Journal article

Stand-alone error characterisation of microwave satellite soil moisture using a Fourier method

C Su, D Ryu, WT Crow, AW Western

Remote Sensing of Environment | Elsevier BV | Published : 2014

Abstract

Error characterisation of satellite-retrieved soil moisture (SM) is crucial for maximizing their utility in research and applications in hydro-meteorology and climatology. It can provide insights for retrieval development and validation, and inform suitable strategies for data fusion and assimilation. Su et al. (2013a) proposed a potential Fourier method for quantifying the errors based on the difference between the empirical power spectra of these SM data and a water balance model via spectral fitting (SF), circumventing the need for any ancillary data. This work first evaluates its utility by estimating the errors in two passive and active microwave satellite SM over Australia, and compari..

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Grants

Awarded by Bureau of Meteorology, Australia, under ARC Linkage Project


Funding Acknowledgements

We thank Wolfgang Wagner, Kaighin McColl and Luigi Renzullo for valuable discussions, and Camila Alvarez-Garreton, Shelly Chua, and Venkata Radha for their helpful comments on the early drafts of the manuscript. We also thank our editor, Dr. Marvin Bauer, and his two anonymous reviewers for helpful suggestions and the opportunity to improve upon the submitted manuscript. We are grateful to all who contributed to the data sets used in this study. Yanco in situ data were produced by Jeff Walker and colleagues at Monash University and the University of Melbourne who have been involved in the OzNet programme. AMSR-E data were produced by Richard de Jeu and colleagues at Vrije University Amsterdam and NASA. ASCAT level 3 data were produced by the Vienna University of Technology within the framework of EUMETSAT's Satellite Application Facility on Support of Operational Hydrology and Water Management from MetOp-A observations. The MERRA-Land and TRMM/TMPA data sets were provided by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). GMTED2010 elevation data is made available by the U.S. Geological Survey. The MODIS LAI data set is made available by CSIRO (Commonwealth Scientific and Industrial Research Organisation) via http://www.auscover.org.au. National soil data were provided by the Australian Collaborative Land Evaluation Program ACLEP, endorsed through the National Committee on Soil and Terrain NCST (www.clw.csiro.au/aclep). This research was conducted with financial support from the Australian Research Council and the Bureau of Meteorology, Australia, under ARC Linkage Project No. LP110200520.