D/H isotope ratios in the global hydrologic cycle
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
10.1002/2015GL064117
John Wiley & Sons Ltd.
Version of Record
http://cdss.library.oregonstate.edu/sa-termsofuse
PUBLICATIONS
Geophysical Research Letters
RESEARCH LETTER
10.1002/2015GL064117
Key Points:
• Global data set of bias-corrected
near-surface vapor D/H ratios available
• Marine surface vapor D/H values
indicate patterns of atmospheric
mixing
• The D/H ratios of continental
evapotranspiration and runoff are
determined
Supporting Information:
• Texts S1–S4, Figures S1 and S2, Tables S1
and S2, and Data Set S1 caption
• Figure S1
• Figure S2
• Data Set S1
Correspondence to:
S. P. Good,
stephen.good@oregonstate.edu
Citation:
Good, S. P., D. Noone, N. Kurita, M. Benetti,
and G. J. Bowen (2015), D/H isotope ratios
in the global hydrologic cycle, Geophys.
Res. Lett., 42, 5042–5050, doi:10.1002/
2015GL064117.
Received 6 APR 2015
Accepted 28 MAY 2015
Accepted article online 29 MAY 2015
Published online 18 JUN 2015
D/H isotope ratios in the global hydrologic cycle
Stephen P. Good1,2, David Noone3, Naoyuki Kurita4, Marion Benetti5, and Gabriel J. Bowen1
1
Department of Geology and Geophysics, University of Utah, Salt Lake City, Utah, USA, 2Department of Biological and
Ecological Engineering, Oregon State University, Corvallis, Oregon, USA, 3College of Earth, Ocean and Atmospheric
Sciences, Oregon State University, Corvallis, Oregon, USA, 4Graduate School of Environmental Studies, Nagoya University,
Nagoya, Japan, 5Sorbonne Universités (UPMC, Univ Paris 06)-CNRS-IRD-MNHN, LOCEAN Laboratory, Paris, France
Abstract
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.
1. Introduction
Variation in the deuterium to hydrogen (D/H) isotope ratio of natural waters, particularly precipitation, has been
studied since the 1960’s as a recorder of hydrologic processes [Craig, 1961; Dansgaard, 1964; Craig and Gordon,
1965]. In precipitation, spatiotemporal patterns in isotope ratios arise due to preferential rainout of isotopically
heavier water molecules during condensation and result in relatively well-understood D/H distributions
informative of atmospheric dynamics at multiple scales [Rozanski et al., 1993; Aggarwal et al., 2012; Noone,
2012; Good et al., 2014b]. This understanding has enabled reconstruction of past climate based on isotopic
compositions archived in ice cores, lake and ocean sediments, and plant materials [Dansgaard, 1964; Gat,
1996]. Furthermore, these spatiotemporal patterns in precipitation isotope ratios serve as useful tracers with
established applications in hydrogeology and ecology [Gat, 1996; Good et al., 2014a; Vander Zanden et al.,
2014; Bowen and Good, 2015].
Given the critical importance of isotope ratios as a geochemical tracer of the Earth’s hydrologic cycle, it is
surprising that the global mass balance of HDO remains poorly constrained, with the largest uncertainties
persisting in continental evapotranspiration and runoff. Compared with precipitation, measurements of
evapotranspiration flux isotopic composition are much more recent, uncertain, and sparse [Good et al.,
2012; Welp et al., 2012]. Similarly, though many isotopic measurements have been made of specific river
systems [Kendall and Coplen, 2001; International Atomic Energy Agency, 2012] adequate spatial and
temporal coverage is not available to accurately estimate a mass-weighted global runoff D/H composition.
©2015. American Geophysical Union.
All Rights Reserved.
GOOD ET AL.
Over both land and oceans, the HDO vapor pressure gradient between evaporating liquids and the overlying
near-surface vapor is well understood to directly influence the isotopic ratio of evaporative upward fluxes
[Craig and Gordon, 1965; Gat, 1996]. Therefore, accurate geochemical estimation of evapotranspiration
composition requires knowledge of surface vapor isotope ratios, which are inadequately documented by
current observations. Dynamical modeling of these isotope ratios in order to estimate the HDO vapor
pressure deficit also remains challenging due to the poorly constrained influence of atmospheric
entrainment of tropospheric vapor into the boundary layer [Lee et al., 2007; Angert et al., 2008; Yoshimura
et al., 2008]. Previous estimates of the global HDO cycle have therefore been data limited and thus
involved critical assumptions and simplifications, e.g., ignoring the terrestrial component of the water cycle
[Craig and Gordon, 1965] or assuming that atmospheric vapor is in isotopic equilibrium with precipitation
[Gat, 1996] or isotopically identical to evaporative flux [Merlivat and Jouzel, 1979].
