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Modeling and projection spatial variations of seasonal temperature in Iran based on regional Medium scale model REGCM4
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Saeed Jahanbakhsh   , Masomeh Tadayoni , Mehdi Asadi * 1, Abbasali Dadashi rodbari |
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Abstract: (3706 Views) |
Emissions of greenhouse gases and their continuous accumulation in the atmosphere directly affect the temperature of the air and increasing air temperatures is a serious threat to the climate of the planet. The purpose of this study is to determine the spatial modeling of seasonal temperature in Iran two data sets were used for this purpose: 1- Average temperature data of 115 synoptic stations (1980-2014) and 2- EH5OM database data for the period 2015-2050 in the form of 3-hour observations (8 times a day) under the scenario A1B. The REGCM4 model was used downscale the EH5OM base data. Then the hourly temperature data of the air temperature is downscaled and with a spatial resolution of 0.27 × 0.27 arc, they were transformed into a 15-by-15-square-meter curry grunge method which resulted in a matrix with a dimension of 7200 × 4. The accuracy of the modeling data was evaluated using three (R2), (MAE) and (RMSE) statistics and their authenticity was confirmed with high confidence. Temperature modeling has shown that temperatures in Iran during the summer and winter seasons for the period 2015-2050 will increase under the A1B scenario with values of 0.91 and 0.33 degrees Celsius, respectively. Temperature Auto-correlation with Geary C statistics indicates the strong association of temperature spatial units in Iran. The center of gravity of Iran under the influence of global warming has been increasing in all seasons and also, the directional distribution function of the spatial deviation of the seasonal temperature of Iran was normal which has led to the discovery of the role of heights and the direction of a large rectilinear system of atmospheric pressure on the other at Iran's temperature.
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| Keywords: Seasonal temperature, EH5OM model, REGCM4, Temperature center of gravity, Iran. |
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Full-Text [PDF 1230 kb]
(822 Downloads)
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Type of Study: Research |
Subject:
Special
Received: 2017/09/25 | Accepted: 2018/06/24 | Published: 2019/12/1
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