Transit Information Utilization during an Extreme Weather Event: An Analysis of Smartphone App Data

2018 ◽  
Vol 2672 (1) ◽  
pp. 90-100 ◽  
Author(s):  
Coline Remy ◽  
Candace Brakewood ◽  
Niloofar Ghahramani ◽  
Eun Jin Kwak ◽  
Jonathan Peters
Keyword(s):  
New York ◽  
Ordinary Least Squares ◽  
Extreme Weather ◽  
Transportation Systems ◽  
Extreme Weather Event ◽  
Extreme Weather Events ◽  
Weather Event ◽  
Information Utilization ◽  
Weather Events ◽  
Shared Mobility

Extreme weather events such as heavy snow can severely disrupt urban transportation systems. When this occurs, travelers often seek information about the status of transportation services. This study aims to assess information utilization during an extreme weather event by analyzing data from a smartphone application (“app”) called Transit, which provides real-time transit and shared mobility information in many cities. This research focuses on a snowstorm that hit the northeastern United States in January 2016 and severely disrupted transit and shared mobility services. An analysis of Transit app data is conducted in four parts for New York City, Philadelphia, and Washington, D.C. First, hourly app utilization during the snowstorm was compared with mean hourly app utilization prior to the storm. Second, the rate of app usage was calculated by dividing hourly utilization during the storm by the mean hourly volume before the storm. Third, an ordinary least squares regression model of hourly app usage was estimated for each city. Last, a feature within the app used to request Uber vehicles was examined. The results of the first three analyses reveal that overall app usage decreased during the snowstorm in all three cities; after the storm, New York experienced a significant increase in overall app use during the first Monday commuting period. The analysis of Uber data reveals that app users continued to search for ridehailing services during the snowstorm, despite travel bans. These findings are important for transportation operators and app developers to understand how travelers use information during extreme weather events.

The Extreme Weather Event Real-time Attribution Machine (EWERAM) – An Overview

2020 ◽  
Author(s):  
Jordis Tradowsky ◽  
Greg Bodeker ◽  
Leroy Bird ◽  
Stefanie Kremser ◽  
Peter Kreft ◽  
...  
Keyword(s):  
Climate Change ◽  
New Zealand ◽  
Public Awareness ◽  
Extreme Weather ◽  
Extreme Weather Event ◽  
Extreme Weather Events ◽  
Weather Event ◽  
Business Innovation ◽  
Weather Events

<p>As greenhouse gases continue to accumulate in Earth’s atmosphere, the nature of extreme weather events (EWEs) has been changing and is expected to change in the future. EWEs have contributions from anthropogenic climate change as well as from natural variability, which complicates attribution statements. EWERAM is a project that has been funded through the New Zealand Ministry of Business, Innovation and Employment Smart Ideas programme to develop the capability to provide, within days of an EWE having occurred over New Zealand, and while public interest is still high, scientifically defensible statements about the role of climate change in both the severity and frequency of that event. This is expected to raise public awareness and understanding of the effects of climate change on EWEs.</p><p>A team of researchers from five institutions across New Zealand are participating in EWERAM. EWE attribution is a multi-faceted problem and different approaches are required to address different research aims. Although robustly assessing the contribution of changes in the thermodynamic state to an observed event can be more tractable than including changes in the dynamics of weather systems, for New Zealand, changes in dynamics have had a large impact on the frequency and location of EWEs. As such, we have initiated several lines of research to deliver metrics on EWE attribution, tailored to meet the needs of various stakeholders, that encompass the effects of both dynamical and thermodynamical changes in the atmosphere. This presentation will give an overview of EWERAM and present the methodologies and tools used in the project.</p>

Extreme Weather and Climate

2017 ◽  
Author(s):  
Friederike Otto
Keyword(s):  
Extreme Events ◽  
The United States ◽  
Extreme Weather ◽  
Extreme Weather Events ◽  
Weather Event ◽  
Weather Forecasts ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Weather Events ◽  
Global Mean

