Browse
Abstract
Impact forecasts and warnings (IFW) are key to resilience for hydrometeorological hazards. Communicating the potential social, economic, and environmental hazard impacts allows individuals and communities to adjust their plans and better prepare for the consequences of the hazard. IFW systems require additional knowledge about impacts and underlying vulnerability and exposure. Lack of data or knowledge about impacts, vulnerability, and exposure has been identified as a challenge for IFW implementation. In this study, we begin to address this challenge by developing an understanding of the data needs and uses for IFWs. Using the grounded theory method, we conducted a series of interviews with users and creators of hazard, impact, vulnerability, and exposure data (e.g., warning services, forecasters, meteorologists, hydrologists, emergency managers, data specialists, risk modelers) to understand where these data are needed and used in the warning value chain, a concept used to represent and understand the flow of information among actors in the warning chain. In support of existing research, we found a growing need for creating, gathering, and using impact, vulnerability, and exposure data for IFWs. Furthermore, we identified different approaches for impact forecasting and defining impact thresholds using objective models and subjective impact-oriented discussions depending on the data available. We also provided new insight into a growing need to identify, model, and warn for social and health impacts, which have typically taken a back seat to modeling and forecasting physical and infrastructure impacts. Our findings on the data needs and uses within IFW systems will help guide their development and provide a pathway for identifying specific relevant data sources.
Abstract
Impact forecasts and warnings (IFW) are key to resilience for hydrometeorological hazards. Communicating the potential social, economic, and environmental hazard impacts allows individuals and communities to adjust their plans and better prepare for the consequences of the hazard. IFW systems require additional knowledge about impacts and underlying vulnerability and exposure. Lack of data or knowledge about impacts, vulnerability, and exposure has been identified as a challenge for IFW implementation. In this study, we begin to address this challenge by developing an understanding of the data needs and uses for IFWs. Using the grounded theory method, we conducted a series of interviews with users and creators of hazard, impact, vulnerability, and exposure data (e.g., warning services, forecasters, meteorologists, hydrologists, emergency managers, data specialists, risk modelers) to understand where these data are needed and used in the warning value chain, a concept used to represent and understand the flow of information among actors in the warning chain. In support of existing research, we found a growing need for creating, gathering, and using impact, vulnerability, and exposure data for IFWs. Furthermore, we identified different approaches for impact forecasting and defining impact thresholds using objective models and subjective impact-oriented discussions depending on the data available. We also provided new insight into a growing need to identify, model, and warn for social and health impacts, which have typically taken a back seat to modeling and forecasting physical and infrastructure impacts. Our findings on the data needs and uses within IFW systems will help guide their development and provide a pathway for identifying specific relevant data sources.
Abstract
Snow has numerous effects on traffic, including reduced traffic volumes, greater crash risk, and increased travel times. This research examines how snow affects crash risk, traffic volume, and toll revenue on the New York State Thruway. Daily data from January for a 10-yr period (2010–19) were analyzed for the Thruway from the Pennsylvania state line in western New York to Syracuse. Anywhere from 35% to 50% of crashes are associated with inclement weather, with smaller impacts, proportionally, in areas with greater traffic volumes. As expected, snow was almost always involved when weather was a factor. “Unsafe speed” was the most common cause of crashes in inclement weather with all other factors (e.g., animals, drowsiness) much less likely to play a role. The percentage of crashes resulting in an injury did not change significantly with inclement conditions when compared with crashes occurring in fair conditions, and there were too few fatal crashes to make any inferences about them. Daily snowfall rates predicted about 30% of the variation in crash numbers, with every 5.1 cm of snowfall resulting in an additional crash, except in Buffalo where 5.1 cm of snow resulted in an additional 2.6 crashes. Confirming earlier results, daily snowfall had a large impact on passenger vehicle counts whereas commercial vehicle counts were less affected. Revenue data showed a similar pattern, with passenger revenue typically decreasing by 3%–5% per 2.5 cm of snow, whereas commercial revenue decreases were 1%–4% per 2.5 cm of snow.
Significance Statement
While it seems obvious that snowfall increases the number of crashes, decreases traffic volume, and reduces toll revenues, research is limited to support these assumptions, especially the latter two. This study involved an analysis of such items for the New York State Thruway. We found that increasing amounts of snow did cause more crashes. While traffic counts decreased, most of the decrease was in the number of passenger vehicles; commercial vehicle traffic was much less affected. Every 2.5 cm of snow costs the New York State Thruway approximately $1300 at each toll barrier and about $331 at each exit. These findings are helpful to law enforcement, emergency responders, and highway managers.
