Browse

You are looking at 81 - 90 of 499 items for :

  • Weather, Climate, and Society x
  • Refine by Access: Content accessible to me x
Clear All
Lindsay C. Maudlin, Karen S. McNeal, Heather Dinon-Aldridge, Corey Davis, Ryan Boyles, and Rachel M. Atkins

ABSTRACT

Decision support systems—collections of related information located in a central place to be used for decision-making—can be used as platforms from which climate information can be shared with decision-makers. Unfortunately, these tools are not often evaluated, meaning developers do not know how useful or usable their products are. In this study, a web-based climate decision support system (DSS) for foresters in the southeastern United States was evaluated by using eye-tracking technology. The initial study design was exploratory and focused on assessing usability concerns within the website. Results showed differences between male and female forestry experts in their eye-tracking behavior and in their success with completing tasks and answering questions related to the climate information presented in the DSS. A follow-up study, using undergraduate students from a large university in the southeastern United States, aimed to determine whether similar gender differences existed and could be detected and, if so, whether the cause(s) could be determined. The second evaluation, similar to the first, showed that males and females focused their attention on different aspects of the website; males focused more on the maps depicting climate information while females focused more on other aspects of the website (e.g., text, search bars, and color bars). DSS developers should consider the possibility of gender differences when designing a web-based DSS and include website features that draw user attention to important DSS elements to effectively support various populations of users.

Free access
Calum G. Turvey, Apurba Shee, and Ana Marr

Abstract

Climate risk financing programs in agriculture have caught the attention of researchers and policy makers over the last decade. Weather index insurance has emerged as a promising market-based risk financing mechanism. However, to develop a suitable weather index insurance mechanism it is essential to incorporate the distribution of underlying weather and climate risks to a specific event model that can minimize intraseasonal basis risk. In this paper we investigate the erratic nature of rainfall patterns in Kenya using Climate Hazards Group Infrared Precipitation with Station Data (CHIRPS) rainfall data from 1983 to 2017. We find that the patterns of rainfall are fractional, both erratic and persistent, which is consistent with the Noah and Joseph effects that are well known in mathematics. The erratic nature of rainfall emerges from the breakdown of the convergence to a normal distribution. Instead we find that the distribution about the average is approximately lognormal, with an almost 50% higher chance of deficit rainfall below the mean than adequate rainfall above the mean. We find that the rainfall patterns obey the Hurst law and that the measured Hurst coefficients for seasonal rainfall pattern across all years range from a low of 0.137 to a high above 0.685. To incorporate the erratic and persistent nature of seasonal rainfall, we develop a new approach to weather index insurance based upon the accumulated rainfall in any 21-day period falling below 60% of the long-term average for that same 21-day period. We argue that this approach is more satisfactory to matching drought conditions within and between various phenological stages of growth.

Full access
Dana M. Tobin, Matthew R. Kumjian, and Alan W. Black

Abstract

Data from the National Highway Traffic Safety Administration’s (NHTSA) Fatality Analysis Reporting System (FARS) database were used to identify vehicle-related fatalities that occurred during active precipitation from 2013 to 2017. Changes to FARS for 2013–present allow the identification of freezing rain, in addition to rain, snow, sleet, and precipitation mixtures as prevailing precrash atmospheric conditions. The characteristics of vehicle-related fatalities for each precipitation type identified in FARS were assessed in terms of total numbers, roadway surface conditions, location, and annual and diurnal variability. Vehicle-related fatalities were also matched to nearby Automated Surface Observing System (ASOS) and Automated Weather Observing System (AWOS) precipitation-type reports to determine their agreement with precipitation types documented in FARS. Of the vehicle-related fatalities examined, 8.6% occurred during precipitation, with these fatalities further divided by precipitation type of approximately 81% rain, 14% snow, and 5% sleet, freezing rain, and mixtures of precipitation. Unexpected discrepancies between the numbers of sleet- versus freezing-rain-related fatalities reveal that caution should be taken when using FARS to identify these precipitation types. ASOS/AWOS precipitation-type reports have moderate agreement with FARS at 20 mi (32.2 km), and are capable of distinguishing precipitation and nonprecipitation indicated in FARS. Rain and snow have good agreement between the databases, whereas sleet, freezing rain, and precipitation mixtures have significantly reduced agreement due to a combination of ASOS/AWOS limitations and suspected FARS limitations. To provide a more accurate account of precipitation types for fatal crashes, the use of crashes where FARS-identified precipitation types are confirmed by nearby ASOS/AWOS reports is suggested.

