Earth and Planetary Science Letters 513 (2019) 20–28

Contents lists available at ScienceDirect

Earth and Planetary Science Letterswww.elsevier.com/locate/epsl

Dominant inﬂuence of the humidity in the moisture source region on
the 17 O-excess in precipitation on a subtropical island
Yuina Uechi, Ryu Uemura ∗Department of Chemistry, Biology, and Marine Science, University of the Ryukyus, 1 Senbaru, Nishihara, Okinawa, 903-0213, Japana r t i c l e

i n f oArticle history:
Received 23 August 2018
Received in revised form 20 December 2018
Accepted 10 February 2019
Available online 25 February 2019
Editor: J. Adkins
Keywords:
triple oxygen isotopes
17
O-excess
precipitation
subtropical hydrological cycle
d-excess
Asian monsoon

a b s t r a c t
A high-precision analysis of the triple oxygen isotope composition of water provides a new tracer
denoted as 17 O-excess. Early theoretical and experimental studies suggest that changes in the 17 Oexcess in precipitation can be interpreted as variations in the relative humidity in moisture source
regions for precipitation. However, subsequent studies on 17 O-excess in the precipitation in polar anddry regions suggest the importance of additional fractionation, such as snow formation and raindrop
re-evaporation processes, which diminish the relative humidity information in oceanic source regions.
To date, whether humidity in the moisture source region can be quantiﬁed based on observations of17
O-excess in precipitation has not been proven. Here, we show a two-year record of the 17 O-excess inprecipitation on a maritime island in the East Asian monsoon region. The normalized relative humidity
in the source region was reconstructed from 17 O-excess data using a simple evaporation model. We
demonstrate that the reconstructed relative humidity is quantitatively consistent with observations in
the oceanic moisture source region. This result suggests that the 17 O-excess in precipitation on thesubtropical island is determined largely by diffusional fractionation during evaporation in the ocean. We
also test the impact of a possibly different 17 O–18 O slope suggested by a recent study on the 17 O-excess
deﬁnition. This different deﬁnition results in a minor impact on the data from tropical and subtropicalregions but a signiﬁcant change in the data from polar regions. These results suggest that the 17 Oexcess in precipitation in tropical and subtropical regions is a unique quantitative tracer for the relative
humidity in oceanic moisture source regions and thus will be a useful tracer and proxy for hydrologicaland paleoclimate studies.
© 2019 Elsevier B.V. All rights reserved.

1. Introduction
The oxygen and hydrogen isotope ratios (δ 18 O and δ D, respectively) in precipitation have been widely used as tracers of
the water cycle (e.g., Dansgaard, 1964). A combination of these
two isotope ratios generates a moisture source parameter, namely,
the deuterium excess (d-excess = δ D–8 δ 18 O) (Dansgaard, 1964),
which originates from diffusional fractionation during evaporationand is expressed as a non-zero intercept of the global meteoric
water line (Craig, 1961). An isotopic model predicts that d-excess
can effectively reﬂect the relative humidity and sea surface temperature (SST) in oceanic moisture sources (Merlivat and Jouzel,1979); this theory is generally supported by observations of water
vapor in the boundary layer (Benetti et al., 2015; Steen-Larsen etal., 2014b; Uemura et al., 2008).

* Corresponding author.

E-mail address: ruemura@sci.u-ryukyu.ac.jp (R. Uemura).

https://doi.org/10.1016/j.epsl.2019.02.012
0012-821X/© 2019 Elsevier B.V. All rights reserved.

A new parameter known as 17 O-excess has been establishedbased on recent developments in the acquisition of high-precision
measurements of the 17 O/16 O ratio, namely, δ 17 O (Angert et al.,
2004; Barkan and Luz, 2005). Analogous to d-excess, an excess ofδ 17 O in a δ 17 O–δ 18 O plot results from diffusional isotopic fractionation during evaporation in the ocean; furthermore, theory
and experimentation both suggest that 17 O-excess reﬂects variations in the relative humidity at the ocean surface in the moisture source region and that the temperature dependence of 17 Oexcess is smaller than that of d-excess (Barkan and Luz, 2005;
Barkan and Luz, 2007; Luz and Barkan, 2010). In fact, an observation of the atmospheric water vapor over the ocean showed that17
O-excess exhibits a negative correlation with the relative humidity (Uemura et al., 2010).
Because the δ 18 O and δ D of water in polar ice cores containinvaluable information on past hydroclimatic changes (e.g., Jouzel,
2013; Uemura et al., 2018), many studies have attempted to reveal
17
O-excess variations in polar regions (e.g., Landais et al., 2008;
Risi et al., 2010; Steen-Larsen et al., 2014a). In a pioneering investigation, the 17 O-excess variations over glacial cycles in the Antarctic

Y. Uechi, R. Uemura / Earth and Planetary Science Letters 513 (2019) 20–28

Vostok ice core were interpreted as changes in the relative humidity normalized to the SST and/or wind speed in the moisturesource region (Landais et al., 2008). Ice cores from coastal sites
suggest that 17 O-excess values at inland sites such as Vostok may
be highly sensitive to local effects (Winkler et al., 2012); in inland
areas, the 17 O-excess of snow decreases due to isotopic fractionation during the formation of snow (Pang et al., 2015; Touzeau
et al., 2016). In conjunction with isotope modeling, ice core datafrom West Antarctica suggest a limited role of changes in the relative humidity in determining the glacial–interglacial changes in
the Antarctic 17 O-excess (Schoenemann et al., 2014). Most recently,
Miller (2018) suggested that the precipitation regime has a substantial inﬂuence on Antarctic precipitation. In summary, the ﬁndings of previous studies suggest that 17 O-excess data in ice corescan be interpreted in multiple ways.
In addition to those in polar regions, hydroclimatic changes intropical and subtropical regions are also crucial for understanding the mechanism of natural climate change. Analogous to thoseof ice cores, the isotopic compositions of past rainwater in tropical and subtropical regions are preserved within ﬂuid inclusions
trapped in speleothems (e.g., Affolter et al., 2015; Uemura et al.,2016). Furthermore, recent studies demonstrated that past 17 Oexcess variations can be measured through the δ 17 O values ofcalcite (Barkan et al., 2015; Passey et al., 2014). Thus, 17 O-excesschanges are a promising proxy for reconstructing past relative humidity changes in tropical and subtropical regions.
With regard to mid- and low-latitude regions, an investigation
in a dry African region showed that the 17 O-excess in precipitation is strongly inﬂuenced by re-evaporation during convective
activity (Landais et al., 2010). In the United States, the spatial distribution of 17 O-excess based on tap waters (Li et al., 2015) anda 2-year monitoring campaign based on rainfall/snowfall collectedfrom a single location (Tian et al., 2018) were reported, but a humidity reconstruction was not provided. We should note that the17
O-excess signal in a humid climate is expected to preserve diffusional fractionation during evaporation with minimal additional
isotopic fractionation caused by the re-evaporation of precipitation.
However, to the best of our knowledge, no observational study has
proven that the 17 O-excess in precipitation preserves normalized
relative humidity information in oceanic moisture source regions.
In this study, to evaluate the 17 O-excess in precipitation as aproxy for investigating the relative humidity in oceanic moisturesource regions, we measured the 17 O-excess in precipitation fallingover the subtropical island of Okinawa, Japan. The precipitation on
this island is an ideal sample for such an evaluation because (i) thehigh humidity in the air minimizes raindrop re-evaporation effect,and (ii) the strong East Asian monsoon results in large seasonalvariations in the relative humidity throughout the oceanic moisture source regions. In this paper, we present a two-year recordof the 17 O-excess in the precipitation on a subtropical maritime
island. To test the accuracy of the 17 O-excess measurements, theisotope ratios are calibrated carefully with respect to internationalreferences. The 17 O-excess data are compared with those from anarid region to investigate the magnitude of the rain re-evaporation
effect. We reconstruct the normalized relative humidity in oceanic
moisture source regions from the 17 O-excess data using a simple
evaporation model based on a closure assumption. Then, the reconstructed humidity based on 17 O-excess is compared with theobservational humidity data in the moisture source oceans basedon backward trajectory analyses. Finally, the inﬂuences of possible
processes other than the evaporation and the uncertainty causedby the deﬁnition of 17 O-excess are also discussed.

