Relocatable Tide Prediction and Storm Surge Forecasting

2018 ◽  
Author(s):  
Thomas Prime
Keyword(s):  
Sea Level ◽  
Storm Surge ◽  
Marine Environment ◽  
Agricultural Land ◽  
Extreme Event ◽  
Negative Impact ◽  
Early Warning Systems ◽  
Coastal Communities ◽  
Prevention Measures ◽  
Storm Surge Forecasting

The marine environment represents a large and important resource for communities around the world. However, the marine environment increasingly presents hazards that can have a large negative impact. One important marine hazard results from storms and their accompanying surges. This can lead to coastal flooding, particularly when surge and astronomical high tides align, with resultant impacts such as destruction of property, saline degradation of agricultural land and coastal erosion. Where tide and storm surge information are provided and accessed in a timely, accurate and understandable way, the data can provide: 1. Evidence for planning: Statistics of past conditions such as the probability of extreme event occurrence can be used to help plan improvements to coastal infrastructure that are able to withstand and mitigate the hazard from a given extreme event. 2. Early warning systems: Short term forecasts of storm surge allow provide early warnings to coastal communities enabling them to take actions to allow them to withstand extreme events, e.g. deploy flood prevention measures or mobilise emergency response measures. Data regarding sea level height can be provided from various in-situ observations such as tide gauges and remote observations such as satellite altimetry. However, to provide a forecast at high spatial and temporal resolution a dynamic ocean model is used. Over recent decades the National Oceanography Centre has been a world leading in developing coastal ocean models. This paper will present our progress on a current project to develop an information system for the Madagascan Met Office. The project, C-RISC, being executed in partnership with Sea Level Research Ltd, is translating the current modelling capability of NOC in storm surge forecasting and tidal prediction into a system that will provide information that can be easily transferred to other regions and is scalable to include other hazard types The outcome, an operational high-resolution storm surge warning system that is easy to relocate, will directly benefit coastal communities, giving them information they need to make effective decisions before and during extreme storm surge events.

scholarly journals Understanding Sea Level Processes During Western Mediterranean Storm Gloria

2021 ◽  
Vol 8 ◽  
Author(s):  
Begoña Pérez-Gómez ◽  
Manuel García-León ◽  
Javier García-Valdecasas ◽  
Emanuela Clementi ◽  
César Mösso Aranda ◽  
...  
Keyword(s):  
Sea Level ◽  
Storm Surge ◽  
Extreme Event ◽  
Tide Gauge ◽  
Breaking Waves ◽  
Western Mediterranean ◽  
Measured Data ◽  
Confidence Bands ◽  
Forecasting System ◽  
The Impact

In January 2020, the storm Gloria hit the Western Mediterranean Sea causing severe coastal damages, destruction of infrastructures, flooding and several casualties. This extreme event was characterized by strong Eastern winds, record-breaking waves heights and periods, and a storm surge that locally beat the record along Valencia’s coastline. This paper analyses the dynamic evolution of sea level during this storm. The study employs both the in situ data and the operational forecasts of the PORTUS early warning system. Tide gauge data are analyzed on the different temporal scales that contribute to total sea level: long-term and seasonal, tides and storm surges, and higher frequency oscillations. It was found that, due to the unusual long wave periods, infragravity waves were generated and dominate the high frequency energy band, contributing significantly to extreme sea level records. This is a relevant finding, since this kind of oscillations are usually associated with larger basins, where swell can develop and propagate. The impact of sea level rise is also analyzed and considered relevant. A multi-model ensemble storm surge forecasting system is employed to study the event. The system was able to correctly forecast the surge, and the measured data were always inside the confidence bands of the system. The differences of the results obtained by the available operational forecasting system integrated into the ensemble, including those from Copernicus Marine Service, are described. All the models provided useful forecasts during the event, but differences with measured data are described and connected with the known limitations in physics (for example, barotropic vs. baroclinic) and set-up of the models (model domain, lack of tides and different inverse barometer implementations at the open boundaries amongst others).

