Browse

You are looking at 21 - 30 of 554 items for :

  • Weather, Climate, and Society x
  • Refine by Access: All Content x
Clear All
Adrian Brügger, Christina Demski, and Stuart Capstick

Abstract

The proportion of the world’s population exposed to above-average monthly temperatures has been rising consistently in recent decades and will continue to grow. This and similar trends make it more likely that people will personally experience extreme weather events and seasonal changes related to climate change. A question that follows from this is to what extent experiences may influence climate-related beliefs, attitudes, and the willingness to act. Although research is being done to examine the effects of such experiences, many of these studies have two important shortcomings. First, they propose effects of experiences but remain unclear on the psychological processes that underlie those effects. Second, if they do make assumptions about psychological processes, they do not typically corroborate them with empirical evidence. In other words, a considerable body of research in this field rests on relatively unfounded intuitions. To advance the theoretical understanding of how experiences of climate change could affect the motivation to act on climate change, we introduce a conceptual framework that organizes insights from psychology along three clusters of processes: 1) noticing and remembering, 2) mental representations, and 3) risk processing and decision-making. Within each of these steps, we identify and explicate psychological processes that could occur when people personally experience climate change, and we formulate theory-based, testable hypotheses. By making assumptions explicit and tying them to findings from basic and applied research from psychology, this paper provides a solid basis for future research and for advancing theory.

Restricted access
Hua He, Guorong Chai, Yana Su, Yongzhong Sha, Shengliang Zong, and Hairong Bao

Abstract

This study assessing the lag and interactive effects between the daily average temperature and relative humidity on respiratory disease (RD) morbidity in Lanzhou, China, using data from daily outpatient visits for RD between 2014 and 2017 and meteorological and pollutant data during the same period analyzed with Poisson generalized linear model and distributed lag nonlinear models; the effects are further explored by classifying the RD by gender, age, and disease type. The results showed that the effect of temperature and relative humidity on outpatient visits of different populations and types of RD is nonlinear, with a significant lag effect. Relative to 11°C, every 1°C decrease in temperature is associated with 10.98% [95% confidence interval (CI): 9.87%–12.11%] increase for total RD. Chronic obstructive pulmonary disease is affected only by low temperature, upper respiratory tract infection is affected by both low and high temperatures, and asthma is influenced by high temperature. When the relative humidity is less than 32%, every 1% decrease in relative humidity is associated with 6.00% (95% CI: 3.00%–9.11%) increase for total RD; relative humidity has different effects on the outpatient risk of different types of RD. Temperature and relative humidity have an obvious interactive effect on different types and populations of RD: when both temperature and humidity are at low levels, the number of outpatient visits for RD is higher. When the relative humidity is ≤50% and the temperature is ≤11°C, total RD outpatient visits increase by 4.502% for every 1°C drop in temperature; that is, a dry environment with low temperature has the most significant impact on RD.

Restricted access
Basanta Raj Adhikari

Abstract

Lightning is one of the most devastating hazards in Nepal because of a large amount of atmospheric water vapor coming from the Indian Ocean and a large orographic lifting of this moist air. In 2019, a total of 2884 people were affected, with loss of USD 110,982, and the fatality number was the highest (94) in reported lightning events since 1971. The long-term analysis of this hazard is very scanty in Nepal. Therefore, this study analyzes lightning fatality events, fatality rates, and economic loss from 1971 to 2019 collected from the DesInventar dataset and the Disaster Risk Reduction portal of the government of Nepal using Statistical Package for Social Sciences (SPSS) and geographic information system (ArcGIS) tools. The analysis shows that the overall countrywide lightning fatality rate of the entire period is 1.77 per million per year. District lightning fatality rates range from 0.10 to 4.83 per million people per year, and the Bhaktapur district has the highest fatality density (0.067). Furthermore, there were a total of 2501 lightning fatality events in which 1927 people lost their lives and 20 569 people were affected. The increase in lightning fatality events in recent years is due to internet penetration and other measures of information gathering that result in lightning fatality reports reaching agencies collecting information. The high and low concentrations of loss and damage are mainly due to geographic distribution, population density, and economic activities. This study recommends the establishment of lightning early warning systems in the Nepal Himalayas to save life and property.

