Economic Vulnerability to Climate Change in Coastal New Jersey: A Stakeholder-Based Assessment

2014 ◽  
Vol 01 (01) ◽  
pp. 1450003 ◽  
Author(s):  
Robin Leichenko ◽  
Melanie McDermott ◽  
Ekaterina Bezborodko ◽  
Michael Brady ◽  
Erik Namendorf
Keyword(s):  
Climate Change ◽  
New Jersey ◽  
Climate Extremes ◽  
Hurricane Sandy ◽  
Assessment Process ◽  
Economic Vulnerability ◽  
Climate Assessment ◽  
Wide Range ◽  
Economic Assets ◽  
Post Disaster

This study investigates economic vulnerabilities to climate extremes and climate change in coastal New Jersey before and after Hurricane Sandy. Drawing upon methodological best-practices in climate adaptation and disaster risk management, which emphasize co-production of climate assessment information, the study employs a stakeholder-based approach to identify key climate-related economic stresses, risks and vulnerabilities. Interviews with stakeholders conducted in the months prior to Sandy highlighted a myriad of climatic, environmental and economic stresses in the region and revealed a wide range of economic assets, activities, and populations that are economically vulnerable. Post-Sandy meetings with stakeholders reinforced findings of the pre-Sandy interviews but also brought to light some new and unexpected vulnerabilities. The study illustrates the value of stakeholder participation in economic vulnerability assessments, including deeper and more nuanced understanding of local economic assets, activities, and populations at risk to climate extremes and climate change. The study also demonstrates the importance of stakeholder-engagement for creating buy-in to the climate assessment process and for facilitating new learning opportunities in a post-disaster context. Given climatic non-stationarity and continually evolving economic conditions, stakeholder-based assessments will need to be conducted and updated on an on-going basis in order to ensure continual relevance to post-disaster learning and response.

scholarly journals When rebuilding no longer means recovery: the stress of staying put after Hurricane Sandy

2021 ◽  
Vol 165 (3-4) ◽  
Author(s):  
Liz Koslov ◽  
Alexis Merdjanoff ◽  
Elana Sulakshana ◽  
Eric Klinenberg
Keyword(s):  
Climate Change ◽  
Mental Health ◽  
Health Outcomes ◽  
Social Economic ◽  
Hurricane Sandy ◽  
Flood Insurance ◽  
Health Consequences ◽  
The Usa ◽  
Policy Shifts ◽  
Post Disaster

AbstractAfter a disaster, it is common to equate repopulation and rebuilding with recovery. Numerous studies link post-disaster relocation to adverse social, economic, and health outcomes. However, there is a need to reconsider these relationships in light of accelerating climate change and associated social and policy shifts in the USA, including the rising cost of flood insurance, the challenge of obtaining aid to rebuild, and growing interest in “managed retreat” from places at greatest risk. This article presents data from a survey of individuals who opted either to rebuild in place or relocate with the help of a voluntary home buyout after Hurricane Sandy. Findings show those who lived in buyout-eligible areas and relocated were significantly less likely to report worsened stress than those who rebuilt in place. This suggests access to a government-supported voluntary relocation option may, under certain circumstances, lessen the negative mental health consequences associated with disaster-related housing damage.

A Quality-Controlled Global Sub-daily Precipitation Dataset and Sub-daily Precipitation Indices

2020 ◽  
Author(s):  
Hayley Fowler ◽  
Liz Lewis ◽  
Stephen Blenkinsop ◽  
David Pritchard ◽  
Selma Guerreiro ◽  
...  
Keyword(s):  
Climate Change ◽  
Daily Precipitation ◽  
Climate Extremes ◽  
Research Programme ◽  
Grand Challenge ◽  
Maximum Rainfall ◽  
Daily Precipitation Data ◽  
Hourly Rainfall ◽  
Wide Range ◽  
Precipitation Indices

<p>Extremes of precipitation can cause flooding and droughts which can lead to substantial damages to infrastructure and ecosystems and can result in loss of life. It is still uncertain how hydrological extremes will change with global warming as we do not fully understand the processes that cause extreme precipitation under current climate variability. Progress has been limited so far in this area due to the lack of data available to researchers. The INTENSE project, part of the with the World Climate Research Programme (WCRP)'s Grand Challenge on 'Understanding and Predicting Weather and Climate Extremes', has used a novel and fully-integrated data-modelling approach to provide a step-change in our understanding of the nature and drivers of global sub-daily precipitation extremes and change on societally relevant timescales.</p><p>The first step towards achieving this was to construct a new global sub-daily precipitation dataset. The dataset contains hourly rainfall data from ~25,000 gauges across >200 territories from a wide range of sources. A rigorous, flexible quality-control algorithm has been developed to ensure that the data collected is as accurate as possible. The QC methodology combines a number of checks against neighbouring gauges, known biases and errors, and thresholds based on the Expert Team on Climate Change Detection and Indices (ETCCDI) Climate Change Indices.  An open source version of the QC software will set a new standard for verifying sub-daily precipitation data.</p><p>A set of global sub-daily precipitation indices have also been produced (and will be made freely available later this year) based upon stakeholder recommendations including indices that describe maximum rainfall totals and timing, the intensity, duration and frequency of storms, frequency of storms above specific thresholds and information about the diurnal cycle. The talk will discuss the major findings from the production of these new global sub-daily precipitation indices.</p>