Full access
Rebecca Page and Lisa Dilling

Abstract

Significant effort has been put into advancing the use and usability of information products to support adaptation to drought and climate variability, particularly for the water supply sector. Evidence and experience show that advancing the usability of information through processes such as coproduction is time consuming for both providers and users of information. One challenge for boundary organizations and researchers interested in enhancing the usability of their information is how such processes might “scale” to all the potential organizations and individual managers that might possibly be able to benefit from improved climate information. This paper examines information use preferences and practices specifically among managers of small water systems in the Upper Colorado River basin, with an eye toward identifying new opportunities to effectively scale information usability and uptake among all water managers—regardless of location or capacity—in a resource-constrained world. We find that boundary organizations and other usable science efforts would benefit from capitalizing on the communities of practice that bind water managers together. Specifically, strategic engagement with larger, well-respected water systems as early adopters, supporting dissemination of successes and experiences with new information products among a broader community of water managers, and increasing well-respected water systems’ capacity to engage directly with rural systems may all serve as useful strategies to promote widespread distribution, access, and adoption of information.

Open access
Rahul S. Todmal

Abstract

In the prevailing climate change scenario, to cope with drought, it is necessary to understand the characteristics of meteorological droughts in water-scarce regions to formulate judicial plans for the utilization of water resources. The present investigation, therefore, endeavored to assess the intensity and frequency of droughts over the five semiarid river basins in Maharashtra during the past (1980–2013) and future (2015–50). The study was carried out with the application of standardized precipitation index (SPI) methodology. The agricultural and satellite [normalized difference vegetation index (NDVI)] data were analyzed to understand the effects of meteorological droughts. Although the study area experienced three severe rainfall droughts in 1985/86, 2002/03, and 2011/12, higher frequency of low-intensity droughts is observed, particularly after 2000. The estimation suggests occurrence of moderate, severe, and extreme droughts once in 6, 28, and 50 years, respectively. Among the selected basins, the Agrani, the Karha, and the Man are expected to experience intense droughts and hence require special attention in drought management. The study also highlights that El Niño events considerably retard the monsoon rainfall. However, the occurrence of the positive phase of the Indian Ocean dipole in the El Niño years reduces the intensity of droughts. As agricultural productivity and cropped areas heavily depend on the monsoon rainfall, the meteorological droughts result in agricultural droughts. Moreover, the future warming (by 1.02°C) over the study area is very likely to exacerbate the meteorological droughts (estimated to occur in the 2030s) and increase the agricultural water demand, further adding to an already difficult water management challenge in the study basins.

Full access
Jeannette Sutton, Scott L. Renshaw, Sarah C. Vos, Michele K. Olson, Robert Prestley, C. Ben Gibson, and Carter T. Butts

Abstract

Networked social media provide governmental organizations, such as the National Weather Service (NWS), the opportunity to communicate directly with stakeholders over long periods of time as a form of online engagement. Typologies of engagement include aspects of message content that provide information, contribute to community building, and inspire action and aspects of message microstructural features that facilitate interaction and dialogue, such as directed messages, hashtags, and URLs. Currently, little is known regarding the effect of message strategies on behavioral outcomes, and whether those effects vary under different weather conditions. In this paper we examine how message practices used on Twitter by the NWS are related to message engagement under routine and nonroutine weather conditions. Our analysis employs a census of tweets sent by 12 NWS Weather Forecast Offices in spring 2016 and uses a combination of manual and automated coding to identify engagement content and microstructure features present in each message. We identify factors that increase and decrease message retransmission (retweets) within this corpus under varying threat conditions, using a mixed-effects negative binomial regression model. We find that inclusion of actionable message content, information about historical weather facts, attached visual imagery (such as a map or infograph), and named event hashtags increases message passing during both threat and nonthreat periods. In contrast, messages that include forecast and nowcast content and messages that are sent in reply to other users have a lower passing rate. Findings suggest that common message features do alter message passing, potentially informing message design practices aimed at increasing the reach of messages sent under threat conditions.

Full access
Xiaoguang Chen, Guoping Tian, Zhilong Qin, and Xiang Bi

Abstract

We analyze a provincial-scale dataset of winter wheat yield, together with finescale daily weather outcomes from 1979 to 2011, to assess the responses of winter wheat yield in China to temperature fluctuations. Contrary to the majority of the previous literature, we find that winter wheat yield in China responded positively to higher nighttime temperature T min, with the positive T min effects most significant in the northern China winter wheat region. Consistent with the previous studies, winter wheat yield in China exhibited negative responses to higher daytime temperature T max. As a result of these opposing temperature effects on yield, the net economic impact of weather variations on China’s winter wheat sector is uncertain and is sensitive to specifications and data. Average winter wheat yield is projected to decline by 5.3%–7.0% by 2050 under the global climate model HadGEM2-ES and by 2.0%–3.4% under the NorESM1-M model.