Abstract
Snow has numerous effects on traffic, including reduced traffic volumes, greater crash risk, and increased travel times. This research examines how snow affects crash risk, traffic volume, and toll revenue on the New York State Thruway. Daily data from January for a 10-yr period (2010–19) were analyzed for the Thruway from the Pennsylvania state line in western New York to Syracuse. Anywhere from 35% to 50% of crashes are associated with inclement weather, with smaller impacts, proportionally, in areas with greater traffic volumes. As expected, snow was almost always involved when weather was a factor. “Unsafe speed” was the most common cause of crashes in inclement weather with all other factors (e.g., animals, drowsiness) much less likely to play a role. The percentage of crashes resulting in an injury did not change significantly with inclement conditions when compared with crashes occurring in fair conditions, and there were too few fatal crashes to make any inferences about them. Daily snowfall rates predicted about 30% of the variation in crash numbers, with every 5.1 cm of snowfall resulting in an additional crash, except in Buffalo where 5.1 cm of snow resulted in an additional 2.6 crashes. Confirming earlier results, daily snowfall had a large impact on passenger vehicle counts whereas commercial vehicle counts were less affected. Revenue data showed a similar pattern, with passenger revenue typically decreasing by 3%–5% per 2.5 cm of snow, whereas commercial revenue decreases were 1%–4% per 2.5 cm of snow.
Significance Statement
While it seems obvious that snowfall increases the number of crashes, decreases traffic volume, and reduces toll revenues, research is limited to support these assumptions, especially the latter two. This study involved an analysis of such items for the New York State Thruway. We found that increasing amounts of snow did cause more crashes. While traffic counts decreased, most of the decrease was in the number of passenger vehicles; commercial vehicle traffic was much less affected. Every 2.5 cm of snow costs the New York State Thruway approximately $1300 at each toll barrier and about $331 at each exit. These findings are helpful to law enforcement, emergency responders, and highway managers.
Abstract
Projections of warmer global temperatures in fast-approaching time horizons warrant planning strategies for reducing impacts on human morbidity and mortality. This study sought to determine whether increases in temperature and other changes in weather indices had an impact on rates of fatal accidents occurring in the popular mountainous regions of Austria, with the purpose of improving prevention and accident-mitigation strategies in the mountains. The study was based on the merging of 3285 fatal outdoor accidents reported by the Austrian Alpine Safety Board for the period 2006 to 2018 with daily meteorological data from 43 nearby climate stations during the same period. Multivariable logistic regression was used to model the odds of one or more fatal accidents per station and day with weather indices as predictors, controlling for weekend effects bringing more visitors to the mountains. Separate prediction models were performed for summer and winter activities, as well as for specific disciplines. Even after adjustment for concomitant effects impacting mountain fatal accidents, the daily weather indices of temperature, relative humidity, global radiation, cloudiness, snow cover and precipitation were statistically significantly associated with fatal-accident risk. In particular, a 1° increase in temperature was associated with a 13% increase in odds of a mountain-biking accident in the summer and an 8% increase in odds of a mountain suicide in the winter. An increase in global radiation by 1 kW h m−2 was associated with an 11% and 28% increase in fatal-accident odds for mountaineering in the summer and touring in the winter, respectively.
Abstract
Projections of warmer global temperatures in fast-approaching time horizons warrant planning strategies for reducing impacts on human morbidity and mortality. This study sought to determine whether increases in temperature and other changes in weather indices had an impact on rates of fatal accidents occurring in the popular mountainous regions of Austria, with the purpose of improving prevention and accident-mitigation strategies in the mountains. The study was based on the merging of 3285 fatal outdoor accidents reported by the Austrian Alpine Safety Board for the period 2006 to 2018 with daily meteorological data from 43 nearby climate stations during the same period. Multivariable logistic regression was used to model the odds of one or more fatal accidents per station and day with weather indices as predictors, controlling for weekend effects bringing more visitors to the mountains. Separate prediction models were performed for summer and winter activities, as well as for specific disciplines. Even after adjustment for concomitant effects impacting mountain fatal accidents, the daily weather indices of temperature, relative humidity, global radiation, cloudiness, snow cover and precipitation were statistically significantly associated with fatal-accident risk. In particular, a 1° increase in temperature was associated with a 13% increase in odds of a mountain-biking accident in the summer and an 8% increase in odds of a mountain suicide in the winter. An increase in global radiation by 1 kW h m−2 was associated with an 11% and 28% increase in fatal-accident odds for mountaineering in the summer and touring in the winter, respectively.
