two, we find that the most extreme significant wave heights are systematically overestimated. The overestimation is shown to be confined to a region around the peak frequency in the spectra: 0.05–0.15 Hz. Wave direction and directional spread are unaffected. A bias due to tilt error can be observed starting at winds of 10 m s−1 or wave heights of 4 m. The bias increases as a function of wind speed and wave height, i.e., the bias is +10% when winds are 20 m s−1. Very high waves and winds are relatively rare, so while the tilt error does not affect overall statistics and basic analyses it could potentially affect analysis sensitive to the extremes. A correction is derived for significant wave height, which is a quadratic function of wind speed. The correction is shown to reduce wave heights in uncorrected records, but is found inadequate for general use. There is evidence of tilt error at other NDBC stations, but the full extent of prevalence in the record is not known at this time. [ABSTRACT FROM AUTHOR]

Sea ice growth and consolidation play a significant role in heat and momentum exchange between the atmosphere and the ocean. However, few in situ observations of sea ice kinematics have been reported owing to difficulties of deployment of buoys in the marginal ice zone (MIZ). To investigate the characteristics of sea ice kinematics from MIZ to packed ice zone (PIZ), eight drifting buoys designed by Taiyuan University of Technology were deployed in the open water at the ice edge of the Canadian Basin. Sea ice near the buoy constantly increased as the buoy drifted, and the kinematics of the buoy changed as the buoy was frozen into the ice. This process can be determined using sea ice concentration, sea skin temperature, and drift speed of buoy together. Sea ice concentration data showed that buoys entered the PIZ in mid-October as the ice grew and consolidated around the buoys, with high amplitude, high frequency buoy motions almost ceasing. Our results confirmed that good correlation coefficient in monthly scale between buoy drift and the wind only happened in the ice zone. The correlation coefficient between buoys and wind was below 0.3 while the buoys were in open water. As buoys entered the ice zone, the buoy speed was normally distributed at wind speeds above 6 m/s. The buoy drifted mainly to the right of the wind within 45° at wind speeds above 8 m/s. During further consolidation of the ice in MIZ, the direct forcing on the ice through winds will be lessened. The correlation coefficient value increased to 0.9 in November, and gradually decreased to 0.7 in April. [ABSTRACT FROM AUTHOR]

The importance of quantifying the accuracy in wave measurements is critical to not only understand the complexities of wind-generated waves, but imperative for the interpretation of implied accuracy of the prediction systems that use these data for verification and validation. As wave measurement systems have unique collection and processing attributes that result in large accuracy ranges, this work quantifies bias that may be introduced into wave models from the newly operational NOAA National Data Buoy Center (NDBC) 2.1-m hull. Data quality consistency between the legacy NDBC 3-m aluminum hulls and the new 2.1-m hull is compared to a relative reference, and provides a standardized methodology and graphical representation template for future intrameasurement evaluations. Statistical analyses and wave spectral comparisons confirm that the wave measurements reported from the NDBC 2.1-m hulls show an increased accuracy from previously collected NDBC 3-m hull wave data for significant wave height and average wave period, while retaining consistent accuracy for directional results, purporting that hull size does not impact NDBC directional data estimates. Spectrally, the NDBC 2.1-m hulls show an improved signal-to-noise ratio, allowing for increase in energy retention in the lower-frequency spectral range, with an improved high-frequency spectral accuracy above 0.25 Hz within the short seas and wind chop wave component regions. These improvements in both NDBC bulk and spectral data accuracy provide confidence for the wave community's use of NDBC wave data to drive wave model technologies, improvements, and validations. [ABSTRACT FROM AUTHOR]

