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A Review of Antarctic Surface Snow Isotopic Composition : Observations, Atmospheric Circulation, and Isotopic Modeling

TL;DR: In this article, a database of surface Antarctic snow isotopic composition is constructed using available measurements, with an estimate of data quality and local variability, and the capacity of theoretical isotopic, regional, and general circulation atmospheric models to reproduce the observed features and assess the role of moisture advection in spatial deuterium excess fluctuations.
Abstract: A database of surface Antarctic snow isotopic composition is constructed using available measurements, with an estimate of data quality and local variability. Although more than 1000 locations are documented, the spatial coverage remains uneven with a majority of sites located in specific areas of East Antarctica. The database is used to analyze the spatial variations in snow isotopic composition with respect to geographical characteristics (elevation, distance to the coast) and climatic features (temperature, accumulation) and with a focus on deuterium excess. The capacity of theoretical isotopic, regional, and general circulation atmospheric models (including “isotopic” models) to reproduce the observed features and assess the role of moisture advection in spatial deuterium excess fluctuations is analyzed.

Summary (2 min read)

1. Introduction

  • Regional Antarctic temperature reconstructions are also essential for the comparison between observed past climatic changes and simulations performed by AGCMs, conducted only for the inland East Antarctic plateau (Masson-Delmotte et al. 2006).
  • To analyze the stable isotopic composition of snowfall in a model framework that is compatible with the observed climatology, several methods must be combined.

2. A database of Antarctic snow isotopic composition

  • A. Sampling sites and related documentation Table 2 presents the list and references of the various sources of information compiled to produce the full Antarctic database (available as an Excel file online at http://www.lsce.ipsl.fr/Pisp/24/valerie.masson-delmotte. html).
  • Annual mean surface air or firn temperatures are available for only 811 sites; the situation is even more restricted for annual mean accumulation data, available only for 322 sites (Fig. 2).
  • The first two criteria are expected to reflect the quality of the isotopic measurements and sample preservation; the last three criteria have been defined with respect to the temporal scale and resolution of the samples, with the purpose of building “climatologies” of surface snow isotopic composition.
  • The authors now describe the range of variability of D, 18O, and deuterium excess data, both spatially (from site to site) and temporally (within one site when several measurements have been averaged to produce the local average value).
  • The amplitude of local D range (difference between maximum and minimum values of individual sample measurements at one location) varies between 4.9‰ and 262.3‰, with a mean range of 74.1‰.

D and 88% of the 18O spatial variance:

  • The observations show isotopic values that are less depleted than the calculation (positive anomalies) on the flanks of the ice sheet (at elevations from 1000 to 2000 m) and inland West Antarctica, whereas they show isotopic values that are more depleted than the calculation (negative anomalies) in the central Antarctic Peninsula and the central East Antarctic plateau.
  • To assess the spatial variations of this slope, the authors have developed a methodology to estimate local slopes.
  • The distribution of deuterium excess as a function of D (Fig. 6d) now relies on 789 data points, including new traverse data available from the coast to the interior of East Antarctica and 269 data points from the Taylor Valley in the Dry Valleys (with many negative deuterium excess values).

In the Lambert Glacier area, deuterium excess values

  • Atmospheric models can be used to analyze the vertical moisture advection to Antarctica (see section 3) and test this hypothesis.
  • The observed deuterium excess spatial distribution also reflects changes in the D– 18O slope depending on the range of isotopic values (Fig. 4).
  • These slope uncertainties have been obtained from a Monte Carlo method using 1000 random subsets.

7.30‰ (‰) 1 are observed in central East Antarctic ice cores (Vimeux et al. 1999; Stenni et al. 2001).

  • Different moisture origins at coastal versus inland locations should influence the distribution of deuterium excess, but also 18O, D, and their relationships to local climatic parameters.
  • Changes in isotope– temperature slopes between locations may be related to atmospheric transport paths.
  • In fact, such spatial slopes very likely include the combined effects of distillation, including temperature gradients between source and site temperatures, and equilibrium fractionation effects along different ranges of temperatures.
  • Isotopic models are used in the next section to assess the relative weight and role of these different physical processes on the Antarctic snow isotopic composition.

