Understanding the public's sources, perceptions, uses, and values of weather forecasts is integral to providing those forecasts in the most societally beneficial manner. To begin developing this knowledge, we conducted a nationwide survey with more than 1,500 respondents to assess 1) where, when, and how often they obtain weather forecasts; 2) how they perceive forecasts; 3) how they use forecasts; and 4) the value they place on current forecast information. Our results indicate that the average U.S. adult obtains forecasts 115 times per month, which totals to more than 300 billion forecasts per year by the U.S. public. Overall, we find that respondents are highly satisfied with forecasts and have decreasing confidence in forecasts as lead time increases. Respondents indicated that they use forecasts across a range of decision-making contexts. Moreover, nearly three-quarters stated that they usually or always use forecasts simply to know what the weather will be like. Using a simplified valuation approach, we estimate the value of current weather forecast information to be approximately $286 per U.S. household per year, or $31.5 billion total per year value to U.S. households. This compares favorably with total U.S. public and private sector meteorology costs of $5.1 billion a year. To better support the provision of societally beneficial weather information, we advocate for well-designed periodic evaluations of the public's sources, perceptions, uses, and values of weather forecasts. These should include investigations of other important topics such as interpretations of hazardous weather warnings and presentation of uncertainty information.

Abstract

Storm surge associated with tropical and extratropical cyclones has a long history of causing death and destruction along our coastlines. With more than 123 million people living in coastal shoreline areas and much of the densely populated Atlantic and Gulf coastal areas less than 10 ft (∼3 m) above mean sea level, the threat has never been greater. In this article, we summarize and integrate the most intensive series of studies completed to date on communication of storm surge risk. These were primarily geographically focused stakeholder surveys for evaluating the storm surge communication perceptions and preferences of forecasters, broadcast meteorologists, public officials, and members of the public—each a primary user group for storm surge forecasts. According to findings from seven surveys, each group strongly supports the National Weather Service (NWS) issuing watches and warnings for storm surge, whether associated with tropical cyclones (TC) or extratropical (ET) cyclones. We discuss results on public understanding of storm surge vulnerability, respondents’ preferences for separate storm surge information products, and initial assessments of potential storm surge warning text and graphics. Findings from the research reported here are being used to support relevant NWS decisions, including a storm surge watch and warning product that has been approved for use on an experimental basis in 2015 and the National Hurricane Center (NHC) issuance of local surge inundations maps on an experimental basis in 2014.

Weather and Society*Integrated Studies (WAS*IS) is a grassroots movement to change the weather enterprise by comprehensively and sustainably integrating social science into meteorological research and practice. WAS*IS is accomplishing this by establishing a framework for a) building an interdisciplinary community of practitioners, researchers, and stakeholders who are dedicated to the integration of meteorology and social science, and b) providing this community with a means to learn and further examine ideas, methods, and examples related to integrated weather-society work.

In its first year, WAS*IS focused on achieving its mission primarily through several workshops. Between July 2005 and August2006, there were three WAS*IS workshops with a total of 86 selected participants. The workshops focused on the following: laying the groundwork for conducting interdisciplinary work, teaching basic tools and concepts relevant to integrated weather-society efforts, using real-world examples to learn about effective integrated work, and developing opportunities and relationships for doing WAS*IS-type work. By emphasizing the importance of developing a lifelong cohort, as well as helping participants learn and apply social science tools and concepts, WAS*IS can address societal impacts of weather in powerful and sustained ways.

This article discusses the need and motivation for creating WAS*IS; the development, scope, and implementation of WAS*IS through summer of 2006; and WAS*IS-related outcomes thus far, as well as future prospects of the WAS*IS movement.

Reducing loss of life and harm when a hurricane threatens depends on people receiving hurricane risk information that they can interpret and use in protective decisions. To understand and improve hurricane risk communication, this article examines how National Weather Service (NWS) forecasters at the National Hurricane Center and local weather forecast offices, local emergency managers, and local television and radio media create and convey hurricane risk information. Data from in-depth interviews and observational sessions with members of these groups from Greater Miami were analyzed to examine their roles, goals, and interactions, and to identify strengths and challenges in how they communicate with each other and with the public. Together, these groups succeed in partnering with each other to make information about approaching hurricane threats widely available. Yet NWS forecasters sometimes find that the information they provide is not used as they intended; media personnel want streamlined information from NWS and emergency managers that emphasizes the timing of hazards and the recommended response and protective actions; and emergency managers need forecast uncertainty information that can help them plan for different scenarios. Thus, we recommend that warning system partners 1) build understanding of each other's needs and constraints; 2) ensure formalized, yet flexible mechanisms exist for exchanging critical information; 3) improve hurricane risk communication by integrating social science knowledge to design and test messages with intended audiences; and 4) evaluate, test, and improve the NWS hurricane-related product suite in collaboration with social scientists.

To estimate the economic effects of weather variability in the United States, the authors define and measure weather sensitivity as the variability in economic output that is attributable to weather variability, accounting for changes in technology and changes in levels of economic inputs (i.e., capital, labor, and energy). Using 24 yr of economic data and weather observations, quantitative models of the relationship between state-level sectoral economic output and weather variability are developed for the 11 nongovernmental sectors of the U.S. economy; temperature and precipitation measures were used as proxies for all weather impacts. All 11 sectors are found to have statistically significant sensitivity to weather variability. Economic inputs were then constant and economic output was estimated in the 11 estimated sector models, varying the weather inputs only using 70 yr of historic weather observations. It was found that U.S. economic output varies by up to $485 billion yr⁻¹ of 2008 gross domestic product, about 3.4%, owing to weather variability. U.S. states that are more sensitive to weather variability are identified and sectors are ranked by their degree of weather sensitivity. This work illustrates a valid approach to measuring the economic impact of weather variability, gives baseline information and methods for more detailed studies of the sensitivity of each sector to weather variability, and lays the groundwork for assessing the value of current or improved weather forecast information given the economic impacts of weather variability.

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

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.