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

Model code and software

Python Multivariate Land Data Assimilation System with High Performance Computing for CLM 4.5 X. Han, X. Li, G. He, P. Kumbhar, C. Montzka, S. Kollet, T. Miyoshi, R. Rosolem, Y. Zhang, H. Vereecken, and H.-J. H. Franssen

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.