Restricted access
Ronald L. Holle, William A. Brooks, and Kenneth L. Cummins

Abstract

National park visitors travel primarily to view natural features while outdoors; however, visits often occur in warmer months when lightning is present. This study uses cloud-to-ground flashes from 1999 to 2018 and cloud-to-ground strokes from 2009 to 2018 from the National Lightning Detection Network to identify lightning at the 46 contiguous United States national parks larger than 100 km2. The largest density is 6.10 flashes per kilometer squared per year within Florida’s Everglades, and the smallest is near zero in Pinnacles National Park. The six most-visited parks are Great Smoky Mountains, Grand Canyon, Rocky Mountain, Zion, Yosemite, and Yellowstone. For each of these parks, lightning data are described by frequency and location as well as time of year and day. The four parks west of the Continental Divide have most lightning from 1 July to 15 September and from 1100 to 1900 LST. Each park has its own spatial lightning pattern that is dependent on local topography. Deaths and injuries from lightning within national parks have the same summer afternoon dominance shown by lightning data. Most casualties occur to people visiting from outside the parks’ states. The most common activities and locations are mountain climbing, hiking, and viewing canyons from overlooks. Lightning fatality risk, the product of areal visitor and CG flash densities, shows that many casualties are not in parks with high risk, while very small risk indicates parks where lightning awareness efforts can be minimized. As a result, safety advice should focus on specific locations such as canyon rims, mountains, and exposed high-altitude roads where lightning-vulnerable activities are engaged in by many visitors.

Restricted access
Restricted access
Majid Shafiee-Jood, Tatyana Deryugina, and Ximing Cai

Abstract

Forecast valuation studies play a key role in understanding the determinants of the value of weather and climate forecasts. Such understanding provides opportunities to increase the value that users can obtain from forecasts, which can in turn increase the use of forecasts. One of the most important factors that influences how users process forecast information and incorporate forecasts into their decision-making is trust in forecasts. Despite the evidence from empirical and field-based studies, modeling users’ trust in forecasts has not received much attention in the literature and is therefore the focus of our study. We propose a theoretical model of trust in information, built into a forecast valuation framework, to better understand 1) the role of trust in users’ processing of drought forecast information and 2) the dynamic process of users’ trust formation and evolution. Using a numerical experiment, we show that considering the dynamic nature of trust is critical in more realistic assessment of forecast value. We find that users may not perceive a potentially valuable forecast as such until they trust it enough, implying that exposure to even highly accurate forecasts may not immediately translate into forecast use. Ignoring this dynamic aspect could overestimate the economic gains from forecasts. Furthermore, the model offers hypotheses with regard to targeting strategies that can be tested with empirical and field-based studies and used to guide policy interventions.

Restricted access
Manishka De Mel, William Solecki, Radley Horton, Ryan Bartlett, Abigail Hehmeyer, Shaun Martin, and Cynthia Rosenzweig

Abstract

Integrating climate risk information into resilience-building activities in the field is important to ensure that adaptation is based on the best available science. Despite this, many challenges exist when developing, communicating, and incorporating climate risk information. There are limited resources on how stakeholders perceive risks, use risk information, and what barriers exist to limit knowledge integration. This paper seeks to define the following: 1) What do conservation stakeholders consider to be the most significant climate risks they face now and possibly in the future? 2) What have been the most significant barriers to their using climate risk information? 3) What sources and types of knowledge would be most useful for these managers to overcome these barriers? A survey was conducted among stakeholders (n = 224) associated with World Wildlife Fund projects in tropical and subtropical countries. A very high proportion of stakeholders used climate risk information and yet faced integration-related challenges, which included too much uncertainty and the lack of a relevant scale for planning. The main factors preventing the use of climate risk information in decision-making were unavailability of climate risk information, no or limited financial or human resources available to respond, lack of organizational mandate or support, and no or limited institutional incentives. Comparing perceived current and future risks revealed a decline in concern for some future climate hazards. Survey respondents identified scientific reports, climate scientists, and online sources as the most useful information sources of climate risk information, while (i) maps and illustrations; (ii) scenarios format; and (iii) data tables, graphs, and charts were identified as user-friendly formats.

