scholarly journals BEACH PLANFORM EQUILIBRIUM, APPLICATION AND METHODOLOGIES FOR CLIMATE CHANGE RESILIENCY CONSIDERATION

2020 ◽  
pp. 43
Author(s):  
Mohamed Dabees
Keyword(s):  
Climate Change ◽  
Coastal Areas ◽  
Equilibrium Conditions ◽  
Long Term Stability ◽  
Open Coast ◽  
Coastal Cities ◽  
Water Elevations ◽  
Added Uncertainty ◽  
Evaluation Parameters

Climate change and sea level rise (SLR) present a challenge and added uncertainty for managing coastal areas. Many coastal cities and developed coastal areas are assessing future vulnerabilities to SLR and developing adaptation plans for improved resiliency. Equilibrium conditions for beach planform can be critical to the long-term stability of beaches and dunes fronting coastal cities. In many cases, resiliency and adaptation programs for beachfront areas are based on assumptions of evaluating scenarios of higher water elevations and hydrodynamic forcing under present time topographic and bathymetric conditions. These evaluation parameters suggest that the coastline and existing morphological features are near equilibrium condition and are expected to remain near similar equilibrium over the SLR scenarios under consideration. Such assumptions may be limited to open coast conditions where the beach and the developed coastal planform follows theoretical open coast conditions or constant equilibrium planform. This paper discusses factors influencing beach planform along the Florida Atlantic and Gulf of Mexico coastlines and proposes conceptual methodologies in various applications.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/gWsbmi6VIo0

Climate Change, Humanitarian Risks, and Social-Political (In)stability Along the Gulf of Aden: Expert Elicitation for the Case of Somalia and Yemen

2021 ◽  
Author(s):  
Laurent Lambert ◽  
Mahmood Almehdhar ◽  
Mustafa Haji
Keyword(s):  
Climate Change ◽  
Tropical Cyclones ◽  
Political Stability ◽  
Coastal Areas ◽  
Expert Elicitation ◽  
Coastal Communities ◽  
Gulf Of Aden ◽  
The World ◽  
Environmental Events

<p><strong>Abstract</strong>: Changes in the global oceanic system have already negatively affected the world’s marine life and the livelihoods of many coastal communities across the world, including in the Middle East' and Eastern Africa's Least Developed Countries (LDCs). Coastal communities in Somalia and Yemen for instance, have been particularly affected by extreme environmental events (EEEs), with an increase in the frequency of tropical cyclones over the past 20 years. Using expert elicitation as a method to generate data to assess and quantify a specific issue in the absence of sufficient and/or reliable data, the authors interviewed selected specialists in or from Somalia and Yemen, from diverse fields of expertise related to climate change, extreme environmental events, disaster risk reduction, and humanitarian affairs. Ten experts followed the elicitation protocol and answered a specific series of questions in order to better quantify the expectable mid-to-long-term climatic and humanitarian levels of risks, impacts, and consequences that climate change and related issues (e.g., sea-level rise, tropical cyclones, and sea surge) may generate in coastal areas along the Gulf of Aden's coastal cities of Aden and Bossaso, in Yemen and Somalia, respectively.</p><p>The findings indicate that there is cause for significant concern as climate change is assessed by all interviewees - irrespective of their background -, as very likely to hold a negative to a devastating impact on (fresh) water security, food security, public health, social conflicts, population displacement, and eventually political stability; and to strongly worsen the humanitarian situations in Somalia and Yemen, both in the medium-term (i.e., 2020-2050) and the long-term (i.e., 2020-2100). The authors call on the scientific community to further research the issue of climate change in the understudied coastal areas of the Gulf of Aden, and on the international community to pro-actively and urgently help the local populations and relevant authorities to rapidly and strongly build up their adaptation capacities, especially in the niche of coastal EEEs.</p>

scholarly journals Temporally Generalizable Land Cover Classification: A Recurrent Convolutional Neural Network Unveils Major Coastal Change through Time

2021 ◽  
Vol 13 (19) ◽  
pp. 3953
Author(s):  
Patrick Clifton Gray ◽  
Diego F. Chamorro ◽  
Justin T. Ridge ◽  
Hannah Rae Kerner ◽  
Emily A. Ury ◽  
...  
Keyword(s):  
Neural Network ◽  
Climate Change ◽  
Deep Learning ◽  
Land Cover ◽  
Convolutional Neural Network ◽  
Agricultural Land ◽  
Coastal Areas ◽  
Support Vector ◽  
Validation Data

The ability to accurately classify land cover in periods before appropriate training and validation data exist is a critical step towards understanding subtle long-term impacts of climate change. These trends cannot be properly understood and distinguished from individual disturbance events or decadal cycles using only a decade or less of data. Understanding these long-term changes in low lying coastal areas, home to a huge proportion of the global population, is of particular importance. Relatively simple deep learning models that extract representative spatiotemporal patterns can lead to major improvements in temporal generalizability. To provide insight into major changes in low lying coastal areas, our study (1) developed a recurrent convolutional neural network that incorporates spectral, spatial, and temporal contexts for predicting land cover class, (2) evaluated this model across time and space and compared this model to conventional Random Forest and Support Vector Machine methods as well as other deep learning approaches, and (3) applied this model to classify land cover across 20 years of Landsat 5 data in the low-lying coastal plain of North Carolina, USA. We observed striking changes related to sea level rise that support evidence on a smaller scale of agricultural land and forests transitioning into wetlands and “ghost forests”. This work demonstrates that recurrent convolutional neural networks should be considered when a model is needed that can generalize across time and that they can help uncover important trends necessary for understanding and responding to climate change in vulnerable coastal regions.

scholarly journals Influence of late-Holocene climate change on the solid-phase speciation and long-term stability of arsenic in sub-Arctic lake sediments

