Project Group 7

Error quantification and development of quality layers for global, daily remote sensing products for surface water and snow cover extent and dynamics

A key prerequisite for achieving the overarching goal of the RU is the availability of high quality observational data on water and snow extent including uncertainty information that is suitable for integration into the C/DA approach. This kind of data will be developed and provided within this project, based on two existing satellite earth observation time series products, the DLR Global WaterPack and the DLR Global SnowPack. Continued improvement of the Global WaterPack algorithm will further advance the reliability and validity of this product. The subsequent development of sound uncertainty information for the water and snow cover time series will enable the integration of these products via C/DA approaches into the hydrological model WaterGAP. We hypothesize that in this way we can enhance both model outputs and earth observation based datasets, and thus contribute to a better understanding of the global freshwater system.