Hourly Air Temperature Modeling Based on Atmospheric Pressure, Global Solar Radiation and Relative Humidity Data

Djamel Bensahal, A. Yousfi
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引用次数: 2

Abstract

This paper is focusing on hourly air temperature estimation model (MAT) using available meteorological measured data located in Laghouat (Algeria). The hourly air temperature defined by the present model can be calculated at any time of the night or the day period based on atmospheric pressure, global solar radiation and relative humidity data. This work was compared with three published models from the literature as: Wave, Idliman and Double cosine. Fifteen months of hourly atmospheric pressure, global solar radiation, relative humidity and air temperature data collected during the period (January 2015 to March 2016) were used to test the accuracy of the various models studied. The analysis of the days selected randomly showed that the MAT model gave substantially good fit to the observed data. The RMSE of the MAT model is less than 0.5 oC during all the period of study than the other models studied ranged in the interval (2 oC, 4 oC). The estimated results are compared to the measured ones by using statistical parameters tests such as the mean bias error (MBE), the mean percentage error (MPE), the mean absolute error (MAE), the root mean square error (RMSE) and the coefficient of determination (R2).
基于大气压力、全球太阳辐射和相对湿度数据的逐时气温模型
本文的重点是利用位于Laghouat(阿尔及利亚)的现有气象测量数据进行逐时气温估算模型(MAT)。本模式所定义的每小时气温,可根据大气压力、全球太阳辐射及相对湿度资料,在夜间或白天的任何时间计算。这项工作是比较从文献中发表的三个模型:波,伊德利曼和双余弦。在2015年1月至2016年3月期间收集了15个月的每小时大气压力、全球太阳辐射、相对湿度和气温数据,用于测试所研究的各种模型的准确性。对随机选择的天数的分析表明,MAT模型对观测数据有很好的拟合。在2 oC、4 oC区间内,MAT模式的RMSE均小于0.5 oC。采用平均偏置误差(MBE)、平均百分比误差(MPE)、平均绝对误差(MAE)、均方根误差(RMSE)和决定系数(R2)等统计参数检验,将估计结果与实测值进行比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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