3. Model–data comparisons

  • The authors also analyze the capability of AGCMs to simulate this observed distribution.
  • The isotopic AGCMs offer the advantage of consistent simulations of climate and isotopic processes, but make it difficult to isolate the impact of each process on the isotopic composition of precipitation (Table 1).
  • Diagnostic of the fraction of simulated fifth-generation Pennsylvania State University (PSU)–National Center for Atmospheric Research (NCAR) Mesoscale Model (MM5) annual precipitation that is removed from the surface by sublimation (Bromwich et al. 2004). rence) condensation temperature, estimated by the temperature at the vertical level of the maximum condensed moisture (Helsen et al. 2007).
  • The model–data comparison therefore points to the following two systematic model biases: (i) a lack of isotopic depletion, even in AGCMs simulating a correct range of Antarctic surface temperature, and (ii) an underestimation of moisture supply to inland Antarctica (specifically at temperatures below 30°C).

4. Conclusions and perspectives

  • The authors compilation of surface Antarctic snow composition provides better spatial coverage than earlier studies, although it is still strongly biased toward East Antarctic locations.
  • Systematic measurements of water vapor and snow isotopic composition should allow us to disentangle the effect of depositional and postdepositional processes.
  • Intensive efforts based on accumulation histories derived from ice cores suggest that, despite a warming detected in winter tropospheric temperature in Antarctica during the past decades (Turner et al. 2006), there is no significant change in Antarctic accumulation since the International Geophysical Year in 1957–58 (Monaghan et al. 2006).
  • This database confirms earlier findings regarding the spatial variability of the isotope distribution in relation to geographical parameters (latitude, distance from the coast, and elevation).
  • It shows regional signatures, with variations mostly within 20%–.

