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Johannes Möllmann, Matthias Buchholz, and Oliver Musshoff

Abstract

Weather derivatives are considered a promising agricultural risk management tool. Station-based meteorological indices typically provide the data underlying these instruments. However, the main shortcoming of these weather derivatives is an imperfect correlation between the weather index and the yield of the insured crop, called basis risk. This paper considers three available remotely sensed vegetation health (VH) indices, namely, the vegetation condition index (VCI), the temperature condition index (TCI), and the vegetation health index (VHI), as indices for weather derivatives in a German case study. We investigated the correlation and period of highest correlation with winter wheat yield. Moreover, we analyzed whether the use of remotely sensed VH indices for weather derivatives can reduce basis risk and thus improve the performance of weather derivatives. The two commonly used meteorological indices, precipitation and temperature sums, were employed as benchmarks. Quantile regression and index value simulation were used for the design and pricing of the weather derivatives. The analysis for the selected farms and corresponding counties in northeastern Germany revealed that, on average, the VHI resulted in the highest correlation with winter wheat yield, and VHI-based weather derivatives were also superior in terms of the hedging effectiveness. The total periods of the highest correlations ranged from the beginning of April to the end of July. VHI- and VCI-based weather derivatives led to statistically significant reductions of basis risk, compared to the benchmarks. Our results indicate that the VHI-based weather derivatives can be useful alternatives to meteorological indices, especially in regions with sparser weather station networks.

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Jamie Hannaford, Kevin Collins, Sophie Haines, and Lucy J. Barker

Abstract

Drought is widely written about as a complex, multifaceted phenomenon, with complexity arising not just from biophysical drivers, but also human understanding and experiences of drought and its impacts. This has led to a proliferation of different drought definitions and indicators, creating a challenge for the design of drought monitoring and early warning (MEW) systems, which are a key component of drought preparedness. Here, we report on social learning workshops conducted in the United Kingdom aimed at improving the design and operation of drought MEW systems as part of a wider international project including parallel events in the United States and Australia. We highlight key themes for MEW design and use: “types” of droughts, indicators and impacts, uncertainty, capacity and decision-making, communications, and governance. We shed light on the complexity of drought through the multiple framings of the problem by different actors, and how this influences their needs for MEW. Our findings suggest that MEW systems need to embrace this complexity and strive for consistent messaging while also tailoring information for a wide range of audiences in terms of the drought characteristics, temporal and spatial scales, and impacts that are important for their particular decision-making processes. We end with recommendations to facilitate this approach.

Open access
Jason Senkbeil, Jennifer Collins, and Jacob Reed

Abstract

Hurricane Irma was one of the strongest Atlantic hurricanes in history before landfall and caused a large evacuation. A total of 155 evacuees at interstate rest areas were asked to rank their concern about damage at their residence for six different geophysical hurricane hazards. Additionally, they were asked about their perceived maximum wind speeds (PMWS) and the wind speeds at which they thought damage would occur (DW) at their residence. These wind speeds were then compared to the actual peak wind gusts (APG) nearest to each resident’s location. Results show a significantly greater concern for wind and storm size, compared to other hazards (tornadoes, rainfall/flooding, storm surge, falling trees). The mean PMWS of evacuees was greater than the mean APG, suggesting widespread misperception of wind speeds. Furthermore, the mean APG was less than the mean DW, and the mean PMWS was also higher than the DW. Additional tests found no significant differences in wind perception between residents with previous storm experiences and no experience, and no significant differences between those who resided in mandatory evacuation zip codes and those who did not. These results suggest that wind speed risk is poorly understood, even though it is a high concern for evacuees from hurricanes. The communication of wind speed risk in forecasts should possibly be modified by placing greater emphasis on postlandfall impacts, wind speed decay after landfall, and wind speeds that cause damage to different types of residences.

