Here we examine seasonal grain-size trends on 18 beaches in the Northeastern US and dispersed along the post-glacial coast of Massachusetts (USA) in order to explore the mechanisms influencing median grain size and slope. Over 800 grain size samples were collected along 200 summer and winter cross-shore beach elevation surveys. Obtained grain size and beach slope data are compared to coastal morphology, sediment source, wave height, and tidal magnitude in order to ascertain controls on beach characteristics. In general, median grain size increases with intertidal beach slope in the study region. However, grain sizes along post-glaciated beaches in the study are as much as an order of magnitude coarser for the same beach slopes when compared to beaches for other regions of the US. Grain size and slope for beaches in the northeastern US also exhibit less correlation with oceanographic processes (i.e. wave climate and tidal magnitude). Instead, grain size trends are primarily driven by the composition of nearby glacial deposits that serve as the primary source of sediment to beaches in the study region. Results provide quantitative support for the distribution and composition of legacy glacial deposits rather than oceanographic conditions serving as the predominant governor of beach grain size along post-glaciated coastlines of the Atlantic continental margin.

<p>In order to understand how waves influence the exchange of momentum, latent heat and other parameters, between the ocean surface and the atmosphere, one can use models. A coupling between a wave model and an atmospheric regional climate model, for the Baltic Sea, will be performed at the Meteorology Institute in Uppsala University. The wave model is a state of the art, third generation wave model called WAM.</p><p>The new version of the WAM model (cycle 4) needs to be validated. The aim of this thesis is to perform this validation and also to investigate what meteorological forcing one should use to achieve best results. Two different types of forcing are analyzed, ERA40 reanalysis and the RCA climate model. In order to do this, observations from six different buoys in the Baltic Sea will be compared with the model output from WAM. The parameters that will be compared in this study are significant wave height, direction and peak period.</p><p>A consistent phenomenon for all the buoys is a slightly overestimation by the model of what the rate of this increases with increasing wave height. If one compares the model output when WAM are forced with the RCA climate model and when it is forced with ERA40 reanalysis, the differences between them are notable but not large. ERA40 is slightly better.</p><p>Significant wave height is quite good and gives a reasonably result. Some buoys and periods are better and some are worse. There are some differences for the significant wave height between the east coast and the west coast of Sweden, when forcing the model with RCA. It is slightly better on the west coast. On the contrary, the results from ERA40 are very coherent. The quality of the hindcast for the direction and the peak period, in contrast to the significant wave height, is not that good. The results are not bad, but it only gives a rough picture of the sea state.</p>

Our paleotsunami surveys of the southern Java coast led to the discovery of five imbricate coastal boulder fields near Pacitan, Indonesia that may date to the mid-to-late 19th century or prior and two similar fields at Pantai Papuma and Pantai Pasir Putih that were tsunami-emplaced during the 1994 7.9 Mw event in East Java. Estimated ages for the fields near Pacitan are based on historical records and radiocarbon analyses of coral boulders. The largest imbricated boulders in fields near Pacitan and in East Java are similar in size (approximately 3 m^3) and are primarily composed of platy beachrock dislodged from the intertidal platform during one or several unusually powerful wave impactions. Hydrodynamic wave height reconstructions of the accumulations near Pacitan indicate the boulders were likely tsunami rather than storm-wave emplaced, as the size of the storm waves needed to do so is not viable. We evaluate the boulders as an inverse problem, using their reconstructed wave heights and ComMIT tsunami modeling to suggest a minimum 8.4 Mw earthquake necessary to dislodge and emplace the largest boulders near Pacitan assuming they were all deposited during the same tsunami event and that the rupture source was located along the Java Trench south of Pacitan. A combined analysis of historical records of Java earthquakes and plate motion measurements indicates a seismic gap with >25 m of slip deficit along the Java Trench. A 1000-1500 km rupture along the subduction interface of this segment is capable of producing a 9.0-9.3 Mw megathrust earthquake and a giant tsunami. However, evidence for past megathrust earthquake events along the this trench remains elusive. We use epicenter independent tsunami modelling to estimate wave heights and inundation along East Java in the event that the trench were to fully rupture. By translocating ComMIT slip parameters of Japan's 2011 9.1 Mw event along the trench offshore East Java, we demonstrate possible wave heights in excess of 20 m at various locations along its southern coasts. Approximately 300,000-500,000 people in low-lying coastal communities on the southern coasts of East Java could be directly affected. We recommend at-risk communities practice the "20/20/20 principle" of tsunami hazard awareness and evacuation.

