Non-stationary extreme value models to account for trends and shifts in the extreme wave climate due to climate change

2015 ◽  
Vol 52 ◽  
pp. 201-211 ◽  
Author(s):  
Erik Vanem
Keyword(s):  
Climate Change ◽  
Wave Climate ◽  
Extreme Value ◽  
Extreme Wave ◽  
And Shifts

scholarly journals Future behavior of wind wave extremes due to climate change

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hector Lobeto ◽  
Melisa Menendez ◽  
Iñigo J. Losada
Keyword(s):  
Climate Change ◽  
Wave Climate ◽  
Climate Change Scenarios ◽  
Return Periods ◽  
Extreme Wave ◽  
Future Behavior ◽  
Climate Simulations ◽  
Wave Conditions ◽  
Ne Pacific ◽  
Change In Mean

AbstractExtreme waves will undergo changes in the future when exposed to different climate change scenarios. These changes are evaluated through the analysis of significant wave height (Hs) return values and are also compared with annual mean Hs projections. Hourly time series are analyzed through a seven-member ensemble of wave climate simulations and changes are estimated in Hs for return periods from 5 to 100 years by the end of the century under RCP4.5 and RCP8.5 scenarios. Despite the underlying uncertainty that characterizes extremes, we obtain robust changes in extreme Hs over more than approximately 25% of the ocean surface. The results obtained conclude that increases cover wider areas and are larger in magnitude than decreases for higher return periods. The Southern Ocean is the region where the most robust increase in extreme Hs is projected, showing local increases of over 2 m regardless the analyzed return period under RCP8.5 scenario. On the contrary, the tropical north Pacific shows the most robust decrease in extreme Hs, with local decreases of over 1.5 m. Relevant divergences are found in several ocean regions between the projected behavior of mean and extreme wave conditions. For example, an increase in Hs return values and a decrease in annual mean Hs is found in the SE Indian, NW Atlantic and NE Pacific. Therefore, an extrapolation of the expected change in mean wave conditions to extremes in regions presenting such divergences should be adopted with caution, since it may lead to misinterpretation when used for the design of marine structures or in the evaluation of coastal flooding and erosion.

Impacts of Climate Change on Extreme Wave Climate Along the Western Coast of Sri Lanka

2016 ◽  
Author(s):  
R. M. J. Bamunawala ◽  
S. S. L. Hettiarachchi ◽  
S. P. Samarawickrama ◽  
P. N. Wikramanayake ◽  
Roshanka Ranasinghe
Keyword(s):  
Climate Change ◽  
Sri Lanka ◽  
Wave Climate ◽  
Western Coast ◽  
Extreme Wave ◽  
Impacts Of Climate Change

EXTREME WAVE CLIMATE CHANGE PROJECTION AT THE END OF 21STCENTURY

2011 ◽  
pp. 341-348 ◽  
Author(s):  
TOMOYA SHIMURA ◽  
NOBUHITO MORI ◽  
SOTA NAKAJO ◽  
TOMOHRO YASUDA ◽  
HAJIME MASE
Keyword(s):  
Climate Change ◽  
Wave Climate ◽  
Extreme Wave ◽  
Climate Change Projection

scholarly journals Projection of Extreme Wave Climate Change under Global Warming

2010 ◽  
Vol 4 (0) ◽  
pp. 15-19 ◽  
Author(s):  
Nobuhito Mori ◽  
Tomohiro Yasuda ◽  
Hajime Mase ◽  
Tracey Tom ◽  
Yuichiro Oku
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Wave Climate ◽  
Extreme Wave

scholarly journals Nonstationary Extreme Value Analysis of Nearshore Sea-State Parameters under the Effects of Climate Change: Application to the Greek Coastal Zone and Port Structures

2021 ◽  
Vol 9 (8) ◽  
pp. 817
Author(s):  
Panagiota Galiatsatou ◽  
Christos Makris ◽  
Yannis Krestenitis ◽  
Panagiotis Prinos
Keyword(s):  
Climate Change ◽  
Sea Level ◽  
Storm Surges ◽  
Extreme Value ◽  
Extreme Value Analysis ◽  
Extreme Wave ◽  
Sea State ◽  
Value Analysis ◽  
Wave Characteristics ◽  
Failure Probabilities

