Snow is a crucial natural resource covers the largest part in cryosphere. The significance of snow cover on climate at regional and global scale is highly recognized. The reflectivity of snow creates higher albedo, which influence the climate by reducing surface net radiation and energy transmission. Furthermore, the significant changes in the aerial distribution of snow cover affects snow melt runoff, fresh water supply, water balance, hydropower generation, and ground water recharge tourism beside others. Thus, mountain dominated countries like Switzerland depend on snow cover and are affected by its variability. Monitoring of the temporal and spatial variability of snow cover over land areas allows us to understand the global and regional climate, the hydrological process, substantial environmental and socio-economic affect. Moreover, it is a primary indicator for climate change.
Among all satellite sensors, only AVHRR provides the opportunity to retrieve long time series of more than 40 years to study global Earth surface process on daily basis. The comprehensive aim of my master thesis will be focused on generating a procedure to address differences and similarities of snow cover products of AVHRR GAC (Global Area Converge) and LAC (Local Area Coverage) data for 5 winter over European region. For that, we will consider different topography and land cover, which is of special interest for the mountainous region of Switzerland. In addition, the accuracy of snow cover products, derived from AVHRR GAC and LAC data, will be measured.
We will be using AVHRR 1.1 km LAC which is archived at University of Bern by RSGB and 4.4 km GAC data available from 1981 until today. We will compare the accuracy of the product from the higher resolution AVHRR LAC data with the coarser GAC data and quantify the change of the snow products derived from two data sets. This study will add information about the status of snow cover on a continental scale and which can supplement climate change studies in future. Furthermore, the study will fill the gap in existing available approaches dealing with development of long term approaches based on AVHRR data. The new comparison between LAC and GAC data will show their individual benefits and additional value for consistent climatic records.
Master Student: Soumita Patra
Advisor/Supervisor: Kathrin Naegeli, Stefan Wunderle