2020 ◽  
Vol 709 ◽  
pp. 136115 ◽  
Author(s):  
Clare B. Miller ◽  
Michael B. Parsons ◽  
Heather E. Jamieson ◽  
Omid H. Ardakani ◽  
Braden R.B. Gregory ◽  
...  
Keyword(s):  
Climate Change ◽  
Lake Sediments ◽  
Late Holocene ◽  
Solid Phase ◽  
Holocene Climate ◽  
Arctic Lake ◽  
Term Stability ◽  
Long Term Stability ◽  
Holocene Climate Change

scholarly journals How long do satellites need to overlap? Evaluation of climate data stability from overlapping satellite records

2017 ◽  
Author(s):  
Elizabeth C. Weatherhead ◽  
Jerald Harder ◽  
Eduardo A. Araujo-Pradere ◽  
Jason M. English ◽  
Lawrence E. Flynn ◽  
...  
Keyword(s):  
Climate Data ◽  
Long Term Stability ◽  
Earth Observations ◽  
Satellite Technology ◽  
Irradiance Data ◽  
Earth’S Climate ◽  
Added Uncertainty ◽  
The Stability

Abstract. Sensors on satellites provide unprecedented understanding of the Earth’s climate system by measuring incoming solar radiation, as well as both passive and active observations of the entire Earth with outstanding spatial and temporal coverage that would be currently impossible without satellite technology. A common challenge with satellite observations is to quantify their ability to provide well-calibrated, long-term, stable records of the parameters they measure. Ground-based intercomparisons offer some insight, while reference observations and internal calibrations give further assistance for understanding long-term stability. A valuable tool for evaluating and developing long-term records from satellites is the examination of data from overlapping satellites. Prior papers have used overlap periods to identify the offset between data from two satellites and estimate the added uncertainty to long-term records. This paper addresses the length of overlap needed to identify an offset or a drift in the offsets of data between two sensors. The results are presented for the general case of sensor overlap by using the case of overlap of the SORCE SIM and SOLSTICE solar irradiance data as an example. To achieve a 1 % uncertainty in estimating the offset for these two instruments’ measurement of the Mg II core (280 nm) requires approximately 5 months of overlap. For relative drift to be identified within 0.1 % yr−1 uncertainty, the overlap for these two satellites would need to be 2.6 years. Additional overlap of satellite measurements is needed if, as is the case for solar monitoring, unexpected jumps may occur because these jumps add to the uncertainty of both offsets and drifts; the additional length of time needed to account for a single jump in the overlap data may be as large as 50 % of the original overlap period in order to achieve the same desired confidence in the stability of the merged dataset. Extension of the results presented here are directly applicable to satellite Earth observations. Approaches for Earth observations may be challenged by the complexity of those observations but may also benefit from ancillary observations taken from ground-based and in situ sources. Difficult choices need to be made when monitoring approaches are considered; we outline some attempts at optimizing networks based on economic principles. The careful evaluation of monitoring overlap is important to the appropriate application of observational resources and to the usefulness of current and future observations.

scholarly journals Sustainable Coastal Cities between Theory and Practice (Case Study: Egyptian Coastal Cities)

2016 ◽  
Vol 9 (4) ◽  
pp. 216 ◽  
Author(s):  
Ingy M. El Barmelgy ◽  
Sarah E. Abdel Rasheed
Keyword(s):  
Climate Change ◽  
Nile Delta ◽  
Mediterranean Coast ◽  
Theory And Practice ◽  
Coastal Cities ◽  
Northern Areas ◽  
The World ◽  
Negative Impacts ◽  
The Impact

<p>Climate change is no longer considered an environmental or scientific issue but rather a developmental challenge that requires urgent, dynamic policy and technical responses at the regional, national and local levels. Its actions and responses impact sustainable development, ensuring the integrity of all ecosystems and the protection of biodiversity. There has been an intensive discussion and research about sea level rise (S.L.R) one of the most negative impacts of climate change which affects many coastal cities around the world. Egypt is considered one of the top five countries expected to be impacted with S.L.R in the world, especially northern areas of the Nile Delta and cities located on the Mediterranean coast.</p>This paper aims to evaluate the impact of S.L.R on the urban development strategies of the Egyptian northern coastal cities; highlighting the national response to global efforts regarding this problem in order to enhance the capacity for the adaptation and mitigation of potential impacts in the long term. Finally, it suggests some recommendations and framework actions to be taken to help Egyptian coastal cities in dealing with climate change over different timescales.

scholarly journals Climate risks to carbon sequestration in US forests

2021 ◽  
Author(s):  
William R. L. Anderegg ◽  
Oriana S. Chegwidden ◽  
Grayson Badgley ◽  
Anna T. Trugman ◽  
Danny Cullenward ◽  
...  
Keyword(s):  
Climate Change ◽  
Carbon Sink ◽  
The United States ◽  
Mitigation Strategies ◽  
Emissions Reductions ◽  
Climate Risks ◽  
Long Term Stability ◽  
Mitigate Climate Change ◽  
Change Mitigation

Forests are currently a substantial carbon sink globally. Many climate change mitigation strategies rely on forest preservation and expansion, but the effectiveness of these approaches hinges on forests sequestering carbon for centuries despite anthropogenic climate change. Yet climate-driven disturbances pose critical risks to the long-term stability of forest carbon. We quantify the key climate drivers that fuel wildfire, drought, and insects, for the United States over 1984-2018 and project future disturbance risks over the 21st century. We find that current risks are widespread and projected to increase across different emission scenarios by a factor of 4-14 for fire and 1.3-1.8 for drought and insects. Our results provide insights for carbon cycle modeling, conservation, and climate policy, underscoring the escalating climate risks facing forests and the need for emissions reductions to mitigate climate change.

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