Nearby Buoy Research Articles

XWaveNet: Enabling uncertainty quantification in short-term ocean wave height forecasts and extreme event prediction

To aid accurate short-term forecast of wave heights and extreme events prediction from buoy data, a deep learning approach is proposed. Wave heights are forecasted up to 72 h in advance from multivariate meteorological and oceanographic data, followed by quantification of uncertainty in the forecasted values, and estimation of exceedance probabilities for extreme event conditions. Using Monte Carlo dropout technique, network regularization and forecast uncertainty assessment were performed. To forecast wave heights, a stacked long short-term memory (LSTM) model was trained on historical buoy data augmented with positionally encoded features. Per comparative evaluation of different models, across the 72 h forecast horizon, positionally encoded temporal attributes resulted in a mean prediction error and forecast uncertainty of only 3 % and 13.5 %, respectively. Contrarily, without temporal feature augmentation mean error was 5 % and uncertainty, 15 %. Therefore, the former model was ensembled with a Random Forest model for exceedance probability estimation. The hybrid model yielded a 21.4 % better separability between the extreme and normal observations in the test data from a nearby buoy in the northern Gulf of Mexico than individual models. All the four extreme events in the test set were correctly predicted with 97 % mean accuracy. Further evaluation of the deep ensemble model on 5 other spatially diverse buoy datasets from the Gulf of Mexico, Atlantic and Pacific coasts, suggested excellent generalizability for short-term wave forecasts and extreme event prediction, with an average maximum error of just 5.2 % across all the 6 buoy test datasets and the entire forecast horizon.

Climate‐Induced Decadal Ocean Wave Height Variability From Microseisms: 1931–2021

AbstractLong‐term coastal wave climate changes under global warming cannot be reliably assessed from relatively short duration buoy significant wave height (Hs) observations that began about 1980. Alternatively, microseisms at double the wave frequency (DFM) provide proxy records of near‐coastal wave activity. An empirical wave reconstruction methodology transforms DFM from UC Berkeley seismic station BKS to seismic Hs (sHs). Broadband digital seismic observations since 1992 at BKS provide DFM reference spectral levels. Earlier digitized archived BKS seismogram DFM levels are adjusted to give spectral levels that are consistent with current observations, yielding a combined 90‐year sHs record for winters (November–March) spanning the 1931–2021 epoch. Mean winter sHs derived from digitized 1980s seismograms are well‐correlated with nearby buoy Hs. Comparison of deep‐water extreme Hs with sHs demonstrates that sHs is dominated by near‐coastal wave activity. Much greater decadal and interannual variability occurred during the 1931–1970 epoch, including extended periods of exceptionally low sHs during 1939–1947 and 1957–1965 that have not occurred since global warming accelerated near 1970, suggesting that winter extratropical storm intensity has generally increased. Comparisons of winter sHs variability with anomalous sea level pressure (SLPa) patterns across the North Pacific demonstrate the association of coastal sHs with broad‐scale atmospheric variability, with differences between long‐term averages of winter SLPa indicating an Aleutian Low intensification, consistent with both increased mean sHs and occurrence of extreme events since 1970. Recent record global annual temperatures suggest that warming may be accelerating, resulting in stronger storms that intimates further increased winter Hs may be forthcoming.

Ocean-Surface Wave Measurements Using Scintillation Theories on Seaborne Software-Defined GPS and SBAS Reflectometry Observations.

In this study, a low-cost, software-defined Global Positioning System (GPS) and Satellite-Based Augmentation System (SBAS) Reflectometry (GPS&SBAS-R) system has been built and proposed to measure ocean-surface wave parameters on board the research vessel New Ocean Researcher 1 (R/V NOR-1) of Taiwan. A power-law, ocean-wave spectrum model has been used and applied with the Small Perturbation Method approach to solve the electromagnetic wave scattering problem from rough ocean surface, and compared with experimental seaborne GPS&SBAS-R observations. Meanwhile, the intensity scintillations of high-sampling GPS&SBAS-R signal acquisition data are thought to be caused by the moving of rough surfaces of the targeted ocean. We found that each derived scintillation power spectrum is a Fresnel-filtering result on ocean-surface elevation fluctuations and depends on the First Fresnel Zone (FFZ) distance and the ocean-surface wave velocity. The determined ocean-surface wave speeds have been compared and validated against nearby buoy measurements.