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Markus Enenkel, Daniel Osgood, Martha Anderson, Bristol Powell, Jessica McCarty, Christopher Neigh, Mark Carroll, Margaret Wooten, Greg Husak, Christopher Hain, and Molly Brown

Abstract

The goal of drought-related weather index insurance (WII) is to protect smallholder farmers against the risk of weather shocks and to increase their agricultural productivity. Estimates of precipitation and vegetation greenness are the two dominant satellite datasets. However, ignoring additional moisture- and energy-related processes that influence the response of vegetation to rainfall leads to an incomplete representation of the hydrologic cycle. This study evaluates the added value of considering multiple independent satellite-based variables to design, calibrate, and validate weather insurance indices on the African continent. The satellite data include two rainfall datasets, soil moisture, the evaporative stress index (ESI), and vegetation greenness. We limit artificial advantages by resampling all datasets to the same spatial (0.25°) and temporal (monthly) resolution, although datasets with a higher spatial resolution might have an added value, if considered as the single source of information for localized applications. A higher correlation coefficient between the moisture-focused variables and the normalized difference vegetation index (NDVI), an indicator for vegetation vigor, provides evidence for the datasets’ capability to capture agricultural drought conditions on the ground. The Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) rainfall dataset, soil moisture, and ESI show higher correlations with the (lagged) NDVI in large parts of Africa, for different land covers and various climate zones, than the African Rainfall Climatology, version 2 (ARC2), rainfall dataset, which is often used in WII. A comparison to drought years as reported by farmers in Ethiopia, Senegal, and Zambia indicates a high “hit rate” of all satellite-derived anomalies regarding the detection of severe droughts but limitations regarding moderate drought events.

Open access
Astrid Kause, Tarlise Townsend, and Wolfgang Gaissmaier

Abstract

The public debate around climate change is increasingly polarized. At the same time, the scientific consensus about the causes and consequences of climate change is strong. This inconsistency poses challenges for mitigation and adaptation efforts. The translation of uncertain numerical climate projections into simpler but ambiguous verbal frames may contribute to this polarization. In two experimental studies, we investigated 1) how “communicators” verbally frame a confidence interval regarding projected change in winter precipitation due to climate change (N = 512) and 2) how “listeners” interpret these verbal frames (N = 385). Both studies were preregistered at the Open Science Framework. Communicators who perceived the change as more severe chose a concerned rather than an unconcerned verbal frame. Furthermore, communicators’ verbal frames were associated with their more general beliefs, like political affiliation and environmental values. Listeners exposed to the concerned frame perceived climate change–induced precipitation change to be more severe than those receiving the unconcerned frame. These results are in line with two pilot studies (N = 298 and N = 393, respectively). Underlying general beliefs about climate and the environment likely shape public communication about climate in subtle ways, and thus verbal framing by the media, policymakers, and peers may contribute to public polarization on climate change.

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Matthew Cotton and Emma Stevens

Abstract

The concept of adaptation is becoming part of mainstream public discourse on climate change. Yet the diversity, complexity, and novelty of the adaptation concept itself leads to interpretive flexibility, differing public understanding of (and engagement with) adaptation strategies, and hence differentiated policy responses. The boundary work of communicative practices and public understanding of the adaptation concept therefore requires empirical analysis in different cases and contexts. This study employs Q-methodology (a combined quantitative–qualitative social research method) to reveal the typologies of perspectives that emerge around the adaptation concept among a diverse group of citizen-stakeholders in the United Kingdom. Four such typologies are identified under the labels 1) top-down climate action, 2) collective action on climate change, 3) optimistic, values-focused adaptation, and 4) adaptation skepticism. The division between these perspectives reveals a perceived “responsibility gap” between the governmental–institutional and/or individual–community levels. Across the emergent discourses we find a consensual call for a multisector, multiscalar, and multistakeholder-led approach that posits adaptation as a contemporary, intragenerational problem, with a strong emphasis upon managing extreme weather events, and not as an abstract future problem. By attending to these public discourses in climate policy, this presents a potential means to lessen such a responsibility gap.

