A Method for Correction of Tropical Rainfall Measuring Mission Satellite Temperature Network in Mazandaran Province

Publish Year: 1403
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:

JR_IJEE-15-1_010

تاریخ نمایه سازی: 3 شهریور 1402

Abstract:

Accurate spatial estimation of temperature is very important in meteorological research. This study investigated the efficiency of temperature products of the Tropical Rainfall Measuring Mission (TRMM) satellite in estimating temperature in Mazandaran Province, and its accuracy were compared with inverse distance weighting and Co-Kriging interpolation methods. Finally, a new method was proposed to improve the accuracy of temperature estimation by combining the TRMM temperature products and terrains. Data recorded at ۲۵ meteorological stations and ۲۶ monthly and annual TRMM satellite images in ۲۰۱۲ and ۲۰۱۳ were used. The results showed a significant correlation between temperature data and satellite products, latitude, and altitude in significance level of ۹۵%. Analyzing error indices showed that TRMM products have underestimation error that this bias error contributed to about ۶۰% of error in these satellite images. Despite the larger error of TRMM products than interpolation methods, the regression analysis results demonstrated the superiority of satellite temperature products over interpolation methods. Furthermore, higher correlation of observed and estimated data showing that satellite products give a better understanding of cold and hot points of the study area despite its underestimation error. Combining satellite temperature products with influential covariates of altitude and latitude in the regression equation reduced the temperature estimation error of the TRMM products by ۸۰%. The estimation precision increased over ۷۰% compared to other temperature interpolation methods. Analyzing isotherm maps indicate the higher temperature of eastern coasts than western coasts. Moreover, evaluating different temperature estimation methods showed the higher precision of the methods that involved covariates than other methods.

Authors

M. Nadi

Department of Water Engineering-Agrometeorology, Faculty of Agricultural Engineering, Sari Agricultural Sciences and Natural Resources University, Sari, Iran

A. Yousefi Kebriya

Department of Water Engineering-Agrometeorology, Faculty of Agricultural Engineering, Sari Agricultural Sciences and Natural Resources University, Sari, Iran

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