Abstract

The authors used data from a sample of 1465 adults living in the United States to perform a confirmatory factor analysis on the Weather Salience Questionnaire (WxSQ), a 29-item instrument designed to measure the ways in which weather is psychologically significant for people. The original measurement model of the WxSQ was confirmed in the present sample. Additional work also was performed to create a WxSQ short form consisting of seven items. The authors then examined the relationship of weather salience with the respondents’ climate zones of residence and several other weather-related attitudes and behaviors that were assessed in the national sample. People residing in continental and temperate climates expressed significantly more weather salience than those living in dry climates. Further, weather salience was significantly and positively related to the following: 1) the frequency with which people sought weather information and forecasts, 2) the frequency of seeking weather information during the day, 3) the frequency of using forecasts to plan daily activities, 4) seeking weather information for wider geographic areas, and 5) the use of precipitation and temperature forecasts. Weather salience also was significantly and positively related to the confidence people expressed about National Weather Service forecasts and to the perceived importance of these forecasts. The results imply that peoples’ level of weather salience, at least in part, affects their uses of weather information and their confidence in it. These results support the validity of the WxSQ and also reveal some of the psychological bases of people’s perceptions and uses of weather information.

Abstract

Hurricane warnings are the primary sources of information that enable the public to assess the risk and develop responses to threats from hurricanes. These warnings have significantly reduced the number of hurricane-related fatalities in the last several decades. Further investment in the science and implementation of the warning system is a primary mission of the National Weather Service and its partners. It is important that the weather community understand the public’s preferences and values for such investments; yet, there is little empirical information on the use of forecasts in evacuation decision making, the economic value of current forecasts, or the potential use or value for improvements in hurricane forecasts. Such information is needed to evaluate whether improved forecast provision and dissemination offer more benefit to society than alternative public investments.

Fundamental aspects of households’ perceptions of hurricane forecasts and warnings and their potential uses of and values for improved hurricane forecast information are examined. The study was designed in part to examine the viability of survey research methods for exploring evacuation decision making and for eliciting values for improved hurricane forecasts and warnings. First, aspects that affect households’ stated likelihood of evacuation are explored, because informing such decisions is one of the primary purposes of hurricane forecasts and warnings. Then, stated-choice valuation methods are used to analyze choices between potential forecast-improvement programs and the accuracy of existing forecasts. From this, the willingness to pay (WTP) for improved forecasts is derived from survey respondents.

Abstract

The National Weather Service's (NWS) point-and-click (PnC) web page is a primary channel through which NWS directly provides routine and hazardous weather information to its users. The research presented here aims to improve risk communication of hazardous weather information on the PnC web page. The focus is on improving communication of threat existence and threat timing because this important information influences how individuals perceive and respond to a weather risk. Experimental presentations of PnC forecast information were designed for two weather scenarios: a severe thunderstorm warning and a flood watch. The experimental presentations were created by adding new textual and graphical pieces of information that were intended to better convey threat existence and timing, and they were evaluated through two rounds of nationwide surveys of PnC web page users. The survey results show that the default presentation of forecast information on the PnC web page was the least effective at conveying hazardous weather threat existence and timing. Adding start-time text and end-time text, when these information pieces were coupled, helped respondents understand the precise time that weather threats were in effect for the rapid-onset, short-duration severe thunderstorm warning and for the delayed-start, longer-duration flood watch. Adding a box graphic placed around the forecast icons further enhanced communication effectiveness by drawing respondents' attention to the weather threat. Other experimental forecast presentations were designed but were less effective at communicating hazardous weather threat existence and timing, illustrating the importance of empirically evaluating weather risk communication prior to providing it operationally.

Abstract

As part of its strategic plan for Building a Weather-Ready Nation, the U.S. National Weather Service (NWS) has increased their efforts to provide decision support services connecting forecasts and warnings to decision-making for core partners responsible for public safety. In 2011, the NWS formalized their approach to provide impact-based decision support services (IDSS) to help core partners better understand and utilize NWS forecasts and warnings in the face of upcoming extreme events. IDSS encourages weather forecasters to better consider societal impacts from weather events. This shift in emphasis toward impacts ensures NWS information and services are more relevant to decision-makers, which will allow those decision-makers to use NWS information and services to take proactive mitigating actions to protect life and property. This study posits that formal IDSS provides core partners with better information and supports decisions that reduce socioeconomic impacts during extreme winter storms. We compare two storms in the New York City area with similar characteristics but differing in their implementation of IDSS: the December 2010 storm occurred before the implementation of formal IDSS, whereas the January 2016 storm occurred after the implementation of formal IDSS. The comparison of the storm events indicates that IDSS and mitigating actions reduce flight cancellations, improve recovery time in the ground transportation sector, and reduce the duration and number of customers affected by power outages. We recommend that future studies of the value of IDSS consider using case studies for a range of weather events as well as other methodological approaches to assessing benefits.

