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Author: Michael Getachew Tadesse Publisher: ISBN: Category : Languages : en Pages : 0
Book Description
Storm surge is the deadliest component of extreme sea levels with one of the highest global death tolls per event. Tide gauges are the primary sources for historical sea-level measurements from which storm surge data is extracted. However, tide gauges are unevenly distributed across the globe, and most records are short in length and have gaps; this creates a challenge to assess long-term trends and perform robust extreme value analysis. This dissertation introduces a data-driven storm surge modeling framework that trains statistical and machine learning models with atmospheric and oceanographic variables. Data-driven models (DDMs) are trained and validated for more than 800 tide gauges globally using datasets that are obtained from tide gauges, satellites, and atmospheric reanalyses. By forcing DDMs with five atmospheric reanalyses, a database of global daily maximum storm surge reconstructions (GSSR, http://gssr.info) is provided for 882 tide gauges covering the 1836-2019 period. The reconstruction datasets provide an opportunity to perform long-term trend analysis and robust extreme value analysis. However, some atmospheric reanalyses have inhomogeneities that translate to surge reconstructions, introducing spurious trends not reflected in observed surges. A Bayesian change point detection method has been applied to identify and remove spurious trends from GSSR surge reconstructions. It is shown in this dissertation, that after the change point analysis, GSSR provides several decades of additional reconstructed surge data in addition to what is already available from sea-level measurements. Utilizing the post-processed surge reconstructions, a long-term trend analysis of storm surge climate has been carried out globally, particularly with respect to the magnitude and frequency of storm surges. Trends are also separately computed for the satellite-era where all five GSSR reconstructions and observed surges overlap. It is shown that the use of ensemble surge reconstructions is advisable, if possible, rather than using a single reconstruction to account for uncertainties stemming from atmospheric reanalyses.
Author: Michael Getachew Tadesse Publisher: ISBN: Category : Languages : en Pages : 0
Book Description
Storm surge is the deadliest component of extreme sea levels with one of the highest global death tolls per event. Tide gauges are the primary sources for historical sea-level measurements from which storm surge data is extracted. However, tide gauges are unevenly distributed across the globe, and most records are short in length and have gaps; this creates a challenge to assess long-term trends and perform robust extreme value analysis. This dissertation introduces a data-driven storm surge modeling framework that trains statistical and machine learning models with atmospheric and oceanographic variables. Data-driven models (DDMs) are trained and validated for more than 800 tide gauges globally using datasets that are obtained from tide gauges, satellites, and atmospheric reanalyses. By forcing DDMs with five atmospheric reanalyses, a database of global daily maximum storm surge reconstructions (GSSR, http://gssr.info) is provided for 882 tide gauges covering the 1836-2019 period. The reconstruction datasets provide an opportunity to perform long-term trend analysis and robust extreme value analysis. However, some atmospheric reanalyses have inhomogeneities that translate to surge reconstructions, introducing spurious trends not reflected in observed surges. A Bayesian change point detection method has been applied to identify and remove spurious trends from GSSR surge reconstructions. It is shown in this dissertation, that after the change point analysis, GSSR provides several decades of additional reconstructed surge data in addition to what is already available from sea-level measurements. Utilizing the post-processed surge reconstructions, a long-term trend analysis of storm surge climate has been carried out globally, particularly with respect to the magnitude and frequency of storm surges. Trends are also separately computed for the satellite-era where all five GSSR reconstructions and observed surges overlap. It is shown that the use of ensemble surge reconstructions is advisable, if possible, rather than using a single reconstruction to account for uncertainties stemming from atmospheric reanalyses.
Author: Michael Siek Publisher: CRC Press ISBN: 041562102X Category : Science Languages : en Pages : 239
Book Description
Accurate predictions of storm surge are of importance in many coastal areas in the world to avoid and mitigate its destructive impacts. For this purpose the physically-based (process) numerical models are typically utilized. However, in data-rich cases, one may use data-driven methods aiming at reconstructing the internal patterns of the modelled processes and relationships between the observed descriptive variables. This book focuses on data-driven modelling using methods of nonlinear dynamics and chaos theory. First, some fundamentals of physical oceanography, nonlinear dynamics and chaos, computational intelligence and European operational storm surge models are covered. After that a number of improvements in building chaotic models are presented: nonlinear time series analysis, multi-step prediction, phase space dimensionality reduction, techniques dealing with incomplete time series, phase error correction, finding true neighbours, optimization of chaotic model, data assimilation and multi-model ensemble prediction. The major case study is surge prediction in the North Sea, with some tests on a Caribbean Sea case. The modelling results showed that the enhanced predictive chaotic models can serve as an efficient tool for accurate and reliable short and mid-term predictions of storm surges in order to support decision-makers for flood prediction and ship navigation.
