Cole Vaughn, Kathleen Sherman-Morris, Michael Brown, Barrett Gutter
{"title":"我的应用程序可不是这么说的:对天气应用程序准确性、一致性和信任度的看法","authors":"Cole Vaughn, Kathleen Sherman-Morris, Michael Brown, Barrett Gutter","doi":"10.1002/met.2205","DOIUrl":null,"url":null,"abstract":"<p>The usage of weather apps for forecast information has increased dramatically over the last 10–15 years. Ensuring that consumers value and trust weather apps is important to the integrity of weather forecasting. Public perception of weather app forecast accuracy and consistency undergirds the apps' value and trustworthiness. With app forecasts being interpreted solely by the app user, misunderstanding and consequent false expectations could jeopardize the public's perception of accuracy and consistency. Furthermore, weather apps often offer excessively—and potentially unrealistically—detailed forecasts on time and spatial scales, extending far into the future without sufficient disclaimers regarding the confidence level associated with such detailed forecasts. A survey of the public found perceived app accuracy and consistency to be positively correlated with the trust in an app. Participants indicated that they take at least modest consideration of uncertainty and spatial variability when assessing specific and longer range forecasts. On average, participants had low to moderate confidence in forecasts beyond 10 days, and a significant majority did not perceive a precipitation forecast as inaccurate, even when no rain occurred at their location, as long as it rained nearby. We tested for misinterpretation using a common expression of uncertainty in weather apps, namely probability of precipitation (PoP). A majority of participants made a correct interpretation of the two PoP values given, although, depending on the percentage, some misinterpreted the values as indicating precipitation intensity, totals, or duration. Overall, these findings offer encouragement for a society heavily reliant on weather apps while also encouraging more research on weather information interpretation.</p>","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":null,"pages":null},"PeriodicalIF":2.3000,"publicationDate":"2024-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.2205","citationCount":"0","resultStr":"{\"title\":\"That's not what my app says: Perceptions of accuracy, consistency, and trust in weather apps\",\"authors\":\"Cole Vaughn, Kathleen Sherman-Morris, Michael Brown, Barrett Gutter\",\"doi\":\"10.1002/met.2205\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>The usage of weather apps for forecast information has increased dramatically over the last 10–15 years. Ensuring that consumers value and trust weather apps is important to the integrity of weather forecasting. Public perception of weather app forecast accuracy and consistency undergirds the apps' value and trustworthiness. With app forecasts being interpreted solely by the app user, misunderstanding and consequent false expectations could jeopardize the public's perception of accuracy and consistency. Furthermore, weather apps often offer excessively—and potentially unrealistically—detailed forecasts on time and spatial scales, extending far into the future without sufficient disclaimers regarding the confidence level associated with such detailed forecasts. A survey of the public found perceived app accuracy and consistency to be positively correlated with the trust in an app. Participants indicated that they take at least modest consideration of uncertainty and spatial variability when assessing specific and longer range forecasts. On average, participants had low to moderate confidence in forecasts beyond 10 days, and a significant majority did not perceive a precipitation forecast as inaccurate, even when no rain occurred at their location, as long as it rained nearby. We tested for misinterpretation using a common expression of uncertainty in weather apps, namely probability of precipitation (PoP). A majority of participants made a correct interpretation of the two PoP values given, although, depending on the percentage, some misinterpreted the values as indicating precipitation intensity, totals, or duration. Overall, these findings offer encouragement for a society heavily reliant on weather apps while also encouraging more research on weather information interpretation.</p>\",\"PeriodicalId\":49825,\"journal\":{\"name\":\"Meteorological Applications\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2024-05-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.2205\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Meteorological Applications\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/met.2205\",\"RegionNum\":4,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"METEOROLOGY & ATMOSPHERIC SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Meteorological Applications","FirstCategoryId":"89","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/met.2205","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
That's not what my app says: Perceptions of accuracy, consistency, and trust in weather apps
The usage of weather apps for forecast information has increased dramatically over the last 10–15 years. Ensuring that consumers value and trust weather apps is important to the integrity of weather forecasting. Public perception of weather app forecast accuracy and consistency undergirds the apps' value and trustworthiness. With app forecasts being interpreted solely by the app user, misunderstanding and consequent false expectations could jeopardize the public's perception of accuracy and consistency. Furthermore, weather apps often offer excessively—and potentially unrealistically—detailed forecasts on time and spatial scales, extending far into the future without sufficient disclaimers regarding the confidence level associated with such detailed forecasts. A survey of the public found perceived app accuracy and consistency to be positively correlated with the trust in an app. Participants indicated that they take at least modest consideration of uncertainty and spatial variability when assessing specific and longer range forecasts. On average, participants had low to moderate confidence in forecasts beyond 10 days, and a significant majority did not perceive a precipitation forecast as inaccurate, even when no rain occurred at their location, as long as it rained nearby. We tested for misinterpretation using a common expression of uncertainty in weather apps, namely probability of precipitation (PoP). A majority of participants made a correct interpretation of the two PoP values given, although, depending on the percentage, some misinterpreted the values as indicating precipitation intensity, totals, or duration. Overall, these findings offer encouragement for a society heavily reliant on weather apps while also encouraging more research on weather information interpretation.
期刊介绍:
The aim of Meteorological Applications is to serve the needs of applied meteorologists, forecasters and users of meteorological services by publishing papers on all aspects of meteorological science, including:
applications of meteorological, climatological, analytical and forecasting data, and their socio-economic benefits;
forecasting, warning and service delivery techniques and methods;
weather hazards, their analysis and prediction;
performance, verification and value of numerical models and forecasting services;
practical applications of ocean and climate models;
education and training.