Abstract
In 2018, tourism was the fastest growing sector in the world, accounting for 10% of all jobs worldwide and 10.4% of the world’s gross domestic product. Tourism is often cited as a strategy for future development at national, regional, and local levels. This paper takes a closer look at the Lofoten Islands in northern Norway, where the increase in nature-based tourism over the last two decades has occurred in parallel with the restructuring of the traditional fisheries. Nature-based tourism in rural regions relies heavily on a broad range of ecosystem services (ES). This paper will present how stakeholders in nature-based tourism assess the influence of climate change on ES crucial for their activities and for the destination and will outline and explain how the practitioners perceive their ability to withstand or adapt to these changes. With the aid of models depicting potential future climate scenarios, we initiated discussions with stakeholders and found that tourism actors have only to a minor degree sought to develop strategies to increase adaptive capacity and therefore resilience to climate change. Based on our findings, we discuss how the adaptive capacity of individual actors in nature-based tourism forms the basis for the system’s resilience, and that a general resilience focus also forms the basis for transformational capacity, a capacity needed for future resilience. In light of our findings and analyses, we will conclude by reflecting on overarching systemic transformative tendencies in the wake of coronavirus disease 2019 (COVID-19) and obligations contained in the Paris Agreement on reducing global emissions.
Abstract
In 2018, tourism was the fastest growing sector in the world, accounting for 10% of all jobs worldwide and 10.4% of the world’s gross domestic product. Tourism is often cited as a strategy for future development at national, regional, and local levels. This paper takes a closer look at the Lofoten Islands in northern Norway, where the increase in nature-based tourism over the last two decades has occurred in parallel with the restructuring of the traditional fisheries. Nature-based tourism in rural regions relies heavily on a broad range of ecosystem services (ES). This paper will present how stakeholders in nature-based tourism assess the influence of climate change on ES crucial for their activities and for the destination and will outline and explain how the practitioners perceive their ability to withstand or adapt to these changes. With the aid of models depicting potential future climate scenarios, we initiated discussions with stakeholders and found that tourism actors have only to a minor degree sought to develop strategies to increase adaptive capacity and therefore resilience to climate change. Based on our findings, we discuss how the adaptive capacity of individual actors in nature-based tourism forms the basis for the system’s resilience, and that a general resilience focus also forms the basis for transformational capacity, a capacity needed for future resilience. In light of our findings and analyses, we will conclude by reflecting on overarching systemic transformative tendencies in the wake of coronavirus disease 2019 (COVID-19) and obligations contained in the Paris Agreement on reducing global emissions.
Abstract
In an era of globalization, the spread of misinformation is becoming increasingly problematic. The dissemination of inaccurate and conflicting news on events such as tropical cyclones can result in people being placed at increased risk and can negatively influence the amount of aid received by the affected region. This study scrutinizes media articles and, with the use of comparative analysis, uncovers the potential cause of misinformation in disaster journalism. The results of the study found that 59% (n = 80) of the articles reported on wind speed values and 80% (n = 80) of the articles reported on the number of fatalities. Results indicate that 44% (n = 80) of the articles used official sources, uncovering that a potential source of misinformation is not only what is provided to journalists from official sources but also how the various sources can lead to contradicting news articles. The variations in news reports can be attributed to factors such as the influx of different reports and the changing conditions during a disaster, all of which make consistent reporting on a disaster a challenging process.
Abstract
In an era of globalization, the spread of misinformation is becoming increasingly problematic. The dissemination of inaccurate and conflicting news on events such as tropical cyclones can result in people being placed at increased risk and can negatively influence the amount of aid received by the affected region. This study scrutinizes media articles and, with the use of comparative analysis, uncovers the potential cause of misinformation in disaster journalism. The results of the study found that 59% (n = 80) of the articles reported on wind speed values and 80% (n = 80) of the articles reported on the number of fatalities. Results indicate that 44% (n = 80) of the articles used official sources, uncovering that a potential source of misinformation is not only what is provided to journalists from official sources but also how the various sources can lead to contradicting news articles. The variations in news reports can be attributed to factors such as the influx of different reports and the changing conditions during a disaster, all of which make consistent reporting on a disaster a challenging process.