21

2. Methods
2.1. Rainwater samples and meteorological data
Precipitation samples were collected weekly from January 2011
to December 2012 on the roof of the Okinawa Prefectural Institute of Health and Environment at Oozato in the southern part of
Okinawa Island (oﬃcially called Okinawa-jima; “jima” means island in Japanese), Japan (26◦ 11 11 N, 127◦ 45 13 E, 90 m above
mean sea level; Fig. 1). The sampling procedure was describedin detail in a previous study (Uemura et al., 2012), in which thesame samples were used for δ 18 O and δ D analyses. The precipitation samples were collected using a sampling machine whose
lid is opened automatically when it rains. This system minimizes
secondary evaporation and contamination from dry deposition of
atmospheric dust. We measured 95 samples for which a suﬃcientamount of precipitation (>2.0 mL) was collected. Meteorological
data were obtained at the Naha meteorological station, which islocated 7 km to the northwest of the sampling site and is operated by the Japan Metrological Agency.
2.2. Deﬁnitions of the isotope ratios and 17 O-excess
The isotopic composition is expressed in units of per mill (h)using delta notation (δ = R sample / R ref − 1), where R is the isotopic
ratio, and R sample and R ref are the isotopic ratios of the sample
and reference water, respectively. 17 O-excess is deﬁned by the following equation (Barkan and Luz, 2005) using logarithmic delta
notation (δ  = ln(δ + 1) = ln( R sample / R ref )):17

O-excess = δ 17 O − 0.528 × δ 18 O

where

17

(1)

O-excess is indicated in units of per meg (= 1 × 10−6 ).

2.3. Isotope measurements
The δ 17 O, δ 18 O and δ D values were measured simultaneously
using a cavity ring-down spectrometer (L2140-i, Picarro Inc.) witha vaporizer unit (V1120-i, Picarro Inc.). The details of this laser
spectrometer system were described in Steig et al. (2014). To obtain precise δ 17 O values that are suitable for an evaluation of 17 Oexcess, many repeated measurements are needed. Consequently,
we used a 350 μL vial (C400-LV1, Thermo, National Scientiﬁc Ltd.),
and the gap between the inner wall and outer wall of the vial wassealed with an epoxy resin to avoid evaporation.
One batch consists of 20 samples and two working standards(WSs). The WS is used to calibrate the data on the Vienna Standard
Mean Ocean Water (VSMOW)-Standard Light Antarctic Precipitation (SLAP) scale. For each injection, 1 μL of liquid sample wasused. A sample measurement was performed with 10 injections.
For a WS measurement, 60 injections (i.e., 6 vials) were performed.
Approximately 48 hours are required for one batch measurement.
Memory effect corrections were applied to the isotope measurements (Gupta et al., 2009). Each sample was measured 3–6 times(i.e., in a total of 30–60 injections over 3–6 batches for each sample).
The uncertainty
was estimated using the standard error of the√mean (1σ / n; hereafter SE). Based on the repeated measurementsof the samples (i.e., the number of measurements, n, is 3–6), theuncertainties of the analyzed data are 0.007h for δ 17 O, 0.008h
for δ 18 O and 0.05h for δ D, and those of 17 O-excess and d-excess
are 5 per meg and 0.09h, respectively.
2.4. Calibration of δ 17 O values
The isotope compositions were normalized onto the VSMOWSLAP scale using a linear normalization method (Schoenemann etal., 2013); thus, the SLAP δ 17 O value was assigned as −29.6986h

22

Y. Uechi, R. Uemura / Earth and Planetary Science Letters 513 (2019) 20–28

Fig. 1. Backward trajectory analysis for four seasons. (a) Backward trajectories (thin orange lines) and their average (bold red line) for the winter (DJF) season. (b) The sameas (a) but for the spring (MAM). (c) The same as (a) but for the summer (JJA). (d) The same as (a) but for the autumn (SON). Colored grid points indicate the point densityof the trajectory above the threshold value, and reﬂect the estimated moisture source area. The red star indicates the sampling location. (For interpretation of the colors inthe ﬁgure(s), the reader is referred to the web version of this article.)(vs. VSMOW). The isotope compositions of the laboratory WSs
were carefully determined with international reference waters. Because the SLAP water was exhausted, we used SLAP2 water, whoseδ 18 O and δ 17 O values are indistinguishable from those of the SLAP
water (Lin et al., 2010). To minimize memory effects, ﬁve WSs with
gradual differences in δ 18 O values were measured between the
VSMOW2 and SLAP2 waters. To evaluate the accuracy of our measurements, we also measured the Greenland Ice Sheet Precipitation(GISP) water provided by the International Atomic Energy Agency(IAEA) without assuming an assigned value. Each WS and IAEA
reference water was measured by 50–150 injections; for the calibration, we adopted the averaged value of 20–60 injections fromthe latter measurement, where the memory effect was no longer
observed. This sequence was performed 6 times; for example, 240
injections were performed to obtain the result for the GISP water.
2.5. Backward trajectory and ocean surface data
To compare the relative humidity in the moisture source region
estimated from 17 O-excess, we calculated the observed relative humidity in the ocean. The moisture source region was evaluatedby air mass backward trajectories, for which we used the Hybrid
Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model(Stein et al., 2015; https://ready.arl.noaa.gov/HYSPLIT.php). For all