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A Review of Antarctic Surface Snow Isotopic Composition: Observations, Atmospheric
Circulation, and Isotopic Modeling*
V. MASSON-DELMOTTE,
a
S. HOU,
b
A. EKAYKIN,
c
J. JOUZEL,
a
A. ARISTARAIN,
d
R. T. BERNARDO,
e
D. BROMWICH,
f
O. CATTANI,
a
M. DELMOTTE,
a
S. FALOURD,
a
M. FREZZOTTI,
g
H. GALLÉE,
h
L. GENONI,
i
E. ISAKSSON,
j
A. LANDAIS,
a,k
M. M. HELSEN,
l
G. HOFFMANN,
a
J. LOPEZ,
m
V. MORGAN,
n
H. MOTOYAMA,
o
D. NOONE,
p
H. OERTER,
q
J. R. PETIT,
h
A. ROYER,
a
R. UEMURA,
o
G. A. SCHMIDT,
r
E. SCHLOSSER,
s
J. C. SIMÕES,
e
E. J. STEIG,
t
B. STENNI,
i
M. STIEVENARD,
a
M. R. VAN DEN BROEKE,
l
R. S. W. VAN DE WAL,
l
W. J. VAN DE BERG,
l
F. VIMEUX,
a,u
J. W. C. WHITE
v
a
Laboratoire des Sciences du Climat et de l’Environnement, IPSL/CEA-CNRS-UVSQ, Saclay, Gif-sur-Yvette, France
b
Laboratory of Cryosphere and Environment, Chinese Academy of Sciences, Lanzhou, China
c
Arctic and Antarctic Research Institute, St. Petersburg, Russia
d
Laboratorio de Estratigrafía Glaciar y Geoquímica del Agua y de la Nieve, Instituto Antártico Argentino, Mendoza, Argentina
e
Nucleo de Pesquisas Antarcticas e Climaticas, Departmento de Geografia, Instituto de Geociencias, Universidade Federal do Rio
Grande do Sul, Porto Alegre, Brazil
f
The Ohio State University, Columbus, Ohio
g
ENEA, Rome, Italy
h
Laboratoire de Glaciologie et de Géophysique de l’Environnement, CNRS-Université Joseph Fourier, Saint Martin d’Hères, France
i
Department of Geological, Environmental and Marine Sciences, University of Trieste, Trieste, Italy
j
Norwegian Polar Institute, Tromsø´, Norway
k
Earth Science Institute, Hebrew University, Jerusalem, Israel
l
Institute for Marine and Atmospheric Research, Utrecht University, Utrecht, Netherlands
m
Departamento de Geologica y Geoquimica, Universidad Autonoma de Madrid, Madrid, Spain
n
Antarctic Climate and Ecosystems CRC, and Australian Antarctic Division, Hobart, Australia
o
National Institute of Polar Research, Research Organization of Information and Systems, Tokyo, Japan
p
Department of Atmospheric and Oceanic Sciences, and Cooperative Institute for Research in Environmental Sciences, University of
Colorado, Boulder, Colorado
q
Alfred-Wegener-Institute für Polar und Meeresforschung, Bremerhaven, Germany
r
NASA GISS, New York, New York
s
Institute of Meteorology and Geophysics, University of Innsbruck, Innsbruck, Austria
t
Department of Earth and Space Sciences, University of Washington, Seattle, Washington
u
UR Greatice, IRD, Paris, France
v
INSTAAR, Boulder, Colorado
(Manuscript received 6 July 2007, in final form 27 November 2007)
ABSTRACT
A database of surface Antarctic snow isotopic composition is constructed using available measurements,
with an estimate of data quality and local variability. Although more than 1000 locations are documented,
the spatial coverage remains uneven with a majority of sites located in specific areas of East Antarctica. The
database is used to analyze the spatial variations in snow isotopic composition with respect to geographical
characteristics (elevation, distance to the coast) and climatic features (temperature, accumulation) and with
a focus on deuterium excess. The capacity of theoretical isotopic, regional, and general circulation atmo-
spheric models (including “isotopic” models) to reproduce the observed features and assess the role of
moisture advection in spatial deuterium excess fluctuations is analyzed.
* European Project for Ice Coring in Antarctica Publication Number 188 and Laboratoire des Sciences du Climat et l’Environnement
Contribution Number 2739.
Corresponding author address: Valérie Masson-Delmotte, Laboratoire des Sciences du Climat et de l’Environnement, IPSL/CEA-
CNRS-UVSQ, UMR 1572, Bat 701, L’Orme des Merisiers CEA, Saclay, 91 191 Gif-sur-Yvette CEDEX, France.
E-mail: valerie.masson@cea.fr
1J
ULY 2008 M A S SON-DELMOTTE ET AL. 3359
DOI: 10.1175/2007JCLI2139.1
© 2008 American Meteorological Society
JCLI2139

1. Introduction
Since the 1950s, it has been observed that the stable
isotopic composition of precipitation in the mid- and
high latitudes is related to air temperature (Dansgaard
1953; Epstein and Mayeda 1953; Craig 1961). In Ant-
arctica (Fig. 1), surface snow was sampled along
traverses to inland stations and firn temperature mea-
surements were used as indicators of annual mean sur-
face temperature (Epstein et al. 1963). Early studies
were conducted to determine the spatial relationship
between precipitation isotopic composition and local
temperature (Lorius et al. 1969).
Assuming that this relationship remains valid over
time, these calibrations were then used as an isotopic
thermometer to quantify past changes in temperature
based on the stable isotopic composition of deep ice
cores, such as the recently obtained Eupropean Project
for Ice Coring in Antarctica (EPICA) ice cores drilled
at Dome C (DC; EPICA Community Members 2004)
and in Dronning Maud Land (DML; EPICA Commu-
nity Members 2006). In Greenland, the use of the spa-
tial isotopetemperature slope has been challenged by
alternative paleothermometry methods, such as the in-
version of the borehole temperature profile (Cuffey et
al. 1992; Johnsen et al. 1995), and the thermal and
gravitational diffusion of air in the firn arising during
abrupt climate changes (Severinghaus et al. 1998; Lang
et al. 1999; Landais et al. 2004a,b,c).
In central East Antarctica, inversion of the borehole
temperature profiles is problematic because of the low
accumulation rates (Salamatin et al. 1998). Because
Antarctic climate changes are less rapid than in Green-
land, the gas fractionation method is problematic and
cannot be used easily to quantify past temperature
changes (Caillon et al. 2001; Landais et al. 2006). How-
ever, the stable isotope profiles derived from East Ant-
arctic ice cores can be directly used to estimate past
changes in accumulation through relationships between
stable isotopes, air temperature, and saturation vapor
pressure that are included in inversed glaciological dat-
ing methods (Parrenin et al. 2001). The dating of deep
ice cores itself, when constrained by age markers, can
be used to assess the stability of the isotopetempera-
ture relationship back in time. When applied to inland
Antarctic sites, such as Vostok (Parrenin et al. 2001),
Dome Fuji (Watanabe et al. 2003), or EPICA Dome C
(EPICA Community Members 2004), inverse methods
suggest that the present-day-observed isotopetemper-
ature slopes remain valid for past periods within 20%
30%, consistent with estimates provided by atmo-
spheric general circulation models (AGCMs) (Jouzel et
al. 2003).
Obtaining past temperature reconstructions together
with a precise estimate of their uncertainties remains
critical for the understanding of the natural pacing of
Antarctic temperature (and accumulation) changes. A
recent synthesis effort conducted over the past 200 yr
using well-dated ice cores has revealed strong interan-
nual and decadal variability, with antiphase behavior
between the Antarctic Peninsula and the inland sites,
and the impact of the Southern Hemisphere (SH) an-
FIG. 1. Map of Antarctic topography showing (left) the names of different geographical sectors mentioned in the text and (right)
the main deep ice core sites together with the main ice divide.
3360 JOURNAL OF CLIMATE VOLUME 21

