2021
DOI: 10.1029/2021ms002562
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A Joint Soil‐Vegetation‐Atmospheric Modeling Procedure of Water Isotopologues: Implementation and Application to Different Climate Zones With WRF‐Hydro‐Iso

Abstract: Water isotopologues, namely water molecules that contain an isotope of oxygen or hydrogen, are natural tracers that characterize the Earth's water cycle in the present and past days (Gat, 1996), which is the reason why their observation and modeling has been raising the interest of the scientific community for many decades (e.g., Dansgaard, 1954;Joussaume et al., 1984;Steen-Larsen et al., 2017). In this work, the focus is on modeling the isotopic fractionation processes in the coupled land-atmosphere regional … Show more

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Cited by 4 publications
(1 citation statement)
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“…Despite the above-mentioned advanced features of our newly developed WRFage model, one potential limitation of our RCM-based age-weighted regional water tagging approach is that the model-derived results of tracked evaporated water and respective atmospheric residence times depend on how realistically an RCM can simulate all the relevant processes of terrestrial hydrology, vegetation, and atmosphere (Gimeno et al, 2012). Direct validation of our model-derived results would be possible by tracking the water isotopologues as done in, e.g., Arnault, Jung, et al (2021) and Arnault et al (2022).…”
Section: Discussionmentioning
confidence: 99%
“…Despite the above-mentioned advanced features of our newly developed WRFage model, one potential limitation of our RCM-based age-weighted regional water tagging approach is that the model-derived results of tracked evaporated water and respective atmospheric residence times depend on how realistically an RCM can simulate all the relevant processes of terrestrial hydrology, vegetation, and atmosphere (Gimeno et al, 2012). Direct validation of our model-derived results would be possible by tracking the water isotopologues as done in, e.g., Arnault, Jung, et al (2021) and Arnault et al (2022).…”
Section: Discussionmentioning
confidence: 99%