Natural disasters and extreme weather events have been of great societal importance throughout history and often brought everyday life to a catastrophic halt, in a way sometimes comparable to wars and epidemics, only without the lead time. Extreme weather events with large impacts serve as an anchor point of the collective memory of the population in the affected area. Every northern German of the right age remembers the storm surge of 1962 and where they were at the time and has friends or family effected by the event. The “dust bowl” of the 1930s with extensive droughts and heat waves shaped the life of a generation in the United States, and the Sahel droughts in the 1960s and 1970s led to famine and dislocation of population on a massive scale the region arguably never quite recovered from. Hurricane Hyian in 2013 is said to have directly influenced the outcome of the annual Conference of the Parties (COP) United Nation Framework Convention for Climate Change Negotiations in Warsaw, leading to the inclusion of a mechanism to deal with loss and damage from climate-related disasters. Though earthquakes are still fairly unpredictable on short timescales, this is not the case for weather events. Weather forecasts today are so good that we normally know the time and location of the landfall of a hurricane within a 100-mile radius days in advance. Improvements in the prediction of slow-onset events such as droughts (which depend on the rainfall over a large region and whole season) are less striking but have still improved dramatically in the late 20th and early 21st centuries. One of the major reasons for the large increase in the accuracy of weather forecasts is the exponential increase in computing power, which allows scientists to predict and study extreme weather events using complex computer models, simulating possible weather events under certain conditions to understand the statistics of and physical mechanisms behind extreme events. Extreme events are by definition rare and thus impossible to understand from historical records of weather observation alone. Despite the progress on our understanding of and ability to predict extreme weather events, substantial uncertainties remain. Two aspects are of particular importance. Firstly, we know that the climate is changing, having observed almost a one-degree increase in global mean temperature. However, global mean temperature doesn’t kill anyone, extreme weather events do. Their frequency and intensity is changing and will continue to change, but the extent of these changes depends on a host of both global and local factors. Secondly, whether or not a rare weather event leads to extreme impacts depends largely on the vulnerability and exposure of the affected societies. If these are high, even a perfectly forecasted weather event leads to disaster.

scholarly journals Evaluating the Hydrodynamic Response of Coastal Bridges during an Extreme Weather Event

2019 ◽  
Vol 271 ◽  
pp. 01002
Author(s):  
Reza Nasouri ◽  
Adnan Shahriar ◽  
Adolfo Matamoros ◽  
Arturo Montoya ◽  
First Testik
Keyword(s):  
Wave Velocity ◽  
Water Waves ◽  
Numerical Study ◽  
Extreme Weather ◽  
Extreme Weather Event ◽  
Extreme Weather Events ◽  
Wave Impact ◽  
Weather Event ◽  
Coastal Bridges ◽  
Hydrodynamic Response

The frequency and intensity of recent hurricanes have demonstrated the need of taking proactive actions to prevent major damages during an extreme weather event. This work presents the results of a numerical study evaluating the hydrodynamic response of coastal bridges during an extreme hurricane event. A finite element model of a concrete bridge girder superstructure with a pier-substructure was developed in the commercial software Abaqus. The Coupled Eulerian-Lagrangian technique was used to model the interaction between water waves and the bridge as the structure deformed due to wave impacts. The wave velocity and the angle of wave impact were varied in the simulation to determine their effects on the response of the bridge. It was found that the resultant shear and uplift forces increase with wave velocity, while the angle of impact only had a significant effect on the resultant shear forces. The developed numerical framework will support further studies that will investigate variations in the bridge design and construction practices in order to enhance the resilience of coastal bridges against extreme weather events.

scholarly journals Defining Single Extreme Weather Events in a Climate Perspective

2018 ◽  
Vol 99 (8) ◽  
pp. 1557-1568 ◽  
Author(s):  
Julien Cattiaux ◽  
Aurélien Ribes
Keyword(s):  
Climate Change ◽  
Extreme Weather ◽  
Anthropogenic Climate Change ◽  
Extreme Weather Events ◽  
Intense Rainfall ◽  
Small Probability ◽  
Weather Extremes ◽  
Weather Event ◽  
Road Map ◽  
Weather Events

AbstractWeather extremes are the showcase of climate variability. Given their societal and environmental impacts, they are of great public interest. The prevention of natural hazards, the monitoring of single events, and, more recently, their attribution to anthropogenic climate change constitute key challenges for both weather services and scientific communities. Before a single event can be scrutinized, it must be properly defined; in particular, its spatiotemporal characteristics must be chosen. So far, this definition is made with some degree of arbitrariness, yet it might affect conclusions when explaining an extreme weather event from a climate perspective. Here, we propose a generic road map for defining single events as objectively as possible. In particular, as extreme events are inherently characterized by a small probability of occurrence, we suggest selecting the space–time characteristics that minimize this probability. In this way, we are able to automatically identify the spatiotemporal scale at which the event has been the most extreme. According to our methodology, the European heat wave of summer 2003 would be defined as a 2-week event over France and Spain and the Boulder, Colorado, intense rainfall of September 2013 a 5-day local event. Importantly, we show that in both cases, maximizing the rarity of the event does not maximize (or minimize) its fraction of attributable risk to anthropogenic climate change.

Preparedness and response at long-term care facilities following Hurricane Sandy: A qualitative analysis of experiences and attitudes among staff and administrators

2020 ◽  
Vol 18 (5) ◽  
pp. 383-398
Author(s):  
Lynn Jiang, MD ◽  
Christopher M. Tedeschi, MD, MA
Keyword(s):  
New York ◽  
Electrical Power ◽  
Extreme Weather ◽  
Hurricane Sandy ◽  
Extreme Weather Events ◽  
Semistructured Interview ◽  
Term Care ◽  
Weather Events ◽  
Care Facilities