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Figure 1. (a) Annual average isotopic composition of the marine surface layer, δA, derived from TES retrievals corrected with ship-based observations at 2°×2° resolution.
Grid cells with black outline are locations in which ship-based collections occurred within 500 km and 12 h of TES retrievals. (b) Zonal average of δA for December/
January/February (DJF), June/July/August (JJA), and zonal average of ship-based surface observations (Obs) during all months with associated error bars (1σ).
In this study, we combine ship-based vapor isotope measurements from the world’s oceans [Uemura et al.,
2008; Kurita, 2011; Kurita et al., 2011; Benetti et al., 2014] with HDO and H2O satellite retrievals from the
Tropospheric Emissions Spectrometer (TES) [Worden et al., 2012] to produce the first global estimate
of average monthly marine surface (15–20 m above sea level) vapor D/H isotopic composition. Our
approach uses an optimal merging of surface and satellite-retrieved vapor mixing ratios to bias correct
the satellite-based estimates of near-surface D/H ratios. The resulting estimates of the marine surface
vapor isotopic composition are combined with estimated bulk evaporation rates [Yu and Weller, 2007] to
calculate the global flux-weighted isotopic composition of oceanic evaporation. This information allows
a global mass balance of HDO to be solved using estimated precipitation isotopic composition [Bowen
and Wilkinson, 2002; Bowen and Revenaugh, 2003] and bulk precipitation amounts [Adler et al., 2003].
The result of this syntheses of land, sea, and space-based liquid and vapor isotope observations is a
statistically rigorous assessment of the global HDO budget that provides new constraints on global-scale
hydrological fluxes in the modern Earth system.
2. Data Sources and Methods
Retrievals from the Tropospheric Emissions Spectrometer (TES) were used to estimate the spatial pattern of
HDO and H2O vapor mixing ratios in the marine surface layer globally. TES provides soundings of gas profiles
in the atmosphere via infrared Fourier transform spectroscopy [Worden et al., 2006, 2012], with atmospheric
profiles inferred through a nonlinear optimization procedure that determines the vertical distribution most
likely to produce the radiative spectra observed by TES [Clough et al., 2006]. This study used the “TES Lite”
products which aggregate all level 2 version 5 TES H2O and HDO retrievals and include known corrections
to the retrieval algorithm [Worden et al., 2011, 2012]. The TES instrument is not optimized to retrieve
information about gasses in the lower troposphere, and large uncertainties exist in both the absolute values
and errors associated with TES retrievals, though TES version 5 demonstrates improved performance [Worden
et al., 2012; Sutanto et al., 2015]. We therefore bias correct all retrievals based on a calibration derived from
direct ship-based measurements of surface vapor.
All TES retrievals within 500 km and 12 h of any ship-based observations were treated as colocated
measurements (1351 total, with locations shown as black boxes in Figure 1a). Ship-based surface layer D/H
atmospheric vapor isotope ratio measurements, δA(Ship) (reported relative to the Vienna SMOW standard),
were made in the Pacific [Kurita, 2013], Atlantic [Benetti et al., 2014], Indian [Uemura et al., 2008; Kurita
et al., 2011], and Arctic [Kurita, 2011] Oceans. Vapor was collected via cryogenic traps [Uemura et al., 2008;
Kurita, 2011; Kurita et al., 2011] and also analyzed continuously via laser spectroscopy [Benetti et al., 2014].
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Figure 2. (a) Average across months from 2005 to 2012 of the number of TES retrievals in each grid cell per month. (b) Standard deviation between Monte Carlo
simulations of monthly δA based on variation in correction coefficients from Jackknifing and the total number of retrievals in all years. (c) Seasonal difference in
estimated marine surface layer moisture expressed as June/July/August (JJA) minus December/January/February (DJF). (Figure 2b) Annual mean difference between
surface layer isotope ratios calculated following the atmospheric closure assumption, δMJ79, and corrected TES estimates.
