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Max Martin, S. Abhilash, Vijaykumar Pattathil, R. Harikumar, N. T. Niyas, T. M. Balakrishnan Nair, Yatin Grover, and Filippo Osella

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.

Open access
Tyler Fricker and Corey Friesenhahn

Abstract

Tornadoes account for the third highest average annual weather-related fatality rate in the United States. Here, tornado fatalities are examined as rates within the context of multiple physical and social factors using tornado-level information including population and housing units within killer tornado damage paths. Fatality rates are further evaluated across annual, monthly, and diurnal categories as well as between fatality locations and across age and sex categories. The geographic distribution of fatalities is then given by season, time of day, and residential structures. Results can be used by emergency managers, meteorologists, and planners to better prepare for high-impact (i.e., fatality) events and used by researchers as quantitative evidence to further investigate the relationship between tornadoes, climate, and society.

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Christine D. Miller Hesed, Michael Paolisso, Elizabeth R. Van Dolah, and Katherine J. Johnson

Abstract

Climate adaptation is context specific, and inclusion of diverse forms of knowledge is crucial for developing resilient social–ecological systems. Emphasis on local inclusion is increasing, yet participatory approaches often fall short of facilitating meaningful engagement of diverse forms of knowledge. A central challenge is the lack of a comprehensive and comparative understanding of the social–ecological knowledge that various stakeholders use to inform adaptation decisions. We employed cultural consensus analysis to quantitatively measure and compare social–ecological knowledge within and across three stakeholder groups: government employees, researchers, and local residents in rural coastal Maryland. The results show that 1) local residents placed more emphasis on addressing socioeconomic and cultural changes than researchers and government employees, and 2) that the greatest variation in social–ecological knowledge was found among local residents. These insights yielded by cultural consensus analysis are beneficial for facilitating more inclusive adaptation planning for resilient social–ecological systems.

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Berill Blair, Malte Müller, Cyril Palerme, Rayne Blair, David Crookall, Maaike Knol-Kauffman, and Machiel Lamers

Abstract

Forecasts of sea-ice evolution in the Arctic region for several months ahead can be of considerable socio-economic value for a diverse range of marine sectors and for local community supply logistics. However, subseasonal-to-seasonal (S2S) forecasts represent a significant technical challenge, while translating user needs into scientifically manageable procedures and robust user confidence requires collaboration among a range of stakeholders. We developed and tested a novel, transdisciplinary co-production approach that combined socio-economic scenarios and participatory, research-driven simulation-gaming to test a new S2S sea-ice forecast system with experienced mariners in the cruise tourism sector. Our custom-developed computerized simulation-game ICEWISE integrated sea-ice parameters, forecast technology and human factors, as a participatory environment for stakeholder engagement. We explored the value of applications-relevant S2S sea-ice prediction and linked uncertainty information. Results suggest that the usefulness of S2S services is currently most evident in schedule-dependent sectors but expected to increase due to anticipated changes in the physical environment and continued growth in Arctic operations. Reliable communication of uncertainty information in sea-ice forecasts must be demonstrated and trialed before users gain confidence in emerging services and technologies. Mariners’ own intuition, experience, and familiarity with forecast service provider reputation impact the extent to which sea-ice information may reduce uncertainties and risks for Arctic mariners. Our insights into the performance of the combined foresight/simulation co-production model in brokering knowledge across a range of domains demonstrates promise. We conclude with an overview of the potential contributions from S2S sea-ice predictions and from experiential co-production models to the development of decision-driven and science-informed climate services.

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Ling Tan and David M. Schultz

Abstract

Because many viral respiratory diseases show seasonal cycles, weather conditions could affect the spread of COVID-19. Although many studies pursued this possible link early in the pandemic, their results were inconsistent. Here, we assembled 158 quantitative empirical studies examining the link between weather and COVID-19. A meta-regression analysis was performed on their 4,793 correlation coefficients to explain these inconsistent results. We found four principal findings. First, 80 of the 158 studies did not state the time lag between infection and reporting, rendering these studies ineffective in determining the weather–COVID-19 relationship. Second, the research outcomes depended on the statistical analysis methods employed in each study. Specifically, studies using correlation tests produced outcomes that were functions of the geographical locations of the data from the original studies, whereas studies using linear regression produced outcomes that were functions of the analyzed weather variables. Third, Asian countries had more positive associations for air temperature than other regions, possibly because the air temperature was undergoing its seasonal increase from winter to spring during the rapid outbreak of COVID-19 in these countries. Fourth, higher solar energy was associated with reduced COVID-19 spread, regardless of statistical analysis method and geographical location. These results help interpret the inconsistent results and motivate recommendations for best practices in future research. These recommendations include calculating the effects of a time lag between the weather and COVID-19, using regression analysis models, considering nonlinear effects, increasing the time period considered in the analysis to encompass more variety of weather conditions and to increase sample size, and eliminating multicollinearity between weather variables.