In order to understand how waves influence the exchange of momentum, latent heat and other parameters, between the ocean surface and the atmosphere, one can use models. A coupling between a wave model and an atmospheric regional climate model, for the Baltic Sea, will be performed at the Meteorology Institute in Uppsala University. The wave model is a state of the art, third generation wave model called WAM. The new version of the WAM model (cycle 4) needs to be validated. The aim of this thesis is to perform this validation and also to investigate what meteorological forcing one should use to achieve best results. Two different types of forcing are analyzed, ERA40 reanalysis and the RCA climate model. In order to do this, observations from six different buoys in the Baltic Sea will be compared with the model output from WAM. The parameters that will be compared in this study are significant wave height, direction and peak period. A consistent phenomenon for all the buoys is a slightly overestimation by the model of what the rate of this increases with increasing wave height. If one compares the model output when WAM are forced with the RCA climate model and when it is forced with ERA40 reanalysis, the differences between them are notable but not large. ERA40 is slightly better. Significant wave height is quite good and gives a reasonably result. Some buoys and periods are better and some are worse. There are some differences for the significant wave height between the east coast and the west coast of Sweden, when forcing the model with RCA. It is slightly better on the west coast. On the contrary, the results from ERA40 are very coherent. The quality of the hindcast for the direction and the peak period, in contrast to the significant wave height, is not that good. The results are not bad, but it only gives a rough picture of the sea state.

In this thesis, the wind-wave records obtained at three locations along the Turkish coasts (Alanya, Dalaman and Hopa) are analyzed. Probability distributions of individual wave characteristics (wave height, wave period and wave steepness) are obtained and compared with the model distributions. Goodness of fit of the observed distributions is checked by Chi-square test and Kolmogorov-Smirnov tests. Joint probability distribution of individual wave heights and periods is also studied and compared with the theoretical distributions. The relationships among various statistical wave height parameters and statistical wave period parameters are investigated and compared with the theoretical and reported values.

Tsunamis are characterized as shallow water waves, with long periods and wavelengths. They occur by a sudden water volume displacement. Earthquake is one of the main reasons of a tsunami development. Historical data for an observation period of 3500 years starting from 1500 B.C. indicates that approximately 100 tsunamis occurred in the seas neighboring Turkey. Historical earthquake and tsunami data were collected and used to develop two artificial neural network models to forecast tsunami characteristics for future occurrences and to estimate the tsunami return period. Artificial Neural Network (ANN) is a system simulating the human brain learning and thinking behavior by experiencing measured or observed data. A set of artificial neural network is used to estimate the future earthquakes that may create a tsunami and their magnitudes. A second set is designed for the estimation of tsunami inundation with relation with the tsunami intensity, the earthquake depth and the earthquake magnitude that are predicted by the first set of neural networks. In the case study, Marmara and Aegean regions are taken into consideration for the estimation process. Return periods including the last occurred earthquake in the Turkish seas, which was the izmit (Kocaeli) Earthquake in 1999, were utilized together with the average earthquake depths calculated for Marmara and Aegean regions for the prediction of the earthquake magnitude that may create a tsunami in the stated regions for various return periods of 1-100 years starting from the year of 2004. The obtained earthquake magnitudes were used together with tsunami intensities and earthquake depth to forecast tsunami wave height at the coast. It is concluded that, Neural Networks predictions were a satisfactory first step to implement earthquake parameters such as depth and magnitude, for the average tsunami height on the shore calculations.

The aim of this thesis is to process data on wave event measurement on hulín lagoon and their evaluation. The data is processed in the MATLAB environment, thanks to which basic parameters such as wave heights and lengths, period and spectrum shape can be evaluated.

<p dir="ltr">The recent surge in water levels within the Great Lakes has laid bare the vulnerability of the surrounding coastal areas. Over the past few years, communities along the Great Lakes coast have struggled with widespread coastal transformations, witnessing phenomena such as shoreline retreat, alterations in habitat, significant recession of bluffs and dunes, infrastructure and property damage, coastal flooding, and the failure of coastal protection structures. Unlike the ocean coasts, the Great Lakes coastal regions experience a unique confluence of large interannual water level fluctuations, coastal storms, and ice cover dynamics, which complicates the ongoing coastal management endeavors. To address this multifaceted challenge, the interplay between all these factors and their impact on coastal changes should be understood and applied to improve the resilience of Great Lakes coastal areas.</p><p><br></p><p dir="ltr">In this dissertation, several steps were taken to improve knowledge of coastal processes in the Great Lakes, spanning from the initial use of remote sensing for quantifying coastal changes to the subsequent stages of modeling and predicting shoreline changes as well as leveraging machine learning techniques to simulate and forecast influential factors like waves and ice cover. First, a fully automated shoreline detection algorithm was developed to quantify the shoreline changes in Lake Michigan, detecting the most vulnerable areas, and determining the main factors responsible for the spatial variability in the shoreline changes. Additionally, a reduced complexity model was designed to simulate the shoreline changes in Lake Michigan by considering both waves and water level fluctuations, which significantly improved the shoreline changes modeling and forecasting for Lake Michigan. Furthermore, new deep learning-based frameworks based on the Convolution Long Short-Term Memory (ConvLSTM) and Convolution Neural Network (CNN) were introduced to model and extend the current records of wave heights and ice cover datasets, adding 70% and 50% data to the existing waves and ice time series respectively. Finally, the extended waves and ice time series were used to study the long-term trends and the correlation between the interannual water level and waves changes, revealing a statically significant decreasing trend in the ice cover over Lake Michigan of 0.6 days/year, and an increasing trend in the waves interannual variability at Chicago area.</p>