For cryogenic collections, vapor was collected over periods of 2–24 h (average collection interval ~12 h), which
corresponds to approximately ~10–500 km of ship movement. Laser spectroscopy systems ran continuously
and were averaged over shorter time periods. Analytical precision for ship-based observations ranged from
0.4‰ to 2‰ for D/H ratios. All ship-based measurements were made from heights between 15 m and 20 m
above the sea surface.
Initial comparisons between space- and ship-based observations of surface atmospheric vapor composition,
δA, revealed a global bias of 14.5‰ between δA(TES) and δA(Ship) with and a root-mean-square error 42.5‰
(Figure S1 in the supporting information), which is considerably less than the 123‰ bias reported at
1000 hPa based on aircraft observations in Alaska [Herman et al., 2014]. A parsimonious regression model
was created between δA(Ship) and the estimated and a priori TES isotope and water vapor mixing ratios at
the surface and in the troposphere (Text S1 and Table S1) which was used to estimate a corrected surface
vapor composition, δA(Cor). A N-1 Jackknifing approach was used to verify the regression model, wherein
each ship-based observation is removed in turn, a new set of regression coefficients generated, and that
observation predicted. Variance in regression coefficients was low (Table S1) and the correction procedure
removed the prediction bias and reduced the TES prediction errors, with a corrected root-mean-squared
error of 13.4‰ (Figure S1).
Corrected TES data from 2005 to 2013 were averaged together at a monthly timescale, producing a set of
global “climatological” grids of marine surface layer composition for each month (Data Set 1 and annual
average shown in Figure 1a). A spatial resolution of 2° was chosen based on the spacing of TES retrievals
in order to ensure that at least one measurement is likely to have occurred in each grid cell in each month
of each year (Figure 2a). Uncertainty in regression coefficients and the spatial patterns in the number of
retrievals per grid cell were used to generate 1000 different Monte Carlo ensemble estimates of δA(Cor),
with a mean uncertainty in the corrected monthly climatological surface isotope ratio grids of 2.9‰, based
on the standard deviation of averaged δA(Cor) predictions across all ensemble members (Figure 2b).
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Differences between the isotopic ratio of the marine surface layer vapor and seawater strongly affect the
composition of evaporating water (δE) in a manner analogous to the effects of vapor pressure deficit on
bulk evaporation. The Craig-Gordon model [Craig and Gordon, 1965] is used here to estimate global grids
of δE in a manner that incorporates this effect as well as the effects of equilibrium and kinetic fractionation
(Text S2). TES retrievals of mean sea surface temperature and water vapor mixing ratios were used to
estimate surface conditions during evaporation. Using monthly means to resolve fluxes removes some
short-term variability, such as mass weighting δE to days with higher evaporation rates or consequences of
diurnal temperature variation. However, given the limited number of collocated TES retrievals per grid cell
per month, a monthly time step is the smallest temporal resolution resolvable with this approach
The newly estimated grids of δE and previously determined girds of δp [Bowen and Revenaugh, 2003] are merged
with satellite-based global precipitation and evaporation estimates to calculate the global budget of H2O and
HDO in the hydrologic cycle (Text S3). This budget is resolved by using a mass balance of the oceanic
evaporation and precipitation to solve for continental runoff as the remainder and by using a mass balance of
global precipitation and oceanic evaporation to solve for continental evapotranspiration as the remainder. The
Global Precipitation Climatology Project (GPCP) [Adler et al., 2003] and Objectively Analyzed Air-Sea Fluxes
(OAFlux) [Yu and Weller, 2007] are the basis for the current best understanding of the global H2O balance
[Syed et al., 2010] and were used here to estimate the magnitude of precipitation and evaporation bulk fluxes.
Bulk fluxes from GPCP and OAFlux for 2005–2012 (the TES period) were regridded to a 2° by 2° grid resolution
globally for each month. Evaporation and precipitation occurring within each gird cell was summed over the
year to determine total oceanic evaporation, total oceanic precipitation, and total continental precipitation.
Similarity, each bulk water flux is multiplied by its isotopic ratio to determine the HDO flux of total oceanic
evaporation, δEðOÞ , total oceanic precipitation, δPðOÞ , and total continental precipitation, δPðLÞ .
