Articles | Volume 16, issue 17
https://doi.org/10.5194/gmd-16-4957-2023
https://doi.org/10.5194/gmd-16-4957-2023
Model evaluation paper
 | 
31 Aug 2023
Model evaluation paper |  | 31 Aug 2023

Uncertainty estimation for a new exponential-filter-based long-term root-zone soil moisture dataset from Copernicus Climate Change Service (C3S) surface observations

Adam Pasik, Alexander Gruber, Wolfgang Preimesberger, Domenico De Santis, and Wouter Dorigo

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Cited articles

Adeaem, Gößwein, B., Hahn, S., Preimesberger, W., and BM, B.: TUW-GEO/pyswi: v1.0 (v1.0), Zenodo [code], https://doi.org/10.5281/zenodo.7534919, 2023. a
Albergel, C., Rüdiger, C., Pellarin, T., Calvet, J.-C., Fritz, N., Froissard, F., Suquia, D., Petitpa, A., Piguet, B., and Martin, E.: From near-surface to root-zone soil moisture using an exponential filter: an assessment of the method based on in-situ observations and model simulations, Hydrol. Earth Syst. Sci., 12, 1323–1337, https://doi.org/10.5194/hess-12-1323-2008, 2008. a, b, c, d, e, f, g, h, i
Al Bitar, A. and Mahmoodi, A.: Algorithm Theoretical Basis Document (ATBD) for the SMOS Level 4 Root Zone Soil Moisture (Version v30_01), Tech. Rep., https://doi.org/10.5281/zenodo.4298572, 2020. a
Alday, J. G., Camarero, J. J., Revilla, J., and Resco de Dios, V.: Similar diurnal, seasonal and annual rhythms in radial root expansion across two coexisting Mediterranean oak species, Tree Physiol., 40, 956–968, https://doi.org/10.1093/treephys/tpaa041, 2020. a
Al-Yaari, A., Dayau, S., Chipeaux, C., Aluome, C., Kruszewski, A., Loustau, D., and Wigneron, J.-P.: The AQUI Soil Moisture Network for Satellite Microwave Remote Sensing Validation in South-Western France, Remote Sensing, 10, 1839, https://doi.org/10.3390/rs10111839, 2018. a
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Short summary
We apply the exponential filter (EF) method to satellite soil moisture retrievals to estimate the water content in the unobserved root zone globally from 2002–2020. Quality assessment against an independent dataset shows satisfactory results. Error characterization is carried out using the standard uncertainty propagation law and empirically estimated values of EF model structural uncertainty and parameter uncertainty. This is followed by analysis of temporal uncertainty variations.