nular mode on Antarctic temperature variability
(Schneider et al. 2006), together with the variability
associated with ENSO (Schneider and Noone 2007).
The Antarctic-scale coherence of temperature change
remains uncertain at lower frequencies. A stack of five
central Antarctic ice cores stable isotope records also
suggests a small magnitude (0.2°C) of common cen-
tennial-scale temperature variability (Goosse et al.
2004). Regional Antarctic temperature and accumula-
tion reconstructions are essential for forcing Antarctic
ice sheet models and for understanding the Antarctic
ice sheet mass balance and dynamical reaction to
changing climate and sea level. Because stable isotope
records may be affected by changes in moisture origin,
syntheses of stable isotope records should be per-
formed over areas with similar moisture origins
(Reijmer et al. 2002). Regional Antarctic temperature
reconstructions are also essential for the comparison
between observed past climatic changes and simula-
tions performed by AGCMs, conducted only for the
inland East Antarctic plateau (Masson-Delmotte et al.
2006).
In parallel, the factors controlling the isotopic com-
position of Antarctic snowfall have been analyzed
based on a hierarchy of modeling approaches (Table 1).
Distillation models calculate the theoretical fraction-
ation that occurs along a cooling path with prescribed
initial evaporation and condensation conditions. Such
models have been used to assess the impact of equilib-
rium and kinetic fractionation processes on the snowfall
isotopic composition (Merlivat and Jouzel 1979; Jouzel
and Merlivat 1984). The second-order isotopic param-
eter deuterium excess d
D 8
18
O (Dansgaard
1964) is expected to be highly sensitive to kinetic effects
occurring either during evaporation at the ocean sur-
face or during atmospheric transport (e.g., reevapora-
tion of droplets or ice crystal formation). The observed
high deuterium excess values of inland Antarctic snow
cannot be simulated without taking into account kinetic
fractionation in supersaturation conditions over ice
crystals (Jouzel and Merlivat 1984; Salamatin et al.
2004). Sensitivity tests conducted with distillation mod-
els suggest that spatial variations of deuterium excess in
Antarctica may reflect, at least partly, different mois-
ture origins (Ciais and Jouzel 1994; Ciais et al. 1995;
Kavanaugh and Cuffey 2003; Masson-Delmotte et al.
2004).
AGCMs equipped with the explicit representation of
water-stable isotopes (Joussaume et al. 1984; Jouzel et
al. 1987b, 1991; Hoffmann et al. 2000) allow us to dis-
entangle the different factors involved in the spatial
(Brown and Simmonds 2004; Schmidt et al. 2005), sea-
sonal (Koster et al. 1992; Delmotte et al. 2000), inter-
annual (Werner et al. 2001; Werner and Heimann 2002;
Noone and Simmonds 2002a), or glacialinterglacial
changes (Delaygue et al. 2000) in Antarctic snow iso-
topic composition. They offer the advantage of a con-
sistent frame where tracers can be used to tag moisture
of different geographical origins (Koster et al. 1986;
Delaygue et al. 2000).
From these modeling efforts, it appears that the key
factors controlling the observed distribution of stable
isotopes in Antarctic snow are related to spatial
changes of the integrated condensation temperature
(including changes along the vapor trajectory, vertical
changes, and the intermittency of snowfall days), and
the origin of moisture (transported either at different
elevations or from different geographical areas). In
principle, condensation temperature during snowfall
episodes should be the relevant climatic parameter
used to analyze the spatial distribution of stable iso-
topes. Because only very few records of Antarctic con-
densation temperature are available, inversion tem-
perature has been used as a surrogate for condensation
temperature (Jouzel and Merlivat 1984). A detailed
study for Vostok (Ekaykin 2003) confirmed the validity
of this assumption for central Antarctica. However, this
study highlighted that most of the local accumulation
does not arise from cloud condensation, but from clear-
sky deposition of diamond dust. Until now, the com-
parison between AGCMs and isotopic data has not
been focused on the different types of precipitation.
Biases of the simulated spatial distribution for the
Antarctic surface air temperature range and of the
amount or origin of snowfall can induce difficulties in
the comparison of AGCM results with Antarctic isoto-
pic data. To analyze the stable isotopic composition of
snowfall in a model framework that is compatible with
the observed climatology, several methods must be
combined. For example, background fields of transport
that are more consistent with observations can be pro-
vided by nudging AGCMs with reanalyses (Yoshimura
et al. 2004; Noone 2006). Regional atmospheric models
can also be used to simulate local features of the Ant-
arctic atmospheric circulation and to analyze the factors
controlling the regional origin of Antarctic moisture.
Atmospheric reanalyses are used to calculate back
trajectories for individual Antarctic snowfall events.
Along the back trajectories, distillation models can be
implemented to estimate the snowfall isotopic compo-
sition (Helsen et al. 2007). Because the backward tra-
jectories generally do not capture the evaporation pro-
cess in the moisture source areas, monthly mean fields
of atmospheric water vapor isotopic composition simu-
lated by general circulation models have been used to
initialize vapor isotopic composition for trajectory cal-
1JULY 2008 M A S SON-DELMOTTE ET AL. 3361