The estimates of oceanic evaporation and precipitation bulk fluxes and their isotopic composition were
combined to estimate the mass balance of HDO in the world’s oceans, with continental runoff
composition, δRðLÞ , calculated as the residual. Similarly, we combined estimates of oceanic evaporation and
precipitation bulk fluxes and the isotopic composition of these fluxes with terrestrial precipitation isotope
values and fluxes to estimate the isotopic composition of terrestrial evapotranspiration, δETðLÞ , (which
includes evaporation, transpiration, and intercepted precipitation) as the residual of the mass balance for
the atmosphere. In both cases, mass balance was assumed at the annual timescale only, with fluxes
summed for each grid cell across all months to estimate a flux-weighted annual amount. In our approach,
we do not consider changes in oceanic or continental water storage, nor temporal trends in global
hydrologic fluxes. Though these phenomena have recently been identified, the constitute small changes
relative to total fluxes [Syed et al., 2010], and we instead choose to minimize our total uncertainty by
pooling all available data into annual average estimates.
A Monte Carlo approach is applied to constrain uncertainty in the global HDO estimated above (Text S4). This
approach propagates uncertainty in δA(Cor) calibration coefficients, residual δA(Cor) variance not accounted for
in bias correction, uncertainty in precipitation isotope ratios, uncertainty in temperature and relative
humidity, uncertainty in kinetic fractionation, and uncertainty in the bulk flux amounts. As noted above,
we begin by using the uncertainties in the TES bias correction and the number of TES retrievals per grid
cell to generate 1000 different ensemble simulations of δA(Cor). For each of these simulation, a random
value centered about the local mean temperature and humidity are then generated for each grid cell, as
well as a random kinetic fractionation factor, and these local conditions are used to calculate unique
values of δE in each cell for each simulation. Similarly, for each simulation bulk fluxes from a single
year between 2005 and 2013 are resampled and combined with simulated isotope fluxes to calculate the
flux-weighted values of δE ðOÞ , δPðOÞ , and δPðLÞ . Finally, the atmospheric and oceanic mass balance is
calculated for each simulation to estimate δRðLÞ and δETðLÞ , with the mean and standard deviation of all
1000 simulations used to estimate the global D/H fluxes and their associated uncertainty.
3. Patterns in Marine Surface Layer D/H Ratios
The D/H isotopic composition of the marine surface layer, δA, estimated from bias-corrected TES retrievals,
exhibits coherent spatiotemporal patterns across the globe (Figure 1a), including strong zonal and seasonal
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gradients (Figures 1b and 2c). Annual δA averages range from approximately 130‰ near the poles to values of
approximately 75‰ near 10° north and south. The bias-corrected estimates are least accurate in the Arctic,
where the TES instrument has limited sensitivity [Worden et al., 2012]. Because evaporative bulk fluxes are
low at high latitudes, this bias will have little effect on the global HDO budget. Overall, values reported here
are higher (more enriched in HDO) than the total column averages retrieved by Scanning Imaging
Absorption Spectrometer for Atmospheric Chartography, on Envisat (SCIAMACHY) [Frankenberg et al., 2009],
which ranged from 260‰ to 80‰. We find that variations in surface values of δA are substantially
damped relative to SCIAMACHY column average, TES midtroposphere estimates, and continental
precipitation values. This damping is likely due to the influence of higher-altitude moisture within the total
column SCIAMACHY observations as well as the stabilizing influence of oceanic evaporation on D/H ratio of
the atmospheric surface layer. Globally, the unweighted average value of δA is 106‰, with average
compositions of 86‰ within the tropics (<15°N/S), 90‰ in the subtropics (>15°, <30°N/S), and 117‰
in the middle and high latitudes (>30°N/S).
Within each hemisphere, summertime marine surface vapor is isotopically heaviest in the midlatitudes and
lighter near the equator and poles (Figure 1b). Summer minus winter differences are strongest at ~30–40°N
with an average δA shift of ~12‰ (Figure 2c). These seasonal differences likely reflect stronger wintertime
advection of low-humidity air below the subtropical inversion as part of equatorward return flow as well as
winter depletion of HDO in the downwelling arms of Hadley circulation, previously observed over the inner
Sahel [Frankenberg et al., 2009]. Differences in seasonal rainout effects, moisture source variation, and
tropospheric entrainment have been suggested to alter δA over the Mediterranean Sea [Angert et al.,
2008], where we observe summer minus winter shifts of over 30‰. We also observe an equatorial
depression in δA values that moves seasonally with the intertropical convergence zone and is on the
order of ~10‰, indicating seasonality in mesoscale convective mixing across the marine boundary layer.