Climate Change, Extreme Events, and Hurricane Sandy: From Non-Stationary Climate to Non-Stationary Policy

2014 ◽  
Vol 01 (01) ◽  
pp. 1450008 ◽  
Author(s):  
William Solecki ◽  
Cynthia Rosenzweig
Keyword(s):  
Climate Change ◽  
New York ◽  
Extreme Events ◽  
Climate Adaptation ◽  
Hurricane Sandy ◽  
Generation Process ◽  
Stationary Policy ◽  
Building Stock ◽  
Policy Window ◽  
Post Disaster

This paper illustrates and examines the development of a flexible climate adaptation approach and non-stationary climate policy in New York City in the post-Hurricane Sandy context. Extreme events, such as Hurricane Sandy, are presented as learning opportunities and create a policy window for outside-of-the-box solutions and experimentation. The research investigates the institutionalization of laws, standards, and codes that are required to reflect an increasingly dynamic set of local environmental stresses associated with climate change. The City of New York responded to Hurricane Sandy with a set of targeted adjustments to the existing infrastructure and building stock in a way that both makes it more resistant (i.e., strengthened) and resilient (i.e., responsive to stress) in the face of future extreme events. Post-Sandy New York experiences show that the conditions for a post-disaster flexible adaptation response exist, and evidence shows that the beginnings of a non-stationary policy generation process have been put into place. More broadly, post-disaster policy processes have been configured in New York to enable continuous co-production of knowledge by scientists and the community of decision-makers and stakeholders.

EAARL-B submerged topography: Barnegat Bay, New Jersey, post-Hurricane Sandy, 2012-2013

Data Series ◽  
10.3133/ds887 ◽  
2014 ◽  
Author(s):  
C. Wayne Wright ◽  
Rodolfo J. Troche ◽  
Christine J. Kranenburg ◽  
Emily S. Klipp ◽  
Xan Fredericks ◽  
...  
Keyword(s):  
New Jersey ◽  
Hurricane Sandy ◽  
Barnegat Bay

EAARL-B coastal topography: eastern New Jersey, Hurricane Sandy, 2012: first surface

Data Series ◽  
10.3133/ds767 ◽  
2014 ◽  
Author(s):  
C. Wayne Wright ◽  
Xan Fredericks ◽  
Rodolfo J. Troche ◽  
Emily S. Klipp ◽  
Christine J. Kranenburg ◽  
...  
Keyword(s):  
New Jersey ◽  
Hurricane Sandy ◽  
Coastal Topography

A MODELING SYSTEM FOR CLIMATE CHANGE RISK ASSESSMENT, MANAGEMENT AND HEDGING IN COASTAL AREAS

2017 ◽  
Author(s):  
Sergei Soldatenko ◽  
Sergei Soldatenko ◽  
Genrikh Alekseev ◽  
Genrikh Alekseev ◽  
Alexander Danilov ◽  
...  
Keyword(s):  
Climate Change ◽  
Risk Assessment ◽  
Coastal Areas ◽  
Mitigation Strategies ◽  
System Structure ◽  
The Arctic ◽  
Risk Modeling ◽  
Wide Range ◽  
Adverse Weather ◽  
The Impact

Every aspect of human operations faces a wide range of risks, some of which can cause serious consequences. By the start of 21st century, mankind has recognized a new class of risks posed by climate change. It is obvious, that the global climate is changing, and will continue to change, in ways that affect the planning and day to day operations of businesses, government agencies and other organizations and institutions. The manifestations of climate change include but not limited to rising sea levels, increasing temperature, flooding, melting polar sea ice, adverse weather events (e.g. heatwaves, drought, and storms) and a rise in related problems (e.g. health and environmental). Assessing and managing climate risks represent one of the most challenging issues of today and for the future. The purpose of the risk modeling system discussed in this paper is to provide a framework and methodology to quantify risks caused by climate change, to facilitate estimates of the impact of climate change on various spheres of human activities and to compare eventual adaptation and risk mitigation strategies. The system integrates both physical climate system and economic models together with knowledge-based subsystem, which can help support proactive risk management. System structure and its main components are considered. Special attention is paid to climate risk assessment, management and hedging in the Arctic coastal areas.