On three types of sea breeze in Qingdao of East China: an observational analysis

Our knowledge of sea breeze remains poor in the coastal area of East China, due largely to the high terrain heterogeneity. Five–year (2016–2020) consecutive wind observations from a 10-m wind tower and radar wind profiler are used to characterize the sea–land breeze at Qingdao, a coastal city in East China. The sea surface temperatures at the nearby buoy station in the Yellow Sea are further used to elucidate the land–sea thermal contrast. First of all, three types of sea breeze are determined according to the temporal evolution of wind direction, including pure sea breeze (PSB), corkscrew sea breeze (CSB) and backdoor sea breeze (BSB). Statistically, there are 522 days experiencing sea breezes, of which 61 days belong to pure sea breeze, 40 days witness corkscrew sea breeze, and only 2 days see the backdoor sea breeze. The occurrence of sea breeze is found to peak from April to September and the average wind speed lies at 3–5 m s−1. This suggests a salient seasonality of sea breeze at Qingdao, which is likely caused by the seasonal dependence of land–sea thermal contrast. In terms of the diurnal variability, the sea breezes tend to occur more frequently and have more intensity in the afternoon compared with in the morning, irrespective of sea breeze types. Interestingly, the backdoor sea breeze is merely observed in autumn, whereas corkscrew sea breeze and pure sea breeze can be found year round. Among all types of sea breeze, the pure sea breeze has the highest intensity and most frequency throughout the daytime, same in the seasons of spring, summer and autumn. Further analyses are conduced of the atmospheric circulation, lower troposphere stability and bulk Richard number (Ri) for three types of sea breeze. Both pure sea breeze and corkscrew sea breeze in Qingdao are characterized by prevailing westerlies at 500 hPa. In contrast, the backdoor sea breeze is generally accompanied with easterlies at 850 hPa. Meanwhile, the backdoor sea breeze has the lowest lower troposphere stability, in sharp contrast to the highest lower troposphere stability for the pure sea breeze. This indicates that the backdoor sea breeze (pure sea breeze) tends to occur in an unstable (stable) lower troposphere. The findings obtained here highlight the importance of typing sea breeze.

Seismic noise characterisation at a potential gravitational wave detector site in Australia

A critical consideration in the design of next-generation gravitational wave detectors is the understanding of the seismic environment that can introduce coherent and incoherent noise of seismic origin at different frequencies. We present detailed low-frequency ambient seismic noise characterisation (0.1–10 Hz) at the Gingin site in Western Australia. Unlike the microseism band (0.06–1 Hz) for which the power shows strong correlations with nearby buoy measurements in the Indian Ocean, the seismic spectrum above 1 Hz is a complex superposition of wind induced seismic noise and anthropogenic seismic noise which can be characterised using beamforming to distinguish between the effects of coherent and incoherent wind induced seismic noise combined with temporal variations in the spatio-spectral properties of seismic noise. This also helps characterise the anthropogenic seismic noise. We show that wind induced seismic noise can either increase or decrease the coherency of background seismic noise for wind speeds above 6 m s−1 due to the interaction of wind with various surface objects. In comparison to the seismic noise at the Virgo site, the secondary microseism (0.2 Hz) noise level is higher in Gingin, but the seismic noise level between 1 and 10 Hz is lower due to the sparse population and absence of nearby road traffic.

Near‐Coastal Winter Waves From Microseisms

AbstractLong‐term coastal wave climate variability cannot be reliably assessed from relatively short duration buoy observations that began about 1980. Microseisms at double the wave frequency (DFM) provide a proxy record of coastal wave activity. Here, we show that winter (November to March) wave activity can be well characterized from near‐coastal seismometer DFM observations, although extreme wave events are not consistently well reproduced. Reconstructed mean winter seismic significant wave height, sHs, determined using simultaneous seismic and buoy observations, closely track nearby buoy Hs over 1992–2017 winters. Buoy‐measured mean winter short‐period wave variability in the [0.1, 0.15] Hz band is also well reproduced. Generally lower sHs for high amplitude events, compared with offshore buoy Hs, suggests that DFM generation is closer to the coast where shore‐reflected long‐period opposing wave components are likely higher. These results indicate that digitized pre‐1980 archived analog seismograms at near‐coastal seismic stations can reliably characterize long‐term wave climate changes and decadal variability.