Wave buoys are a popular choice for measuring sea surface waves, and there is also an increasing interest for wave information from ice-covered water bodies. Such measurements require cost-effective, easily deployable, and robust devices. We have developed LainePoiss (LP)—an ice-resistant and lightweight wave buoy. It calculates the surface elevation by double integrating the data from the inertial sensors of the microelectromechanical system (MEMS), and transmits wave parameters and spectra in real time over cellular or satellite networks. LP was validated through 1) sensor tests, 2) wave tank experiments, 3) a field validation against a Directional Waverider, 4) an intercomparison of several buoys in the field, and 5) field measurements in the Baltic Sea marginal ice zone. These extensive field and laboratory tests confirmed that LP performed well (e.g., the bias of Hm0 in the field was 0.01 m, with a correlation of 0.99 and a scatter index of 8%; the mean absolute deviation of mean wave direction was 7°). LP was also deployed with an unmanned aerial vehicle and we present our experience of such operations. One issue that requires further development is the presence of low-frequency artifacts caused by the dynamic noise of the gyroscope. For now, a correction method is presented to deal with the noise. Significance Statement: Operational wave buoys are large and therefore expensive and inconvenient to deploy. Many commercially available devices cannot measure short waves and are not tested in ice. Our purpose was to develop an affordable wave buoy that is lightweight, ice resistant, capable of measuring short waves, and also has a longer operating life than existing research buoys. The buoy is easily deployed with a small boat or even an industrial drone, thus reducing operating costs. The buoy is accurate, and captures waves that are too short for operational wave buoys. This is relevant for coastal planning in, e.g., archipelagos and narrow fjords. We measured waves in ice in the Baltic Sea, and are planning to extend these measurements to Antarctica. [ABSTRACT FROM AUTHOR]

The full fluxes and associated air-sea variables based on three months of operational buoy observations in the East China Sea (ECS) in summer 2020 were analyzed for the first time. The surface net heat flux (Qnet) was positive (139.7±77.7 W/m2) and was dominated by the combined effects of solar shortwave radiation (SW) and latent heat fluxes (LH). The mean heat flux components of 4 reanalysis datasets (NCEP2, MERRA-2, CFSR, and ERA5) and buoy data were compared to assess the mean ability of the modeling/reanalysis simulation. Among the four components of air-sea flux, SW was the best simulated, while LH was the worst simulated. The longwave radiation (LW) and LH values from reanalysis were higher than those from buoy data, especially LH. The high LH resulted in low Qnet. Furthermore, the 4 reanalysis datasets were compared with the buoy dataset. Among all flux products, the difference in radiation flux was the smallest, while that in the turbulent flux was the greatest. The observed variables related to turbulent flux were analyzed to help determine the cause of the flux discrepancies. High wind speeds were the main cause of this difference. Using the variables provided by the reanalysis data and the same bulk formulas of the Coupled Ocean-Atmospheric Response Experiment (COARE 3.0), we found that the recalculated sensible heat flux (SH) and LH were closer to the observed heat fluxes than the direct model outputs. The significant differences between these methods could account for the discrepancies among different data. Among all air-sea flux products, the air-sea flux in ERA5 was closer to the in-situ observations than the other products. The comparison results of reanalysis data provide an important reference for more accurate studies of the summer heat flux in the ECS at the synoptic and climatic scales. [ABSTRACT FROM AUTHOR]

The Coastal Land–Air–Sea Interaction (CLASI) project aims to develop new "coast-aware" atmospheric boundary and surface layer parameterizations that represent the complex land–sea transition region through innovative observational and numerical modeling studies. The CLASI field effort involves an extensive array of more than 40 land- and ocean-based moorings and towers deployed within varying coastal domains, including sandy, rocky, urban, and mountainous shorelines. Eight Air–Sea Interaction Spar (ASIS) buoys are positioned within the coastal and nearshore zone, the largest and most concentrated deployment of this unique, established measurement platform. Additionally, an array of novel nearshore buoys and a network of land-based surface flux towers are complemented by spatial sampling from aircraft, shore-based radars, drones, and satellites. CLASI also incorporates unique electromagnetic wave (EM) propagation measurements using a coherent array, drone receiver, and a marine radar to understand evaporation duct variability in the coastal zone. The goal of CLASI is to provide a rich dataset for validation of coupled, data assimilating large-eddy simulations (LES) and the Navy's Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS). CLASI observes four distinct coastal regimes within Monterey Bay, California (MB). By coordinating observations with COAMPS and LES simulations, the CLASI efforts will result in enhanced understanding of coastal physical processes and their representation in numerical weather prediction (NWP) models tailored to the coastal transition region. CLASI will also render a rich dataset for model evaluation and testing in support of future improvements to operational forecast models. [ABSTRACT FROM AUTHOR]

