D/H isotope ratios in the global hydrologic cycle Public Deposited

Surface isotope data collected during cruises were first presented in Uemura et al. [2008], Kurita [2013], and Benetti et al. [2014] and are available by request from Naoyuki Kurita ( and Marion Benetti ( as well as in Table 2 of Uemura et al. [2008]. Tropospheric Emissions Spectrometer data is available at Globally gridded precipitation isotope values were first reported in Bowen and Revenaugh [2003], with data sets available at and by request from Gabriel Bowen (

Dataset located at:

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Attribute NameValues
  • Deuterium to hydrogen (D/H) ratios in Earth’s hydrologic cycle have long served as important tracers of climate processes, yet the global HDO budget remains poorly constrained because of uncertainties in the isotopic compositions of continental evapotranspiration and runoff. Here bias-corrected satellite retrievals of HDO and H₂O concentrations from the Tropospheric Emissions Spectrometer are used to estimate the marine atmospheric surface layer HDO vapor pressure deficit, from which we calculate the global flux-weighted average oceanic evaporation isotopic composition as -37.6‰. Using these estimates, combined with D/H ratios in precipitation, global mass balance suggests H isotope compositions for global runoff and terrestrial evapotranspiration of -77.3‰ and -40.0‰, respectively. By resolving the HDO budget, we establish an accurate global baseline for geochemically enabled Earth system models, demonstrate patterns in entrainment of moisture into the marine surface layer, and determine the isotopic composition of continental fluxes critical for global ecohydrologic investigations.
Resource Type
Date Available
Date Issued
  • Good, S. P., Noone, D., Kurita, N., Benetti, M., & Bowen, G. J. (2015). D/H isotope ratios in the global hydrologic cycle. Geophysical Research Letters, 42(12), 5042-5050. doi:10.1002/2015GL064117
Journal Title
Journal Volume
  • 42
Journal Issue/Number
  • 12
Rights Statement
Funding Statement (additional comments about funding)
  • This project was funded by the National Science Foundation Macrosystems Ecology program, grant EF-01241286 and the Department of Defense. D.N. acknowledges the support of the NSF Climate and Large Scale Dynamic program as part of a Faculty Early Career Development award (AGS-0955841). The support and resources from the Center for High Performance Computing at the University of Utah is also gratefully acknowledged.
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