Articles | Volume 19, issue 1
Hydrol. Earth Syst. Sci., 19, 17–31, 2015
https://doi.org/10.5194/hess-19-17-2015
Hydrol. Earth Syst. Sci., 19, 17–31, 2015
https://doi.org/10.5194/hess-19-17-2015
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, https://doi.org/10.1016/j.rse.2011.11.017, 2012.
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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, https://doi.org/10.1109/TGRS.2011.2177468, 2012.
Caires, S. and Sterl, A.: Validation of ocean wind and wave data using triple collocation, J. Geophys. Res., 103, 3098, https://doi.org/10.1029/2002JC001491, 2003.
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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.