precipitation events (daily precipitation >0.5 mm) at the Naha meteorological station, the trajectory of the air mass (at 2000 m AGL)
was calculated until 72 hours prior to the onset of precipitation.
The 72-hour was used as a standard case because an averagetime between moisture uptake in the boundary layer and the arrival of the air parcel over Greenland is 3–4 days based on a
Lagrangian diagnostic model (Sodemann et al., 2008). However,a longer transport time (∼7–9 days), is found in limited regions(Sodemann et al., 2008). Thus, the trajectories were also calculated
for 10 days backward, which is about the maximum timescale onwhich integrity of the traced air parcel can be assumed (Pfahl andWernli, 2008). In subtropical area, an average moisture residence
time is ca. 10 days (Aggarwal et al., 2012). For sensitivity tests, different starting altitudes, 1000 m and 3000 m, were also calculated.
The moisture source area was determined based on point density of the trajectories (an hourly point on the trajectory was taken
as a point). The threshold value was determined so that the cumulative percentage of the trajectories in 1◦ × 1◦ grid points becomes
60%. Then, all the 1◦ × 1◦ grid points above a threshold percentage are considered as the source area.
Then, the relative humidity in the moisture source region
was calculated using an observational data set, namely, the International Comprehensive Ocean–Atmosphere Data Set (ICOADS;
Freeman et al., 2017). The relative humidity normalized to the SST

Y. Uechi, R. Uemura / Earth and Planetary Science Letters 513 (2019) 20–28

23

in the oceanic moisture source region (hn ) was calculated using
the 1◦ × 1◦ grid points data-set of SST and humidity from ICOADS.
Land grid points were excluded from the calculation.
3. Results and discussion
3.1. 17 O-excess of the GISP waterThe δ 18 O and δ D values of the GISP water are −24.774 ±
0.033h (±1σ ) and −189.39 ± 0.30h, respectively. Accounting forthe number of measurements, the uncertainties based on the SE
are ±0.007h for δ 18 O and ±0.07h for δ D. For comparison, the
IAEA recommended value for δ 18 O is −24.76 ± 0.01h (±SE), andthat for δ D is −189.5 ± 0.2h (±SE) (IAEA, 2007). Thus, our δ 18 O
and δ D values agree well with the international recommended
values within their mutual error range, thereby certifying our calibration method.
The 17 O-excess value of the GISP water in this study is 33 ±12 per meg (±1σ ). These 17 O-excess data exhibit a normal frequency distribution, suggesting negligible systematic error. Considering the number of repeated analyses, our 17 O-excess value for
the GISP is 33 ± 2 per meg (±SE). For comparison, recent analyses
using different methods reported values of 23 ± 2 per meg by offaxis integrated cavity output spectroscopy (Berman et al., 2013),
28 ± 4 per meg by isotope ratio mass spectroscopy (Schoenemannet al., 2013) and 27 ± 4 per meg by cavity ring-down spectroscopy(CRDS; Steig et al., 2014). The overall average of previous measurements after VSMOW-SLAP normalization is 27 ± 11 per meg(±1σ ) (Schoenemann et al., 2013). Thus, our data are consistent
with the ﬁndings of previous studies within their mutual error
ranges.
3.2. Backward trajectory analysis
The results of 72-hour backward trajectory analysis are shownin Fig. 1. The wind direction on Okinawa Island changes seasonallybecause of the East Asian monsoon. In the winter (December–
February), the air masses mainly originate from the direction of
the East China Sea (Fig. 1a). In contrast, during the summertime(June–August), most of the air masses come from the direction of
the Paciﬁc Ocean (Fig. 1c). Most of the air masses in the spring(March–May) originate from the southwest (Fig. 1b). The autumn
season (September–November) marks a transition from summer
to winter and thus shows scattered wind directions (Fig. 1d). Results of sensitivity tests for different starting altitudes ranged from1000 m to 3000 m does not show signiﬁcant changes for moisturesource regions (Supplementary material, Fig. S1).
The oceanic moisture source region for precipitation, deﬁned
to reﬂect 60% of the point density of the trajectories, are shownin Fig. 1 (colored grid points). For example, the oceanic moisturesource regions are the East China Sea for the winter, the area between the East China Sea and Philippine Sea for the spring, and
the Philippine Sea for the summer and autumn.
The results of 10-day backward trajectory are shown in Supplementary material (Fig. S2). The seasonality of the wind direction
is essentially the same as 72-hour results, but estimated moisturesource regions are extended. For example, in summer, a part ofmoisture source region is extended to cover the Indian Ocean.
3.3. 17 O-excess in precipitation
The isotopic compositions of the precipitation on Okinawa Island and the meteorological data are shown in Fig. 2 and Supplementary Tables (Tables S1 and S2). Monthly isotope ratios were
calculated by a precipitation-weighted average. Clear seasonal cycles were observed in the temperature and relative humidity, bothFig. 2. Oxygen isotopic ratios in precipitation and meteorological data in Okinawa.
(a) Monthly precipitation-weighted average values of δ 18 O and δ 17 O in precipitation. (b) Weekly 17 O-excess in precipitation (thin red line). The bold line indicatesthe monthly precipitation-weighted average of 17 O-excess. (c) Monthly relative humidity at the meteorological station. (d) Monthly precipitation amount (blue bar)and air temperature (red line) at the meteorological station.

of which were high during the summer and low during the winter.
The amount of precipitation shows an irregular pattern but generally large values during the Meiyu/Baiu rainy season and summertime (April–September). Because the δ D, δ 18 O and d-excess results
were previously discussed in Uemura et al. (2012), in this study,
we focus on 17 O-excess variations. Accordingly, a clear seasonality in 17 O-excess was observed with low values in the summer(5–25 per meg) and high values in the winter (25–50 per meg).
3.4. Humidity at the sampling site versus 17 O-excess
The 17 O-excess in the precipitation on Okinawa Island exhibitsa negative correlation with the relative humidity (Fig. 3), whichis consistent with the prediction of an evaporation model in theocean (Barkan and Luz, 2007). Because Okinawa Island is surrounded by the ocean, the humidity at the Naha meteorologicalstation (3 km from the coast) is expected to be inﬂuenced largelyby the changes in relative humidity in the moisture source ocean.
Furthermore, the negative correlation between the Okinawa 17 Oexcess and relative humidity is similar to the correlation found inmeasurements of marine water vapor from the Southern Indian
Ocean and the Southern Ocean (Uemura et al., 2010).
In contrast, a raindrop re-evaporation effect was observed in
the precipitation 17 O-excess over West Africa (Landais et al., 2010).
Lower observed 17 O-excess values under conditions of lower humidity mainly result from the re-evaporation of raindrops; as24

