Statistical Forecast of Daily Maximum Air Temperature in Arid Areas at Summertime
Author(s) -
Monim H. Al-Jiboori,
Mahmoud Jawad Abu Al-Shaeer,
Ahmed S. Hassan
Publication year - 2020
Publication title -
journal of mathematical and fundamental sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.216
H-Index - 12
eISSN - 2337-5760
pISSN - 2338-5510
DOI - 10.5614/j.math.fund.sci.2020.52.3.8
Subject(s) - environmental science , wind speed , climatology , cloud cover , meteorology , arid , atmospheric sciences , air temperature , range (aeronautics) , linear regression , storm , dust storm , maximum temperature , statistics , geography , mathematics , cloud computing , paleontology , materials science , computer science , composite material , biology , geology , operating system
Based on historical observations of daily maximum temperature, minimum air temperature and wind speed during the summertime for the period from 2004 to 2018, measured at time 0600 GMT, a non-linear regression hypothesis was developed for forecasting daily maximum air temperature (Tmax) in arid areas with a hot climate and no rain events or cloud cover, for example around Baghdad International airport station. Observations with dust storm events were excluded, so this hypothesis could be used to predict daily Tmax at any day during the summertime characterized by fair weather. Using the mean annual daily temperature range, the daily minimum temperature and the trend of maximum temperature with wind speed, Tmax values were forecasted and then compared to those recorded by meteorological instruments. To improve the accuracy of the hypothesis, daily forecast errors, biases and mean absolute error were analyzed to detect their characteristics by calculating relative frequencies of occurrence. Based on this analysis, a value of -0.45 oC was added to the hypothesis as a bias term.
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