Long-term omni-directional ambient noise was collected at several sites in the Gulf of Mexico during 2004 and 2005. The Naval Oceanographic Office deployed bottom moored Environmental Acoustic Recording System (EARS) buoys approximately 159 nautical miles south of Panama City, Florida, in water depths of 3200 meters. The hydrophone of each buoy was 265 meters above the bottom. The data duration ranged from 10-14 months. The buoys were located near a major shipping lane, with an estimated 1.5 to 4.5 ships per day passing nearby. The data were sampled at 2500 Hz and have a bandwidth of 10-1000 Hz. Data are processed in eight 1/3-octave frequency bands, centered from 25 to 950 Hz, and monthly values of the following statistical quantities are computed from the resulting eight time series of noise spectral level: mean, median, standard deviation, skewness, kurtosis and coherence time. Four hurricanes were recorded during the summer of 2004 and they have a major impact on all of the noise statistics. Noise levels at higher frequencies (400-950 Hz) peak during extremely windy months (summer hurricanes and winter storms). Standard deviation is least in the region 100-200 Hz but increases at higher frequencies, especially during periods of high wind variability (summer hurricanes). Skewness is positive from 25-400 Hz and negative from 630-950 Hz. Skewness and kurtosis are greatest near 100 Hz. Coherence time is low in shipping bands and high in weather bands, and it peaks during hurricanes. The noise coherence is also analyzed. The 14-month time series in each 1/3- octave band is highly correlated with other 1/3-octave band time series ranging from 2 octaves below to 2 octaves above the band's center frequency. Spatial coherence between hydrophones is also analyzed for hydrophone separations of 2.29, 2.56 and 4.84 km over a 10-month period. The noise field is highly coherent out to the maximum distance studied, 4.84 km. Additionally, fluctuations of each time series are analyzed to determine time scales of greatest variability. The 14-month data show clearly that variability occurs primarily over three time scales: 7-22 hours (shipping-related), 56-282 hours (2-12 days, weather-related) and over an 8-12 month period.

Title from PDF of title page. / Document formatted into pages; contains 84 pages. / Thesis (M.S.)--University of South Florida, 2003. / Includes bibliographical references. / Text (Electronic thesis) in PDF format. / ABSTRACT: Hurricane hazards result from the combined processes of wind, waves, storm surge, and overwash (Lennon et al., 1996). Predicting the severity of these hazards requires immense effort to quantify the processes and then predict how different coastal regions respond to them. A somewhat simpler, but no less daunting task is to begin to predict the hazards due to potential erosion of barrier islands. A four-part scale has been developed by Sallenger (2000) to provide a framework for understanding how barrier islands might respond during extreme storm events. These four regimes describe how beach and dune elevations interact with surge and wave runup. This study will produce estimates of potential hazards through combining lidar surveys of dune elevation with modeled elevations of storm water levels. Direct measurements of maximum wave heights during hurricanes are rare. / ABSTRACT: We evaluated three simple equations proposed by Kjerfve (1986), Young (1988), and Hsu (1998) to forecast the maximum wave height (Hmax) generated by three 1999 hurricanes. Model results were compared to wave data recorded by the National Oceanic and Atmospheric Administration (NOAA) wave rider buoys. The radius of maximum winds, wind speed, forward velocity, distance from buoy to the storm's eye-wall (r), and buoy's position relative to the quadrant of the storm (Q) were found to have significant and direct roles in evaluating recorded hurricane induced wave heights (H) and thus, were individually examined for each comparison. The implications of the r and Q on H were assessed when determining the overall effectiveness of the modelers' equations. Linear regression analyses tested the accuracy of each modeled prediction of the Hmax, comparing it to the observed wave heights. Three statistical criteria were used to quantify model performance. / ABSTRACT: Hsu's model was the most reliable and useful forecasting technique. Despite the predictive skill of Hsu's model, direct observations of the maximum wave conditions, when available and appropriate, are preferred as inputs for SWAN, a 3rd generation shoaling wave model. Outputs from SWAN are used to calculate the empirical relationships for wave runup. For our test case, pre and post-storm topographies were surveyed as part of a joint USGS-NASA program using lidar technology. These data sets were used to calculate changes in the elevation and location of the dune crest (Dhigh) and dune base (Dlow) for the North Carolina Outer Banks. We hindcast potential coastal hazards (erosional hot spots) using the pre-storm morphology and modeled wave runup and compare those estimates to the measured results from the post-storm survey. / ABSTRACT: Links among the existing topography and spatial variations in wave runup were found to be 95% correlated for the north-south and east-west facing barrier islands. Application of Sallenger's (2000) four-part Storm Impact Scale to the pre-storm Dhigh elevation survey and wave runup extremes (Rhigh and Rlow) were found to accurately predict zones of overwash and showed potential to forecast the inundation regime. / System requirements: World Wide Web browser and PDF reader. / Mode of access: World Wide Web.