Open access
Ruhollah Oji, Mehdi Hesam, and Victoria Keener

Abstract

Increased cooperation of an interdisciplinary group of climate change professionals as a social network can play a crucial role in adaptation to climate change. To investigate this relationship at the country-scale, this study uses a case study in Iran in order to 1) measure the cooperative relationship among climate change professionals using the network analysis approach, and; 2) analyze the potential of the network in promoting adaptation measures based on sustainable development. Social network analysis, which is both a quantitative and qualitative method of grounded theory was used to analyze the data. Data collection was performed using two questionnaires including network analysis and a survey, as well as a number of semi-structured interviews with the climate change professionals. The data was collected from climate change professionals including a sample of 55 individuals who were surveyed as a complete network. The network relationship results have been analyzed using different tests at three (micro, macro and the interactions between the two) levels. The results have shown that the connectedness of the network is 23.7%, with 42.4% mutual links. The transitivity rate in the network is 51.39%, which determines the possibility of each professional communicating with a third party. According to the normalized degree index, 34.29% of the cases are in contact with other researchers in the network and 53.15% received a connection from others. Grounded theory analysis showed that five core categories including social capital, managerial factors, research, relations, and coordination affected the quality and utility of Iranian climate change professionals’ network.

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Lisa K. Zottarelli, Starla A. Blake, and Michelle T. Garza

Abstract

Extreme heat events pose a threat to human health. Forecasting and warning strategies have been developed to mitigate heat-health hazards. Yet, studies have found that the public lacks knowledge about their heat-health risks and preventive actions to take to reduce risks. Local governmental websites are an important means to communicate preparedness to the public. The purpose of this study is to examine information provided to the public on municipal government webpages of the 10 most populous U.S. cities. A two-level document and content analyses were conducted. A direct content analysis was conducted using federal government websites and documents to create the Extreme Heat Event Public Response Rubric. The Rubric contains two broad categories of populations and actions that are further specified. The Rubric was then used to examine local government extreme heat event websites for the 10 most populous cities in the U.S. The examination of the local government sites found that information included on the websites failed to identify the breadth of populations at greater risk for adverse heat-health outcomes and omitted some recommended actions designed to prevent adverse heat-health events. Local governments often communicated concrete and simple content to the public but more complex information was not included on their websites.

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Matthias Neumair, Nicole Estrella, Annette Menzel, and Donna P. Ankerst

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 impacted rates of fatal accidents occurring in the popular mountainous regions of Austria with the purpose of improving mountain prevention and accident mitigation strategies. 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 one-degree Celsius increase in temperature was associated with a 13% increase in odds of a mountain biking accident in the summer and a 8% increase in odds of a mountain suicide in the winter. An increase in global radiation by 1 kWh/m2 was associated with a 11% and 28% increase in fatal accident odds for mountaineering in the summer and touring in the winter, respectively.

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Jacob R. Reed, Susan A. Jasko, and Jason C. Senkbeil

Abstract

Weather icons are some of the most frequently used visual tools meteorologists employ to communicate weather information. Previous research has shown a tendency for the public to make inferences about weather forecast information based on the icon shown. For example, people may infer a higher likelihood of precipitation, assume a higher intensity of precipitation, or determine the duration of expected precipitation if the weather icon appears to show heavy rain. It is unknown to what extent these inferences align with what the meteorologist who chose the icon intended to convey. However, previous studies have used simulated weather icons rather than ones currently in use. The goal of our study was to explore how members of the public interpret actual weather icons they see on television or in mobile applications. An online survey distributed by broadcast meteorologists through social media was used to collect 6,253 responses between August and September of 2020. Eleven weather icons currently used by broadcast meteorologists were included in the study. We also tested eight common weather phrases and asked people whether they thought the icons were good illustrators of those phrases. Additionally, people were asked to assign a probability of precipitation (PoP) to the icons. The findings of our study offer new and unique insights that will improve the communication of weather information by giving meteorologists information about how their audiences interpret weather icons.

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Ibrahima Diouf, Roberto Suárez-Moreno, Belen Rodríguez-Fonseca, Cyril Caminade, Malick Wade, Wassila M. Thiaw, Abdoulaye Deme, Andrew P. Morse, Jaques-André Ndione, Amadou T. Gaye, Anta Diaw, and Marie Khemesse Ngom Ndiaye

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 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 (cold) SST anomalies are responsible for increased (decreased) surface air temperatures and precipitation over West Africa, resulting in higher (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.

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