TABLE 1. Hierarchy of modeling approaches used to analyze the processes responsible for the isotopic composition of Antarctic
snowfall.
Method References Advantages Limitations
Rayleigh or mixed phase
distillation model
Jouzel and Merlivat (1984),
Jouzel (1986),
Fisher (1990), Ciais and
Jouzel (1994), Kavanaugh
and Cuffey (2003), and
Salamatin et al. (2004)
Key microphysical processes
represented
Assumption on initial evaporation
conditions (closure equation or
iso-AGCM water vapor fields)
Ability to perform sensitivity tests
on different aspects of the
fractionation along the water
cycle path (evaporation,
supersaturation, etc.)
Assumption on the relationship
between condensation and
surface temperature
Poor representation of convection
processes (not a key limitation
for inland Antarctica)
Atmospheric general
circulation models
equipped with the
explicit modeling of
water-stable isotopes
Joussaume et al. (1984),
Jouzel et al. (1987b),
Hoffmann et al. (1998,
2000), Werner and
Heimann (2002), Noone
and Simmonds (1998), and
Schmidt et al. (2005)
Intrinsic model coherency Potential biases in model
climatologies, especially in
Antarctica
Full coupling between
meteorological conditions and
distillation
Limitations resulting from model
resolution and adaptation of
parameterizations for
Antarctica (katabatic winds,
boundary layer processes,
stratospheric processes, cloud
microphysics)
Possibility to explore the temporal
stability of spatial relationships
in response to various climate
forcings
Difficult to isolate the relative role
of different processes (moisture
origin, trajectory, condensation,
etc.)
Identification of synoptic
weather characteristics
and back trajectories for
snowfall events using
atmospheric reanalyses
Reijmer et al. (2002) and
Schlosser et al. (2004)
Realistic synoptic framework Difficult to isolate the relative role
of different processes (moisture
origin, trajectory, condensation,
etc.) on final precipitation
isotopic composition
Possibility to relate clusters of
snowfall events to synoptic
weather systems using their
isotopic composition
Difficult to follow moisture
transport in the back trajectories
Simple isotopic model
calculations along back
trajectories using
AGCM water vapor
climatological
distribution
Helsen et al. (2007) Quantify the impact of airmass
origins on final moisture
isotopic composition
Possible incoherencies between
iso-AGCM water vapor isotopic
composition fields and back
trajectories from reanalyses
No hypothesis on condensation
temperature (derived from
reanalyses)
Limited representation of
convective processes
Nudging of iso-AGCMs
with reanalyses
Noone (2006) Analysis of model results in a
dynamical framework coherent
with observations
See section on iso-AGCM
regarding AGCM limitations
Regional atmospheric
models nudged with
reanalyses
Gallee et al. (2001),
Bromwich et al. (2004),
and van den Broeke and
van Lipzig (2005)
Good representation of key
processes relevant for Antarctic
precipitation (cloud
microphysics, boundary layer,
postdepositional effects)
Difficult to follow moisture
transport
Difficult to isolate the relative role
of different processes (moisture
origin, trajectory, condensation,
etc.) on final precipitation
isotopic composition
Regional atmospheric
models with the explicit
modeling of stable
isotopes
Sturm et al. (2005) Advantages of mesoscale models
with the coherency between
atmospheric dynamics and
isotopes of water
Not yet achieved for Antarctica
3362 JOURNAL OF CLIMATE VOLUME 21