Author: H. Kremer Publisher: Springer ISBN: 9789400767126 Category : Science Languages : en Pages : 0
Book Description
Storm surges represent a major hazard for many coastal regions worldwide. The 1953 and 1962 catastrophes are well remembered in Europe, and recent incidents in Bangladesh and Myanmar caused over 100,000 casualties. Developing innovative responses and overcoming the frequently fragmented discussion about this global phenomenon and its regional implications call for improved knowledge of present risks and future conditions based on sound interdisciplinary approaches. This selection of articles presents multiple scientific and management oriented perspectives on current and future storm surges, covering the fields of observing, modelling and forecasting, risk and vulnerability analysis, planning and innovative coastal protection concepts. It originates from the international ‘2010 Storm Surges Congress - Risk and Management of Current and Future Storm Surges,’ initiated and organized by the Institute of Coastal Research, Helmholtz-Zentrum Geesthacht (formerly the GKSS-Research Centre) in collaboration with the KlimaCampus (CliSAP) of the University of Hamburg, Germany. The Land-Ocean Interactions in the Coastal Zone (LOICZ) co-sponsored the event and its international project office (IPO) provided the necessary organizational support. The congress was generously supported by international and national partners. Some highlights: Remote sensing surveillance and mapping of storm surge extent based on NASA MODIS sensors may ultimately provide new global insights into the vulnerability of deltas where human pressures outbalance natural land-ocean forcing. Up-scaling hazard lines and risk mapping from local to full continental scale is the ambition in India. From an insurance risk perspective, its societal perception and economic issues determine societal response options. In urban contexts flood risk is anticipated as a combination of climate change-induced sea level rise and socio-economic drivers. A cost-benefit analysis of flood defence in London underlines the fact that future investment will be highly beneficial; thoughtful planning rather than rushing to new engineering solutions is preferable. Several modelling case studies and approaches are presented, covering the effects of individual storms, the development of analytical models that can help us to understand relevant processes and mechanisms, and sensitivity studies that test the impact and relevance of various physical processes for storm surge generation and evolution. Hydrodynamic models applied to different emission scenarios suggest that the threat of extreme storm surges in the North Sea may increase but strong decadal fluctuations and internal variability need to be considered. A Korean study suggests that future global warming may not always lead to an increase in the number of intense cyclones or the magnitude of associated storm surges. Past and recent storm surges arising at the dune coast of France call for improved assessment and management of a growing flood risk in future sea-level rise projections. In the same context rather than deterministic approaches, considering the uncertainties that influence extreme water levels can significantly improve the design levels of coastal structures and flood defences. The innovative Dutch “Building with Nature” concept employs natural processes for coastal flood protection. Previously published in Natural Hazards, Volume 66, No. 3, 2013
Author: Masaya Toyoda Publisher: CRC Press ISBN: 1040148042 Category : Technology & Engineering Languages : en Pages : 105
Book Description
This accessible shortform book describes storm surge forecasting to enable port managers and practitioners to forecast these and mitigate their effects. This is particularly useful as global warming increases the severity of typhoons, particularly windstorms and storm surge disasters, globally. The authors first summarize the current status of typhoons and storm surges in practice. They also present a combination of the latest findings at the research level and at the practical level. Throughout the book, the authors carefully explain the use and limitations of empirical typhoon models that practitioners should learn from, including statistical, numerical, probabilistic, data-driven and coastal vulnerability models. They also explore artificial neural networks and convolutional neural networks and their use in such models. Finally, the book describes the potential for further development of empirical typhoon models (such as future climate experiments). This book is a vital resource that enables port managers to make effective and informed decisions when conducting storm surge forecasting in practice. It also contains useful insights for civil engineering students, especially those studying coastal engineering.
Author: Michael Getachew Tadesse
Author: Michael Getachew Tadesse
Author: Michael Siek
Author: 
Author: H. Kremer
Author: Harold Francis Needham (III)
Author: United States. Army. Corps of Engineers. Committee on Tidal Hydraulics
Author: 
Author: United States. Army. Corps of Engineers
Author: Masaya Toyoda
Author: