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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #321290
Title: Robust estimates of soil moisture and latent heat flux coupling strength obtained from triple collocation

Author
item Crow, Wade
item LEI, FANGNI - Wuhan University
item Anderson, Martha
item HAIN, C. - University Of Maryland
item Scott, Russell - Russ
item BILLESBACH, D. - University Of Nebraska
item ARKEBAUER, T. - University Of Nebraska

Submitted to: Geophysical Research Letters
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/15/2015
Publication Date: 10/23/2015
Citation: Crow, W.T., Lei, F., Anderson, M.C., Hain, C., Scott, R.L., Billesbach, D., Arkebauer, T. 2015. Robust estimates of soil moisture and latent heat flux coupling strength obtained from triple collocation. Geophysical Research Letters. 42:8415-8423. doi: 10.1002/2015GL065929.

Interpretive Summary: Accurately estimating fluxes of water and energy between the layer atmosphere and the land surface is an important aspect of: numerical weather prediction, irrigation scheduling and agricultural drought monitoring. However, such fluxes are notoriously different to measure and all available estimates are plagued with high uncertainty. This uncertainty, in turn, hampers our ability to understand how such fluxes are coupled to land surface states like soil moisture. This paper develops and applies a new mathematical technique for removing the impact of measurement errors from estimates of the correlation between surface soil moisture and surface evaporation. Removing such error provides an unbiased estimate of the true energetic coupling existing between the land surface and the lower atmosphere and allows us to better evaluate, and therefore improve, models attempting to represent such coupling. Improved representation of surface/atmosphere coupling within these models will translate into improved monitoring and evaluation of agricultural drought and is therefore of great interest to the numerical weather prediction community.

Technical Abstract: Land surface models (LSMs) are often applied to predict the one-way coupling strength between surface soil moisture (SM) and surface latent heat (LH) flux. However, the ability of LSMs to accurately represent such coupling has not been adequately established. Likewise, the estimation of one-way SM/LH coupling strength using ground-based observational data is potentially compromised by the impact of independent SM and LH measurements errors. Here we apply a new statistical technique to acquire estimates of one-way SM/LH coupling strength that are non-biased in the presence of random error using a triple collocation approach based on leveraging the simultaneous availability of independent SM and LH estimates acquired from: 1) LSMs, 2) satellite remote sensing and 3) ground-based observations. Results suggest that LSMs do not generally overestimate the strength of one-way surface SM/LH coupling.