Articles | Volume 19, issue 1
Hydrol. Earth Syst. Sci., 19, 17–31, 2015
Hydrol. Earth Syst. Sci., 19, 17–31, 2015
Research article
06 Jan 2015
Research article | 06 Jan 2015

Multi-scale analysis of bias correction of soil moisture

C.-H. Su and D. Ryu

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Cited articles

Albergel, C., De Rosnay, P., Gruhier, C., Muñoz-Sabater, J., Hasenauer, S., Isaksen, L., Kerr, Y., and Wagner, W.: Evaluation of remotely sensed and modelled soil moisture products using global ground-based in situ observations, Remote Sens. Environ., 118, 215–226,, 2012.
Australian Bureau of Rural Science: Land Use of Australia, version 4, 2005/2006, available at: (last access: 24 July 2014), 2010.
Brocca, L., Moramarco, T., Melone, F., Wagner, W., Hasenauer, S., and Hahn, S.: Assimilation of surface- and root-zone ASCAT soil moisture products into rainfall–runoff modeling, IEEE T. Geosci. Remote, 50, 2542–2555,, 2012.
Caires, S. and Sterl, A.: Validation of ocean wind and wave data using triple collocation, J. Geophys. Res., 103, 3098,, 2003.
Chang, S. G., Yu, B., and Yeterli, M.: Adaptive wavelet thresholding for imaging denoising and compression, IEEE T. Image Process., 9, 1532–1546,, 2000.
Short summary
Global environmental monitoring requires geophysical measurements from a variety of sources and sensors to close the information gap. This paper proposes a novel approach for analysing temporal scale-by-scale differences (biases and errors) between geophysical estimates from disparate sources. This allows assessment of different bias correction schemes, and forms the basis for a multi-scale bias correction scheme and data-adaptive, non-linear de-noising.