Estimating the snow melt onset using AMSR-E data in Eurasia

Knowing the onset of snow melt is an important factor in climatological and weather forecasting models. The carbon cycle in the atmosphere is directly related to melting of snow and thus is a key information understanding global climate change. Microwave radiometers are sensitive to liquid water and thus well suited for melt detection. The rather coarse resolution is ideal for monitoring the snow melt globally. However, many snow melt detection algorithms are applicable only on arctic tundra or snow covered glaciers. The authors of this paper have earlier developed melt detection algorithms for boreal forest zone using SSM/I-data. In this paper AMSR-E data is used and the algorithm is slightly modified to operate without using additional data such as ground based measurements. The algorithm is applied over the whole Northern Eurasia and the results obtained are reliable and valuable for further development.