Knowledge Base

Why does the root zone soil moisture in the SMAP Level-4 soil moisture products vary in such close unison with the surface soil moisture?

The surface and root zone soil moisture estimates in the SMAP Level-4 soil moisture products are the outputs of a land surface model into which SMAP observations of brightness temperature have been assimilated. The coupling between the surface layer and the root zone layer is known to be very strong in this model (the Catchment model of Koster et al. [2000]), perhaps overly so, and this will indeed lead to similarity in the surface and root zone soil moisture time series. Nevertheless, the two variables are not identical; the surface soil moisture generally shows higher temporal variability as expected.

In Version 4 of the Level-4 soil moisture algorithm, the land surface modeling system was revised to bring the modeled surface soil moisture into closer agreement with in situ measurements and SMAP Level-2 retrievals. Specifically, the replenishment of soil moisture near the surface from below under non-equilibrium conditions was substantially reduced (Koster et al. 2018). As a result, the surface and root zone soil moisture estimates are less similar to each other in the Version 4 product than in the Version 3 product.

There are three additional points to consider. First, one's intuition regarding how "uncoupled" the two variables should be may be based on the behavior of soil at a point, as represented by a set of in situ measurements. The SMAP product represents soil moisture averaged over a large area, for which (in nature) the correspondence between the surface and root zone values may indeed be greater. Second, some idealized analyses suggest that, in the absence of information on the true level of coupling in nature at large spatial scales, a model with a stronger coupling between the variables is probably more appropriate for soil moisture data assimilation activities [Kumar et al. 2009]. Third, typical values for surface and root zone soil moisture are strongly determined by soil properties and climate. At large scales, the spatial variability imposed by soils and climate can overwhelm the differences between surface and root zone values.

Koster, R. D., M. J. Suarez, A. Ducharne, M. Stieglitz, and P. Kumar, 2000: A catchment-based approach to modeling land surface processes in a general circulation model, 1, Model structure.  J. Geophys. Res., 105, 24809-24822.

Koster, R. D., Q. Liu, S. P. P. Mahanama, and R. H. Reichle, 2018: Improved Hydrological Simulation Using SMAP Data: Relative Impacts of Model Calibration and Data Assimilation. J. Hydromet., 19, 727-741, doi:10.1175/JHM-D-17-0228.1.

Kumar, S. V., R. H. Reichle, R. D. Koster, W. T. Crow, and C. D. Peters-Lidard, 2009: Role of subsurface physics in the assimilation of surface soil moisture observations.  J. Hydromet., 10, 1534-1547.

* Level-4 soil moisture products:

Last Updated June 2018

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