Y. Uechi, R. Uemura / Earth and Planetary Science Letters 513 (2019) 20–28

Fig. 3. 17 O-excess versus the relative humidity at sampling sites. 17 O-excess in the
precipitation on Okinawa Island against relative humidity data at the Naha meteorological station (red circle). The blue square indicates the 17 O-excess in atmosphericwater vapor in the Southern Ocean against the relative humidity at the samplingsites (Uemura et al., 2010). Triangles indicate the 17 O-excess in the precipitation inWest Africa against the relative humidity at the sampling sites for three-month observations (deep brown) and for a squall event (light brown) (Landais et al., 2010).
Dotted lines indicate linear regressions of each data set. Note that the data are plotted against the relative humidity instead of hn .

a result, the precipitation 17 O-excess correlates positively withthe relative humidity at the sampling site (Fig. 3). In a raindrop re-evaporation model (Bony et al., 2008), the intensity ofre-evaporation is very low under a high relative humidity, andthe droplets and the surrounding water vapor are close to isotopic equilibrium. The effect of the re-evaporation of raindrops at
the sampling site would be negligible because of the high humidity on Okinawa Island. Therefore, the observed negative correlation
between the Okinawa 17 O-excess and relative humidity suggests
insigniﬁcant inﬂuence of a raindrop evaporation process on Okinawa Island.
3.5. Observational humidity in the source oceans
To compare the relative humidity reconstructed from
O-excess, we calculate the relative humidity normalized to the
SST (hn ) in the moisture source oceans. We should note thathn reconstructed from 17 O-excess does not represent the common relative humidity; rather, it denotes the relative humidity
normalized to the saturation pressure at the SST in the oceanic
moisture source region. A combined ICOADS hn record in the moisture source region was constructed by connecting the hn values foreach season (Fig. 4a). On average, variability of the monthly meanvalues within a moisture source region based on the 3-day backward analysis (i.e., spatial variability of the temporal mean within
the region) is 9% (1σ ).
The hn values for the moisture source areas are similar to relative humidity data at Naha meteorological station, except for thoseduring the winter; the difference between the hn values in moisture source areas and relative humidity at the station reaches 10%.
During the wintertime, a very dry monsoon wind originates fromthe continent, and a warm Kuroshio Current supplies moisture to
the dry air. In fact, a very large latent heat ﬂux was observedin the East China Sea during the winter (Uemura et al., 2012).
17

Fig. 4. Reconstructed normalized humidity in the oceanic moisture source regions.
(a) Observed hn in the oceanic moisture source regions for the winter (blue), spring(green), summer (red), and autumn (brown). Relative humidity at Naha (dotted
purple). (b) The hn estimate from 17 O-excess in precipitation (red line) with uncertainty (red shaded area). The uncertainty was estimated based on uncertainty
of 18 α diff (i.e., 1.0096 ± 0.0018) and analytical error of 17 O-excess. The hn fromICOADS data set in the moisture source regions based on the 3-day backward trajectory analysis (black line) with uncertainties (black shaded area). (c) The same as(b) but for the hn from ICOADS data set in the moisture source regions were calculated based on the 10-day backward trajectory analysis (black line). (d) The same as(b) but the hn estimate from 17 O-excess in precipitation (red line) is corrected forother effects (precipitation, closure assumption and ocean water isotopic composition).

These unique conditions (i.e., dry air over a relatively warm ocean)results in very low hn values in the source region during the winter.
The hn values in moisture source regions based on 10-day
backward analysis (Fig. 4c) is very similar to those based on
3-day backward analysis (Fig. 4b). In addition, the values of hn ofmoisture source regions based on the different starting altitudes(Fig. S1) agree within ±1%. These results suggest that the hn estimate is not sensitive to the calculational conditions for backward
trajectory analysis.

Y. Uechi, R. Uemura / Earth and Planetary Science Letters 513 (2019) 20–28

3.6. Source humidity estimate based on evaporation model
We evaluate a consistency between the humidity reconstructedfrom 17 O-excess in precipitation and humidity in oceanic moisturesource regions. Based on a closure assumption (i.e., that vapor in
the boundary layer originates from evaporation only) (Merlivat andJouzel, 1979), the hn can be related to 17 O-excess in oceanic water
vapor (17 O-excess(v) ) as follows (Barkan and Luz, 2007):
17

O-excess(v) = − ln

18

0.529
αeq

18

0.518
αdiff
(1 − hn ) + hn

18 18
+ 0.528 ln αeq αdiff (1 − hn ) + hn

(2)where 18 α eq and 18 α diff respectively indicate equilibrium and diffusional fraction factors for 18 O/16 O. The 18 α diff was determined tobe 1.0096 ± 0.0018 based on observations of water vapor in theocean (Luz and Barkan, 2010; Uemura et al., 2010).
The sensitivity of reconstructed hn to α diff depends on absolute value of hn ; the uncertainty of hn reconstruction decreases inhigher humidity condition because of weaker contribution of diffusional fractionation. For example, the uncertainty of hn estimate
caused by that of α diff (i.e., ±0.0018) ranges from ±4% (at 81% ofhn ) to ±14% (at 38% of hn ) (±8% on average). Although 18 α eq depends on the temperature, this temperature dependence has little
inﬂuence on the reconstructed hn . For example, the estimates of hnvaried only by 1% when the values of 18 α eq changed from 1.00979
to 1.00897 (corresponding to SST changed from 20 to 30 ◦ C). Thus,
we calculated hn with a constant 18 α eq (at SST of 25 ◦ C) and withthe measured 17 O-excess in the precipitation using Eq. (2).
The hn estimates derived from the 17 O-excess data based on
Eq. (2) are shown in Fig. 4b. The hn reconstructed from 17 O-excess
data shows a high correlation with the combined hn record in
the moisture source areas based on the 3-day backward trajectory
analysis (slope = 0.74, R 2 = 0.60, p < 0.01). Although there is anoffset of hn (7% on average) between them, the seasonal amplitude(and its phase) of hn are consistent with each other within theirmutual uncertainty range.
A similarly high correlation is also found between the hn data
based on the 10-day backward trajectory analysis and the hn derived from 17 O-excess (R 2 = 0.48; Fig. 4c). These results suggestthat the hn reconstructed from the 17 O-excess in precipitation isconsistent with the hn in the oceanic moisture source area. We
should note, however, Eq. (2) estimates 17 O-excess of water vapor in the moisture source region. Other processes that may affect17
O-excess in precipitation will be discussed in next section.
3.7. Source humidity estimate corrected for other processes