The evolution of the tropical cyclone boundary layer (TCBL) wind field before landfall is examined in this study. As noted in previous studies, a typical TCBL wind structure over the ocean features a supergradient boundary layer jet to the left of motion and Earth-relative maximum winds to the right. However, the detailed response of the wind field to frictional convergence at the coastline is less well known. Here, idealized numerical simulations reveal an increase in the offshore radial and vertical velocities beginning once the TC is roughly 200 km offshore. This increase in the radial velocity is attributed to the sudden decrease in frictional stress once the highly agradient flow crosses the offshore coastline. Enhanced advection of angular momentum by the secondary circulation forces a strengthening of the supergradient jet near the top of the TCBL. Sensitivity experiments reveal that the coastal roughness discontinuity dominates the friction asymmetry due to motion. Additionally, increasing the inland roughness through increasing the aerodynamic roughness length enhances the observed asymmetries. Last, a brief analysis of in situ surface wind data collected during the landfall of three Gulf of Mexico hurricanes is provided and compared to the idealized simulations. Despite the limited in situ data, the observations generally support the simulations. The results here imply that assumptions about the TCBL wind field based on observations from over horizontally homogeneous surface types—which have been well documented by previous studies—are inappropriate for use near strong frictional heterogeneity. [ABSTRACT FROM AUTHOR]

The inception of a moored buoy network in the northern Indian Ocean in 1997 paved the way for systematic collection of long-term time series observations of meteorological and oceanographic parameters. This buoy network was revamped in 2011 with Ocean Moored buoy Network for north Indian Ocean (OMNI) buoys fitted with additional sensors to better quantify the air–sea fluxes. An intercomparison of OMNI buoy measurements with the nearby Woods Hole Oceanographic Institution (WHOI) mooring during the year 2015 revealed an overestimation of downwelling longwave radiation (LWR↓). Analysis of the OMNI and WHOI radiation sensors at a test station at National Institute of Ocean Technology (NIOT) during 2019 revealed that the accurate and stable amplification of the thermopile voltage records along with the customized datalogger in the WHOI system results in better estimations of LWR↓. The offset in NIOT measured LWR↓ is estimated first by segregating the LWR↓ during clear-sky conditions identified using the downwelling shortwave radiation measurements from the same test station, and second, finding the offset by taking the difference with expected theoretical clear-sky LWR↓. The corrected LWR↓ exhibited good agreement with that of collocated WHOI measurements, with a correlation of 0.93. This method is applied to the OMNI field measurements and again compared with the nearby WHOI mooring measurements, exhibiting a better correlation of 0.95. This work has led to the revamping of radiation measurements in OMNI buoys and provides a reliable method to correct past measurements and improve estimation of air–sea fluxes in the Indian Ocean. Significance Statement: Downwelling longwave radiation (LWR↓) is an important climate variable for calculating air–sea heat exchange and quantifying Earth's energy budget. An intercomparison of LWR↓ measurements between ocean observing platforms in the north Indian Ocean revealed a systematic offset in National Institute of Ocean Technology (NIOT) Ocean Moored buoy Network for north Indian Ocean (OMNI) buoys. The observed offset limited our capability to accurately estimate air–sea fluxes in the Indian Ocean. The sensor measurements were compared with a standard reference system, which revealed problems in thermopile amplifier as the root cause of the offset. This work led to the development of a reliable method to correct the offset in LWR↓ and revamping of radiation measurements in NIOT-OMNI buoys. The correction is being applied to the past measurements from 12 OMNI buoys over 8 years to improve the estimation of air–sea fluxes in the Indian Ocean. [ABSTRACT FROM AUTHOR]

Tropical convection regimes range from deep organized to shallow convective systems. Mesoscale processes such as cold pools within tropical convective systems can play a significant role in the evolution of convection over land and open ocean. Although cold pools are widely observed, their diurnal properties are not well understood over tropical oceans and land. The oceanic cold pool identification metric applied herein uses the gradient feature (GF) technique and is compared with diurnally resolved buoy-identified thermal cold pools. This study provides a first-ever diurnal climatology of GF number, area, and attributed TRMM 3B42 precipitation using a spaceborne scatterometer (RapidSCAT). Buoy data over the Pacific, Atlantic, and Indian Oceans have been used to validate and examine the RapidSCAT-identified diurnal cycle of GF number and precipitation. Buoy-observed cold pool duration, precipitation, temperature, and wind speed is analyzed to understand the in situ cold pool properties over tropical oceans. GF- and buoy-observed cold pool number and precipitation exhibits a similar bimodal diurnal variability with morning and afternoon maxima, thus establishing confidence in using GF as a proxy to observe cold pools over tropical oceans. The morning peak is attributed to cold pools associated with deep moist convection while the afternoon peak is related to shallower clouds in relatively drier environments resulting in smaller cold pools over global tropical oceans. Significance Statement: The global diurnal cycle of oceanic convectively generated cold pools (cool outflows from convection) is observed for the first time using the gradient feature method—revealing a bimodal distribution of cold pools organized by deep, organized convective systems in the early morning and afternoon cold pools predominated by shallower, more isolated convection. This analysis will provide a reference for high-resolution climate models to mimic in order to accurately represent key processes that organize convection and govern air–sea interactions. [ABSTRACT FROM AUTHOR]