Without global observations of marine surface vapor composition, calculations of δE in previous studies have
traditionally followed the atmospheric closure assumption [Merlivat and Jouzel, 1979], wherein surface layer
vapor is assumed to consist entirely of local oceanic evaporation. This approach is known to overestimate the
isotopic composition of surface layer vapor [Kurita, 2013; Benetti et al., 2014], and deviations from this
assumption can be interpreted as an indicator of entrainment of free troposphere water vapor with more
negative δ values [Benetti et al., 2015]. We calculate marine boundary layer vapor following this closure
assumption (hereafter δMJ79) and compare this estimate with the TES-derived values (Figure 2d). Overall,
our bias-corrected satellite retrievals demonstrate that δA is globally depleted in HDO relative to values
expected based on the closure assumption by ~15‰, with this difference varying spatially and seasonally.
We find that near the equator and at latitudes greater the 30°, regions with climatologically high rainfall
rates are associated with large discrepancies between δA and δMJ79, reflecting the role of mesoscale
convective systems in bringing isotopically lighter moisture into the boundary layer either though
downdrafts or reevaporation of precipitation [Kurita, 2013]. Deviations from the closure assumption are
smallest in regions with strong evaporative flux, warm sea surface temperatures, and low relative humidity.
4. The Global HDO Cycle
Globally, the flux-weighted annual average isotopic composition of oceanic precipitation is δPðOÞ ¼
34:4 ± 0:4‰ ð1σ Þ and that of continental precipitation is δPðLÞ ¼ 50:0 ± 0:9‰, with the uncertainties
reflecting the fact that the correlation length scale for precipitation isotope ratios is small [West et al., 2010],
causing random errors to diminish at global scales. Over both the oceans and continents, temperature
gradients and progressive Rayleigh-like distillation of precipitation during meridional transport result in
decreasing δP values from the midlatitudes toward the poles (Figures 3a and 3b) [Dansgaard, 1964; Bowen
and Revenaugh, 2003]. Seasonality is caused by both summer-winter temperature shifts and by variability in
precipitation amount, with continental precipitation isotope seasonality strongest in the northern
midlatitudes [Bowen, 2008]. Migration of the Intertropical Convergence Zone and monsoon flow produces
increased precipitation during summer months in the tropics and is associated with more negative δP
values. Low precipitation amounts, coupled with possible reevaporation of hydrometeors during rainfall in
the horn of Africa region (~10°N) in late winter and early spring result in precipitation enriched in HDO
relative to standard ocean water.
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Figure 3. Seasonal flux D/H isotope composition by latitude for precipitation over the (a) oceans, (b) over land, and (c) evaporation over the oceans. Note that there is
no land at 60°S.
The global flux-weighted average oceanic evaporation isotopic composition based on the HDO and H2O
vapor pressure deficits is estimated as δEðOÞ ¼ 37:6 ± 1:2‰ and is also characterized by both spatial
gradients and strong seasonality (Figure 3c). This estimate is more negative than previous global
estimates of 22‰ which was based on observations in the tropics and subtropics only [Craig and
Gordon, 1965; Gat, 1996]. The strongest seasonal gradients in δE(O) occur in the Northern Hemisphere
from 40° to 80° north. Migration of the Intertropical Convergence Zone is also associated with seasonal
shifts in δE(O) values, with tropical wintertime fluxes more depleted in HDO. Overall, there is a strong
evaporation amount effect on ocean flux composition, acting opposite the precipitation amount effect,
wherein larger evaporative bulk fluxes are associated with less fractionated and more positive δE(O)
values. This amount effect arises because δE is determined by the ratio of the HDO vapor pressure deficit
to the bulk H2O vapor pressure deficit, and as evaporation is directly proportional to the bulk H2O vapor
pressure deficient, an inverse relationship between evaporation and δE exists [see Yoshimura et al., 2008,
Appendix A]. Similar to oceanic precipitation, seasonality in δE(O) is much weaker in the Southern
Hemisphere, likely due to the absence of large continental influence. Previous results from global
Figure 4. Schematic of the global hydrologic cycle and its D/H isotopic composition, with ±1 standard deviation shown for
δ values and bulk flux amounts. Arrow widths correspond to bulk water flux amounts.