Methods to Estimate Surface Roughness Length for Offshore Wind Energy

The northeastern coast of the U.S. is projected to expand its offshore wind capacity from the existing 30 MW to over 22 GW in the next decade, yet, only a few wind measurements are available in the region and none at hub height (around 100 m today); thus, extrapolations are needed to estimate wind speed as a function of height. A common method is the log-law, which is based on surface roughness length (z0). No reliable estimates of z0 for the region have been presented in the literature. Here, we fill this knowledge gap using two field campaigns that were conducted in the Nantucket Sound at the Cape Wind (CW) platform: the 2003–2009 “CW Historical”, which collected wind measurements on a meteorological tower at three levels (20, 41, and 60 m AMSL) with sonic and cup/vane anemometers, and the 2013–2014 IMPOWR (Improving the Mapping and Prediction of Offshore Wind Resources), which collected high-frequency wind and flux measurements at 12 m AMSL. We tested three different methods to calculate z0: (1) analytical method, dependent on friction velocity u∗ and a stability function ψ; (2) the Charnock relationship between z0 and u∗; and (3) a statistical method based on wind speed observed at the three levels. The first two methods are physical, whereas the statistical method is purely mathematical. Comparing mean and median of z0, we find that the median is a more robust statistics because the mean varies by over four orders of magnitude across the three methods and the two campaigns. In general, the median z0 exhibits little seasonal variability and a weak dependency on atmospheric stability, which was predominantly unstable (54–67%). With the goal of providing the most accurate estimates of wind speed near the hub height of modern turbines, the statistical method, despite delivering unrealistic z0 values at times, gives the best estimates of 60 m winds, even when the 5 m wind speed from a nearby buoy is used as the reference. The unrealistic z0 values are caused by nonmonotonic wind speed profiles, occurring about 41% of the time, and should not be rejected because they produce realistic fits. Furthermore, the statistical method outperforms the other two even though it does not need any stability information. In summary, if wind speed data from multiple levels are available, as is the case with vertically pointing floating lidar and meteorological towers, the statistical method is recommended, regardless of the seemingly unrealistic z0 values at times. If multilevel wind speeds are not available but advanced sonic anemometry is available at one level, the analytical method is recommended over Charnock’s. Lastly, if a single, constant value of z0 is sought after to characterize the region, we recommend the median from the statistical method, i.e., 6.09×10−3 m, which is typical of rough seas.

SeaPRISM observations in the western basin of Lake Erie in the summer of 2016

In the summer of 2016, a robotic sun photometer called the Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) Photometer Revision for Incident Surface Measurements (SeaPRISM), was deployed at a Coast Guard channel marker in western Lake Erie, measuring atmospheric properties and spectral water-leaving radiance. The instrument was deployed by the National Oceanic and Atmospheric Administration (NOAA) to support remote sensing validation and harmful algal bloom (HAB) satellite products. The Lake Erie SeaPRISM is also part of the international federated AERONET program maintained by the National Aeronautics and Space Administration (NASA), and more specifically is part of the AERONET Ocean Color (AERNOET-OC) network. The main purpose of this component of AERONET is specific to calibration/validation efforts for ocean color. The AERONET-OC network currently consists of 23 field radiometers at aquatic sites around the world. The Lake Erie site is the second freshwater lake location world-wide after the Palgrunden site in Sweden. During its operating period from mid-July to early September 2016, various environmental conditions were observed including a cyanobacteria bloom. Water-leaving radiance observations were generated on 43 out of 51 days, and varied by a factor of five. The variability in the above-water radiometry tracked that of in-water measurements made by a nearby buoy. During this brief operating window, satellite matchups were generated for several satellites. We highlight the first year's observations in relation to remote sensing validation and report on observations of cyanobacteria blooms from hourly to weekly time scales.