scholarly journals Hydrodynamic and Waves Response during Storm Surges on the Southern Brazilian Coast: A Hindcast Study

Water ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3538
Author(s):  
Andre de Souza de Lima ◽  
Arslaan Khalid ◽  
Tyler Will Miesse ◽  
Felicio Cassalho ◽  
Celso Ferreira ◽  
...  
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Storm Surge ◽  
Storm Surges ◽  
Coastal Communities ◽  
Brazilian Coast ◽  
Forecast System ◽  
Modeling Framework ◽  
Meteorological Forcing ◽  
The Impact

The Southern Brazilian Coast is highly susceptible to storm surges that often lead to coastal flooding and erosive processes, significantly impacting coastal communities. In addition, climate change is expected to result in expressive increases in wave heights due to more intense and frequent storms, which, in conjunction with sea-level rise (SLR), has the potential to exacerbate the impact of storm surges on coastal communities. The ability to predict and simulate such events provides a powerful tool for coastal risk reduction and adaptation. In this context, this study aims to investigate how accurately storm surge events can be simulated in the Southwest Atlantic Ocean employing the coupled ADCIRC+SWAN hydrodynamic and phase-averaged wave numerical modeling framework given the significant data scarcity constraints of the region. The model’s total water level (TWL) and significant wave height (Hs) outputs, driven by different sources of meteorological forcing, i.e., the Fifth Generation of ECMWF Atmospheric Reanalysis (ERA 5), the Climate Forecast System Version 2 (CFSv2), and the Global Forecast System (GFS), were validated for three recent storm events that affected the coast (2016, 2017, and 2019). In order to assess the potentially increasing storm surge impacts due to sea-level rise, a case study was implemented to locally evaluate the modeling approach using the most accurate model setup for two 2100 SLR projections (RCP 4.5 and 8.5). Despite a TWL underestimation in all sets of simulations, the CFSv2 model stood out as the most consistent meteorological forcing for the hindcasting of the storm surge and waves in the numerical model, with an RMSE range varying from 0.19 m to 0.37 m, and an RMSE of 0.56 m for Hs during the most significant event. ERA5 was highlighted as the second most accurate meteorological forcing, while adequately simulating the peak timings. The SLR study case demonstrated a possible increase of up to 82% in the TWL during the same event. Despite the limitations imposed by the lack of continuous and densely distributed observational data, as well as up to date topobathymetric datasets, the proposed framework was capable of expanding TWL and Hs information, previously available for a handful of gauge stations, to a spatially distributed and temporally unlimited scale. This more comprehensive understanding of such extreme events represents valuable knowledge for the potential implementation of more adequate coastal management and engineering practices for the Brazilian coastal zone, especially under changing climate conditions.

scholarly journals Storm surge in the Adriatic Sea: observational and numerical diagnosis of an extreme event

2006 ◽  
Vol 7 ◽  
pp. 371-378 ◽  
Author(s):  
L. Zampato ◽  
G. Umgiesser ◽  
S. Zecchetto
Keyword(s):  
High Resolution ◽  
Sea Level ◽  
Storm Surge ◽  
Hydrodynamic Model ◽  
Adriatic Sea ◽  
Extreme Event ◽  
Numerical Models ◽  
Limited Area ◽  
Wind Fields ◽  
Northern Adriatic

Abstract. Storm surge events occur in the Adriatic Sea, in particular during autumn and winter, often producing flooding in Venice. Sea levels are forecasted by numerical models, which require wind and pressure fields as input. Their performances depend crucially on the quality of those fields. The storm surge event on 16 November 2002 is analysed and simulated through a finite element hydrodynamic model of the Mediterranean Sea. Several runs were carried out, imposing different atmospheric forcings: wind fields from ECMWF analysis, high resolution winds from the limited area model LAMI and satellite observed winds from QuikSCAT (NASA). The performance of the hydrodynamic model in each case has been quantified. ECMWF fields are effective in reproducing the sea level in the northern Adriatic Sea, if the wind speed is enhanced by a suitable multiplying factor. High resolution winds from LAMI give promising results, permitting an accurate simulation of the sea level maxima. QuikSCAT satellite wind fields produce also encouraging results which claim, however, for further research.