In 1976, a pilot experiment, called first Equatorial Mooring (EQUA-1), tested an innovative technique for anchoring a taut-line surface mooring at 0°, 150°W where the water depth is 4.5 km. The 36-day deployment contained a wind recorder and fixed-level current meters at 50 and 100 m in the Equatorial Undercurrent (EUC). The following year, in a second pilot experiment, named EQUA-2, a similar mooring was deployed at 0°, 125°W for 99 days. EQUA-2, with current meters at 10, 50, 100, 150, and 200 m, recorded a surge in EUC transport during April 1977 when 3-day-averaged eastward current speeds at 50-m depth reached 2 m s−1. The associated eastward transport per unit meridional width over the 50–200-m layer was 190 m2 s−1. Based on observations recorded in April 1980, the EQUA-2 pulse would correspond to a total EUC transport surge of about 38 Sv (1 Sv ≡ 106 m3 s−1) and would represent an equatorially trapped first-mode baroclinic Kelvin wave. This paper describes EQUA Project observations and why and how I created the high-risk-of-failure opportunity to record pioneering time series measurements at the equator. The enduring legacy of the EQUA Project is the sustained maintenance of in situ surface wind and upper-ocean current and temperature measurements at numerous sites in the equatorial oceans, starting in the Pacific to improve forecasts of the El Niño and La Niña phenomenon. For example, the 40-yr records of surface wind and upper-ocean current and temperature measurements at 0°, 110°W and 0°, 140°W are some of oceanography's longest time series recorded far from land. [ABSTRACT FROM AUTHOR]

An examination of the applicability and accuracy of the empirical wave inversion method in the presence of swell waves is presented. The ability of the method to invert Doppler spectra to wave directional spectra and bulk wave parameters is investigated using 1-month data from a 12-MHz Wellen Radar (WERA) high-frequency (HF) radar system and in situ data from a wave buoy. Three different swell inversion models are evaluated from Lipa et al. (LPM), from Wang et al. (WFG), and empirical (EMP), an empirical approach introduced in this study. The swell inversions were carried out using two different scenarios: 1) a single beam from a single radar site and two beams from a single radar site, and 2) two beams from two sites (a single beam per site) intersecting each other at the buoy location. The LPM method utilizing two beams from two different sites was found to provide the best estimations of swell parameters (swell height RMS error: 0.24 m) and showed a good correlation with the partitioned swell in situ values. For the wind-wave inversion, the empirical method presented here is used with an empirical coefficient of 0.3, which seems to be suitable for universal application for all radar operating frequencies. The inverted swell parameters are used to create a swell spectrum that is combined with the inverted wind-wave spectrum to create a full directional wave spectrum. The wave inversion method presented in this study although empirical does not require calibration with in situ data and can be applied to any beam-forming system and operating frequency. [ABSTRACT FROM AUTHOR]

The NOAA Daily Optimum Interpolation Sea Surface Temperature dataset (DOISST) has recently been updated to v2.1 (January 2016–present). Its accuracy may impact the climate assessment, monitoring and prediction, and environment-related applications. Its performance, together with those of seven other well-known sea surface temperature (SST) products, is assessed by comparison with buoy and Argo observations in the global oceans on daily 0.25° × 0.25° resolution from January 2016 to June 2020. These seven SST products are NASA MUR25, GHRSST GMPE, BoM GAMSSA, UKMO OSTIA, NOAA GPB, ESA CCI, and CMC. Our assessments indicate that biases and root-mean-square difference (RMSDs) in reference to all buoys and all Argo floats are low in DOISST. The bias in reference to the independent 10% of buoy SSTs remains low in DOISST, but the RMSD is slightly higher in DOISST than in OSTIA and CMC. The biases in reference to the independent 10% of Argo observations are low in CMC, DOISST, and GMPE; also, RMSDs are low in GMPE and CMC. The biases are similar in GAMSSA, OSTIA, GPB, and CCI whether they are compared against all buoys, all Argo, or the 10% of buoy or 10% of Argo observations, while the RMSDs against Argo observations are slightly smaller than those against buoy observations. These features indicate a good performance of DOISST v2.1 among the eight products, which may benefit from ingesting the Argo observations by expanding global and regional spatial coverage of in situ observations for effective bias correction of satellite data. [ABSTRACT FROM AUTHOR]