culations (Helsen et al. 2006). Backward air trajectories
calculated for different Antarctic areas (Reijmer et al.
2002; Helsen et al. 2006) showed different moisture
transport paths for coastal areas, where seasonal con-
vection and cyclonic activity play a large role, and in-
land sites, where clear-sky precipitation may be a dom-
inant contribution to local snowfall (Ekaykin 2003).
Parallel with these improvements on the modeling
side, intensive field campaigns have been carried out in
various sectors of Antarctica, including coordinated in-
ternational traverses and presite surveys in search of
optimal deep-drilling sites (Table 2). In this work, we
have compiled a database of the available measure-
ments of snowfall, surface snow, or firn core isotopic
composition, taking into account their local variability.
This database predominantly includes published mea-
surements of Antarctic snow isotopic composition, and
some unpublished data (Table 2) prior to the new field
campaigns planned during the fourth International Po-
lar Year.
The second section describes the various datasets,
the quality control methodology, and the assessment of
uncertainties, as well as the resulting spatial distribu-
tion of Antarctic snow-stable isotopic composition. The
third section is focused on the comparison between
these observations and a variety of model results based
on simple isotopic models, regional atmospheric mod-
els, and isotopic AGCMs. The main outcomes of the
paper and suggested ways forward are presented in the
conclusions.
2. A database of Antarctic snow isotopic
composition
a. Sampling sites and related documentation
Table 2 presents the list and references of the various
sources of information compiled to produce the full
Antarctic database (available as an Excel file online at
http://www.lsce.ipsl.fr/Pisp/24/valerie.masson-delmotte.
html). When available, we have included geographical
information on the sampling location, such as annual
mean temperature (estimated either from firn tempera-
ture measurements or automatic weather station sur-
face air monitoring), latitude, longitude, and elevation
(Fig. 2). In some cases, estimates of local accumulation
rates are available, based on the identification of an-
nual layers and reference horizons (e.g., Frezzotti et al.
2005). To quantify the continentality of the sites, we
have estimated the horizontal distance to the nearest
coast using the Antarctic coastline (this measurement
may not reflect the distance along moisture trajectories,
which is important for isotope physics). We have not
included error bars on the estimates of annual mean
temperature and accumulation rate because of a lack of
consistent methodologies to evaluate these uncertain-
ties.
The surface snow isotopic composition has been
measured from direct precipitation sampling at a few
sites [Global Network for Isotopes in Precipitation
(GNIP) stations from the following International
Atomic Energy Agency (IAEA) stations: Neumayer,
Dumont dUrville, Vostok, and Dome Fuji] over vary-
ing durations, sometimes over 1 yr (Motoyama et al.
2005; Fujita and Abe 2006) or, for Neumayer, continu-
ously since 1981 (Schlosser et al. 2004). Most surface
snow samples have been collected along traverses con-
ducted by individual groups or coordinated within the
International Trans-Antarctic Scientific Expeditions
(ITASE; Mayewski et al. 2005).
Surface snow-sampling procedures differ signifi-
cantly from one site to another. In some cases, shallow
snow cores or pits, typically 1 m deep, were sampled
and one or several measurements were performed. In
other cases, longer firn or ice cores have been analyzed
with a subannual resolution. The database includes a
description of the depth range and, if available, the
temporal range (dating). In places where deep firn or
ice cores have been drilled, meteorological data and
detailed snow measurements are available. In some
cases, there is no seasonal resolution either because of
the low accumulation rates or the crude measurement
resolution.
Finally, for each location we have reported the snow
isotopic composition (
D,
18
O, and deuterium excess
d), in per mille () with respect to the Vienna Standard
Mean Ocean Water (V-SMOW). When more than five
measurements were performed at the same location
(corresponding either to detailed measurements on a
firn profile or to seasonal samples of snowfall), we have
also included basic statistics (number, mean, maximum,
minimum values, and standard deviation of the mea-
surements) in the table. The country where the mea-
surements were performed is also indicated.
The final database includes 1279 locations, out of
which 938 have
D measurements, 1125 have
18
O
measurements, and 794 have both isotopes, making it
possible to calculate the deuterium excess (Fig. 3). For
each site, deuterium excess values were calculated from
individual measurements of
D and
18
O conducted on
the same samples. Note that for each site we have cal-
culated an average of all
D data available, an average
of all
18
O data available, and an average of deuterium
excess data (which may be on a restricted subset of data
for which both isotopes have been measured). There-
fore, the reported deuterium excess is not systemati-
cally identical to
D 8
18
O calculated from the mean
1JULY 2008 M A S SON-DELMOTTE ET AL. 3363

