scholarly journals LARGE-SCALE LABORATORY EXPERIMENTS AND NUMERICAL MODELING OF WAVE FORCE AND PRESSURE ACTING ON THE URBAN STRUCTURES

2020 ◽  
pp. 28
Author(s):  
Dayeon Lee ◽  
Sungwon Shin ◽  
Hyoungsu Park ◽  
Dan Cox
Keyword(s):  
Sea Level ◽  
Large Scale ◽  
Wave Force ◽  
High Elevation ◽  
Coastal Communities ◽  
Submerged Breakwater ◽  
Sea Levels ◽  
Urban Structures ◽  
Overland Flows ◽  
Hard Structures

Low lying coastal communities are most vulnerable to the flooding which causes from sea-level rise (SLR), and extreme coastal flooding events such as hurricanes and tsunami. Notably, the high elevation of sea-levels due to SLR and local tidal conditions could accelerate the damages on the coastal communities. Hard coastal structures such as a submerged breakwater and seawall would consider minimizing the impacts of overland flows to the urban area from the extreme coastal events, but the effectiveness of those hard structures are significantly alter depending on the various waves and sea-level conditions.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/GCOOpB4C3tA

scholarly journals Atmospheric circulation changes and their impact on extreme sea levels around Australia

2019 ◽  
Vol 19 (5) ◽  
pp. 1067-1086 ◽  
Author(s):  
Frank Colberg ◽  
Kathleen L. McInnes ◽  
Julian O'Grady ◽  
Ron Hoeke
Keyword(s):  
Sea Level ◽  
Large Scale ◽  
Climate Models ◽  
Tide Gauge ◽  
Austral Summer ◽  
Sea Level Changes ◽  
Sea Level Variability ◽  
Sea Levels ◽  
Extreme Sea Levels ◽  
Coastal Sea

Abstract. Projections of sea level rise (SLR) will lead to increasing coastal impacts during extreme sea level events globally; however, there is significant uncertainty around short-term coastal sea level variability and the attendant frequency and severity of extreme sea level events. In this study, we investigate drivers of coastal sea level variability (including extremes) around Australia by means of historical conditions as well as future changes under a high greenhouse gas emissions scenario (RCP 8.5). To do this, a multi-decade hindcast simulation is validated against tide gauge data. The role of tide–surge interaction is assessed and found to have negligible effects on storm surge characteristic heights over most of the coastline. For future projections, 20-year-long simulations are carried out over the time periods 1981–1999 and 2081–2099 using atmospheric forcing from four CMIP5 climate models. Changes in extreme sea levels are apparent, but there are large inter-model differences. On the southern mainland coast all models simulated a southward movement of the subtropical ridge which led to a small reduction in sea level extremes in the hydrodynamic simulations. Sea level changes over the Gulf of Carpentaria in the north are largest and positive during austral summer in two out of the four models. In these models, changes to the northwest monsoon appear to be the cause of the sea level response. These simulations highlight a sensitivity of this semi-enclosed gulf to changes in large-scale dynamics in this region and indicate that further assessment of the potential changes to the northwest monsoon in a larger multi-model ensemble should be investigated, together with the northwest monsoon's effect on extreme sea levels.

Statistical Downscaling of daily extreme Sea Level with Random Forest: Examples from South-East Asia and the Baltic Sea

2020 ◽  
Author(s):  
Svenja Bierstedt ◽  
Eduardo Zorita ◽  
Birgit Hünicke
Keyword(s):  
Random Forest ◽  
Baltic Sea ◽  
East Asia ◽  
Sea Level ◽  
Large Scale ◽  
South East Asia ◽  
The Baltic Sea ◽  
Sea Levels ◽  
Extreme Sea Levels ◽  
The Baltic