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climate simulations indicate that δE(O) values are expected to increase near the poles due to very low values
of δA arising from distillation effects [Lee et al., 2007]. The inability of our bias correction to match
observations at latitudes greater the 60° north likely causes underestimation of δE(O) in these regions,
and the strong high latitude patterns in Figure 3c may be unreliable. However, the total evaporative flux
occurring above 60°N is only 1.9% of total annual oceanic evaporations, and this effect is likely small
when evaluating the global HDO cycle.
Merging precipitation and evaporation bulk fluxes with estimated δPðOÞ , δPðLÞ , and δE ðOÞ estimates, we
calculate continental land-atmosphere flux average isotopic composition as δETðLÞ ¼ 40:0 ± 6:5‰ based on a
mass balance of the atmosphere and global continental runoff isotopic composition as δRðLÞ ¼ 77:3 ± 17:5‰
(Figure 4) based on a mass balance of the oceans. The majority of the Earth’s hydrologic cycle occurs
in and over the oceans; therefore, oceanic precipitation is isotopically similar to that of oceanic
evaporation. However, large spatial and seasonal variability coupled with atmospheric transport results
in quantitative spatiotemporal differences between these fluxes (i.e., Figure 3a versus Figure 3c), and
these differences constrain the value of δETðLÞ , which has significance for estimation of water cycle
parameters such as the global evaporation/transpiration ratio [Jasechko et al., 2013]. The depletion of
HDO in continental runoff, relative to total continental precipitation, suggests that, in general, a larger
fraction of precipitation becomes runoff at higher latitudes, altitudes, and during the cool seasons,
where and when precipitation HDO is depleted [Dettinger and Diaz, 2000; Fekete et al., 2006]. Our
estimated runoff value is higher than that obtained in a global isotope budget analysis of [Gat, 1996]
(94‰), but consistent with our synthesis of isotopic data from major rivers (see Table S2), which gives
values between 130‰ and 45‰ and an unweighted median value of 78‰. Few measurements of
evapotranspiration flux D/H ratios have been made due instrumental and methodological difficulties
[Good et al., 2012; Sutanto et al., 2014], with published values ranging from below 290‰ to +100‰
(see Table S3). Due to attenuation of temporal variability in the terrestrial hydrological system, we
cannot assess seasonality in evapotranspiration or runoff composition.
5. Conclusions
Acknowledgments
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. 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
(nkurita1126@nifty.com) and Marion
Benetti (marionbenetti@locean-ipsl.
upmc.fr) as well as in Table 2 of Uemura
et al. [2008]. Tropospheric Emissions
Spectrometer data is available at
http://tes.jpl.nasa.gov/. Globally
gridded precipitation isotope values were
first reported in Bowen and Revenaugh
[2003], with data sets available at http://
waterisotopes.org and by request from
Gabriel Bowen (gabe.bowen@utah.edu).
The Editor thanks two anonymous
reviewers for their assistance in evaluating
this paper.
GOOD ET AL.
Through a synthesis of surface- and space-based observations of liquid and vapor water isotope ratios, this
study presents a global estimate of the D/H ratio of marine surface layer vapor. Though marine surface
vapor is strongly related to evaporation isotopic composition, atmospheric entrainment, subsidence, and
other processes result in a divergence from the closure assumption of Merlivat and Jouzel [Merlivat
and Jouzel, 1979]. The strength of this divergence from values based on the closure assumption varies
spatiotemporally with surface environmental factors.
The HDO vapor pressure gradient in the marine boundary layer determines the oceanic evaporation D/H
ratios, and the global HDO budget presented here provides a first global baseline that incorporates
observations of this spatiotemporally varying constraint. Compared to total continental precipitation, we
find that total continental evapotranspiration is ~10‰ enriched in HDO while total continual runoff is
~27‰ depleted in HDO, with these differences likely reflecting strong spatial and temporal gradients in
runoff production and evaporation/transpiration partitioning.
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