Full access
Makenzie J. Krocak, Joseph T. Ripberger, Hank Jenkins-Smith, and Carol Silva

Abstract

As numerical modeling methods and forecasting technologies continue to improve, people may start to see more specific severe weather timing and location information hours before the event occurs. While studies have investigated response actions on the warning time scales, little work has been done to understand what types of actions residents will take given 4–8 h of advance notice for a possible tornado. This study uses data from the 2018 Severe Weather and Society Survey, an annual survey of U.S. adults, to begin analyzing response actions and how those responses differ with either 4 or 8 h of advance notice. Results show that response actions are largely the same between the two time periods. The small differences that do exist show that sheltering behaviors are more common with 4 h of advance notice whereas monitoring behaviors are more common with 8 h of notice. In addition, respondents claimed they would “wait and see” more often in the 8-h category, indicating they would seek additional information before deciding how to respond. Perhaps more important than the types of actions that respondents identify is the increase in those who are unsure of how to react or would choose to do nothing when given 8 h of notice. Respondents may be anchored to the current system and may not have considered all of the possible actions they can take given more time. Therefore, we emphasize the need for education campaigns as technology, forecasts, and desired responses continue to evolve.

Full access
Urša Ciuha, Tjaša Pogačar, Lučka Kajfež Bogataj, Mitja Gliha, Lars Nybo, Andreas D. Flouris, and Igor B. Mekjavic

Abstract

Occupational heat strain is a public health threat, and for outdoor industries there is a direct influence from elevated environmental temperatures during heat waves. However, the impact in indoor settings is more complex as industrial heat production and building architecture become factors of importance. Therefore, this study evaluated effects of heat waves on manufacturing productivity. Production halls in a manufacturing company were instrumented with 33 dataloggers to track air temperature and humidity. In addition, outdoor thermal conditions collected from a weather station next to the factory and daily productivity evaluated as overall equipment efficiency (OEE) were obtained, with interaction between productivity and thermal conditions analyzed before, during, and after four documented heat waves (average daily air temperature above 24°C on at least three consecutive days). Outdoor (before: 21.3° ± 4.6°C, during: 25.5° ± 4.3°C, and after: 19.8° ± 3.8°C) and indoor air temperatures (before: 30.4° ± 1.3°C, during: 32.8° ± 1.4°C, and after: 30.1° ± 1.4°C) were significantly elevated during the heat waves (p < 0.05). OEE was not different during the heat waves when compared with control, pre-heat-wave, and post-heat-wave OEE. Reduced OEE was observed in 3-day periods following the second and fourth heat wave (p < 0.05). Indoor workers in settings with high industrial heat production are exposed to a significant thermal stress that may increase during heat waves, but the impact on productivity cannot be directly derived from outdoor factors. The significant decline in productivity immediately following two of the documented heat waves could relate to a cumulative effect of the thermal strain experienced during work combined with high heat stress in the recovery time between work shifts.

Open access
Melanie M. Colavito, Sarah F. Trainor, Nathan P. Kettle, and Alison York

Abstract

Boundary organizations facilitate two-way, sustained interaction and communication between research and practitioner spheres, deliver existing science, and develop new, actionable scientific information to address emerging social–ecological questions applicable to decision-making. There is an increasing emphasis on the role of boundary organizations in facilitating knowledge coproduction, which is collaborative research with end users to develop actionable scientific information for decision-making. However, a deeper understanding of how boundary organizations and knowledge coproduction work in practice is needed. This paper examines the Alaska Fire Science Consortium (AFSC), a boundary organization focused on fire science and management in Alaska that is working to address climate impacts on wildfire. A case study approach was used to assess AFSC activities over time. AFSC’s boundary spanning involves a continuum of outputs and activities, but their overall trajectory has involved a deliberate transition from an emphasis on science delivery to knowledge coproduction. Key factors that facilitated this transition included a receptive and engaged audience, built-in evaluation and learning, subject matter expertise and complementarity, and embeddedness in the target audience communities. Recommendations for boundary organizations wishing to develop knowledge coproduction capacity include knowing your audience, employing trusted experts in boundary spanning, and engaging in frequent self-evaluation to inform change over time.

Full access