Articles | Volume 21, issue 11
Research article
28 Nov 2017
Research article |  | 28 Nov 2017

SMOS brightness temperature assimilation into the Community Land Model

Dominik Rains, Xujun Han, Hans Lievens, Carsten Montzka, and Niko E. C. Verhoest


Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Reconsider after major revisions (further review by Editor and Referees) (03 Aug 2017) by Matthew McCabe
AR by Dominik Rains on behalf of the Authors (30 Aug 2017)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (04 Sep 2017) by Matthew McCabe
RR by Luigi J. Renzullo (15 Sep 2017)
RR by Anonymous Referee #3 (03 Oct 2017)
ED: Publish as is (03 Oct 2017) by Matthew McCabe
Short summary
We have assimilated 6 years of satellite-observed passive microwave data into a state-of-the-art land surface model to improve surface soil moisture as well as root-zone soil moisture simulations. Long-term assimilation effects/biases are identified, and they are especially dependent on model perturbations, applied to simulate model uncertainty. The implications are put into context of using such assimilation-improved data for classifying extremes within hydrological monitoring systems.