Snow Cover changes in Central Asia derived from long term time series analysis of medium resolution remote sensing data

Kurzfassung

Climate change alters the distribution, amount, and duration of snow cover and therefore affects the global radiation budget, tourism, flora and fauna, and water availability. In Central Asia with its continental climate, most precipitation is falling as snow during winter. Changing snow cover characteristics have a direct impact on water related issues such as irrigation, water scarcity, hydropower generation, and political tensions. It is therefore important to monitor the occurring processes, analyse possible trends, and identify those regions which are most vulnerable in terms of future developments. The Global SnowPack of DLR is a set of medium resolution (500 m – 1000 m) snow cover information derived from Moderate-resolution Imaging Spectroradiometer (MODIS) and Advanced Very High Resolution Radiometer (AVHRR) data. Available for Central Asia since 1986, it is an ideal dataset to analyse the snow cover changes in the mountains of Pamir, Tian Shan, and Altai – the region where the rivers Syr Darya, Amu Darya, and Ili originate. These rivers are most relevant for the water availability, and any process altering their runoff regimes potentially affect millions of people. The 30 year lasting time series of the daily Global SnowPack data revealed a significant shift of the snow cover season towards earlier onset and melt dates in many of Central Asia’s mountain regions. This shift causes the runoff peak for many upstream tributaries to occur earlier, while at the same time the runoff during the end of the season is reduced. The analysis clearly demonstrated the value of long term time series of medium resolution data. Even though the capabilities of sensors such as AVHRR are limited, their availability since the 1980s renders them a most valuable and unique source of information when trying to analyse the long term effects of climate change on our environment.