scholarly journals Projected incremental changes to extreme wind-driven wave heights for the twenty-first century

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
J. G. O’Grady ◽  
M. A. Hemer ◽  
K. L. McInnes ◽  
C. E. Trenham ◽  
A. G. Stephenson
Keyword(s):  
Global Climate ◽  
Global Scale ◽  
First Century ◽  
Extreme Value Analysis ◽  
Extreme Wave ◽  
Value Analysis ◽  
Incremental Change ◽  
Wave Heights ◽  
Twenty First Century ◽  
Wind Sea

AbstractGlobal climate change will alter wind sea and swell waves, modifying the severity, frequency and impact of episodic coastal flooding and morphological change. Global-scale estimates of increases to coastal impacts have been typically attributed to sea level rise and not specifically to changes to waves on their own. This study provides a reduced complexity method for applying projected extreme wave changes to local scale impact studies. We use non-stationary extreme value analysis to distil an incremental change signal in extreme wave heights and associate this with a change in the frequency of events globally. Extreme wave heights are not projected to increase everywhere. We find that the largest increases will typically be experienced at higher latitudes, and that there is high ensemble model agreement on an increase (doubling of events) for the waters south of Australia, the Arabian Sea and the Gulf of Guinea by the end of the twenty-first century.

Bias and Uncertainty in the Estimation of Extreme Wave Heights and Crests

2009 ◽  
Author(s):  
Richard Gibson ◽  
Colin Grant ◽  
George Z. Forristall ◽  
Rory Smyth ◽  
Peter Owrid ◽  
...  
Keyword(s):  
North Sea ◽  
Extreme Value ◽  
Accurate Prediction ◽  
Design Parameters ◽  
Extreme Value Analysis ◽  
Extreme Wave ◽  
Data Set ◽  
Value Analysis ◽  
Design Values ◽  
Wave Heights

The accurate prediction of extreme wave heights and crests is important to the design of offshore structures. For example, knowledge of the extreme crest elevation is required to set the deck elevation of the topside of a jacket structure. However, methods of extreme value analysis have an inherent bias, and the manner in which they are applied affects this bias. Furthermore, there is uncertainty in the design parameters at the time of design and the possibility that the predictions will change during the life of the structure. This paper is concerned with the accurate prediction of design values that incorporate uncertainty. In the first part of this paper the details of commonly applied extreme value analysis techniques are examined. This is achieved through analysis of simulated data of known distribution. In particular it is the application of least squares minimisation routines that is investigated; however, comparisons are made with maximum likelihood estimation. From this, preferred approaches to the analysis are recommended and their advantages and disadvantages discussed. The methods are applied to the analysis of a North Sea data set and the implications for the design values ascertained. In the second part of the paper Bayesian inference is used to consider the effect of uncertainty in the predicted wave heights and crest elevations. The practical implications are determined by the analysis of a measured North Sea data set.

Spatial stochastic simulation to aid local extreme value analysis of cyclone-induced wave heights when numerical hydrodynamic simulations are scarce

2021 ◽  
Author(s):  
Jeremy Rohmer ◽  
Rodrigo Pedreros ◽  
Yann Krien
Keyword(s):  
Confidence Interval ◽  
Stochastic Simulation ◽  
Extreme Value ◽  
Return Level ◽  
Extreme Value Analysis ◽  
Percentage Error ◽  
Value Analysis ◽  
Return Levels ◽  
Wave Heights ◽  
Local Extreme

<p>To estimate return levels of wave heights (Hs) induced by tropical cyclones at the coast, a commonly-used approach is to (1) randomly generate a large number of synthetic cyclone events (typically >1,000); (2) numerically simulate the corresponding Hs over the whole domain of interest; (3) extract the Hs values at the desired location at the coast and (4) perform the local extreme value analysis (EVA) to derive the corresponding return level. Step 2 is however very constraining because it often involves a numerical hydrodynamic simulator that can be prohibitive to run: this might limit the number of results to perform the local EVA (typically to several hundreds). In this communication, we propose a spatial stochastic simulation procedure to increase the database size of numerical results with synthetic maps of Hs that are stochastically generated. To do so, we propose to rely on a data-driven dimensionality-reduction method, either unsupervised (Principal Component Analysis) or supervised (Partial Least Squares Regression), that is trained with a limited number of pre-existing numerically simulated Hs maps. The procedure is applied to the Guadeloupe island and results are compared to the commonly-used approach applied to a large database of Hs values computed for nearly 2,000 synthetic cyclones (representative of 3,200 years – Krien et al., NHESS, 2015). When using only a hundred of cyclones, we show that the estimates of the 100-year return levels can be achieved with a mean absolute percentage error (derived from a bootstrap-based procedure) ranging between 5 and 15% around the coasts while keeping the width of the 95% confidence interval of the same order of magnitude than the one using the full database. Without synthetic Hs maps augmentation, the error and confidence interval width are both increased by nearly 100%. A careful attention is paid to the tuning of the approach by testing the sensitivity to the spatial domain size, the information loss due to data compression, and the number of cyclones. This study has been carried within the Carib-Coast INTERREG project (https://www.interreg-caraibes.fr/carib-coast).</p>