Vector field observations near the continental slope off Big Sur, California

In this work, data collected approximately 3 km off the coast of Big Sur, California, by a low frequency vector sensor system will be analyzed. Directional and temporal variations in the ambient noise field will be evaluated, and causes will be considered including flow noise due to currents, surface (wind) noise, distant shipping, and marine mammals. Bearing estimation results for shipping will be compared with AIS tracks recorded during the period of deployment. Local sound speed measurements and bathymetry in the vicinity of the deployment area will be used as inputs to a two-dimensional propagation model that properly invokes reciprocity of the acoustic vector field. Surface wave spectra collected by a nearby buoy will be used to generate rough surface realizations in order to evaluate the impact of these perturbations on low frequency vector field structure. These results will be combined with acoustic data observations in attempts to determine the impact of propagation on the structure of the field. Such an approach may allow us to infer acoustic source levels of AIS traffic off the coast.

Consistency between Sea Surface Reconstructions from Nautical X-Band Radar Doppler and Amplitude Measurements

AbstractThis study comprises the analysis and the interpretation of the coherent and the noncoherent parts of a coherent-on-receive microwave radar at grazing incidence conditions. The Doppler measurement is an extension of standard civil marine radar technology. While intensity images require interpretation based on understanding the underlying imaging mechanism, the Doppler signal measures the motion of an area of sea surface and is therefore closely related to the wave physics. Both the measured Doppler signal and the backscatter intensity signal are suitable for surface inversion and give almost identical surface elevations. A statistical comparison with a nearby buoy showed good correlation for the significant wave height and the peak period. By comparing the Doppler signal and the amplitude in the backscatter, the study amends the understanding of imaging mechanisms in marine radars at grazing incidence.

Modeling the electrical grid impact of wind ramp-up forecasting error offshore in the Mid-Atlantic region

The large wind resource and population centers along the Mid-Atlantic Coast of the United States make it an attractive region to develop offshore wind power. Understanding and accurately predicting the meteorology offshore is fundamental to efficient integration of these future wind farms into an electrical grid. Particular interest is focused on anticipating and reducing errors associated with wind ramps, which are characterized by rapid, sustained changes in wind speed over a period of hours. Using meteorological observations from a coastal buoy, we characterize 428 wind ramp-ups between 2005 and 2012 in terms of frequency, duration and magnitude, time and date of occurrence, and large-scale synoptics. From this group, we select 24 case studies that represent typical and extreme ramp-ups at this location and then model the impact that the forecasting error of these ramp-ups could have on the electrical grid. The case studies are modeled with the Weather Research and Forecasting (WRF) model and compared with nearby buoy observations to assess forecast errors in ramp-up timing, shape, and magnitude. WRF frequently simulated ramp-ups too early, relative to observations, and often predicted the pre-ramp-up wind speed to be too high or the post-ramp-up wind speed to be too low. In the case of August 14, 2007, all three forecast errors occurred. The simulated impact on the grid is calculated by comparing the errors in forecast power with concurrent electrical load data in PJM's Mid-Atlantic Area Council-East (PJM-E) region. The largest impacts on the electrical grid were found to occur in the winter or at night in the summer. This framework allows for the identification of events that would potentially cause problems for the electrical grid in the PJM-E region.

Preliminary measurements of passive acoustics in Lake Superior

In July 2016, a hydrophone was deployed for eight days in 54 m of water in the western arm of Lake Superior. This is, to the best of our knowledge, the first recording of passive acoustic information in a large lake. The signal is dominated by noise from passing ships (30-100 Hz) and by surface winds (broad spectrum). Noise from passing ships drops off as approximately r-6, suggesting that there are significant transmission losses associated with reflections off of the bottom. The signal associated with wind is highly correlated with wind speed as measured at a nearby buoy. Intermittent “clicks” look similar to burbot calls previously observed, and appear to occur only in the absence of ship noise. This suggests a potential behavioral response to ambient acoustic energy. Ray tracing experiments suggest the acoustic environment within the lake will change drastically as the lake transitions from summer stratified conditions to unstratified, and again when inverse winter stratification sets in.