<p>The coastlines of the Baltic Sea and Indonesia are both relatively complex, so that the estimation of extreme sea levels caused by the atmospheric forcing becomes complex with conventional methods. Here, we explore whether Machine Learning methods can provide a model surrogate to compute more rapidly daily extremes in sea level from large-scale atmosphere-ocean fields. We investigate the connections between the atmospheric and ocean drivers of local extreme sea level in South East Asia and along the Baltic Sea based on statistical analysis by Random Forest Models, driven by large-scale meteorological predictors and daily extreme sea level measured by tide-gauge records over the last few decades.</p><p>First results show that in some Indonesian areas extremes are driven by large-scale climate fields; in other areas they are incoherently driven by local processes. An area where random forest predicted extremes show good correspondence to observed extremes is found to be the Malaysian coastline. For the Indonesian coasts, the Random Forest Algorithm was unable to predict extreme sea levels in line with observations. Along the Baltic Sea, in contrast, the Random Forest model is able to produce reasonable estimations of extreme sea levels based on the large-scale atmospheric fields. An analysis of the interrelations of extreme sea levels in the South Asia regions suggests that either the data quality may be compromised in some regions or that other forcing factors, distinct from the large-scale atmospheric fields, may also be involved.</p>

scholarly journals Future flood risk exacerbated by the dynamic impacts of sea level rise

2020 ◽  
Author(s):  
Matthew Bilskie ◽  
Diana Del Angel ◽  
David Yoskowitz ◽  
Scott Hagen
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Flood Risk ◽  
Residential Buildings ◽  
Flood Damage ◽  
Coastal Communities ◽  
Modeling Framework ◽  
Sea Levels ◽  
Coastal Landscapes ◽  
Block Level

Abstract A growing concern of coastal communities is an increase in flood risk and non-monetary consequences as a result of climate-induced impacts such as sea level rise (SLR). While previous studies have outlined the importance of quantifying future flood risk, most have focused on broad aggregations of monetary loss using bathtub SLR-type models. Here we quantify, for the first time at the multi-state scale, actual impacts to coastal communities at the census block level using a dynamic, high-resolution, biogeophysical modeling framework that accounts for future sea-levels and coastal landscapes. We demonstrate that future SLR can increase the number of damaged residential buildings by 600%, the population of displaced people by 500% and the need for shelter assistance of up to 460% from present-day conditions. An exponential increase in flood damage associated with increasing sea level deems it essential for stakeholders to plan for plausible future conditions rather than the current reality.

Relocation as an Adaptation to Sea-Level Rise: Valuable Lessons from the Narikoso Village Relocation Project in Fiji

2019 ◽  
Vol 3 (1) ◽  
pp. 1-7 ◽  
Author(s):  
Amanda Bertana
Keyword(s):  
Climate Change ◽  
Sea Level ◽  
Coastal Erosion ◽  
Prime Minister ◽  
Adaptation Strategy ◽  
Coastal Communities ◽  
Financial Resources ◽  
Sea Levels ◽  
The Village

Relocation as an adaptation strategy to coastal degradation remains on the fringes of climate change discourse. Yet, as sea levels are projected to rise, relocating is an inevitable response for vulnerable coastal communities worldwide. In fact, some Fijian villages are facing such severe coastal erosion that they have already begun the process of shifting to higher ground, and many more villages throughout the islands have been slated for relocation. This case study is based on the planned relocation efforts of Narikoso village on Ono Island in Kadavu, Fiji. In Narikoso, regional NGOs, INGOs, and local and national government are working with the community to relocate the village inland. The process of moving the community began in 2012 when Prime Minister Bainimarama sent the Fiji military to Ono Island to clear land for the new village. It came to an abrupt stop due to a lack of funding and ecological degradation caused by the preparation for the new village site. Since the relocation process began, a myriad of issues have arisen ranging from concerns regarding community engagement, availability of financial resources, and resistance to moving inland.