Restricted access
Inez Z. Ponce de Leon

Abstract

Supertyphoon Haiyan hit the Philippines in 2013, causing massive damage and loss of lives. The media blamed the government for faulty warnings, including using the term “storm surge,” which people reportedly did not understand. As a result, the national agency tasked with disaster risk management recommended translating the term for better response in future storms. Such an approach shortchanges the complexity of risk construction and dismisses the possibility that different communities also have different understandings of risk. In this study, the researcher examined the special case of Coron, Palawan: a major tourist destination that is rarely hit by storms but that became the site of Haiyan’s last landfall. Guided by encoding–decoding theory, the researcher interviewed local government officials and carried out focus group discussions with representatives of two communities (whose names have been hidden under pseudonyms for this study): Central, close to the municipal center, and Island, a coastal village far away from potential aid and rescue. The researcher found a portrait of contrasts that split Coron: a mayor who surrendered all control and a risk management officer who planned for long-term hazard response—Island waiting for government instructions despite knowing about storm behavior and Central taking the initiative to create long-term solutions. Island also knew what storm surges were and did not need translation of the term. These findings show that risk constructions can differ even at the municipal level, which should prompt further research into the role of local knowledge in understanding risk and hazard warnings.

Restricted access
Kelley M. Murphy, Eric C. Bruning, Christopher J. Schultz, and Jennifer K. Vanos

Abstract

A lightning risk assessment for application to human safety was created and applied in 10 west Texas locations from 2 May 2016 to 30 September 2016. The method combined spatial lightning mapping data, probabilistic risk calculation adapted from the International Electrotechnical Commission Standard 62305-2, and weighted average interpolation to produce risk magnitudes that were compared with tolerability thresholds to issue lightning warnings. These warnings were compared with warnings created for the same dataset using a more standard lightning safety approach that was based on National Lightning Detection Network (NLDN) total lightning within 5 n mi (1 n mi = 1.852 km) of each location. Four variations of the calculation as well as different units of risk were tested to find the optimal configuration to calculate risk to an isolated human outdoors. The best-performing risk configuration using risk (10 min)−1 or larger produced the most comparable results to the standard method, such as number of failures, average warning duration, and total time under warnings. This risk configuration produced fewer failures than the standard method but longer total time under warnings and higher false alarm ratios. Median lead times associated with the risk configuration were longer than the standard method for all units considered, whereas median down times were shorter for risk (10 min)−1 and risk (15 min)−1. Overall, the risk method provides a baseline framework to quantify the changing lightning hazard on the storm scale and could be a useful tool to aid in lightning decision support scenarios.

Restricted access
Yajie Li, Amanda Lee Hughes, and Peter D. Howe

Abstract

Message diffusion and message persuasion are two important aspects of success for official risk messages about hazards. Message diffusion enables more people to receive lifesaving messages, and message persuasion motivates them to take protective actions. This study helps to identify win–win message strategies by investigating how an underexamined factor, message content that is theoretically important to message persuasion, influences message diffusion for official risk messages about heat hazards on Twitter. Using multilevel negative binomial regression models, the respective and cumulative effects of four persuasive message factors—hazard intensity, health risk susceptibility, health impact, and response instruction—on retweet counts were analyzed using a dataset of heat-related tweets issued by U.S. National Weather Service accounts. Two subsets of heat-related tweets were also analyzed: 1) heat warning tweets about current or anticipated extreme heat events and 2) tweets about nonextreme heat events. This study found that heat-related tweets that mentioned more types of persuasive message factors were retweeted more frequently, and so were two subtypes of heat-related tweets. Mentions of hazard intensity also consistently predicted increased retweet counts. Mentions of health impacts positively influenced message diffusion for heat-related tweets and tweets about nonextreme heat events. Mentions of health risk susceptibility and response instructions positively predicted retweet counts for tweets about nonextreme heat events and tweets about official extreme heat warnings, respectively. In the context of natural hazards, this research informs practitioners with evidence-based message strategies to increase message diffusion on social media. Such strategies also have the potential to improve message persuasion.

Restricted access