In the present work, a methodological framework, based on nonstationary extreme value analysis of nearshore sea-state parameters, is proposed for the identification of climate change impacts on coastal zone and port defense structures. The applications refer to the estimation of coastal hazards on characteristic Mediterranean microtidal littoral zones and the calculation of failure probabilities of typical rubble mound breakwaters in Greek ports. The proposed methodology hinges on the extraction of extreme wave characteristics and sea levels due to storm events affecting the coast, a nonstationary extreme value analysis of sea-state parameters and coastal responses using moving time windows, a fitting of parametric trends to nonstationary parameter estimates of the extreme value models, and an assessment of nonstationary failure probabilities on engineered port protection. The analysis includes estimation of extreme total water level (TWL) on several Greek coasts to approximate the projected coastal flooding hazard under climate change conditions in the 21st century. The TWL calculation considers the wave characteristics, sea level height due to storm surges, mean sea level (MSL) rise, and astronomical tidal ranges of the study areas. Moreover, the failure probabilities of a typical coastal defense structure are assessed for several failure mechanisms, considering variations in MSL, extreme wave climates, and storm surges in the vicinity of ports, within the framework of reliability analysis based on the nonstationary generalized extreme value (GEV) distribution. The methodology supports the investigation of future safety levels and possible periods of increased vulnerability of the studied structure to different ultimate limit states under extreme marine weather conditions associated with climate change, aiming at the development of appropriate upgrading solutions. The analysis suggests that the assumption of stationarity might underestimate the total failure probability of coastal structures under future extreme marine conditions.

Structural safety and design under climate change

2019 ◽  
Author(s):  
Pietro Croce ◽  
Paolo Formichi ◽  
Filippo Landi
Keyword(s):  
Climate Change ◽  
Greenhouse Gas ◽  
Structural Reliability ◽  
Greenhouse Gas Emission ◽  
Extreme Value ◽  
Structural Safety ◽  
Climate Projections ◽  
Climate Conditions ◽  
Impact Of Climate Change ◽  
The Impact

<p>The impact of climate change on climatic actions could significantly affect, in the mid-term future, the design of new structures as well as the reliability of existing ones designed in accordance to the provisions of present and past codes. Indeed, current climatic loads are defined under the assumption of stationary climate conditions but climate is not stationary and the current accelerated rate of changes imposes to consider its effects.</p><p>Increase of greenhouse gas emissions generally induces a global increase of the average temperature, but at local scale, the consequences of this phenomenon could be much more complex and even apparently not coherent with the global trend of main climatic parameters, like for example, temperature, rainfalls, snowfalls and wind velocity.</p><p>In the paper, a general methodology is presented, aiming to evaluate the impact of climate change on structural design, as the result of variations of characteristic values of the most relevant climatic actions over time. The proposed procedure is based on the analysis of an ensemble of climate projections provided according a medium and a high greenhouse gas emission scenario. Factor of change for extreme value distribution’s parameters and return values are thus estimated in subsequent time windows providing guidance for adaptation of the current definition of structural loads.</p><p>The methodology is illustrated together with the outcomes obtained for snow, wind and thermal actions in Italy. Finally, starting from the estimated changes in extreme value parameters, the influence on the long-term structural reliability can be investigated comparing the resulting time dependent reliability with the reference reliability levels adopted in modern Structural codes.</p>

Statistical Analysis on the Extreme Events of Big Waves Under Wave Climate Change Around Taiwan Waters

2011 ◽  
Author(s):  
Ching-Her Hwang ◽  
Wen-Ching Lee ◽  
Wen-Fang Hsieh ◽  
Ching-Piao Tsai ◽  
Hwa Chien
Keyword(s):  
Climate Change ◽  
Wave Field ◽  
Extreme Events ◽  
Wind Field ◽  
Wave Climate ◽  
Model Parameters ◽  
Climate Change Research ◽  
Weather Bureau ◽  
Central Weather Bureau ◽  
Typhoon Wind