precipitation at dewpoint temperature (12 ◦ C) is larger than that ofcorresponding vapor by 11 per meg. Thus, this minor seasonal amplitude of the precipitation effect (i.e., difference between winterand summer is 2 per meg) would not affect the seasonal amplitude of 17 O-excess of precipitation at the sampling site (difference
between winter and summer is 20 per meg on average). However,these results suggest that temperature effect may cause systematic
offset (ca. 9–11 per meg) between the vapor and precipitation.
Another potential bias of 17 O-excess evaporation model may becaused by the closure assumption used in the derivation of Eq. (2)(Merlivat and Jouzel, 1979). Only a few studies have investigatedthis problem on 17 O-excess, but an observation of d-excess in water vapor in the subtropical North Atlantic suggests that mixing
in the boundary layer may affect the negative correlation between
d-excess and hn (Benetti et al., 2015). A recent study on d-excess
suggested that the closure assumption is valid during strong largescale ocean evaporation (such an event is characterized by low hnof ca. 50%) but is most likely not fulﬁlled under high hn conditions (Aemisegger and Sjolte, 2018). A single-column isotopic
model suggests that the closure assumption results in lower 17 Oexcess in the boundary layer by 3 per meg due to vapor ﬂux fromunsaturated downdraft into the boundary layer (Risi et al., 2010).
Although this level of difference is within the analytical uncertainty, this effect also may add a systematic offset between theobserved hn and the hn reconstructed based on the closure assumption model.
Finally, 17 O-excess of the ocean water also should be considered. Eq. (2) is derived on the assumption that 17 O-excess ofthe ocean water is the same as that of VSMOW. A measurement of ocean surface water from the Paciﬁc and Atlantic oceans
showed that the 17 O-excess of ocean water with respect to VSMOW (17 O-excess(ocean/VSMOW) ) is −5 per meg (Luz and Barkan,2010). Since there is no spatial and temporal data set of 17 O-excessof the ocean water in the moisture source regions of this study, weused the averaged value of −5 per meg for correction.
Considering these factors, we re-evaluate the hn reconstruction
based on the 17 O-excess in precipitation. The 17 O-excess of vapor
correcting for closure assumption bias (closure = 3 per meg) and17
O-excess(ocean/VSMOW) can be written as follows:
17

O-excess(v_cor) = 17 O-excess(v) + closure+ 17 O-excess(ocean/VSMOW)
17

(3)
17

where O-excess(v_cor) indicates the corrected O-excess of vapor. Then, 17 O-excess of the initial precipitation (17 O-excess(p) ) isexpressed by the following:
17

Besides evaporation in the moisture source region, 17 O-excess
of precipitation can vary with the temperature of precipitation formation. A further increase of 17 O-excess is caused by the fact thatthe equilibrium fractionation slope of 0.529 is slightly higher thanthat of meteoric water line (0.528) (Luz and Barkan, 2010). This effect is larger at lower precipitation forming temperature. Luz andBarkan (2010) estimated that the 17 O-excess increases by 17 and23 per meg for precipitation forming at −10 and −40 ◦ C, respectively.
Here, we simply estimate an isotope ratio of initial small
amount of precipitation (R p0 ) formed under isotopic equilibriumwith surrounding vapor (i.e., R p0 = R v0 ·18 α eq ). The isotope ratio
of initial vapor (R v0 ) was obtained using the evaporation model(Eq. (2)). For example, under summer-time evaporation conditions(SST = 28 ◦ C and RH = 80%), the 17 O-excess of an initial precipitation at dewpoint temperature (24 ◦ C) is larger than that ofcorresponding vapor by 9 per meg. For winter-time evaporation
conditions (SST = 21 ◦ C and RH = 60%), the 17 O-excess in the 1st

25

O-excess(p) = 17 O-excess(v_cor) + prep .

(4)Here, the value of precipitation effect (prep ) ranges from 9 per meg(for summer) and 10 per meg (for spring and autumn) to 11 per meg(for winter).
The hn reconstruction based on Eqs. (3) and (4) are shown in
Fig. 4d. Seasonality and its amplitude are essentially the same as
the hn reconstruction based on Eq. (2). However, the absolute valueof hn shows an excellent agreement with the hn from ICOADS
observation. The average hn offset between the 17 O-excess based
estimate and the observation is only −1 %, which is smaller thanthe offset based on Eq. (2) (i.e., 7%). This result suggests that thepotential inﬂuences on the 17 O-excess of precipitation other than
the simple evaporation effect would not signiﬁcantly affect the accuracy of the hn reconstruction because the sum of the correction
factors is not large (7 to 9 per meg). Rather, the correction improves the accuracy of hn reconstruction.
Although we attempted to estimate the potential size of inﬂuences on the 17 O-excess other than evaporation, there are

26

Y. Uechi, R. Uemura / Earth and Planetary Science Letters 513 (2019) 20–28
17Fig. 5. Different deﬁnitions of 17 O-excess against δ  18 O. (a) 17 Oxs, deﬁned as thedifference between 17 Oxs(527) and 17 Oxs(528) . (b) Latitudes of te sampling locations.
Positive values indicate the Northern Hemisphere, and negative values indicate theSouthern Hemisphere. (c) 17 Oxs(528) (black symbols) and 17 Oxs(527) (red symbols) inrainwater and snow samples; also shown are Okinawa rainwater (black circle; thisstudy), Antarctic surface snow (asterisk; Landais et al., 2008), Antarctic surface snow
(hash mark; Pang et al., 2015, a shallow ice core drilled at the North Greenland
Eemian Ice Drilling (NEEM) site in Greenland (open square; Landais et al., 2012b),
rain and snow of diverse provenance (open circle; Luz and Barkan, 2010), tap waterin the United States (open triangle; Li et al., 2015), and rain and snow in the central
United States (black triangle; Tian et al., 2018). For the tap water data, tap water
data whose d-excess values are consistent with (within 5.2h) interpolated local
precipitation values were used.