Surface Wave Measurements from Subsurface Floats

AbstractPressure gradient measurements on a subsurface Lagrangian float are used to measure the spectrum of surface waves for 100 days of measurements at Ocean Weather Station Papa. Along Lagrangian trajectories of surface waves, the pressure is constant and the vertical pressure gradient fluctuations equal the Eulerian fluctuations at the mean float depth to second order in wave height. Measurement of the pressure difference between the top and the bottom of the float can thus be used to measure the waves. Corrections for the wave decay with depth, for the vertical motion of the float, for the finite sampling interval, and for the sampling noise (among others) are necessary to obtain accurate results. With these corrections, scalar spectra accurately match those from a nearby Waverider buoy for significant wave heights greater than about 3 m. For smaller wave heights, noise in the pressure measurements biases the float spectral measurements. Significant wave height is measured with an rms error of 0.37 m over the measured range of 1–9 m. This demonstrates that Lagrangian floats accurately follow the Lagrangian trajectories of surface waves. More detailed and quieter measurements of float motion could likely measure directional wave spectra from below the surface. Similar methods could be used to infer surface wave properties from other subsurface vehicles.

Application of the ICF Coherence Time Method for Ocean Remote Sensing Using Digital Communication Satellite Signals

This paper applies an ocean remote sensing method, first developed for reflected Global Navigation Satellite System (GNSS-R) signals, to reflected digital communication satellite signals. The fundamental observation is the time series of the Interferometric Complex Field (ICF) of the reflected signal. A relationship is derived between the coherence time of the ICF time series and the significant wave height (SWH) and mean wave period (MWP) of the ocean. Direct and reflected signals from the S-band satellite transmissions providing the commercial XM radio service were recorded at Platform Harvest over a 65-day period. In situ measurements from a nearby buoy were used to calibrate this measurement by determining coefficients of a semi-empirical model. SWH retrievals using this model on 1 min of reflected signal observations were found to have a standard deviation of 0.38 m over the range from 1 to 4.5 m. An error analysis was done to show that the primary contribution to this error was uncertainty in the relationship between MWP and SWH, and to quantify the retrieval error from different forward models.

Distinguishing high surf from volcanic long‐period earthquakes

AbstractRepeating long‐period (LP) earthquakes are observed at active volcanoes worldwide and are typically attributed to unsteady pressure fluctuations associated with fluid migration through the volcanic plumbing system. Nonvolcanic sources of LP signals include ice movement and glacial outburst floods, and the waveform characteristics and frequency content of these events often make them difficult to distinguish from volcanic LP events. We analyze seismic and infrasound data from an LP swarm recorded at Pagan volcano on 12–14 October 2013 and compare the results to ocean wave data from a nearby buoy. We demonstrate that although the events show strong similarity to volcanic LP signals, the events are not volcanic but due to intense surf generated by a passing typhoon. Seismo‐acoustic methods allow for rapid distinction of volcanic LP signals from those generated by large surf and other sources, a critical task for volcano monitoring.

Estimation of the wave power resource in the Caribbean Sea in areas with scarce instrumentation. Case study: Isla Fuerte, Colombia

There are great difficulties in properly evaluating the power present in waves in the Caribbean Sea due to of the scarcity of marine instrumentation and the reduced length of the existing records. This research aimed to design a new methodology for estimating wave power potential in places lacking instrumentation by using reanalysis wind and wave generation models to generate hourly synthetic wave information (maps and wave series), which was later compared and corrected with nearby buoy measurements. Nested runs of the models allowed the results to be downscaled and detailed wave power maps to be created. The best sites for a possible wave farm could then be identified. These maps were built from the propagation of characteristic sea-states of the synthetic series, and were chosen using joint probability, power percentiles and the k-means clustering algorithms. New series were generated in the chosen locations and processed to determine the wave power potential in different time scales. Isla Fuerte, a small non grid-connected island in the Colombian Caribbean, served as a case study for the implementation of the methodology.

East Coast Cool-Weather Storms in the New York Metropolitan Region

Abstract New York coastal regions are frequently exposed to winter extratropical storm systems that exhibit a wide range of local impacts. Studies of these systems either have used localized water-level or beach erosion data to identify and characterize the storms or have used meteorological conditions from reanalysis data to provide a general regional “climatology” of storms. The use of meteorological conditions to identify these storms allows an independent assessment of impacts on the coastal environment and therefore can be used to predict the impacts. However, the intensity of these storms can exhibit substantial spatial variability that may not be captured by the relatively large scales of the studies using reanalysis data, and this fact may affect the localized assessment of storm impact on the coastal communities. A method that uses data from National Data Buoy Center stations in the New York metropolitan area to identify East Coast cool-weather storms (ECCSs) and to describe their climatological characteristics is presented. An assessment of the presence of storm conditions and a three-level intensity scale was developed using surface pressure data as measured at the buoys. This study identified ECCSs during the period from 1977 through 2007 and developed storm climatologies for each level of storm intensity. General agreement with established climatologies demonstrated the robustness of the method. The impact of the storms on the coastal environment was assessed by computing “storm average” values of storm-surge data and by examining beach erosion along the south shore of Long Island, New York. A regression analysis demonstrated that the best storm-surge predictor is based on measurements of significant wave height at a nearby buoy.