Background: In late 2012, Hurricane Sandy struck the eastern United States. Healthcare infrastructure in New York City—including long-term care facilities (LTCFs)—was affected significantly. The authors examined the impact of the storm on LTCFs 2 years after the event, using a qualitative approach consisting of a semistructured interview focused on preparedness and response. Important insights regarding preparedness and response may be lost by quantitative analysis or outcome measurement alone. During Sandy, individuals at LTCFs experienced the event in important subjective ways that, in aggregate, could lead to valuable insights about how facilities might mitigate future risks. The authors used data from a semistructured interview to generate hypotheses regarding the preparation and response of LTCFs. The interview tool was designed to help develop theories to explain why LTCF staff and administrators experienced the event in the way they did, and to use that data to inform future policy and research. Methods: Representatives from LTCFs located in a heavily affected area of New York City were approached for participation in a semistructured interview. Interviews were digitally recorded and transcribed. Recurrent themes were coded based on time period (before, during, or after the storm) and content. A grounded theory approach was used to identify important themes related to the participants’ experiences.Results: A total of 21 interviews were conducted. Several overarching themes were identified, including a perception that facilities had not prepared for an event of such magnitude, of inefficient communication and logistics during evacuation, and of lack of easily identifiable or appropriate resources after the event. Access to electrical power emerged as a key identifier of recovery for most facilities. The experience had a substantial psychological impact on LTCF staff regardless of whether they evacuated or sheltered in place during the storm.Conclusion: Representatives from LTCFs affected by Sandy experienced the preparation, response, and recovery phases of the event with a unique perspective. Their insights offer evidence which can be used to generate testable hypothesis regarding similar events in the future, and can inform policy makers and facility administrators alike as they prepare for extreme weather events in similar settings. Results specifically suggest that LTCFs develop plans which carefully address the unique qualities of extreme weather events, including communication with local officials, evacuation and transfer needs in geographic areas with multiple facilities, and plans for the safe transfer of residents. Emergency managers at LTCFs should consider electrical power needs with the understanding that in extreme weather events, power failures can be more protracted than in other types of emergencies.

scholarly journals Improving Urban Resilience to Rainstorm Disasters: A Comparative Case Study of Beijing

2021 ◽  
pp. 2150010
Author(s):  
Qiaoyun SONG ◽  
Yan ZHENG ◽  
Chenzhen LIN
Keyword(s):  
Analytical Framework ◽  
Extreme Weather ◽  
Extreme Weather Events ◽  
Comparative Case Study ◽  
Urban Resilience ◽  
Weather Event ◽  
Development Level ◽  
Weather Events ◽  
Climatic Risks

Urban resilience is a major indicator of a city’s sustainability. Climate change increases the frequency and intensity of extreme weather events, thereby increasing uncertainty and disaster risk. A city’s capacity to cope with climatic risks can be improved by developing resilience. In China, heavy rainfall is the most frequent and costly extreme weather event. We conducted a comparative case study on Beijing’s extraordinary 7.21 rainstorm disaster in 2012 and the 7.20 rainstorm in 2016. Taken generic resilience and specific resilience as the analytical framework, we found that generic resilience is mainly determined by the socio-economic development level and geography of each district; while the combination of engineering and non-engineering adaptive measures after 2012 disaster has improved the specific resilience to rainstorm disaster, which contributed a good performance in the 2016 rainstorm. As a megacity in China, Beijing is a representative case that provides guidance for other cities to improve their urban resilience to rainstorm disasters.

Assessing impacts to Tennessee State Park infrastructure caused by extreme weather events

2016 ◽  
Vol 14 (1) ◽  
pp. 2-20 ◽  
Author(s):  
Kendra Abkowitz Brooks ◽  
James Clarke
Keyword(s):  
Design Methodology ◽  
Extreme Weather ◽  
Extreme Weather Events ◽  
Event Type ◽  
Weather Event ◽  
Content Type ◽  
Infrastructure Systems ◽  
Weather Events ◽  
Financial Decision ◽  
Heat Events

Purpose – The purpose of this paper is to describe a risk-based methodology developed to identify the severity of impacts to various types of infrastructure located within the Tennessee State Park system when exposed to extreme weather events. Infrastructure systems, composed of various assets, are central to the economic, environmental and cultural functioning of the society. Understanding the potential impacts to these assets from various threats is fundamental to prudent strategic, operational and financial decision-making. Among infrastructure, systems of interest are those managed and operated by park services. Such systems are particularly exposed to extreme weather, given the recreational activities that they provide. Design/methodology/approach – This paper describes a risk-based methodology developed to identify the severity of impacts to various types of infrastructure located within the Tennessee State Park system when exposed to extreme weather events. It consists of the following steps: identifying extreme weather event types experienced in Tennessee; assessing damage to various types of park system infrastructure caused by these events; and deriving an overall impact score associated with specific types of park system infrastructure when exposed to certain types of extreme weather scenarios. Findings – In applying this methodology, tornadic events were found to be most impactful, whereas drought and heat events had the least effect on park infrastructure. Dining and lodging infrastructure were found to incur the most damage, regardless of the weather event type. Originality/value – The approach as described in this paper is transferable to other park systems as well as public sector assets in general.

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