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Seasonal Variation in Microclimates and the Role of Regional Weather and Environmental Factors

机译:微跨度的季节性变化和区域天气和环境因素的作用

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Microclimates are an important component of our ecosystem, and can impact human health through heat-related injuries or by affecting disease vectors. Research on microclimates can be difficu our understanding of the temporal and environmental variation of microclimates is limited. Microclimate data (temperature and relative humidity) were collected over a twelve-month period in a small community in Ecuador, and summarized for over each 24-hour collection period. Using generalized linear models with generalized estimating equations, we assessed the variability of microclimate variables across time and environmental variables, including urbanicity, elevation and vegetation coverage. With local weather station and remotely-sensed climate data, we assessed the relationship between regional weather and microclimates. Two-hundred and eighty-seven log-days of data were collected; the absolute maximum temperature was in July, and the absolute minimum occurred in August. Relative humidity of 100% occurred frequently during the sampling period; the absolute minimum occurred in March. Some microclimate variables were more temporally stable than others (mean, median, and minimum temperature and maximum relative humidity); urban sites had higher temperature variability (p=0.0169) and rural sites had higher mean relative humidity (p=0.0137), compared to suburban areas. Microclimate temperature variables were associated with remotely-sensed surface temperature (p=0.047). Miicroclimate minimum (p=0.0001) and mean (p=0.045) temperature were associated with climate station temperature minimum and mean measures, respectively. Relative humidity mean (p<0.0001), median (p<0.0001), minimum (p=0.038), and maximum (p=0.0018) were associated with the number of days with precipitation at the climate station. These data demonstrate the need for climate and health researchers to reconsider the meaning and impact of climate variables across spatial scales.
机译:微跨度是我们生态系统的重要组成部分,并且可以通过热损伤或影响疾病载体来影响人类健康。对微亚亚麻盐酸的研究可能是困难的;我们对微亚亚亚亚亚酸的时间和环境变化的理解有限。在厄瓜多尔的小社区的十二个月内收集微气候数据(温度和相对湿度),并在每个24小时收集期间汇总。使用具有广义估计方程的广义线性模型,我们评估了跨时间和环境变量的微气候变量的可变性,包括城市性,高程和植被覆盖。随着当地的气象站和远程感知的气候数据,我们评估了区域天气和微跨度之间的关系。收集二百八十七天的日志;绝对最高温度于7月份,绝对最低可能发生在8月。在取样期间经常发生100%的相对湿度; 3月份发生绝对最小值。一些微气候变量比其他微气候变量更稳定(平均值,中值和最小温度和最大相对湿度);与郊区相比,城市遗址具有较高的温度变异性(P = 0.0169),农村地点具有更高的平均相对湿度(P = 0.0137)。微气候温度变量与远程感应的表面温度相关(P = 0.047)。 MIICroClimate最小(p = 0.0001)和平均值(p = 0.045)温度与气候电站温度最小和平均措施相关。相对湿度(p <0.0001),中值(P <0.0001),最小(p = 0.038),最大(p = 0.0018)与气候站沉淀的天数有关。这些数据展示了气候和健康研究人员的需求,重新考虑气候变量跨空间尺度的含义和影响。

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