Despite the meteorological community's long-term interest in weather-society interactions, efforts to understand socioeconomic aspects of weather prediction and to incorporate this knowledge into the weather prediction system have yet to reach critical mass. This article aims to reinvigorate interest in societal and economic research and applications (SERA) activities within the meteorological and social science communities by exploring key SERA issues and proposing SERA priorities for the next decade.

The priorities were developed by the authors, building on previous work, with input from a diverse group of social scientists and meteorologists who participated in a SERA workshop in August 2006. The workshop was organized to provide input to the North American regional component of THORPEX: A Global Atmospheric Research Programme, but the priorities identified are broadly applicable to all weather forecast research and applications.

To motivate and frame SERA activities, we first discuss the concept of high-impact weather forecasts and the chain from forecast creation to value realization. Next, we present five interconnected SERA priority themes—use of forecast information in decision making, communication of forecast uncertainty, user-relevant verification, economic value of forecasts, and decision support— and propose research integrated across the themes.

SERA activities can significantly improve understanding of weather-society interactions to the benefit of the meteorological community and society. However, reaching this potential will require dedicated effort to bring together and maintain a sustainable interdisciplinary community.

Abstract

This study uses data from a survey of coastal Miami-Dade County, Florida, residents to explore how different types of forecast and warning messages influence evacuation decisions, in conjunction with other factors. The survey presented different members of the public with different test messages about the same hypothetical hurricane approaching Miami. Participants’ responses to the information were evaluated using questions about their likelihood of evacuating and their perceptions of the information and the information source. Recipients of the test message about storm surge height and the message about extreme impacts from storm surge had higher evacuation intentions, compared to nonrecipients. However, recipients of the extreme-impacts message also rated the information as more overblown and the information source as less reliable. The probabilistic message about landfall location interacted with the other textual messages in unexpected ways, reducing the other messages’ effects on evacuation intentions. These results illustrate the importance of considering trade-offs, unintended effects, and information interactions when deciding how to convey weather information. Recipients of the test message that described the effectiveness of evacuation had lower perceptions that the information was overblown, suggesting the potential value of efficacy messaging. In addition, respondents with stronger individualist worldviews rated the information as significantly more overblown and had significantly lower evacuation intentions. This illustrates the importance of understanding how and why responses to weather messages vary across subpopulations. Overall, the analysis demonstrates the potential value of systematically investigating how different people respond to different types of weather risk messages.

Abstract

Observing systems consisting of a finite number of in situ monitoring stations can provide high-quality measurements with the ability to quality assure both the instruments and the data but offer limited information over larger geographic areas. This paper quantifies the spatial coverage represented by a finite set of monitoring stations by using global data—data that are possibly of lower resolution and quality. For illustration purposes, merged satellite temperature data from Microwave Sounding Units are used to estimate the representativeness of the Global Climate Observing System Reference Upper-Air Network (GRUAN). While many metrics exist for evaluating the representativeness of a site, the ability to have highly accurate monthly averaged data is essential for both trend detection and climatology evaluation. The calculated correlations of the monthly averaged upper-troposphere satellite-derived temperatures over the GRUAN stations with all other pixels around the globe show that the current 9 certified GRUAN stations have moderate correlations (r ≥ 0.7) for approximately 10% of the earth, but an expanded network incorporating another 15 stations would result in moderate correlations for just over 60% of the earth. This analysis indicates that the value of additional stations can be quantified by using historical, satellite, or model data and can be used to reveal critical gaps in current monitoring capabilities. Evaluating the value of potential additional stations and prioritizing their initiation can optimize networks. The expansion of networks can be evaluated in a manner that allows for optimal benefit on the basis of optimization theory and economic analyses.

Abstract

As integration of solar power into the national electric grid rapidly increases, it becomes imperative to improve forecasting of this highly variable renewable resource. Thus, a team of researchers from the public, private, and academic sectors partnered to develop and assess a new solar power forecasting system, Sun4Cast. The partnership focused on improving decision-making for utilities and independent system operators, ultimately resulting in improved grid stability and cost savings for consumers. The project followed a value chain approach to determine key research and technology needs to reach desired results.

Sun4Cast integrates various forecasting technologies across a spectrum of temporal and spatial scales to predict surface solar irradiance. Anchoring the system is WRF-Solar, a version of the Weather Research and Forecasting (WRF) numerical weather prediction (NWP) model optimized for solar irradiance prediction. Forecasts from multiple NWP models are blended via the Dynamic Integrated Forecast (DICast) System, which forms the basis of the system beyond about 6 h. For short-range (0–6 h) forecasts, Sun4Cast leverages several observation-based nowcasting technologies. These technologies are blended via the Nowcasting Expert System Integrator (NESI). The NESI and DICast systems are subsequently blended to produce short- to midterm irradiance forecasts for solar array locations. The irradiance forecasts are translated into power with uncertainties quantified using an analog ensemble approach and are provided to the industry partners for real-time decision-making. The Sun4Cast system ran operationally throughout 2015 and results were assessed.

This paper analyzes the collaborative design process, discusses the project results, and provides recommendations for best-practice solar forecasting.