still other factors such as; cloud type, condensation temperature, 17 O-excess in background atmosphere, and 17 O-excess inregional ocean surface water. To better constrain these factors andprocesses, further regional observations based on individual rain
events will be useful.
3.8. Robustness against different deﬁnitions
For the 17 O-excess deﬁnition of meteoric water, the δ 17 O–δ 18 O
slope of 0.528 has been widely adopted (Luz and Barkan, 2010;
Meijer and Li, 1998). Recently, Miller (2018) noted that theδ  17 O–δ  18 O slope of the global meteoric water line is reduced
from the common value of 0.528 to 0.5268–0.5270 after removing Antarctic data points (where the δ 18 O value is smaller
than −50h). Therefore, in temperate and tropical regions, theδ  17 O–δ  18 O slope should be signiﬁcantly smaller than 0.528.
To evaluate the impact of this hypothesized lower slope, we
calculate values of 17 O-excess with different slopes. For clarity, theO-excess with a smaller slope of 0.527 is denoted as 17 Oxs(527)(= δ  17 O − 0.527 × δ  18 O). In contrast, the commonly used 17 Oexcess calculated by a slope of 0.528 is denoted as 17 Oxs(528) onlyin this section and Fig. 5. The impacts of the different slopes on
17
O-excess are illustrated in Fig. 5. The difference between them,
namely, 17 Oxs (= 17 Oxs(527) − 17 Oxs(528) ), gradually expands by
ca. 1 per meg per 1h of δ 18 O as δ 18 O decreases (Fig. 5a and 5c).
The δ 18 O values decrease signiﬁcantly in polar regions (absolute latitude > 60◦ ; Fig. 5b). The absolute value of 17 O-excess inpolar regions is very sensitive to small changes in the slope, i.e.,17 Oxs is −50 per meg at a δ 18 O value of −50h. This sensitivity to the slope causes fundamental diﬃculties in interpreting theabsolute value of 17 Oxs(528) in polar regions. In contrast, in the region where δ 18 O is greater than −10h, 17 Oxs is smaller than
10 per meg, which is close to the typical analytical uncertainty
of 17 O-excess measurements. We should note that δ 18 O is greaterthan −10h in most tropical and subtropical regions (i.e., between
35◦ S and 35◦ N) (e.g., Bowen and Wilkinson, 2002). For example,
the average 17 Oxs of our observations in Okinawa is −6 per meg.
Therefore, this analysis shows that 17 Oxs(528) values in tropical andsubtropical regions are insensitive to changes in the slope and thus
constitute a reliable tracer for the hydrological cycle.
In addition to the impacts of different slopes, the overall trendof 17 Oxs(528) shown in Fig. 5c invokes a fundamental question regarding the global distribution of 17 Oxs(528) . Speciﬁcally, 17 Oxs(528)shows a clear increasing trend from 20 per meg to 50 per meg
when the δ 18 O values decrease from −10h to −40h. Interestingly, this trend is similar to water vapor observations at Alert,
Canada (Lin et al., 2013). Lin et al. (2013) interpreted that thisanomaly originated from stratospheric water vapor, although thisconclusion was criticized on the basis of its precision (Miller,2013); mathematically, 17 Oxs(528) increased gradually as the δ 18 O
values decreased simply because it was calculated against a slopeof 0.528 despite the fact that the δ  17 O–δ  18 O slope of the global
meteoric water line (excluding Antarctic data points) is lower than
0.528. Similarly, the strong anticorrelation between 17 Oxs(528) andδ 18 O found in Greenland (δ 18 O ranges from −38h to −28h;Landais et al., 2012b) and in the United States (δ 18 O ranges from
−5 to −25h; Li et al., 2015) will be reduced if one adopts a slopeof 0.527 instead of 0.528. These results suggest that the increasing
trend in 17 Oxs(528) alone is not strong evidence for stratospheric
input because of its sensitivity to small changes in the 17 O-excess
deﬁnition.
In polar regions, the 17 Oxs(528) of snow decreases along witha lower δ 18 O value. 17 Oxs(528) decreases in polar high plateau regions, where the δ 18 O value is lower than −50h. In fact, a verysmall 17 Oxs(528) (< −20 per meg) was observed at Vostok (whereδ 18 O < −50h) in Antarctica (Landais et al., 2012a). The mechanisms underlying this phenomenon are still unclear, but the inﬂuences of diffusional fractionation during snow formation (Landais
et al., 2012a) and the precipitation regime (Miller, 2018) have beensuggested. The presence of this local decreasing trend complicatesthe interpretation of Antarctic ice core data, particularly at remote inland sites (Winkler et al., 2012). This phenomenon remains
even after incorporating 17 Oxs(527) , suggesting that this local effectcannot be explained by the lower δ  17 O–δ  18 O slope. In addition,
17 Oxs reaches ca. −50 per meg at a δ 18 O value of −50h. This
indicates that absolute values of 17 O-excess in polar regions arehighly sensitive to its deﬁnition.
In summary, in regions with low δ 18 O values such as Antarctica,
small changes in the slope affect the absolute value of 17 Oxs(528) ,and thus, additional diﬃculties are expected during the interpretation of 17 Oxs(528) data. In contrast, the impact of uncertainty inthe slope is minimized in tropical and subtropical regions wherethe δ 18 O value is usually large (> −10h).