The transient sensitivity of sea level rise

2020 ◽  
Author(s):  
Aslak Grinsted ◽  
Jens Hesselbjerg Christensen
Keyword(s):  
Surface Temperature ◽  
Sea Level Rise ◽  
Sea Level ◽  
Rate Of Change ◽  
Expert Elicitation ◽  
Coastal Communities ◽  
Observational Period ◽  
Sea Levels ◽  
Global Mean Surface Temperature ◽  
Global Mean

<p>We are warming our planet, and sea levels are rising as oceans expand and ice on land melts. This instigates a threat to coastal communities and ecosystems, and there is an urgent need for sea level predictions encompassing all known uncertainties to plan for it. Comprehensive assessments have concluded that sea level is unlikely to rise by more than about 1.1m this century but with further increase beyond 2100. However, some studies conclude that considerably greater sea level rise could be realised and an expert elicitation assign a substantially higher likelihood to this scenario. Here, we show that models used to assess future sea level in AR5 & SROCC have a lower sea level sensitivity than inferred from observations. By analyzing mean rate of change in sea level (not sea level itself), we identify a near linear relationship with global mean surface temperature in both model projections, and in observations. The model projections fall below expectations from the more recent observational period. This comparison suggests that the likely range of sea level projections in IPCC AR5 and SROCC would be too low.</p>

scholarly journals The long-term variability of extreme sea levels in the German Bight

Ocean Science ◽  
2019 ◽  
Vol 15 (3) ◽  
pp. 651-668 ◽  
Author(s):  
Andreas Lang ◽  
Uwe Mikolajewicz
Keyword(s):  
Sea Level ◽  
German Bight ◽  
Large Scale ◽  
Internal Variability ◽  
Climate System ◽  
System Model ◽  
Tide Gauge Record ◽  
Sea Levels ◽  
The North

Abstract. Extreme high sea levels (ESLs) caused by storm floods constitute a major hazard for coastal regions. We here quantify their long-term variability in the southern German Bight using simulations covering the last 1000 years. To this end, global earth system model simulations from the PMIP3 past1000 project are dynamically scaled down with a regionally coupled climate system model focusing on the North Sea. This approach provides an unprecedented long high-resolution data record that can extend the knowledge of ESL variability based on observations, and allows for the identification of associated large-scale forcing mechanisms in the climate system. While the statistics of simulated ESLs compare well with observations from the tide gauge record at Cuxhaven, we find that simulated ESLs show large variations on interannual to centennial timescales without preferred oscillation periods. As a result of this high internal variability, ESL variations appear to a large extent decoupled from those of the background sea level, and mask any potential signals from solar or volcanic forcing. Comparison with large-scale climate variability shows that periods of high ESL are associated with a sea level pressure dipole between northeastern Scandinavia and the Gulf of Biscay. While this large-scale circulation regime applies to enhanced ESL in the wider region, it differs from the North Atlantic Oscillation pattern that has often been linked to periods of elevated background sea level. The high internal variability with large multidecadal to centennial variations emphasizes the inherent uncertainties related to traditional extreme value estimates based on short data subsets, which fail to account for such long-term variations. We conclude that ESL variations as well as existing estimates of future changes are likely to be dominated by internal variability rather than climate change signals. Thus, larger ensemble simulations will be required to assess future flood risks.

High-resolution topography of the uplifting Huon Peninsula (Papua New Guinea) reveals high interstadial sea-levels over the past ~400 ka

2021 ◽  
Author(s):  
Gino de Gelder ◽  
Laurent Husson ◽  
Anne-Morwenn Pastier ◽  
Denovan Chauveau ◽  
David Fernández-Blanco ◽  
...  
Keyword(s):  
Coral Reef ◽  
Sea Level ◽  
Papua New Guinea ◽  
Large Scale ◽  
New Guinea ◽  
Sea Levels ◽  
Level Curves ◽  
The Past ◽  
Reef Models ◽  
Global Mean Sea Level