Drivers of Twenty-First Century U.S. Winter Precipitation Trends in CMIP6 Models: A Storyline-Based Approach

2021 ◽  
pp. 1-48
Author(s):  
Daniel F. Schmidt ◽  
Kevin M. Grise
Keyword(s):  
Climate Models ◽  
Southern Oscillation ◽  
Global Climate ◽  
The United States ◽  
Winter Precipitation ◽  
Global Climate Models ◽  
First Century ◽  
Precipitation Trend ◽  
Twenty First Century ◽  
Precipitation Trends

AbstractClimate change during the twenty-first century has the potential to substantially alter geographic patterns of precipitation. However, regional precipitation changes can be very difficult to project, and in some regions, global climate models do not even agree on the sign of the precipitation trend. Since some of this uncertainty is due to internal variability rather than model bias, models cannot be used to narrow the possibilities to a single outcome, but they can usefully quantify the range of plausible outcomes and identify the combination of dynamical drivers that would be likely to produce each.This study uses a storylines approach—a type of regression-based analysis—to identify some of the key dynamical drivers that explain the variance in 21st century U.S. winter precipitation trends across CMIP6 models under the SSP3-7.0 emissions scenario. This analysis shows that the spread in precipitation trends is not primarily driven by differences in modeled climate sensitivity. Key drivers include global-mean surface temperature, but also tropical upper-troposphere temperature, the El Niño-Southern Oscillation (ENSO), the Pacific-North America (PNA) pattern, and the East Pacific (EP) dipole (a dipole pattern in geopotential heights over North America’s Pacific coast). Combinations of these drivers can reinforce or cancel to produce various high- or low-impact scenarios for winter precipitation trends in various regions of the United States. For example, the most extreme winter precipitation trends in the southwestern U.S. result from opposite trends in ENSO and EP, whereas the wettest winter precipitation trends in the midwestern U.S. result from a combination of strong global warming and a negative PNA trend.

Twenty-First-Century Virtue

2021 ◽  
pp. 77-96
Author(s):  
Shannon Vallor
Keyword(s):  
Virtue Ethics ◽  
Contemporary Problem ◽  
Emerging Technologies ◽  
Global Scale ◽  
Human Condition ◽  
First Century ◽  
Philosophical Tradition ◽  
Ethical Decisions ◽  
Twenty First Century ◽  
Classical Traditions

This chapter identifies the growing difficulty of making ethical decisions—choices that aim at the “good life”—in our present human condition, one in which the unpredictable, complex, and destabilizing effects of emerging technologies on a global scale make the shape of the human future increasingly opaque and hard to fathom. The chapter suggests that this twenty-first-century challenge for ethics, which we can identify as a state of acute technosocial opacity, is best addressed from a particular philosophical tradition: virtue ethics. It argues that the classical traditions of Aristotelian, Confucian, and Buddhist virtue ethics offer us more resources for managing this contemporary problem than do other, more modern moral theories. The chapter concludes that only the cultivation of distinctly technomoral virtues will preserve humanity’s chances to live well with emerging technologies, and flourish in an increasingly opaque future.

scholarly journals Global Increasing Trends in Annual Maximum Daily Precipitation

2013 ◽  
Vol 26 (11) ◽  
pp. 3904-3918 ◽  
Author(s):  
Seth Westra ◽  
Lisa V. Alexander ◽  
Francis W. Zwiers
Keyword(s):  
Surface Temperature ◽  
Daily Precipitation ◽  
Global Scale ◽  
Extreme Value Analysis ◽  
Trend Test ◽  
Precipitation Data ◽  
Annual Maximum ◽  
Value Analysis ◽  
Near Surface ◽  
Increasing Trends