Y. Uechi, R. Uemura / Earth and Planetary Science Letters 513 (2019) 20–28

4. Conclusions
The 17 O-excess in precipitation on Okinawa Island showed aclear seasonal variation. The relative humidity normalized to the
SST (denoted as hn ) in the oceanic moisture source region wasreconstructed from the 17 O-excess in the precipitation using thesimple evaporation model. Interestingly, the reconstructed hn isconsistent with the hn observed in the oceanic moisture source
region. After correcting for the bias caused by closure assumption, the precipitation effect and 17 O-excess values of ocean-water,
the reconstructed hn shows a better agreement with the hn in theoceanic moisture source region. Furthermore, a sensitivity test revealed that the 17 O-excess values in most tropical and subtropicalregions will not be signiﬁcantly affected by different slope deﬁnitions for 17 O-excess because of its higher δ  18 O value. These results
suggest that the 17 O-excess in the precipitation on Okinawa Island is dominantly controlled by hn in the moisture source region
through variances in the strength of diffusional isotope fractionation. Therefore, the 17 O-excess in humid tropical and subtropicalregions is an important and unique tracer for investigating pastand present hydrogeological cycles because it provides a quantitative estimate of the relative humidity in the oceanic moisturesource region. The ﬁndings presented here also suggest that analyses of ﬂuid inclusions (e.g., water) in speleothems and/or 17 O in
calcite will be useful as a quantitative proxy for paleoclimate variations.
Acknowledgements
We thank the Okinawa Prefectural Institute of Health and Environment for sharing the rainwater samples. We also thank Makoto
Watanabe of Sanyo Furue Science Corporation for technical advice for Picarro analyzer. This research was supported by JSPS andMEXT KAKENHI Grant Numbers: JP15H01729 and JP17KK0012.
Appendix A. Supplementary material
Supplementary material related to this article can be found online at https://doi.org/10.1016/j.epsl.2019.02.012.
References
Aemisegger, F., Sjolte, J., 2018. A climatology of strong large-scale ocean evaporation
events. Part II: relevance for the deuterium excess signature of the evaporation
ﬂux. J. Climate 31, 7313–7336.
Affolter, S., Häuselmann, A.D., Fleitmann, D., Häuselmann, P., Leuenberger, M.,
2015. Triple isotope (δ D, δ 17 O, δ 18 O) study on precipitation, drip water andspeleothem ﬂuid inclusions for a Western Central European cave (NW Switzerland). Quat. Sci. Rev. 127, 73–89.
Aggarwal, P.K., Alduchov, O.A., Froehlich, K.O., Araguas-Araguas, L.J., Sturchio, N.C.,
Kurita, N., 2012. Stable isotopes in global precipitation: a uniﬁed interpretation
based on atmospheric moisture residence time. Geophys. Res. Lett. 39.
Angert, A., Cappa, C.D., DePaolo, D.J., 2004. Kinetic 17 O effects in the hydrologic cycle: indirect evidence and implications. Geochim. Cosmochim. Acta 68,
3487–3495.
Barkan, E., Luz, B., 2005. High precision measurements of 17 O/16 O and 18 O/16 O ratios in H2 O. Rapid Commun. Mass Spectrom. 19, 3737–3742.
Barkan, E., Luz, B., 2007. Diffusivity fractionations of H2 16 O/H2 17 O and H2 16 O/H2 18 O
in air and their implications for isotope hydrology. Rapid Commun. Mass Spectrom. 21, 2999–3005.
Barkan, E., Musan, I., Luz, B., 2015. High-precision measurements of δ 17 O and 17 Oexcess of NBS19 and NBS18. Rapid Commun. Mass Spectrom. 29, 2219–2224.
Benetti, M., Aloisi, G., Reverdin, G., Risi, C., Sèze, G., 2015. Importance of boundary
layer mixing for the isotopic composition of surface vapor over the subtropicalNorth Atlantic Ocean. J. Geophys. Res., Atmos. 120, 2190–2209.
Berman, E.S., Levin, N.E., Landais, A., Li, S., Owano, T., 2013. Measurement of δ 18 O,
δ 17 O, and 17 O-excess in water by off-axis integrated cavity output spectroscopy
and isotope ratio mass spectrometry. Anal. Chem. 85, 10392–10398.
Bony, S., Risi, C., Vimeux, F., 2008. Inﬂuence of convective processes on the isotopic composition (δ 18 O and δ D) of precipitation and water vapor in the tropics: 1. Radiative-convective equilibrium and Tropical Ocean–Global Atmosphere–
Coupled Ocean–Atmosphere Response Experiment (TOGA–COARE) simulations. J.
Geophys. Res. 113.

27

Bowen, G.J., Wilkinson, B., 2002. Spatial distribution of δ 18 O in meteoric precipitation. Geology 30.
Craig, H., 1961. Isotopic variations in meteoric waters. Science 133, 1702–1703.
Dansgaard, W., 1964. Stable isotopes in precipitation. Tellus 16, 436–468.
Freeman, E., Woodruff, S.D., Worley, S.J., Lubker, S.J., Kent, E.C., Angel, W.E., Berry,
D.I., Brohan, P., Eastman, R., Gates, L., Gloeden, W., Ji, Z., Lawrimore, J., Rayner,
N.A., Rosenhagen, G., Smith, S.R., 2017. ICOADS release 3.0: a major update to
the historical marine climate record. Int. J. Climatol. 37, 2211–2232.
Gupta, P., Noone, D., Galewsky, J., Sweeney, C., Vaughn, B.H., 2009. Demonstrationof high-precision continuous measurements of water vapor isotopologues inlaboratory and remote ﬁeld deployments using wavelength-scanned cavity ringdown spectroscopy (WS-CRDS) technology. Rapid Commun. Mass Spectrom. 23,
2534–2542.
IAEA, 2007. Reference sheet for reference material, GISP.
Jouzel, J., 2013. A brief history of ice core science over the last 50 yr. Clim. Past 9,
2525–2547.
Landais, A., Barkan, E., Luz, B., 2008. Record of δ 18 O and 17 O-excess in ice from
Vostok Antarctica during the last 150,000 years. Geophys. Res. Lett. 35, L02709.
Landais, A., Ekaykin, A., Barkan, E., Winkler, R., Luz, B., 2012a. Seasonal variations of17
O-excess and d-excess in snow precipitation at Vostok station, East Antarctica.
J. Glaciol. 58, 725–733.
Landais, A., Risi, C., Bony, S., Vimeux, F., Descroix, L., Falourd, S., Bouygues, A.,
2010. Combined measurements of 17 O-excess and d-excess in African monsoon
precipitation: implications for evaluating convective parameterizations. Earth
Planet. Sci. Lett. 298, 104–112.
Landais, A., Steen-Larsen, H.C., Guillevic, M., Masson-Delmotte, V., Vinther, B., Winkler, R., 2012b. Triple isotopic composition of oxygen in surface snow and water
vapor at NEEM (Greenland). Geochim. Cosmochim. Acta 77, 304–316.
Li, S., Levin, N.E., Chesson, L.A., 2015. Continental scale variation in 17 O-excess of
meteoric waters in the United States. Geochim. Cosmochim. Acta 164, 110–126.
Lin, Y., Clayton, R.N., Gröning, M., 2010. Calibration of δ 17 O and δ 18 O of international
measurement standards – VSMOW, VSMOW2, SLAP, and SLAP2. Rapid Commun.
Mass Spectrom. 24, 773–776.
Lin, Y., Clayton, R.N., Huang, L., Nakamura, N., Lyons, J.R., 2013. Oxygen isotope
anomaly observed in water vapor from Alert, Canada and the implication forthe stratosphere. Proc. Natl. Acad. Sci. USA 110, 15608–15613.
Luz, B., Barkan, E., 2010. Variations of 17 O/16 O and 18 O/16 O in meteoric waters.
Geochim. Cosmochim. Acta 74, 6276–6286.
Meijer, H.A.J., Li, W.J., 1998. The use of electrolysis for accurate δ 17 O and δ 18 O isotope measurements in water. Isot. Environ. Health Stud. 34, 349–369.
Merlivat, L., Jouzel, J., 1979. Global climatic interpretation of the deuterium–oxygen
18 relationship for precipitation. J. Geophys. Res. 84, 5029–5033.
Miller, M.F., 2013. Oxygen isotope anomaly not present in water vapor from Alert,
Canada. Proc. Natl. Acad. Sci. USA 110, E4567.
Miller, M.F., 2018. Precipitation regime inﬂuence on oxygen triple-isotope distributions in Antarctic precipitation and ice cores. Earth Planet. Sci. Lett. 481,
316–327.
Pang, H., Hou, S., Landais, A., Masson-Delmotte, V., Prie, F., Steen-Larsen, H.C., Risi, C.,
Li, Y., Jouzel, J., Wang, Y., He, J., Minster, B., Falourd, S., 2015. Spatial distributionof 17 O-excess in surface snow along a traverse from Zhongshan station to DomeA, East Antarctica. Earth Planet. Sci. Lett. 414, 126–133.
Passey, B.H., Hu, H., Ji, H., Montanari, S., Li, S., Henkes, G.A., Levin, N.E., 2014. Triple
oxygen isotopes in biogenic and sedimentary carbonates. Geochim. Cosmochim.
Acta 141, 1–25.
Pfahl, S., Wernli, H., 2008. Air parcel trajectory analysis of stable isotopes in water
vapor in the eastern Mediterranean. J. Geophys. Res., Atmos. 113.
Risi, C., Landais, A., Bony, S., Jouzel, J., Masson-Delmotte, V., Vimeux, F., 2010. Understanding the 17 O-excess glacial–interglacial variations in Vostok precipitation.
J. Geophys. Res. 115.
Schoenemann, S.W., Schauer, A.J., Steig, E.J., 2013. Measurement of SLAP2 and GISPδ 17 O and proposed VSMOW-SLAP normalization for δ 17 O and 17 O-excess. Rapid
Commun. Mass Spectrom. 27, 582–590.
Schoenemann, S.W., Steig, E.J., Ding, Q., Markle, B.R., Schauer, A.J., 2014. Triple
water-isotopologue record from WAIS Divide, Antarctica: controls on glacial–interglacial changes in 17 O excess of precipitation. J. Geophys. Res., Atmos. 119,8741–8763.
Sodemann, H., Schwierz, C., Wernli, H., 2008. Interannual variability of Greenland
winter precipitation sources: lagrangian moisture diagnostic and North Atlantic
Oscillation inﬂuence. J. Geophys. Res., Atmos. 113.
Steen-Larsen, H.C., Masson-Delmotte, V., Hirabayashi, M., Winkler, R., Satow, K., Prié,F., Bayou, N., Brun, E., Cuffey, K.M., Dahl-Jensen, D., Dumont, M., Guillevic, M.,
Kipfstuhl, S., Landais, A., Popp, T., Risi, C., Steffen, K., Stenni, B., Sveinbjörnsdottír,
A.E., 2014a. What controls the isotopic composition of Greenland surface snow?
Clim. Past 10, 377–392.
Steen-Larsen, H.C., Sveinbjörnsdottir, A.E., Peters, A.J., Masson-Delmotte, V.,
Guishard, M.P., Hsiao, G., Jouzel, J., Noone, D., Warren, J.K., White, J.W.C., 2014b.
Climatic controls on water vapor deuterium excess in the marine boundary layerof the North Atlantic based on 500 days of in situ, continuous measurements.
Atmos. Chem. Phys. 14, 7741–7756.
Steig, E.J., Gkinis, V., Schauer, A.J., Schoenemann, S.W., Samek, K., Hoffnagle, J., Dennis, K.J., Tan, S.M., 2014. Calibrated high-precision 17 O-excess measurements