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Wesley Tourangeau, Kate Sherren, Carlisle Kent, and Bertrum H. MacDonald

Abstract

Producer organizations representing Canada’s farm and livestock sectors are powerful change agents and advocates for their industries, particularly during challenging times such as climate- or weather-related hardships. Such organizations have a complex role: engaging with policy-makers, as well as their memberships and the public, to pursue the interests of their specific communities. This paper includes an examination of how farm producer organizations communicate about climate and weather to these various audiences, and the specific needs and recommendations they advance. Of particular interest are commodities related to pasture-based grazing, which is underrepresented in the climate adaptation literature. A collection of 95 publicly available documents is analyzed, representing a snapshot of climate- and weather-related public and policy engagement of Canadian and Albertan farm and livestock producer organizations from 2010 to 2015. Qualitative coding by scale, commodity, and audience revealed three significant patterns within this exploratory study. First, while national “umbrella” organizations speak climate to government, Alberta-based livestock/forage organizations speak to their members with a focus on weather. Second, while the two national umbrella organizations examined are politically divergent, they appear to be united on the topic of climate change. Third, common ground was also found between climate and weather discourses around on-farm management, specifically rotational grazing. These three patterns reveal a disjointed dialogue within the Canadian farm and livestock sectors on topics of climate adaptation and mitigation, as well as opportunities for future cooperation, and the need for further research on farm organization beliefs and their capacity to create/manage climate knowledge.

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Xi Hu, Xiujuan Zhang, and Jiuchang Wei

Abstract

Hazard warning is vital in disaster management. The rapid development of social media allows warning producers and receivers to exchange warning messages effectively and sufficiently. This study investigates the factors that influence public attention to natural hazard warning information on social media. Drawing from the protective action decision model and framing theory, this study classifies antecedents into three groups, namely, hazard information, publisher’s/reader’s characteristics, and frame setting. To test the hypotheses empirically, we select Sina Weibo, the leading social network in China, as the research context. From this platform, 3452 warning messages issued by authorities in the target area are collected. We code each message based on its attributes that are related to our study for linear regression analyses. Results show that all the factors related to publisher’s/reader’s characteristics exert significant effects on public attention. However, the affected range indicated by a warning message and the formality of the message’s language are not significantly related to public attention to the message.

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Joshua J. Hatzis, Jennifer Koch, and Harold E. Brooks

Abstract

In the hazards literature, a near-miss is defined as an event that had a nontrivial probability of causing loss of life or property but did not due to chance. Frequent near-misses can desensitize the public to tornado risk and reduce responses to warnings. Violent tornadoes rarely hit densely populated areas, but when they do they can cause substantial loss of life. It is unknown how frequently violent tornadoes narrowly miss a populated area. To address this question, this study looks at the spatial distribution of possible exposures of people to violent tornadoes in the United States. We collected and replicated tornado footprints for all reported U.S. violent tornadoes between 1995 and 2016, across a uniform circular grid, with a radius of 40 km and a resolution of 0.5 km, surrounding the centroid of the original footprint. We then estimated the number of people exposed to each tornado footprint using proportional allocation. We found that violent tornadoes tended to touch down in less populated areas with only 33.1% potentially impacting 5000 persons or more. Hits and near-misses were most common in the Southern Plains and Southeast United States with the highest risk in central Oklahoma and northern Alabama. Knowledge about the location of frequent near-misses can help emergency managers and risk communicators target communities that might be more vulnerable, due to an underestimation of tornado risk, for educational campaigns. By increasing educational efforts in these high-risk areas, it might be possible to improve local knowledge and reduce casualties when violent tornadoes do hit.

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Jennifer R. Fownes and Shorna B. Allred

Abstract

The general public’s perceptions of climate change may be shaped by local climate impacts through the mechanism of experiential processing. Although climate change is a long-term global trend, individuals personally experience it as weather from moment to moment. This study assesses how New York State adults’ overall perceptions of their personal experiences with the effects of climate change and extreme weather (surveyed in early 2014) are related to recent weather conditions. This research is unique in that it examines multiple types of weather: temperature and precipitation, over 1 day or 1 week, quantified both as relative and nonrelative measures. Respondents’ perceptions that they had personally experienced climate change or extreme weather significantly increased with warmer relative (percentage of normal) minimum temperatures on the day of the study. Maximum temperatures and total precipitation levels were not significant predictors of perceptions of personal experience, either on the day of the study or over the preceding week. Experiential processing had a smaller effect on perceptions than motivated reasoning, the influence of preexisting ideas. Respondents who believed that climate change was happening agreed more that they had personally experienced it or extreme weather, and this effect increased for individuals who thought that climate change was anthropogenic, as opposed to naturally caused. Of the sociodemographic factors assessed here, political party, gender, and region were significant predictors, while age and education were not.

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