Extraction of snow melting duration and its spatiotemporal variations in the Tibetan Plateau based on MODIS product. Issue 1 (1st July 2022)

• Record Type: Journal Article
• Authors: Jin, Haoyu; Chen, Xiaohong; Zhong, Ruida; Wu, Pan; Ju, Qin; Zeng, Juan; Yao, Tingyue
• Is Part Of: Advances in space research. Volume 70:Issue 1(2022)
• Page Start: 15
• Page End: 34
• Publication Date: 2022-07-01
• Subjects: Snow melt day -- Snow cover ratio -- Glacier -- MODIS -- Tibetan Plateau; Space sciences -- Periodicals; Astronautics -- Periodicals; Geophysics -- Periodicals; 500.505
• DOI: 10.1016/j.asr.2022.04.018
• Languages: English
• ISSNs: 0273-1177

Abstract

Abstract: The Qinghai-Tibet Plateau (TP) is one of the most sensitive areas to climate change, and its ecological environment changes directly or indirectly reflect the global climate change trend. The snow cover ratio (SCR) is one of the important indicators reflecting the climate and environmental changes on the TP. The daily remote sensing data of snow cover on the TP from 2003 to 2014 were used to study the spatiotemporal distribution of snow cover on the TP. This dataset is generated based on the Moderate-Resolution Imaging Spectroradiometer (MODIS) product. The snowmelt days were extracted using the moving average method. The results have shown that the average snowmelt day on the TP starts on the 103rd day and ends on the 223rd day of a year, and the snowmelt duration has a downward trend. Snow is mainly distributed in the Nyainqentanglha Mountains, Karakoram Mountains and Himalayas. The SCR in summer has a downward trend, while in autumn has a rising trend. This shows that the difference in SCR during the year has enlarged, increasing the risk of snowmelt floods. The SCR is highly correlated with temperature, but weakly correlated with precipitation. Using long-term snow cover remote sensing data, the distribution of glacier coverage on the TP can be roughly extracted, of which the glacier area accounts for about 1.1% of the total area of the TP. This study provides an important reference for understanding the spatiotemporal changes of snow cover in the TP.