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Michael D. Gerst, Melissa A. Kenney, Allison E. Baer, Amanda Speciale, J. Felix Wolfinger, Jon Gottschalck, Scott Handel, Matthew Rosencrans, and David Dewitt

Abstract

Visually communicating temperature and precipitation climate outlook graphics is challenging because it requires the viewer to be familiar with probabilities as well as to have the visual literacy to interpret geospatial forecast uncertainty. In addition, the visualization scientific literature has open questions on which visual design choices are the most effective at expressing the multidimensionality of uncertain forecasts, leaving designers with a lack of concrete guidance. Using a two-phase experimental setup, this study shows how recently developed visualization diagnostic guidelines can be used to iteratively diagnose, redesign, and test the understandability the U.S. National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center (CPC) climate outlooks. In the first phase, visualization diagnostic guidelines were used in conjunction with interviews and focus groups to identify understandability challenges of existing visual conventions in temperature and precipitation outlooks. Next, in a randomized control versus experimental treatment setup, several graphic modifications were produced and tested via an online survey of end users and the general public. Results show that, overall, end users exhibit a better understanding of outlooks, but some types of probabilistic color mapping are misunderstood by both end users and the general public, which was predicted by the diagnostic guidelines. Modifications lead to significant gains in end-user and general public understanding of climate outlooks, providing additional evidence for the utility of using control versus treatment testing informed by visualization diagnostics.

Open access
D. H. Cobon, R. Darbyshire, J. Crean, S. Kodur, M. Simpson, and C. Jarvis

Abstract

Seasonal climate forecasts (SCFs) provide opportunities for pastoralists to align production decisions to climatic conditions, as SCFs offer economic value by increasing certainty about future climatic states at decision-making time. Insufficient evidence about the economic value of SCFs was identified as a major factor limiting adoption of SCFs in Australia and abroad. This study examines the value of SCFs to beef production system management in northern Australia by adopting a theoretical probabilistic climate forecast system. Stocking rate decisions in October, before the onset of the wet season, were identified by industry as a key climate sensitive decision. The analysis considered SCF value across economic drivers (steer price in October) and environmental drivers (October pasture availability). A range in forecast value was found ($0–$14 per head) dependent on pasture availability, beef price, and SCF skill. Skillful forecasts of future climate conditions offered little value with medium or high pasture availability, as in these circumstances pastures were rarely overutilized. In contrast, low pasture availability provided conditions for alternative optimal stocking rates and for SCFs to be valuable. Optimal stocking rates under low pasture availability varied the most with climate state (i.e., wet or dry), indicating that producers have more to gain from a skillful SCF at these times. Although the level of pasture availability in October was the major determinant of stocking rate decisions, beef price settings were also found to be important. This analysis provides insights into the potential value of SCFs to extensive beef enterprises and can be used by pastoralists to evaluate the cost benefit of using a SCF in annual management.

Open access
Rachel E. Schattman, Stephanie E. Hurley, Holly L. Greenleaf, Meredith T. Niles, and Martha Caswell

Abstract

Landscape photovisualizations (PVZs) are digitally altered photographs that show existing landscapes altered to include a simulated future scenario. They are commonly used to support dialogue and decision-making in multistakeholder contexts. In agricultural sectors, stakeholders increasingly must contend with pressures to adapt to climatic changes and shifts in weather patterns. This study examines the potential of PVZs to engage agricultural stakeholders about climate change adaptation, specifically around best management practices (BMPs). In 2015, survey data were collected (n = 133) at six agricultural conferences Vermont. Participants were asked about their climate change knowledge, perceptions of adaptation, and their intentions to adopt or recommend one or more of the following BMPs: riparian buffers, drainage tiles with constructed wetlands, retention ponds, and silvopasture. In addition, respondents were asked about how well PVZs did or did not clarify their understanding of each BMP and its associated limiting factors. Results from five multivariate ordered logit models show an increase in interest among some agricultural stakeholders in adopting a BMP (among farmers) or recommending a BMP (among agricultural advisors) after seeing a PVZ depicting that practice. Interest in adoption or recommendation of BMPs was also more likely among respondents who believe that it is important for farms to adapt to climate change. Although PVZs are not common in agricultural outreach programs, these results suggest that PVZs are relevant to agricultural education and land-use decision-making, specifically in the domain of climate change adaptation.

Free access
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.

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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.

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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.

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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.

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