Estimation of the Daily Maximum Air Temperature for Baghdad City Using Multiple Linear Regression

Authors

  • Hayder M. Al-Samarrai Iraqi Meteorological Organization and Seismology, Baghdad, IRAQ.
  • Monim H. Al-Jiboori Atmospheric Sciences Department, College of Science, Mustansiriyah University, Baghdad, IRAQ. https://orcid.org/0000-0002-0816-3918

DOI:

https://doi.org/10.23851/mjs.v33i4.1168

Keywords:

maximum air temperature, bias, subtropical climate, Iraq, multiple linear regression

Abstract

In this paper, we relied on historical observations for the period between (2005-2020) for the Baghdad meteorological station, which is characterized by a hot, dry climate in summer and cold and rainy in winter, as it is an example of a subtropical region. The multiple linear regression equation was developed and improved to produce a formula that predicts maximum air temperature. This was done by relying on climatic elements, namely minimum air temperature, wind speed, and relative humidity, and entering them into the formula as independent inputs that have a direct impact on estimating the maximum air temperature also calculating the correlation coefficients for each of them. The bias of the model was calculated and its value was entered as the correction for errors that accompany the application of the model.

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Key Dates

Published

30-12-2022

Issue

Section

Original Article

How to Cite

[1]
H. M. Al-Samarrai and M. H. . Al-Jiboori, “Estimation of the Daily Maximum Air Temperature for Baghdad City Using Multiple Linear Regression”, Al-Mustansiriyah Journal of Science, vol. 33, no. 4, pp. 9–14, Dec. 2022, doi: 10.23851/mjs.v33i4.1168.

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