Retrieval of Ocean Surface Wind Speed and Wind Direction Using Reflected GPS Signals

Global positioning system (GPS) signals reflected from the ocean surface can be used for various remote sensing purposes. Some possibilities include measurements of surface roughness characteristics from which the rms of wave slopes, wind speed, and direction could be determined. In this paper, reflected GPS measurements that were collected using aircraft with a delay mapping GPS receiver are used to explore the possibility of determining ocean surface wind speed and direction during flights to Hurricanes Michael and Keith in October 2000. To interpret the GPS data, a theoretical model is used to describe the correlation power of the reflected GPS signals for different time delays as a function of geometrical and sea-roughness parameters. The model employs a simple relationship between surface-slope statistics and both a wind vector and wave age or fetch. Therefore, for situations when this relationship holds there is a possibility of indirectly measuring the wind speed and the wind direction. Wind direction estimates are based on a multiple-satellite nonlinear least squares solution. The estimated wind speed using surface-reflected GPS data collected at wind speeds between 5 and 10 m s−1 shows an overall agreement of better than 2 m s−1 with data obtained from nearby buoy data and independent wind speed measurements derived from TOPEX/Poseidon, European Remote Sensing (ERS), and QuikSCAT observations. GPS wind retrievals for strong winds in the close vicinity to and inside the hurricane are significantly less accurate. Wind direction agreement with QuikSCAT measurements appears to be at the 30° level when the airplane has both a stable flight level and a stable flight direction. Discrepancies between GPS retrieved wind speeds/directions and those obtained by other means are discussed and possible explanations are proposed.

GPS Signal Scattering from Sea Surface: Wind Speed Retrieval Using Experimental Data and Theoretical Model

Global Positioning System (GPS) signals reflected from the ocean surface have potential use for various remote sensing purposes. Some possibilities are measurements of surface roughness characteristics from which wave height, wind speed, and direction could be determined. For this paper, GPS-reflected signal measurements collected at aircraft altitudes of 2 km to 5 km with a delay-Doppler mapping GPS receiver are used to explore the possibility of determining wind speed. To interpret the GPS data, a theoretical model has been developed that describes the power of the reflected GPS signals for different time delays and Doppler frequencies as a function of geometrical and environmental parameters. The results indicate a good agreement between the measured and the modeled normalized signal power waveforms during changing surface wind conditions. The estimated wind speed using surface-reflected GPS data, obtained by comparing actual and modeled waveforms, shows good agreement (within 2 m/s) with data obtained from a nearby buoy and independent wind speed measurements derived from the TOPEX/Poseidon altimetric satellite.

Ocean wave height determined from inland seismometer data: Implications for investigating wave climate changes in the NE Pacific

Knowing the wave climate along the California coast is vital from the perspectives of climatological change and planning shore protection measures. Buoy data indicate that the wave climate is very similar along much of the California coast. We show that elements of the wave climate can be accurately reconstructed using near‐coastal inland broadband seismometer data. Such reconstructions are possible because swell approaching the coast generates pressure fluctuations that are locally transformed into seismic waves at the seafloor that propagate inland and are detectable by land‐based seismometers. Buoy and seismometer data show that most of the microseism energy recorded inland near the coast is generated from wave events at nearby coastal locations. A site‐specific, empirically derived seismic‐to‐wave transfer function is demonstrated to be applicable to seismic data from the same location for any year. These results suggest that ocean wave heights estimated from near‐coastal broadband seismometer data are sufficiently reliable for monitoring the coastal wave height when buoy data are unavailable, provided that adequate simultaneous nearby buoy measurements are available to calibrate the seismometer data. The methodology presented here provides an important tool that allows the investigation of potential wave climate changes from reconstructions using archived seismic data collected since the 1930s.