scholarly journals Using Virtual Reality in Sea Level Rise Planning and Community Engagement—An Overview

Water ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1142
Author(s):  
Juliano Calil ◽  
Geraldine Fauville ◽  
Anna Carolina Muller Queiroz ◽  
Kelly L. Leo ◽  
Alyssa G. Newton Mann ◽  
...  
Keyword(s):  
Climate Change ◽  
Virtual Reality ◽  
Sea Level Rise ◽  
Sea Level ◽  
Community Outreach ◽  
Coastal Communities ◽  
Coastal Hazards ◽  
Multidisciplinary Teams ◽  
Simple Task ◽  
Coastal Risks

As coastal communities around the globe contend with the impacts of climate change including coastal hazards such as sea level rise and more frequent coastal storms, educating stakeholders and the general public has become essential in order to adapt to and mitigate these risks. Communicating SLR and other coastal risks is not a simple task. First, SLR is a phenomenon that is abstract as it is physically distant from many people; second, the rise of the sea is a slow and temporally distant process which makes this issue psychologically distant from our everyday life. Virtual reality (VR) simulations may offer a way to overcome some of these challenges, enabling users to learn key principles related to climate change and coastal risks in an immersive, interactive, and safe learning environment. This article first presents the literature on environmental issues communication and engagement; second, it introduces VR technology evolution and expands the discussion on VR application for environmental literacy. We then provide an account of how three coastal communities have used VR experiences developed by multidisciplinary teams—including residents—to support communication and community outreach focused on SLR and discuss their implications.

Assessing inundation damage and timing of adaptation: sea level rise and the complexities of land use in coastal communities

2013 ◽  
Vol 19 (5) ◽  
pp. 551-568 ◽  
Author(s):  
Brenda B. Lin ◽  
Yong Bing Khoo ◽  
Matthew Inman ◽  
Chi-Hsiang Wang ◽  
Sorada Tapsuwan ◽  
...  
Keyword(s):  
Land Use ◽  
Sea Level Rise ◽  
Sea Level ◽  
Coastal Communities

scholarly journals Adjusting the Wind Stress Drag Coefficient in Storm Surge Forecasting Using an Adjoint Technique

2013 ◽  
Vol 30 (3) ◽  
pp. 590-608 ◽  
Author(s):  
Shiqiu Peng ◽  
Yineng Li ◽  
Lian Xie
Keyword(s):  
Data Assimilation ◽  
Drag Coefficient ◽  
Storm Surge ◽  
Wind Stress ◽  
Weather Prediction ◽  
Ocean Model ◽  
Error Sources ◽  
Empirical Parameter ◽  
Forecasting Errors ◽  
Storm Surge Forecasting

Abstract A three-dimensional ocean model and its adjoint model are used to adjust the drag coefficient in the calculation of wind stress for storm surge forecasting. A number of identical twin experiments (ITEs) with different error sources imposed are designed and performed. The results indicate that when the errors come from the wind speed, the drag coefficient is adjusted to an “optimal value” to compensate for the wind errors, resulting in significant improvements of the specific storm surge forecasting. In practice, the “true” drag coefficient is unknown and the wind field, which is usually calculated by an empirical parameter model or a numerical weather prediction model, may contain large errors. In addition, forecasting errors may also come from imperfect model physics and numerics, such as insufficient resolution and inaccurate physical parameterizations. The results demonstrate that storm surge forecasting errors can be reduced through data assimilation by adjusting the drag coefficient regardless of the error sources. Therefore, although data assimilation may not fix model imperfection, it is effective in improving storm surge forecasting by adjusting the wind stress drag coefficient using the adjoint technique.

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