28

Y. Uechi, R. Uemura / Earth and Planetary Science Letters 513 (2019) 20–28

using cavity ring-down spectroscopy with laser-current-tuned cavity resonance.
Atmos. Meas. Tech. 7, 2421–2435.
Stein, A.F., Draxler, R.R., Rolph, G.D., Stunder, B.J.B., Cohen, M.D., Ngan, F., 2015.
NOAA’s HYSPLIT atmospheric transport and dispersion modeling system. Bull.
Am. Meteorol. Soc. 96, 2059–2077.
Tian, C., Wang, L., Kaseke, K.F., Bird, B.W., 2018. Stable isotope compositions δ 2 H,
δ 18 O and δ 17 O of rainfall and snowfall in the central United States. Sci. Rep. 8,
6712.
Touzeau, A., Landais, A., Stenni, B., Uemura, R., Fukui, K., Fujita, S., Guilbaud, S.,
Ekaykin, A., Casado, M., Barkan, E., Luz, B., Magand, O., Teste, G., Le Meur, E.,
Baroni, M., Savarino, J., Bourgeois, I., Risi, C., 2016. Acquisition of isotopic composition for surface snow in East Antarctica and the links to climatic parameters.
Cryosphere 10, 837–852.
Uemura, R., Barkan, E., Abe, O., Luz, B., 2010. Triple isotope composition of oxygenin atmospheric water vapor. Geophys. Res. Lett. 37.
Uemura, R., Matsui, Y., Yoshimura, K., Motoyama, H., Yoshida, N., 2008. Evidence of
deuterium excess in water vapor as an indicator of ocean surface conditions.
J. Geophys. Res. 113, D19114.

Uemura, R., Motoyama, H., Masson-Delmotte, V., Jouzel, J., Kawamura, K., GotoAzuma, K., Fujita, S., Kuramoto, T., Hirabayashi, M., Miyake, T., Ohno, H., Fujita,
K., Abe-Ouchi, A., Iizuka, Y., Horikawa, S., Igarashi, M., Suzuki, K., Suzuki, T., Fujii,Y., 2018. Asynchrony between Antarctic temperature and CO2 associated withobliquity over the past 720,000 years. Nat. Commun. 9, 961.
Uemura, R., Nakamoto, M., Asami, R., Mishima, S., Gibo, M., Masaka, K., Jin-Ping, C.,
Wu, C.-C., Chang, Y.-W., Shen, C.-C., 2016. Precise oxygen and hydrogen isotope
determination in nanoliter quantities of speleothem inclusion water by cavity
ring-down spectroscopic techniques. Geochim. Cosmochim. Acta 172, 159–176.
Uemura, R., Yonezawa, N., Yoshimura, K., Asami, R., Kadena, H., Yamada, K., Yoshida,N., 2012. Factors controlling isotopic composition of precipitation on Okinawa
Island, Japan: implications for paleoclimate reconstruction in the East Asian
Monsoon region. J. Hydrol. 475, 314–322.
Winkler, R., Landais, A., Sodemann, H., Dümbgen, L., Prié, F., Masson-Delmotte, V.,
Stenni, B., Jouzel, J., 2012. Deglaciation records of 17 O-excess in East Antarctica:
reliable reconstruction of oceanic normalized relative humidity from coastal
sites. Clim. Past 8, 1–16.