A database of global storm surge reconstructions.
Ontology highlight
ABSTRACT:
SUBMITTER: Tadesse MG
PROVIDER: S-EPMC8096961 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Reproducible climate reconstructions of the Common Era (1 CE to present) are key to placing industrial-era warming into the context of natural climatic variability. Here we present a community-sourced database of temperature-sensitive proxy records from the PAGES2k initiative. The database gathers 692 records from 648 locations, including all continental regions and major ocean basins. The records are from trees, ice, sediment, corals, speleothems, documentary evidence, and other archives. They range in length from 50 to 2000 years, with a median of 547 years, while temporal resolution ranges from biweekly to centennial. Nearly half of the proxy time series are significantly correlated with HadCRUT4.2 surface temperature over the period 1850-2014. Global temperature composites show a remarkable degree of coherence between high- and low-resolution archives, with broadly similar patterns across archive types, terrestrial versus marine locations, and screening criteria. The database is suited to investigations of global and regional temperature variability over the Common Era, and is shared in the Linked Paleo Data (LiPD) format, including serializations in Matlab, R and Python.
| S-EPMC5505119 | biostudies-literature
Project description:Extreme sea levels are a significant threat to life, property, and the environment. These threats are managed by coastal planers through the implementation of risk mitigation strategies. Central to such strategies is knowledge of extreme event probabilities. Typically, these probabilities are estimated by fitting a suitable distribution to the observed extreme data. Estimates, however, are often uncertain due to the small number of extreme events in the tide gauge record and are only available at gauged locations. This restricts our ability to implement cost-effective mitigation. A remarkable fact about sea-level extremes is the existence of spatial dependences, yet the vast majority of studies to date have analyzed extremes on a site-by-site basis. Here we demonstrate that spatial dependences can be exploited to address the limitations posed by the spatiotemporal sparseness of the observational record. We achieve this by pooling all of the tide gauge data together through a Bayesian hierarchical model that describes how the distribution of surge extremes varies in time and space. Our approach has two highly desirable advantages: 1) it enables sharing of information across data sites, with a consequent drastic reduction in estimation uncertainty; 2) it permits interpolation of both the extreme values and the extreme distribution parameters at any arbitrary ungauged location. Using our model, we produce an observation-based probabilistic reanalysis of surge extremes covering the entire Atlantic and North Sea coasts of Europe for the period 1960-2013.
| S-EPMC6994974 | biostudies-literature
Project description:East China Sea (ECS) Storm Surge Modeling System (ESSMS) is developed based on Regional Ocean Modeling System (ROMS). Case simulation is performed on the Typhoon Soulik, which landed on the coastal region of Fujian Province, China, at 6 pm of July 13, 2013. Modeling results show that the maximum tide level happened at 6 pm, which was also the landing time of Soulik. This accordance may lead to significant storm surge and water level rise in the coastal region. The water level variation induced by high winds of Soulik ranges from -0.1 to 0.15 m. Water level generally increases near the landing place, in particular on the left hand side of the typhoon track. It is calculated that 0.15 m water level rise in this region can cause a submerge increase of ~0.2 km(2), which could be catastrophic to the coastal environment and the living. Additionally, a Globe Visualization System (GVS) is realized on the basis of World Wind to better provide users with the typhoon/storm surge information. The main functions of GVS include data indexing, browsing, analyzing, and visualization. GVS is capable of facilitating the precaution and mitigation of typhoon/storm surge in ESC in combination with ESSMS.
| S-EPMC4216692 | biostudies-other
Project description:Typhoon Haiyan, which struck the Philippines in November 2013, was an extremely intense tropical cyclone that had a catastrophic impact. The minimum central pressure of Typhoon Haiyan was 895 hPa, making it the strongest typhoon to make landfall on a major island in the western North Pacific Ocean. The characteristics of Typhoon Haiyan and its related storm surge are estimated by numerical experiments using numerical weather prediction models and a storm surge model. Based on the analysis of best hindcast results, the storm surge level was 5-6 m and local amplification of water surface elevation due to seiche was found to be significant inside Leyte Gulf. The numerical experiments show the coherent structure of the storm surge profile due to the specific bathymetry of Leyte Gulf and the Philippines Trench as a major contributor to the disaster in Tacloban. The numerical results also indicated the sensitivity of storm surge forecast.
| S-EPMC4373162 | biostudies-literature
Project description:Along the European coasts, changes in the timing of the storm surge season are analyzed. Using 10 long-term tide gauges located in western Europe, a consistent spatio-temporal shift emerged in the storm surge season between 1950 and 2000. Temporal shifts are positive (later events) in the North, negative (earlier events) in the South. Extreme surge events occurred about 4 days/decade later in northern Europe, and 5 days/decade earlier in southern Europe. Such a tendency is similar to the one already reported for European river floods between 1960 and 2010. In northern Europe, extreme surges are known to occur during the positive North Atlantic Oscillation phase (NAO+). Identified spatio-temporal shifts likely trace that NAO+ storms tend to occur later between 1950 and 2000. A new index measuring the timing of the NAO+ and NAO- persistent situations is shown to help capture this spatial distribution in the timing of the storm surge seasons.