This study aimed to analyze the statistical characteristics of wave heights, wave energy and wave steepness, in order to investigate the wave climate changes around Taiwan Waters, especially for extreme events of big waves. The operational observation of Taiwan sea waves was initiated by the Central Weather Bureau in 1998; however, due to insufficient data length and low data space coverage, the data are unable to serve as references for long-term wave climate change research. Hence, this study adopted the SWAN (Simulation of Wave in Nearshore) Numerical Wave Hindcasting Method, which is a common method used in many studies, to hindcast the history of a wave field. The re-analysis on wind field data of the last 60 years (1948∼2008), published by the National Centers for Environmental Prediction (NCEP), was employed to make the wind field grid consistent with the hindcast wave field grid. Moreover, the Typhoon Wind Field Grid Down Scaling technique proposed by Winter & Chiou (2007) was applied to interpolate a U10 analysis field that better fits an actual typhoon wind field. The hindcast wave data were compared and validated with directional spectra, which were observed by the meteorological/oceanographic data buoys set up by the Central Weather Bureau and Water Resources Agency since 1997. Longdong, Hualien and Hsinchu Stations were chosen to represent the wave characteristics of sea areas around the island of Taiwan. According to observation data, model parameters were adjusted so that the hindcast results could be closer to observed data in Taiwan sea areas.

scholarly journals Automated classification of the atmospheric circulation patterns that drive regional wave climates

2014 ◽  
Vol 14 (8) ◽  
pp. 2145-2155 ◽  
Author(s):  
J. Pringle ◽  
D. D. Stretch ◽  
A. Bárdossy
Keyword(s):  
Atmospheric Circulation ◽  
Low Pressure ◽  
Wave Climate ◽  
Automated Classification ◽  
Coastal Vulnerability ◽  
Extreme Wave ◽  
Atmospheric Circulation Patterns ◽  
Circulation Patterns ◽  
Spatially Distributed ◽  
Wave Heights

Abstract. Wave climates are fundamental drivers of coastal vulnerability; changing trends in wave heights, periods and directions can severely impact a coastline. In a diverse storm environment, the changes in these parameters are difficult to detect and quantify. Since wave climates are linked to atmospheric circulation patterns, an automated and objective classification scheme was developed to explore links between synoptic-scale circulation patterns and wave climate variables, specifically wave heights. The algorithm uses a set of objective functions based on wave heights to guide the classification and find atmospheric classes with strong links to wave behaviour. Spatially distributed fuzzy numbers define the classes and are used to detect locally high- and low-pressure anomalies. Classes are derived through a process of simulated annealing. The optimized classification focuses on extreme wave events. The east coast of South Africa was used as a case study. The results show that three dominant patterns drive extreme wave events. The circulation patterns exhibit some seasonality with one pattern present throughout the year. Some 50–80% of the extreme wave events are explained by these three patterns. It is evident that strong low-pressure anomalies east of the country drive a wind towards the KwaZulu-Natal coastline which results in extreme wave conditions. We conclude that the methodology can be used to link circulation patterns to wave heights within a diverse storm environment. The circulation patterns agree with qualitative observations of wave climate drivers. There are applications to the assessment of coastal vulnerability and the management of coastlines worldwide.

scholarly journals Distinguishing Trends and Shifts from Memory in Climate Data

2018 ◽  
Vol 31 (23) ◽  
pp. 9519-9543 ◽  
Author(s):  
Claudie Beaulieu ◽  
Rebecca Killick
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Information Criterion ◽  
Steady Increase ◽  
Climate Data ◽  
Surface Warming ◽  
Abrupt Changes ◽  
Short Memory Process ◽  
The 1960S ◽  
And Shifts

The detection of climate change and its attribution to the corresponding underlying processes is challenging because signals such as trends and shifts are superposed on variability arising from the memory within the climate system. Statistical methods used to characterize change in time series must be flexible enough to distinguish these components. Here we propose an approach tailored to distinguish these different modes of change by fitting a series of models and selecting the most suitable one according to an information criterion. The models involve combinations of a constant mean or a trend superposed to a background of white noise with or without autocorrelation to characterize the memory, and are able to detect multiple changepoints in each model configuration. Through a simulation study on synthetic time series, the approach is shown to be effective in distinguishing abrupt changes from trends and memory by identifying the true number and timing of abrupt changes when they are present. Furthermore, the proposed method is better performing than two commonly used approaches for the detection of abrupt changes in climate time series. Using this approach, the so-called hiatus in recent global mean surface warming fails to be detected as a shift in the rate of temperature rise but is instead consistent with steady increase since the 1960s/1970s. Our method also supports the hypothesis that the Pacific decadal oscillation behaves as a short-memory process rather than forced mean shifts as previously suggested. These examples demonstrate the usefulness of the proposed approach for change detection and for avoiding the most pervasive types of mistake in the detection of climate change.

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