Abstract This study investigates the presence of trends in annual maximum daily precipitation time series obtained from a global dataset of 8326 high-quality land-based observing stations with more than 30 years of record over the period from 1900 to 2009. Two complementary statistical techniques were adopted to evaluate the possible nonstationary behavior of these precipitation data. The first was a Mann–Kendall nonparametric trend test, and it was used to evaluate the existence of monotonic trends. The second was a nonstationary generalized extreme value analysis, and it was used to determine the strength of association between the precipitation extremes and globally averaged near-surface temperature. The outcomes are that statistically significant increasing trends can be detected at the global scale, with close to two-thirds of stations showing increases. Furthermore, there is a statistically significant association with globally averaged near-surface temperature, with the median intensity of extreme precipitation changing in proportion with changes in global mean temperature at a rate of between 5.9% and 7.7% K−1, depending on the method of analysis. This ratio was robust irrespective of record length or time period considered and was not strongly biased by the uneven global coverage of precipitation data. Finally, there is a distinct meridional variation, with the greatest sensitivity occurring in the tropics and higher latitudes and the minima around 13°S and 11°N. The greatest uncertainty was near the equator because of the limited number of sufficiently long precipitation records, and there remains an urgent need to improve data collection in this region to better constrain future changes in tropical precipitation.

scholarly journals Characterization of Extreme Wave Conditions for Wave Energy Converter Design and Project Risk Assessment

2020 ◽  
Vol 8 (4) ◽  
pp. 289 ◽  
Author(s):  
Vincent S. Neary ◽  
Seongho Ahn ◽  
Bibiana E. Seng ◽  
Mohammad Nabi Allahdadi ◽  
Taiping Wang ◽  
...  
Keyword(s):  
Return Period ◽  
Wave Energy ◽  
Wave Energy Converter ◽  
Extreme Value Analysis ◽  
Extreme Wave ◽  
Energy Converter ◽  
Sea State ◽  
Value Analysis ◽  
Wave Conditions ◽  
Wave Models

Best practices and international standards for determining n-year return period extreme wave (sea states) conditions allow wave energy converter designers and project developers the option to apply simple univariate or more complex bivariate extreme value analysis methods. The present study compares extreme sea state estimates derived from univariate and bivariate methods and investigates the performance of spectral wave models for predicting extreme sea states at buoy locations within several regional wave climates along the US East and West Coasts. Two common third-generation spectral wave models are evaluated, a WAVEWATCH III® model with a grid resolution of 4 arc-minutes (6–7 km), and a Simulating WAves Nearshore model, with a coastal resolution of 200–300 m. Both models are used to generate multi-year hindcasts, from which extreme sea state statistics used for wave conditions characterization can be derived and compared to those based on in-situ observations at National Data Buoy Center stations. Comparison of results using different univariate and bivariate methods from the same data source indicates reasonable agreement on average. Discrepancies are predominantly random. Large discrepancies are common and increase with return period. There is a systematic underbias for extreme significant wave heights derived from model hindcasts compared to those derived from buoy measurements. This underbias is dependent on model spatial resolution. However, simple linear corrections can effectively compensate for this bias. A similar approach is not possible for correcting model-derived environmental contours, but other methods, e.g., machine learning, should be explored.

Interhemispheric Temperature Asymmetry over the Twentieth Century and in Future Projections

2013 ◽  
Vol 26 (15) ◽  
pp. 5419-5433 ◽  
Author(s):  
Andrew R. Friedman ◽  
Yen-Ting Hwang ◽  
John C. H. Chiang ◽  
Dargan M. W. Frierson
Keyword(s):  
Twentieth Century ◽  
Global Climate ◽  
First Century ◽  
The Arctic ◽  
Positive Trend ◽  
Anthropogenic Aerosols ◽  
Abrupt Decrease ◽  
Tropical Rainfall ◽  
Twenty First Century ◽  
Temperature Asymmetry