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Cites background from "A Review of Antarctic Surface Snow ..."

  • ...…atmospheric distillation and isotopic depletion 233 leading to a strong correlation (R2=0.9) on the Antarctic plateau between near surface temperature 234 and 18O of precipitation or surface snow along transects (Touzeau, et al., 2016; Stenni et al., 2016; 235 Masson-Delmotte et al., 2008)....

    [...]

  • ...The water vapor 301 advected by these strong continental winds is characterized by low 18O and high d-excess since 302 surface snow 18O has been shown to decrease and d-excess to increase from the coast to inland 303 Antarctica (e.g. Masson-Delmotte et al., 2008; Touzeau et al., 2016)....

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Journal ArticleDOI
TL;DR: The RICE17 chronology as discussed by the authors is a composite chronology combining annual layer interpretations, gas synchronization, and firn modeling strategies in different sections of the core, and is based on the gas age constraints and the ice age-gas age offset estimated by a firn densification model.
Abstract: . In 2013, an ice core was recovered from Roosevelt Island in the Ross Sea, Antarctica, as part of the Roosevelt Island Climate Evolution (RICE) project. Roosevelt Island is located between two submarine troughs carved by paleo-ice-streams. The RICE ice core provides new important information about the past configuration of the West Antarctic Ice Sheet and its retreat during the most recent deglaciation. In this work, we present the RICE17 chronology and discuss preliminary observations from the new records of methane, the isotopic composition of atmospheric molecular oxygen (δ18O-Oatm), the isotopic composition of atmospheric molecular nitrogen (δ15N-N2) and total air content (TAC). RICE17 is a composite chronology combining annual layer interpretations, gas synchronization, and firn modeling strategies in different sections of the core. An automated matching algorithm is developed for synchronizing the high-resolution section of the RICE gas records (60–720 m, 1971 CE to 30 ka) to corresponding records from the WAIS Divide ice core, while deeper sections are manually matched. Ice age for the top 343 m (2635 yr BP, before 1950 C.E.) is derived from annual layer interpretations and described in the accompanying paper by Winstrup et al. (2017). For deeper sections, the RICE17 ice age scale is based on the gas age constraints and the ice age-gas age offset estimated by a firn densification model. Novel aspects of this work include: 1) stratigraphic matching of centennial-scale variations in methane for pre-anthropogenic time periods, a strategy which will be applicable for developing precise chronologies for future ice cores, 2) the observation of centennial-scale variability in methane throughout the Holocene which suggests that similar variations during the late preindustrial period need not be anthropogenic, and 3) the observation of continuous climate records dating back to ∼ 65 ka which provide evidence that the Roosevelt Island Ice Dome was a constant feature throughout the last glacial period.

