Application of MODIS land surface temperature in snow climatology studies, Case Study: Central Alborz Basins

The snow budget in mountainous river basins reacts sensitively to temperature fluctuations. Therefore, the desired temperature increase due to climate change could significantly affect the snow budget in the future. These effects could lead to significant changes in the hydrological regime of river basins such as the Central Alborz basins. The aim of this study is to investigate the application of MODIS land surface temperature (LST) data in studying snow climatology. The analysis included several important snow parameters derived from the snow depletion curves (SDCs). These curves were extracted from cloud-reduced MODIS products of daily snowpack for each river basin studied. Correlations between these snow parameters and the MODIS LST data were then investigated. The results show that several snow parameters variations are significantly correlated with MODIS LST data over past 20 years (2002-2022). Specifically, Maximum Snow Cover (MSC), Maximum Snow Cover Day (MSCD), Snow Melt Ending Day, and Accumulation-Ablation Period (AAP) exhibited substantial correlations with LST, as indicated by the Tau correlation coefficients of -0.74, -0.31, -0.51, and -0.35, respectively, at a confidence level of 90%.The SMED was found to be the most sensitive snow parameter to MODIS LST variations. Strong correlations were observed between SMED and LST across all studied subbasins, with an overall Pearson correlation coefficient of -0.79 and a Tau correlation coefficient of -0.51 for the whole study area. The results of this study show that MODIS LST data successfully explain the dependencies between snow budget and temperature in the Central Alborz basins.