| S-EPMC9114021 | biostudies-literature
Project description:Research performed to-date on data assimilation (DA) in storm surge modeling has found it to have limited value for predicting rapid surge responses (e.g., those accompanying tropical cyclones). In this paper, we submit that a well-resolved, barotropic hydrodynamic model is typically able to capture the surge event itself, leaving slower processes that determine the large scale, background water level as primary sources of water level error. These "unresolved drivers" reflect physical processes not included in the model's governing equations or forcing terms, such as far field atmospheric forcing, baroclinic processes, major ocean currents, steric variations, or precipitation. We have developed a novel, efficient, optimal interpolation-based DA scheme, using observations from coastal water level gages, that dynamically corrects for the presence of unresolved drivers. The methodology is applied for Hurricane Matthew (2016) and results demonstrate it is highly effective at removing water level residuals, roughly halving overall surge errors for that storm. The method is computationally efficient, well-suited for either hindcast or forecast applications and extensible to more advanced techniques and datasets.
| S-EPMC10624563 | biostudies-literature
Project description:Mangroves buffer inland ecosystems from hurricane winds and storm surge. However, their ability to withstand harsh cyclone conditions depends on plant resilience traits and geomorphology. Using airborne lidar and satellite imagery collected before and after Hurricane Irma, we estimated that 62% of mangroves in southwest Florida suffered canopy damage, with largest impacts in tall forests (>10 m). Mangroves on well-drained sites (83%) resprouted new leaves within one year after the storm. By contrast, in poorly-drained inland sites, we detected one of the largest mangrove diebacks on record (10,760 ha), triggered by Irma. We found evidence that the combination of low elevation (median = 9.4 cm asl), storm surge water levels (>1.4 m above the ground surface), and hydrologic isolation drove coastal forest vulnerability and were independent of tree height or wind exposure. Our results indicated that storm surge and ponding caused dieback, not wind. Tidal restoration and hydrologic management in these vulnerable, low-lying coastal areas can reduce mangrove mortality and improve resilience to future cyclones.
| S-EPMC8238932 | biostudies-literature
Project description:University of Washington Medicine (UW Medicine), an academic health system in Washington State, was at the epicenter of the first outbreak of the COVID-19 pandemic in the United States. The extent of emergency activation needed to adequately respond to this global pandemic was not immediately known, as the evolving situation differed significantly from any past disaster response preparations in that there was potential for exponential growth of infection, unproven mitigation strategies, serious risk to health care workers, and inadequate supply chains for critical equipment. The rapid transition of the UW Medicine system to account for projected COVID-19 and usual patient care, while balancing patient and staff safety and conservation of resources, represents an example of an adaptive disaster response. Although our organization's ability to meet the needs of the public was uncertain, we planned and implemented changes to space, supply management, and staffing plans to meet the influx of patients across our clinical entities. The surge management plan called for specific actions to be implemented based on the level of activity. This article describes the approach taken by UW Medicine as we braced for the storm.
| S-EPMC7546945 | biostudies-literature
Project description:Drag coefficient (Cd) is an essential metric in the calculation of momentum exchange over the air-sea interface and thus has large impacts on the simulation or forecast of the upper ocean state associated with sea surface winds such as storm surges. Generally, Cd is a function of wind speed. However, the exact relationship between Cd and wind speed is still in dispute, and the widely-used formula that is a linear function of wind speed in an ocean model could lead to large bias at high wind speed. Here we establish a parabolic model of Cd based on storm surge observations and simulation in the South China Sea (SCS) through a number of tropical cyclone cases. Simulation of storm surges for independent Tropical cyclones (TCs) cases indicates that the new parabolic model of Cd outperforms traditional linear models.
| S-EPMC4620453 | biostudies-literature
Project description:BackgroundAdvances in climate change research contribute to improved forecasts of hydrological extremes with potentially severe impacts on human societies and natural landscapes. Rainfall erosivity density (RED), i.e. rainfall erosivity (MJ mm hm-2 h-1 yr-1) per rainfall unit (mm), is a measure of rainstorm aggressiveness and a proxy indicator of damaging hydrological events.Methods and findingsHere, using downscaled RED data from 3,625 raingauges worldwide and log-normal ordinary kriging with probability mapping, we identify damaging hydrological hazard-prone areas that exceed warning and alert thresholds (1.5 and 3.0 MJ hm-2 h-1, respectively). Applying exceedance probabilities in a geographical information system shows that, under current climate conditions, hazard-prone areas exceeding a 50% probability cover ~31% and ~19% of the world's land at warning and alert states, respectively.ConclusionRED is identified as a key driver behind the spatial growth of environmental disruption worldwide (with tropical Latin America, South Africa, India and the Indian Archipelago most affected).
| S-EPMC9401149 | biostudies-literature