Assimilation of Cosmic‐Ray Neutron Counts for the Estimation of Soil Ice Content on the Eastern Tibetan Plateau. Issue 3 (10th February 2020)

• Record Type: Journal Article
• Authors: Mwangi, Samuel; Zeng, Yijian; Montzka, Carsten; Yu, Lianyu; Su, Zhongbo
• Is Part Of: Journal of geophysical research. Volume 125:Issue 3(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-02-10
• Subjects: soil ice content -- cosmic‐ray neutron probe -- data assimilation -- freezing‐thawing -- Tibetan Plateau; Atmospheric physics -- Periodicals; Geophysics -- Periodicals; 551.5
• DOI: 10.1029/2019JD031529
• Languages: English
• ISSNs: 2169-897X

Abstract

Abstract: Accurate observations and simulations of soil moisture phasal forms are crucial in cold region hydrological studies. In the seasonally frozen ground of eastern Tibetan Plateau, water vapor, liquid, and ice coexist in the frost‐susceptible silty‐loam soil during winter. Quantification of soil ice content is thus vital in the investigation and understanding of the region's freezing‐thawing processes. This study focuses on the retrieval of soil ice content utilizing the in situ soil moisture (i.e., liquid phase) and cosmic ray neutron measurements (i.e., total water including liquid and ice), with Observing System Simulation Experiments. To derive the total soil water from neutron counts, different weighting methods (revised, conventional, and uniform) for calibrating the cosmic‐ray neutron probe (CRNP) were intercompared. The comparison showed that the conventional nonlinear method performed the best. Furthermore, to assimilate fast neutrons using the particle filter, the STEMMUS‐FT (Simultaneous Transfer of Energy, Mass and Momentum in Unsaturated Soil) model was used as the physically based process model, and the COSMIC model (Cosmic‐ray Soil Moisture Interaction Code) used as the observation operator (i.e., forward neutron simulator). Other than background inputs from disturbed initializations in the STEMMUS‐FT, model uncertainties were predefined to assimilate fast neutrons. We observed that with enough spread of uncertainties, the updated states could mimic the CRNP observation. In all setups, assimilating CRNP measurements could enhance total soil water analyses, which consequently led to the improved detection of soil ice content and therefore the freezing thawing‐process at the field scale. Key Points: The conventional nonlinear vertical weighting approach is adherent to cosmic-ray creation and transport theory The applied land surface model is capable of accurately simulating the unfrozen soil water content and soil temperature It was possible to improve total soil water analyses and consequently enhance the quantification of soil ice content by deploying the Observing System Simulation Experiments