scholarly journals COMPARISON OF SHIPBORNE WAVE RECORDER AND WAVERIDER BUOY DATA USED TO GENERATE DESIGN AND OPERATIONAL PLANNING CRITERIA

1978 ◽  
Vol 1 (16) ◽  
pp. 4 ◽  
Author(s):  
C.G. Graham ◽  
G. Verboom ◽  
C.J. Shaw
Keyword(s):  
Water Wave ◽  
Wave Climate ◽  
Operational Planning ◽  
Extreme Value Analysis ◽  
Total Period ◽  
Value Analysis ◽  
Deep Water Wave ◽  
Buoy Data ◽  
Relative Differences ◽  
Wave Recorder

This paper presents the results of recent investigations at three sites where waves have been monitored simultaneously by two commonly used deep-water wave recorders, over a total period of 16 sensor-years. The study confirms earlier statements that there are relative differences between the wave parameters and statistical values calculated from the measurements of the two instruments. However, the large amount of data has enabled the authors to quantify the results in engineering terms and to assess the implications for extreme value analysis, spectral analysis and wave climate operational planning.

Covariate Extreme Value Analysis Using Wave Spectral Partitioning

2020 ◽  
Vol 37 (5) ◽  
pp. 873-888 ◽  
Author(s):  
Jesús Portilla-Yandún ◽  
Edwin Jácome
Keyword(s):  
Extreme Values ◽  
Wind Waves ◽  
Spectral Energy Distribution ◽  
Wave Spectrum ◽  
Wave Climate ◽  
Extreme Value ◽  
Extreme Value Analysis ◽  
Spectral Energy ◽  
Value Analysis ◽  
Spectral Partitioning

AbstractAn important requirement in extreme value analysis (EVA) is for the working variable to be identically distributed. However, this is typically not the case in wind waves, because energy components with different origins belong to separate data populations, with different statistical properties. Although this information is available in the wave spectrum, the working variable in EVA is typically the total significant wave height Hs, a parameter that does not contain information of the spectral energy distribution, and therefore does not fulfill this requirement. To gain insight in this aspect, we develop here a covariate EVA application based on spectral partitioning. We observe that in general the total Hs is inappropriate for EVA, leading to potential over- or underestimation of the projected extremes. This is illustrated with three representative cases under significantly different wave climate conditions. It is shown that the covariate analysis provides a meaningful understanding of the individual behavior of the wave components, in regard to the consequences for projecting extreme values.

Building a Global Resource for Rapid Assessment of the Wave Climate

2004 ◽  
Author(s):  
Cees de Valk ◽  
Peter Groenewoud ◽  
Sander Hulst ◽  
Gert Klopman
Keyword(s):  
Rapid Assessment ◽  
Wave Climate ◽  
Offshore Wind ◽  
Wave Transformation ◽  
Extreme Value Analysis ◽  
Radar Altimeter ◽  
Spectra Analysis ◽  
Value Analysis ◽  
Wave Hindcast ◽  
Wave Data

In order to provide rapid access to reliable wave and wind climate information worldwide, a resource has been created combining: • a global offshore wind- and wave data-base, currently containing calibrated and validated spectral wave data from a wave hindcast model as well data from several satellite microwave sensors; • a simple but effective numerical model to predict nearshore wave conditions from the offshore spectra; • analysis tools to extract various climate parameters from the data such as scatter tables, extreme value analysis and persistency; • a web interface giving instantaneous access to the most commonly needed information. The resource is primarily intended for use in planning and design of operations typically requiring five years of data, but it an also be used for the design of certain structures, as there are now 16 years of significant wave height data from satellite radar altimeter available. This paper describes the components of the system and discusses their merits and limitations. We also present some results of the validation of the global satellite wave and wind data, of the global and regional wave model hindcasts, and of the nearshore wave transformation employed to obtain wave climate at sheltered or shallow-water sites.

scholarly journals Extreme value analysis of wave climate around Farasan Islands, southern Red Sea

2020 ◽  
Vol 207 ◽  
pp. 107395 ◽  
Author(s):  
V.R. Shamji ◽  
V.M. Aboobacker ◽  
T.C. Vineesh
Keyword(s):  
Red Sea ◽  
Wave Climate ◽  
Extreme Value ◽  
Extreme Value Analysis ◽  
Value Analysis ◽  
Farasan Islands

scholarly journals Extreme Value Analysis of Dynamical Wave Climate Projections in the Mediterranean Sea

2015 ◽  
Vol 66 ◽  
pp. 210-219 ◽  
Author(s):  
Zacharias G. Kapelonis ◽  
Panagiotis N. Gavriliadis ◽  
Gerassimos A. Athanassoulis
Keyword(s):  
Mediterranean Sea ◽  
Wave Climate ◽  
Extreme Value ◽  
Extreme Value Analysis ◽  
Climate Projections ◽  
Value Analysis ◽  
The Mediterranean