<p>Quaternary sea-level curves provide crucial insights to constrain tectonic and climatic processes, but require calibration with geological constraints that are particularly scarce for cold periods prior to the last glacial-interglacial cycle. To derive such constraints, we re-visit the Huon Peninsula in Papua New Guinea, which is a classic coral reef terrace (CRT) site that was used for the earliest relative sea-level (RSL) curves. We use digital surface models calculated from 0.5m Pleiades satellite imagery to improve RSL constraints, and unlike previous studies, we find that large-scale tilting of the terrace sequence is generally N-directed. This implies that RSL estimates are several meters higher than previously thought for most highstands over the past ~125 ka. We use the large-scale geometry of the terrace sequence to estimate sea-level highstands up to ~400 ka, and our results suggest that global mean sea-level curves derived from oxygen isotopes consistently underestimate sea-level during the relatively cold Marine Isotope Stages 3, 5a, 5c, 6, 9a and 11a, up to ~10-20 m. We use coral reef models to show that our age interpretation is consistent with the overall terrace sequence morphology, and fits between models and topography improve when adjusting sea-level highstands according to our findings.</p>

Extreme sea levels at the Finnish coast due to large-scale wind storms

2021 ◽  
Author(s):  
Jani Särkkä ◽  
Jani Räihä ◽  
Mika Rantanen ◽  
Kirsti Jylhä
Keyword(s):  
Baltic Sea ◽  
Sea Level ◽  
Large Scale ◽  
Low Pressure ◽  
The Baltic Sea ◽  
Sea Levels ◽  
Sea Level Variation ◽  
Level Model ◽  
The Baltic ◽  
Low Pressure Systems

<p>In the Baltic Sea, the short-term sea level variation might be several meters, even if the tides in the Baltic Sea are negligible. The short-term sea level fluctuations are caused by passing wind storms, inducing sea level variation through wind-induced currents, inverse barometric effect and seiches. Due to the shape of the Baltic Sea with several bays, the highest sea levels are found in the ends of bays like the Gulf of Finland and the Bothnian Bay. The sea level extremes caused by the large-scale windstorms depend strongly on the storm tracks. Within the natural climatic variability during the past centuries, there have most likely been higher sea level extremes than the extreme values found in the tide gauge records.</p><p>To study this variability of sea levels, induced by varying tracks of the passing windstorms, we construct an ensemble of synthetic low-pressure systems. In this ensemble, the parameters of the low-pressure systems (e.g. point of origin, velocity of the center of the system and depth of the pressure anomaly) are varied. The ensemble of low pressure systems is used as an input to a numerical sea level model based on shallow-water hydrodynamic equations. The sea level model is fast to calculate, enabling a study of a large set of varying storm tracks. As a result we have an ensemble of simulated sea levels. From the simulation results we can determine the low-pressure system that induces the highest sea level on a given location on the coast. We concentrate our studies on the Finnish coast, but the method can be applied to the entire Baltic coast. </p>

Communicating Sea Level Rise

2017 ◽  
Author(s):  
Karen Akerlof ◽  
Michelle Covi ◽  
Elizabeth Rohring
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Coastal Communities ◽  
Audience Research ◽  
Natural Phenomena ◽  
Human Beings ◽  
Sea Levels ◽  
Large Cities ◽  
Environmental Decision Making ◽  
Risk Visualization

Three quarters of the world’s large cities are located on coasts. As climate change causes oceans to warm and expand, and triggers vast influxes of water from melting ice sheets and glaciers, by the end of the 21st century, as many as 650 million people globally may be below sea levels or subject to recurrent flooding. Human beings have always faced threats from coastal storms and flooding, but never have so many of us and so much of our societal infrastructure been in harm’s way. With entire nations facing forced emigration, international online media are framing sea level rise as a human rights concern. Yet sea level rise suffers from generally low media attention and salience as a public issue. Coastal communities tasked with developing adaptation strategies are approaching engagement through new forms of risk visualization and models of environmental decision making. As a subfield of climate communication that addresses a variety of other anthropogenic and natural phenomena, sea level rise communication also calls upon the less politicized field of natural hazards risk communication. This review explores media analyses, audience research, and evaluation of communication outreach and engagement, finding many remaining gaps in our understanding of sea level rise communication.

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