Abstract The temperature contrast between the Northern and Southern Hemispheres—the interhemispheric temperature asymmetry (ITA)—is an emerging indicator of global climate change, potentially relevant to the Hadley circulation and tropical rainfall. The authors examine the ITA in historical observations and in phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5) simulations. The observed annual-mean ITA (north minus south) has varied within a 0.8°C range and features a significant positive trend since 1980. The CMIP multimodel ensembles simulate this trend, with a stronger and more realistic signal in CMIP5. Both ensembles project a continued increase in the ITA over the twenty-first century, well outside the twentieth-century range. The authors mainly attribute this increase to the uneven spatial impacts of greenhouse forcing, which result in amplified warming in the Arctic and northern landmasses. The CMIP5 specific-forcing simulations indicate that, before 1980, the greenhouse-forced ITA trend was primarily countered by anthropogenic aerosols. The authors also identify an abrupt decrease in the observed ITA in the late 1960s, which is generally not present in the CMIP simulations; it suggests that the observed drop was caused by internal variability. The difference in the strengths of the northern and southern Hadley cells covaries with the ITA in the CMIP5 simulations, in accordance with previous findings; the authors also find an association with the hemispheric asymmetry in tropical rainfall. These relationships imply a northward shift in tropical rainfall with increasing ITA in the twenty-first century, though this result is difficult to separate from the response to global-mean temperature change.

Square Error Method for threshold estimation in extreme value analysis of wave heights

2017 ◽  
Vol 137 ◽  
pp. 138-150 ◽  
Author(s):  
F. Silva-González ◽  
E. Heredia-Zavoni ◽  
G. Inda-Sarmiento
Keyword(s):  
Extreme Value ◽  
Extreme Value Analysis ◽  
Threshold Estimation ◽  
Value Analysis ◽  
Wave Heights ◽  
Error Method

Impacts and responses to sea-level rise: a global analysis of the SRES scenarios over the twenty-first century

2006 ◽  
Vol 364 (1841) ◽  
pp. 1073-1095 ◽  
Author(s):  
Robert J Nicholls ◽  
Richard S.J Tol
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Global Analysis ◽  
Cost Benefit ◽  
Atmospheric Temperature ◽  
Global Scale ◽  
First Century ◽  
Twenty First Century ◽  
Sres Scenarios ◽  
The Impact

Taking the Special Report on Emission Scenarios (SRES) climate and socio-economic scenarios (A1FI, A2, B1 and B2 ‘future worlds’), the potential impacts of sea-level rise through the twenty-first century are explored using complementary impact and economic analysis methods at the global scale. These methods have never been explored together previously. In all scenarios, the exposure and hence the impact potential due to increased flooding by sea-level rise increases significantly compared to the base year (1990). While mitigation reduces impacts, due to the lagged response of sea-level rise to atmospheric temperature rise, impacts cannot be avoided during the twenty-first century by this response alone. Cost–benefit analyses suggest that widespread protection will be an economically rational response to land loss due to sea-level rise in the four SRES futures that are considered. The most vulnerable future worlds to sea-level rise appear to be the A2 and B2 scenarios, which primarily reflects differences in the socio-economic situation (coastal population, Gross Domestic Product (GDP) and GDP/capita), rather than the magnitude of sea-level rise. Small islands and deltaic settings stand out as being more vulnerable as shown in many earlier analyses. Collectively, these results suggest that human societies will have more choice in how they respond to sea-level rise than is often assumed. However, this conclusion needs to be tempered by recognition that we still do not understand these choices and significant impacts remain possible. Future worlds which experience larger rises in sea-level than considered here (above 35 cm), more extreme events, a reactive rather than proactive approach to adaptation, and where GDP growth is slower or more unequal than in the SRES futures remain a concern. There is considerable scope for further research to better understand these diverse issues.

scholarly journals ESTIMATING GLOBAL SEA LEVEL VARIATIONS AND RESULTING INUNDATION EXPOSURE

2018 ◽  
pp. 71
Author(s):  
Ebru Demirci ◽  
Ian Young
Keyword(s):  
Sea Level ◽  
Global Scale ◽  
Extreme Value Analysis ◽  
Breaking Wave ◽  
Value Analysis ◽  
Sea Levels ◽  
Long Duration ◽  
Flood Exposure ◽  
Coastal Flood Risk ◽  
Global Sea Level

Concerns about climate change highlights the needs to understand extreme sea levels and the resulting flood exposure in coastal areas on a global scale. The combined impacts of storm surge, tide, breaking wave setup and potential sea level rise will pose many economic, societal and engineering challenges in coming years. In order to predict the global coastal flood risk, a global sea level dataset of sufficiently long duration is required to undertake extreme value analysis. This presentation will outline the development and application of such a dataset.

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