The Biology of Mediterranean-Type Ecosystems

2018 ◽  
Author(s):  
Karen J. Esler ◽  
Anna L. Jacobsen ◽  
R. Brandon Pratt
Keyword(s):  
Climate Change ◽  
South Africa ◽  
Invasive Species ◽  
Habitat Loss ◽  
Endemic Species ◽  
Geographic Area ◽  
Cutting Edge ◽  
Wide Range ◽  
The Mediterranean ◽  
Mediterranean Type Ecosystems

The world’s mediterranean-type climate regions (including areas within the Mediterranean, South Africa, Australia, California, and Chile) have long been of interest to biologists by virtue of their extraordinary biodiversity and the appearance of evolutionary convergence between these disparate regions. Comparisons between mediterranean-type climate regions have provided important insights into questions at the cutting edge of ecological, ecophysiological and evolutionary research. These regions, dominated by evergreen shrubland communities, contain many rare and endemic species. Their mild climate makes them appealing places to live and visit and this has resulted in numerous threats to the species and communities that occupy them. Threats include a wide range of factors such as habitat loss due to development and agriculture, disturbance, invasive species, and climate change. As a result, they continue to attract far more attention than their limited geographic area might suggest. This book provides a concise but comprehensive introduction to mediterranean-type ecosystems. As with other books in the Biology of Habitats Series, the emphasis in this book is on the organisms that dominate these regions although their management, conservation, and restoration are also considered.

scholarly journals Building Damage Detection from Post-Event Aerial Imagery Using Single Shot Multibox Detector

2019 ◽  
Vol 9 (6) ◽  
pp. 1128 ◽  
Author(s):  
Yundong Li ◽  
Wei Hu ◽  
Han Dong ◽  
Xueyan Zhang
Keyword(s):  
Machine Learning ◽  
Data Augmentation ◽  
Hurricane Sandy ◽  
Training Data ◽  
Aerial Images ◽  
Detection Methods ◽  
Single Shot ◽  
Data Set ◽  
Augmentation Strategies ◽  
Post Disaster

Using aerial cameras, satellite remote sensing or unmanned aerial vehicles (UAV) equipped with cameras can facilitate search and rescue tasks after disasters. The traditional manual interpretation of huge aerial images is inefficient and could be replaced by machine learning-based methods combined with image processing techniques. Given the development of machine learning, researchers find that convolutional neural networks can effectively extract features from images. Some target detection methods based on deep learning, such as the single-shot multibox detector (SSD) algorithm, can achieve better results than traditional methods. However, the impressive performance of machine learning-based methods results from the numerous labeled samples. Given the complexity of post-disaster scenarios, obtaining many samples in the aftermath of disasters is difficult. To address this issue, a damaged building assessment method using SSD with pretraining and data augmentation is proposed in the current study and highlights the following aspects. (1) Objects can be detected and classified into undamaged buildings, damaged buildings, and ruins. (2) A convolution auto-encoder (CAE) that consists of VGG16 is constructed and trained using unlabeled post-disaster images. As a transfer learning strategy, the weights of the SSD model are initialized using the weights of the CAE counterpart. (3) Data augmentation strategies, such as image mirroring, rotation, Gaussian blur, and Gaussian noise processing, are utilized to augment the training data set. As a case study, aerial images of Hurricane Sandy in 2012 were maximized to validate the proposed method’s effectiveness. Experiments show that the pretraining strategy can improve of 10% in terms of overall accuracy compared with the SSD trained from scratch. These experiments also demonstrate that using data augmentation strategies can improve mAP and mF1 by 72% and 20%, respectively. Finally, the experiment is further verified by another dataset of Hurricane Irma, and it is concluded that the paper method is feasible.

scholarly journals Economic damages from Hurricane Sandy attributable to sea level rise caused by anthropogenic climate change

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Benjamin H. Strauss ◽  
Philip M. Orton ◽  
Klaus Bittermann ◽  
Maya K. Buchanan ◽  
Daniel M. Gilford ◽  
...  
Keyword(s):  
Climate Change ◽  
Sea Level Rise ◽  
Sea Level ◽  
East Coast ◽  
The United States ◽  
Hurricane Sandy ◽  
Water Levels ◽  
Anthropogenic Climate Change ◽  
Economic Damage ◽  
Sea Levels

AbstractIn 2012, Hurricane Sandy hit the East Coast of the United States, creating widespread coastal flooding and over $60 billion in reported economic damage. The potential influence of climate change on the storm itself has been debated, but sea level rise driven by anthropogenic climate change more clearly contributed to damages. To quantify this effect, here we simulate water levels and damage both as they occurred and as they would have occurred across a range of lower sea levels corresponding to different estimates of attributable sea level rise. We find that approximately $8.1B ($4.7B–$14.0B, 5th–95th percentiles) of Sandy’s damages are attributable to climate-mediated anthropogenic sea level rise, as is extension of the flood area to affect 71 (40–131) thousand additional people. The same general approach demonstrated here may be applied to impact assessments for other past and future coastal storms.

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