Abstract
Climate variability is a key factor in driving malaria outbreaks. As shown in previous studies, climate-driven malaria modeling provides a better understanding of malaria transmission dynamics, generating malaria-related parameters validated as a reliable benchmark to assess the impact of climate on malaria. In this framework, the present study uses climate observations and reanalysis products to evaluate the predictability of malaria incidence in West Africa. Sea surface temperatures (SSTs) are shown as a skillful predictor of malaria incidence, which is derived from climate-driven simulations with the Liverpool Malaria Model (LMM). Using the SST-based Statistical Seasonal Forecast model (S4CAST) tool, we find robust modes of anomalous SST variability associated with skillful predictability of malaria incidence Accordingly, significant SST anomalies in the tropical Pacific and Atlantic Ocean basins are related to a significant response of malaria incidence over West Africa. For the Mediterranean Sea, warm SST anomalies are responsible for increased surface air temperatures and precipitation over West Africa, resulting in higher malaria incidence; conversely, cold SST anomalies are responsible for decreased surface air temperatures and precipitation over West Africa, resulting in lower malaria incidence.. Our results put forward the key role of SST variability as a source of predictability of malaria incidence, being of paramount interest to decision-makers who plan public health measures against malaria in West Africa. Accordingly, SST anomalies could be used operationally to forecast malaria risk over West Africa for early warning systems.
Abstract
Climate variability is a key factor in driving malaria outbreaks. As shown in previous studies, climate-driven malaria modeling provides a better understanding of malaria transmission dynamics, generating malaria-related parameters validated as a reliable benchmark to assess the impact of climate on malaria. In this framework, the present study uses climate observations and reanalysis products to evaluate the predictability of malaria incidence in West Africa. Sea surface temperatures (SSTs) are shown as a skillful predictor of malaria incidence, which is derived from climate-driven simulations with the Liverpool Malaria Model (LMM). Using the SST-based Statistical Seasonal Forecast model (S4CAST) tool, we find robust modes of anomalous SST variability associated with skillful predictability of malaria incidence Accordingly, significant SST anomalies in the tropical Pacific and Atlantic Ocean basins are related to a significant response of malaria incidence over West Africa. For the Mediterranean Sea, warm SST anomalies are responsible for increased surface air temperatures and precipitation over West Africa, resulting in higher malaria incidence; conversely, cold SST anomalies are responsible for decreased surface air temperatures and precipitation over West Africa, resulting in lower malaria incidence.. Our results put forward the key role of SST variability as a source of predictability of malaria incidence, being of paramount interest to decision-makers who plan public health measures against malaria in West Africa. Accordingly, SST anomalies could be used operationally to forecast malaria risk over West Africa for early warning systems.
Abstract
This study proposes the concept of quiet weather communication and offers the first framework of quiet weather communication strategies tied to specific public outcomes (e.g., build and maintain organization–public relationships). Most of the risk communication literature focuses on severe weather communication. We posit that through defining and examining quiet weather strategic communication we can better understand how the weather enterprise can prepare communities for future severe weather. Through four virtual focus groups with 28 NWS and broadcast meteorologists, we operationalize quiet weather communication strategies (humanize the organization, provide weather education, share the love of blue skies, and showcase quiet weather trends). We then report meteorologists’ perceptions of the strengths and weaknesses of each strategy and propose future directions for research on quiet weather communication.
Abstract
This study proposes the concept of quiet weather communication and offers the first framework of quiet weather communication strategies tied to specific public outcomes (e.g., build and maintain organization–public relationships). Most of the risk communication literature focuses on severe weather communication. We posit that through defining and examining quiet weather strategic communication we can better understand how the weather enterprise can prepare communities for future severe weather. Through four virtual focus groups with 28 NWS and broadcast meteorologists, we operationalize quiet weather communication strategies (humanize the organization, provide weather education, share the love of blue skies, and showcase quiet weather trends). We then report meteorologists’ perceptions of the strengths and weaknesses of each strategy and propose future directions for research on quiet weather communication.
