Attribution of Flux Partitioning Variations between Land Surface Models over the Continental U.S.
AbstractAccurate quantification of the terrestrial evapotranspiration ( ) 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 . As these models are often used in data assimilation environments for incorporating and extending relevant remote sensing measurements, understanding the sources of inter-model differences in 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 : (1) contribution of the local partitioning and (2) regional distribution of . 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 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 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 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
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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.
Kumar S, Holmes T, Mocko DM, Wang S, Peters-Lidard C. Attribution of Flux Partitioning Variations between Land Surface Models over the Continental U.S.. Remote Sensing. 2018; 10(5):751.Chicago/Turabian Style
Kumar, Sujay; Holmes, Thomas; Mocko, David M.; Wang, Shugong; Peters-Lidard, Christa. 2018. "Attribution of Flux Partitioning Variations between Land Surface Models over the Continental U.S.." Remote Sens. 10, no. 5: 751.
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