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Remote Sens. 2018, 10(5), 751; https://doi.org/10.3390/rs10050751

Attribution of Flux Partitioning Variations between Land Surface Models over the Continental U.S.

1
Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA
2
Science Applications International Corporation, McLean, VA 22102, USA
3
Earth Science Division, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA
Current address: Code 617, NASA GSFC, Greenbelt, MD 20771, USA.
*
Author to whom correspondence should be addressed.
Received: 12 February 2018 / Revised: 9 May 2018 / Accepted: 13 May 2018 / Published: 14 May 2018
(This article belongs to the Special Issue Advances in the Remote Sensing of Terrestrial Evaporation)
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Abstract

Accurate quantification of the terrestrial evapotranspiration ( E T ) components of plant transpiration (T), soil evaporation (E) and evaporation of the intercepted water (I) is necessary for improving our understanding of the links between the carbon and water cycles. Recent studies have noted that, among the modeled estimates, large disagreements exist in the relative contributions of T, E and I to the total E T . As these models are often used in data assimilation environments for incorporating and extending E T relevant remote sensing measurements, understanding the sources of inter-model differences in E T components is also necessary for improving the utilization of such remote sensing measurements. This study quantifies the contributions of two key factors explaining inter-model disagreements to the uncertainty in total E T : (1) contribution of the local partitioning and (2) regional distribution of E T . The analysis is conducted by using outputs from a suite of land surface models in the North American Land Data Assimilation System (NLDAS) configuration. For most of these models, transpiration is the dominant component of the E T partition. The results indicate that the uncertainty in local partitioning dominates the inter-model spread in modeled soil evaporation E. The inter-model differences in T are dominated by the uncertainty in the distribution of E T over the Eastern U.S. and the local partitioning uncertainty in the Western U.S. The results also indicate that uncertainty in the T estimates is the primary driver of total E T errors. Over the majority of the U.S., the contribution of the two factors of uncertainty to the overall uncertainty is non-trivial. View Full-Text
Keywords: evapotranspiration partitioning; transpiration; soil evaporation, uncertainty evapotranspiration partitioning; transpiration; soil evaporation, uncertainty
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Kumar, S.; Holmes, T.; Mocko, D.M.; Wang, S.; Peters-Lidard, C. Attribution of Flux Partitioning Variations between Land Surface Models over the Continental U.S.. Remote Sens. 2018, 10, 751.

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