Spatio-temporal analysis of diurnal air temperature parameterization in Weather Stations over Iran

Gholamnia, M.; Khandan, R.; Darvishi Boloorani, A.; Hamzeh, S.; Gharaylou, M.; Duan, S.; Alavi Panah, S.K.

doi:10.22059/jdesert.2018.66366

Spatio-temporal analysis of diurnal air temperature parameterization in Weather Stations over Iran

Authors

M. Gholamnia ¹

R. Khandan ²

A. Darvishi Boloorani ²

S. Hamzeh ²

M. Gharaylou ³

S. Duan ⁴

S.K. Alavi panah ²

¹ Department of Surveying Engineering, Sanandaj Branch, Islamic Azad University, Sanandaj, Iran

² Department of Remote Sensing and GIS, Faculty of Geography, University of Tehran, Tehran, Iran

³ Institute of Geophysics, University of Tehran, Tehran, Iran

⁴ Key Laboratory of Agricultural Remote Sensing, Ministry of Agriculture/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China

10.22059/jdesert.2018.66366

Abstract

Diurnal air temperature modeling is a beneficial experimental and mathematical approach which can be used in many fields related to Geosciences. The modeling and spatio-temporal analysis of air Diurnal Temperature Cycle (DTC) was conducted using data obtained from 105 synoptic stations in Iran during the years 2013-2014 for the first time; the key variable for controlling the cosine term in DTC modeling known as β was analyzed and considered both as monthly and annual parameter. The effect of environmental variables of humidity, pressure, diurnal air temperature range, and wind speed were analyzed on β. The results showed that there is no significant difference between considering β as monthly (dynamic) or annual (constant) parameter through the year. The RMSE of approach with dynamic β was 2.1 °C and with constant 2.2 °C at 95% percent of whole data in all stations. The analysis of environmental variables showed that humidity had an indirect effect on β. Low pressure areas showed higher β values but high pressure areas showed higher variability in β and lower mean values. In areas with high air diurnal temperature range, lower β values with less standard deviation were observed. High wind areas showed positive effect on β values.

Keywords

Air Temperature

DTC model

Humidity

Pressure, Wind, Spatio-temporal