Abstract
Weather index insurance (WII) has been a promising innovation that protects smallholder farmers against drought risks and provides resilience against adverse rainfall conditions. However, the uptake of WII has been hampered by high spatial and intraseasonal basis risk. To minimize intraseasonal basis risk, the standard approaches to designing WII based on seasonal cumulative rainfall have been shown to be ineffective in some cases because they do not incorporate different water requirements across each phenological stage of crop growth. One of the challenges in incorporating crop phenology in insurance design is to determine the water requirement in crop growth stages. Borrowing from agronomy, crop science, and agrometeorology, we adopt evapotranspiration methods in determining water requirements for a crop to survive in each stage that can be used as a trigger level for a WII product. Using daily rainfall and evapotranspiration data, we illustrate the use of Monte Carlo risk modeling to price an operational WII and WII-linked credit product. The risk modeling approach that we develop includes incorporation of correlation between rainfall and evapotranspiration indices that can minimize significant intertemporal basis risk in WII.
Abstract
Weather index insurance (WII) has been a promising innovation that protects smallholder farmers against drought risks and provides resilience against adverse rainfall conditions. However, the uptake of WII has been hampered by high spatial and intraseasonal basis risk. To minimize intraseasonal basis risk, the standard approaches to designing WII based on seasonal cumulative rainfall have been shown to be ineffective in some cases because they do not incorporate different water requirements across each phenological stage of crop growth. One of the challenges in incorporating crop phenology in insurance design is to determine the water requirement in crop growth stages. Borrowing from agronomy, crop science, and agrometeorology, we adopt evapotranspiration methods in determining water requirements for a crop to survive in each stage that can be used as a trigger level for a WII product. Using daily rainfall and evapotranspiration data, we illustrate the use of Monte Carlo risk modeling to price an operational WII and WII-linked credit product. The risk modeling approach that we develop includes incorporation of correlation between rainfall and evapotranspiration indices that can minimize significant intertemporal basis risk in WII.
Abstract
Ocean State Forecasts contribute to safe and sustainable fishing in India, but their usage among artisanal fishers is often limited. Our research in Thiruvananthapuram district in the southern Indian state of Kerala tested forecast quality and value and how fishers engage with forecasts. In two fishing villages, we verified forecast accuracy, skill, and reliability by comparing forecasts with observations during the 2018 monsoon season (June–September; n = 122). We assessed forecast value by analyzing fishers’ perceptions of weather and risks and the way they used forecasts based on 8 focus group discussions, 20 interviews, conversations, and logs of 10 fishing boats. We find that while forecasts are mostly accurate, inadequate forecasting of unusual events (e.g., wind >45 km h−1) and frequent fishing restrictions (n = 32) undermine their value. Fishers seek more localized and detailed forecasts, but they do not always use them. Weather forecasts are just one of the tools artisanal fishers deploy, used not simply to decide as to whether to go to sea but also to manage potential risks, allowing them to prepare for fishing under hazardous conditions. Their decisions are also based on the availability of fish and their economic needs. From our findings, we suggest that political, economic, and social marginality of south Indian fishers influences their perceptions and responses to weather-related risks. Therefore, improving forecast usage requires not only better forecast skill and wide dissemination of tailor-made weather information, but also better appreciation of risk cultures and the livelihood imperatives of artisanal fishing communities.
Abstract
Ocean State Forecasts contribute to safe and sustainable fishing in India, but their usage among artisanal fishers is often limited. Our research in Thiruvananthapuram district in the southern Indian state of Kerala tested forecast quality and value and how fishers engage with forecasts. In two fishing villages, we verified forecast accuracy, skill, and reliability by comparing forecasts with observations during the 2018 monsoon season (June–September; n = 122). We assessed forecast value by analyzing fishers’ perceptions of weather and risks and the way they used forecasts based on 8 focus group discussions, 20 interviews, conversations, and logs of 10 fishing boats. We find that while forecasts are mostly accurate, inadequate forecasting of unusual events (e.g., wind >45 km h−1) and frequent fishing restrictions (n = 32) undermine their value. Fishers seek more localized and detailed forecasts, but they do not always use them. Weather forecasts are just one of the tools artisanal fishers deploy, used not simply to decide as to whether to go to sea but also to manage potential risks, allowing them to prepare for fishing under hazardous conditions. Their decisions are also based on the availability of fish and their economic needs. From our findings, we suggest that political, economic, and social marginality of south Indian fishers influences their perceptions and responses to weather-related risks. Therefore, improving forecast usage requires not only better forecast skill and wide dissemination of tailor-made weather information, but also better appreciation of risk cultures and the livelihood imperatives of artisanal fishing communities.
