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Using Forecast and Observed Weather Data to Assess Performance of Forecast Products in Identifying Heat Waves and Estimating Heat Wave Effects on Mortality

机译:使用天气预报和天气观测数据评估预报产品在识别热浪和估算热浪对死亡率的影响方面的性能

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摘要

Background: Heat wave and health warning systems are activated based on forecasts of health-threatening hot weather.Objective: We estimated heat–mortality associations based on forecast and observed weather data in Detroit, Michigan, and compared the accuracy of forecast products for predicting heat waves.Methods: We derived and compared apparent temperature (AT) and heat wave days (with heat waves defined as ≥ 2 days of daily mean AT ≥ 95th percentile of warm-season average) from weather observations and six different forecast products. We used Poisson regression with and without adjustment for ozone and/or PM10 (particulate matter with aerodynamic diameter ≤ 10 μm) to estimate and compare associations of daily all-cause mortality with observed and predicted AT and heat wave days.Results: The 1-day-ahead forecast of a local operational product, Revised Digital Forecast, had about half the number of false positives compared with all other forecasts. On average, controlling for heat waves, days with observed AT = 25.3°C were associated with 3.5% higher mortality (95% CI: –1.6, 8.8%) than days with AT = 8.5°C. Observed heat wave days were associated with 6.2% higher mortality (95% CI: –0.4, 13.2%) than non–heat wave days. The accuracy of predictions varied, but associations between mortality and forecast heat generally tended to overestimate heat effects, whereas associations with forecast heat waves tended to underestimate heat wave effects, relative to associations based on observed weather metrics.Conclusions: Our findings suggest that incorporating knowledge of local conditions may improve the accuracy of predictions used to activate heat wave and health warning systems.Citation: Zhang K, Chen YH, Schwartz JD, Rood RB, O’Neill MS. 2014. Using forecast and observed weather data to assess performance of forecast products in identifying heat waves and estimating heat wave effects on mortality. Environ Health Perspect 122:912–918; 
机译:背景:基于威胁健康的炎热天气的预报激活热浪和健康预警系统。目的:我们根据密歇根州底特律的天气预报和观测天气数据估算热量与死亡率的关联,并比较预报产品预测热量的准确性方法:我们从气象观测和六种不同的预报产品中得出并比较了视在温度(AT)和热浪天数(热浪定义为日均≥2天,AT≥暖季平均水平的95%)。我们使用Poisson回归对臭氧和/或PM10(空气动力学直径≤10μm的颗粒物)进行了调整和不进行调整,以估计和比较每日全因死亡率与观察到的和预测的AT和热浪天的关联。结果:1-与所有其他预测相比,本地运行产品的提前一天预测(修订的数字预测)的误报率约为一半。平均而言,在控制热浪的情况下,观察到的AT = 25.3°C的天死亡率比AT = 8.5°C的天数高3.5%(95%CI:–1.6,8.8%)。观察到的热浪天死亡率比非热浪天高6.2%(95%CI:–0.4,13.2%)。预测的准确性各不相同,但是相对于基于观测天气指标的关联而言,死亡率和预测的热量之间的关联通常倾向于高估热效应,而与预测的热浪之间的关联则倾向于低估热浪效应。结论:我们的发现表明,结合知识局部条件可能会提高用于激活热浪和健康预警系统的预测的准确性。引文:张克,陈永辉,施瓦茨JD,鲁德·RB,奥尼尔MS。 2014年。使用天气预报和观测天气数据评估预报产品在识别热浪和估算热浪对死亡率的影响方面的表现。环境健康展望122:912–918;

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