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Dr Chun-Hsu Su is a research fellow at the Environmental Hydrology and Water Resources (EHWR) group at the University of Melbourne (UM). He received his B.E (hons, software), B.Sc (hons, physics) and Ph.D. in theoretical quantum physics from Melbourne University in 2010 and following a year as a scientific software engineer in the Satellite Applications division at the Bureau of Meteorology, he joined EHWR in 2012 to develop a research portfolio in environmental remote sensing for hydrological studies. His current research focus is to develop theoretical methods in post-processing and characterisation of satellite-retrieved surface soil moisture and precipitation for data assimilation.
On evaluation, de-noising and rescaling of satellite-retrieved surface soil moisture
Real-time and global mapping of soil moisture are invaluable for a wide range of applications. In recent year, with Australia experiencing a series of severe flood events, a constellation of satellite missions (ASCAT, SMOS, AMSR-2) with soil moisture retrieval capabilities provides vital opportunities to improve flood forecasting accuracy. In our proposal, we aim to build upon the dual-data assimilation scheme proposed by Crow and Ryu (2009, Hydrology and Earth Systems Sciences, 13, 1-16) to use the remotely-sensed soil moisture to correct both satellite precipitation model input forcing and model state. However this approach relies on the quality of soil moisture products. In this talk, I will report on our research in evaluation and characterisation of three satellite-retrieved soil moisture products (AMSR-E, ASCAT and SMOS) over southeast Australia, and to propose novel post-retrieval methods of de-noising and rescaling of these products before data assimilation.