Wave hindcast for the New Zealand region: Deep‐water wave climate

2003 ◽  
Vol 37 (3) ◽  
pp. 589-612 ◽  
Author(s):  
Richard M. Gorman ◽  
Karin R. Bryan ◽  
Andrew K. Laing
Keyword(s):  
New Zealand ◽  
Deep Water ◽  
Water Wave ◽  
Wave Climate ◽  
Wave Hindcast ◽  
Deep Water Wave

scholarly journals WIND WAVE FREQUENCIES IN A TROPICAL CYCLONE REGION

1978 ◽  
Vol 1 (16) ◽  
pp. 3
Author(s):  
Rodney J. Sobay
Keyword(s):  
Tropical Cyclone ◽  
Continental Shelf ◽  
Wind Wave ◽  
Wave Climate ◽  
Extreme Value Analysis ◽  
Local Wind ◽  
Value Analysis ◽  
Coral Sea ◽  
Wave Conditions

Australia's Coral Sea coast from Bundaberg north to Cape York has a wind wave climate that is almost unique. The coastline is afforded unparalleled protection from the 1900 km Great Barrier Reef, yet it lies in a tropical cyclone region and must expect recurrent intense wind and wave conditions. The Great Barrier Reef is a continuous chain of quite separate coral reef clusters located near the edge of the continental shelf. The separate reefs are often exposed at low tide, the inner fringe of the clusters ranges from 10 km offshore north of Cairns to 200 km offshore south of Rockhampton and the outer fringe is typically some 50 km further offshore, beyond which the ocean bed drops rapidly away. Incident wave energy from the Coral Sea is invariably dissipated on the outer edge of the Reef and wave conditions on the continental shelf can reasonably be considered due to local wind conditions. The Reef imposes an effective fetch limitations on wave generation over the continental shelf and there is, as a consequence, a moderately rapid response of wave conditions to changes in local wind conditions. A pronounced diurnal variation in the wind climate is reflected also in the wave climate and the stability of the region's tropical climate leads to frequent calm to slight sea conditions. This stability however is occasionally exploded by the generation and passage of a tropical cyclone in mid to late summer. Large waves can be generated by the intense winds of the tropical cyclone (hurricane or typhoon), often an order of magnitude greater than those in response to non-cyclonic events. The rational design of coastal structures and the rational pursuit of coastal zone management requires appropriate estimates of the frequency of occurrence of waves of various heights. Ideally such information is obtained from an extreme value analysis of long term wave records at the particular site in question. Permanent wave recording programs unfortunately have only become common practice in the present decade and wave records, if they exist at all for a particular site, are rarely long enough to allow a satisfactory extreme value analysis. It is clear, in the Australian context at least, that historical wave data alone is not yet sufficient to derive satisfactory estimates of long term wave frequencies. The alternative is system modelling. Wind is a major meteorological variable and its long term recording has been a standard meteorological practice now for over half a century.

Extreme value analysis of wave climate in Chesapeake Bay

2018 ◽  
Vol 159 ◽  
pp. 22-36 ◽  
Author(s):  
Arash Niroomandi ◽  
Gangfeng Ma ◽  
Xinyu Ye ◽  
Sha Lou ◽  
Pengfei Xue
Keyword(s):  
Chesapeake Bay ◽  
Wave Climate ◽  
Extreme Value ◽  
Extreme Value Analysis ◽  
Value Analysis

Uncertainties in Extreme Value Analysis of Wave Climate Data and Wave Climate Projections

2015 ◽  
Author(s):  
Erik Vanem
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Wave Climate ◽  
Extreme Value ◽  
Extreme Value Analysis ◽  
Climate Projections ◽  
Data Sets ◽  
Climate Data ◽  
Value Analysis ◽  
Significant Wave

The extreme values of climate data are of interest in design of marine structures and the return values of certain met-ocean parameters such as significant wave height is of particular importance. However, there are various ways of analyzing the extremes and estimating the required return values, which introduce additional uncertainties. These are investigated in this paper by applying different methods to particular data sets of significant wave height, corresponding to the historic climate and two future projections of the climate assuming different forcing scenarios. In this way, the uncertainty due to the extreme value analysis can also be compared to the uncertainty due to a changing climate. The different approaches that will be considered is the initial distribution approach, the block maxima approach, the peak over threshold (POT) approach and the average conditional exceedance rate method (ACER). Furthermore, the effect of different modelling choices within each of the approaches will be explored. Thus, a range of different return value estimates for the different data sets is obtained. This exercise reveals that the uncertainty due to the extreme value analysis method is notable and, as expected, the variability of the estimates increases for higher return periods. Moreover, even though the variability due to the extreme value analysis is greater than the climate variability, a shift towards higher extremes in a future wave climate can clearly be discerned in the particular datasets that have been analysed.

Southern California Deep-Water Wave Climate: Characterization and Application to Coastal Processes

2008 ◽  
Vol 244 ◽  
pp. 1022-1035 ◽  
Author(s):  
Peter N. Adams ◽  
Douglas L. Inman ◽  
Nicholas E. Graham
Keyword(s):  
Deep Water ◽  
Water Wave ◽  
Southern California ◽  
Wave Climate ◽  
Coastal Processes ◽  
Deep Water Wave
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