The Marine Institute of Ireland operates a network of weather buoys around Ireland. A wave of 32.3 m height (crest–trough) was recorded by one of these buoys, the M6 buoy, off the coast of Ireland in October 2020. In this paper, the technological evolution of this network is explored, with a particular emphasis on this extremely high wave. Raw data and bulk parameters collected during the event are presented, and the wider met-ocean context is outlined. In addition, wave data across the buoy deployment period from dual wave sensors installed on the buoy are analysed. Differences in calculation methods are discussed, rogue incidence rates are calculated, and the sensors are found to be generally in good agreement for key sea state parameters. Considerations specific to this network of buoys are described, including recent advances in technology that may affect continuity of historic records. Wave data from the buoys are found to be robust; the importance of keeping technological changes in mind and using the full raw dataset for analysis purposes are highlighted.

Six-month buoy-based heat flux observations from the poorly sampled tropical southeastern Indian Ocean are examined to document the extremes during three tropical cyclones (TCs) from December 2018 to May 2019. The most striking feature at the mooring site (16.9°S, 115.2°E) during the TCs is the extensively suppressed diurnal cycle of the net surface flux (Qnet), with a mean daytime (nighttime) reduction of 470 (131) W m−2, a peak decrease at approximately noon of 695 W m−2 and an extreme drop during TC Riley of 800 W m−2. The mean surface cooling in the daytime is primarily contributed by the 370 W m−2 decrease in shortwave radiation associated with the increased cloudiness. The air–sea turbulent heat fluxes increase by approximately 151 W m−2 in response to the enhanced wind speed under near-neutral boundary conditions. The daily mean rainfall-induced cooling is 8 W m−2, with a maximum magnitude of 90 W m−2. The mean values, seasonal variation, and synoptic variability of the characteristic heat fluxes are used to assess the new reanalysis data from ERA5 and MERRA2 and the analyzed OAFlux. The overall performance of the high-frequency net heat flux estimates at the synoptic scale is satisfactory, but the four flux components exhibit different quality levels. A serious error is that ERA5 and MERRA2 poorly represent TCs, and they show significant daily mean Qnet biases with opposite directions, −59 W m−2 (largely due to the overestimated latent heat with a bias of −76 W m−2) and 50 W m−2 (largely due to the overestimated shortwave radiation with a bias of 41 W m−2), respectively. [ABSTRACT FROM AUTHOR]

A distributed sensor network of over 100 free-drifting, real-time marine weather sensors was deployed in the Pacific Ocean beginning in early 2019. The Spotter buoys used in the network represent a next-generation ocean weather sensor designed to measure surface waves, wind, currents, and sea surface temperature. Large distributed sensor networks like these provide much needed long-dwell sensing capabilities in open-ocean regions. Despite the demand for better weather forecasts and climate data in the oceans, direct in situ measurements of marine surface weather (waves, winds, currents) remain exceedingly sparse in the open oceans. Because of the large expanse of Earth's oceans, distributed paradigms are necessary to create sufficient data density at global scale, similar to advances in sensing on land and in space. Here we discuss initial findings from this long-dwell open-ocean distributed sensor network. Through triple-collocation analysis, we determine errors in collocated satellite-derived observations and model estimates. The correlation analysis shows that the Spotter network provides wave height data with lower errors than both satellites and models. The wave spectrum was also further used to infer wind speed. Buoy drift dynamics are similar to established drogued drifters, particularly when accounting for windage. We find a windage correction factor for the Spotter buoy of approximately 1%, which is in agreement with theoretical estimates. Altogether, we present a completely new open-ocean weather dataset and characterize the data quality against other observations and models to demonstrate the broad value for ocean monitoring and forecasting that can be achieved using large-scale distributed sensor networks in the oceans. [ABSTRACT FROM AUTHOR]

