Abstract
Abstract. Increase of temperature with height in the troposphere is called temperature inversion. Parameters such as strength and depth are characteristics of temperature inversion. Inversion strength is defined as the temperature difference between the surface and the top of the inversion and the depth of inversion is defined as the height of the inversion from the surface. The common approach in determination of these parameters is the use of Radiosonde where these measurements are too sparse. The main objective of this study is detection and modeling the temperature inversion using MODIS thermal infrared data. There are more than 180 days per year in which the temperature inversion conditions are present in Kermanshah city. Kermanshah weather station was selected as the study area. 90 inversion days was selected from 2007 to 2008 where the sky was clear and the Radiosonde data were available. Brightness temperature for all thermal infrared bands of MODIS was calculated for these days. Brightness temperature difference between any of the thermal infrared bands of MODIS and band 31 was found to be sensitive to strength and depth of temperature inversion. Then correlation coefficients between these pairs and the inversion depth and strength both calculated from Radiosonde were evaluated. The results showed poor linear correlation. This was found to be due to the change of the atmospheric water vapor content and the relatively weak temperature inversion strength and depth occurring in Kermanshah. The polynomial mathematical models and Artificial intelligence algorithms were deployed for detection and modeling the temperature inversion. A model with the lowest terms and highest possible accuracy was obtained. The Model was tested using 20 independent test data. Results indicate that the inversion strength can be estimated with RMSE of 0.84° C and R2 of 0.90. Also inversion depth can be estimated with RMSE of 54.56 m and R2 of 0.86.
Highlights
Increase of temperature with height in the troposphere is called temperature inversion (Kahl et al, 1992)
In summers the frequency of near the ground temperature inversion phenomenon increases to its maximum level, because at nights the weather is clear with no clouds and as the day comes due to rapid warming of the earth, temperature inversion is canceled and the air pollution is reduced
Using equations (4) and (5), the model of estimating the strength and depth of temperature inversion was applied on the 20 independent check points that were not involved in determining the structure and coefficients of the model
Summary
Increase of temperature with height in the troposphere is called temperature inversion (Kahl et al, 1992). Parameters such as strength and depth are characteristics of temperature inversion. Inversion strength is defined as the temperature difference between the surface and the top of the inversion and the depth of inversion is defined as the height of the inversion from the surface (Liu and Key, 2003). The common approach in determination of these parameters is field measurements by Radiosonde (Hudson and Brandt, 2005). On the other hand the Radiosonde data are too sparse, so using satellite images is essential for modeling the temperature inversion. The main objective of this study is detection and modeling the temperature inversion using MODIS thermal infrared data
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