Wave measurements from a new, low-cost, real-time wave buoy (Spotter) are investigated in a comparative study as part of a site characterization study at a wave energy candidate site at King Island, Tasmania, Australia. Measurements from the Sofar Ocean Spotter buoy are compared with concurrent measurements from a Teledyne RD Instrument (RDI) 1200 kHz Work Horse ADCP and two RBRsolo3 D wave16 pressure loggers. The comparison period between 8 August and 12 October 2019 provides both the shallowest and longest continuous published comparison undertaken with the Spotter buoy. Strong agreement was evident between the Spotter buoy and RDI ADCP of key wave parameters including the significant wave height, peak wave period, and mean wave direction, with the mean values of those parameters across the full deployment period agreeing within 3%. Surface wave spectra and directional spectra are also analyzed with good agreement observed over the majority of the frequency domain, although the Spotter buoy records approximately 17% less energy within a narrow frequency band near the peak frequency when compared to the RDI ADCP. Measurements derived from the pressure loggers routinely underestimated the significant wave height and overestimated the mean wave period over the deployment period. The comparison highlights the suitability of the Spotter buoy for low-cost wave resource studies, with accurate measurements of key parameters and spectra observed. [ABSTRACT FROM AUTHOR]

Surface wind plays a crucial role in many local/regional weather and climate processes, especially through the exchanges of energy, mass, and momentum across Earth's surface. However, there is a lack of consistent observations with continuous coverage over the global tropical ocean. To fill this gap, the NASA Cyclone Global Navigation Satellite System (CYGNSS) mission was launched in December 2016, consisting of a constellation of eight small spacecrafts that remotely sense near-surface wind speed over the tropical and subtropical oceans with relatively high sampling rates both temporally and spatially. This current study uses data obtained from the Tropical Moored Buoy Arrays to quantitatively characterize and validate the CYGNSS derived winds over the tropical Indian, Pacific, and Atlantic Oceans. The validation results show that the uncertainty in CYGNSS wind speed, as compared with these tropical buoy data, is less than 2 m s−1 root-mean-square difference, meeting the NASA science mission level-1 uncertainty requirement for wind speeds below 20 m s−1. The quality of the CYGNSS wind is further assessed under different precipitation conditions, and in convective cold-pool events, identified using buoy rain and temperature data. Results show that CYGNSS winds compare fairly well with buoy observations in the presence of rain, though at low wind speeds the presence of rain appears to cause a slight positive wind speed bias in the CYGNSS data. The comparison indicates the potential utility of the CYGNSS surface wind product, which in turn may help to unravel the complexities of air–sea interaction in regions that are relatively undersampled by other observing platforms. [ABSTRACT FROM AUTHOR]

A total of 13 ocean-based wind events from 2018, detected by buoys and Coastal-Marine Automated Network (C-MAN) stations, were analyzed using 1-min mesoscale sector Advanced Baseline Imager (ABI) cloud top brightness temperature (CTTB) data, as well as 1-min Geostationary Lightning Mapper (GLM) lightning data. The ABI and GLM instruments are located on the Geostationary Operational Environmental Satellite-16 (GOES-16) satellite. An oceanic wind event was defined as a buoy or C-MAN station-recorded peak wind gust of at least 14ms-1, associated with a convective storm. The wind gust was required to exceed the wind speed by at least 4ms-1 at the time of the event, but not exceed the corresponding wind speed by at least 4ms-1 for more than 30 min. This study hypothesized that prior to a wind event, there should be unique signatures in ABI CTTB and GLM lightning datasets. The presumption was that the minimum CTTB and maximum flash rate should occur near the same time and prior to the event. The minimum CTTB occurred an average of 10.5 min and a median of 7 min prior to events, with a range from 29 min prior to 1 min after the event. Changes in CTTB were often subtle. A maximum flash rate occurred within 5 min of the minimum CTTB for 11 of the 12 events with lightning and did not exceed 11 flashes per minute for 9 of the 12 events with lightning. Operational weather forecasters might use CTTB and lightning trends to help identify storms capable of producing significant oceanic wind events. [ABSTRACT FROM AUTHOR]