15 citations

Journal ArticleDOI
TL;DR: In this paper, secondary minerals in volcaniclastic deposits at Minna Bluff, a 45 km long peninsula in the Ross Sea, are used to infer processes of alteration and environmental conditions in the Late Miocene.
Abstract: Secondary minerals in volcaniclastic deposits at Minna Bluff, a 45 km long peninsula in the Ross Sea, are used to infer processes of alteration and environmental conditions in the Late Miocene. Glassy volcaniclastic deposits are altered and contain phillipsite and chabazite, low to high-Mg carbonates, chalcedony, and clay. The δ18O of carbonates and chalcedony is variable, ranging from −0.50 to 21.53‰ and 0.68 to 10.37‰, respectively, and δD for chalcedony is light (−187.8 to −220.6‰), corresponding to Antarctic meteoric water. A mean carbonate 87Sr/86Sr ratio of 0.70327 ± 0.0009 (1σ, n = 12) is comparable to lava and suggests freshwater, as opposed to seawater, caused the alteration. Minerals were precipitated at elevated temperatures (91 and 104°C) based on quartz-calcite equilibrium, carbonate 13C-18C thermometry (Δ47 derived temperature = 5° to 43°C) and stability of zeolites in geothermal systems (>10 to ∼100°C). The alteration was a result of isolated, ephemeral events involving the exchange between heated meteoric water and glass during or soon after the formation of each deposit. Near-surface evaporative distillation can explain 18O-enriched compositions for some Mg-rich carbonates and chalcedony. The δ18Owater calculated for carbonates (−15.8 to −22.9‰) reveals a broad change, becoming heavier between ∼12 and ∼7 Ma, consistent with a warming climate. These findings are independently corroborated by the interpretation of Late Miocene sedimentary sequences recovered from nearby sediment cores. However, in contrast to a cold-based thermal regime proposed for ice flow at core sites, wet-based conditions prevailed at Minna Bluff; a likely consequence of high heat flow associated with an active magma system.

15 citations

Journal ArticleDOI
TL;DR: The isotopic composition of water vapor, cloud water, and snow in mixed-phase orographic clouds were measured simultaneously for the first time in 2014 as mentioned in this paper, showing that the depletion of heavy isotopes [18O and deuterium (D)] was greatest for vapor, followed by snow, then cloud.
Abstract: The Isotopic Fractionation in Snow (IFRACS) study was conducted at Storm Peak Laboratory (SPL) in northwestern Colorado during the winter of 2014 to elucidate snow growth processes in mixed-phase clouds. The isotopic composition (δ18O and δD) of water vapor, cloud water, and snow in mixed-phase orographic clouds were measured simultaneously for the first time. The depletion of heavy isotopes [18O and deuterium (D)] was greatest for vapor, followed by snow, then cloud. The vapor, cloud, and snow compositions were highly correlated, suggesting similar cloud processes throughout the experiment. The isotopic composition of the water vapor was directly related to its concentration. Isotopic fractionation during condensation of vapor to cloud drops was accurately reproduced assuming equilibrium fractionation. This was not the case for snow, which grows by riming and vapor deposition. This implies stratification of vapor with altitude. The relationship between temperature at SPL and δ18O was used to show...

15 citations

References
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Journal ArticleDOI
01 Nov 1964-Tellus A
TL;DR: In this paper, the isotopic fractionation of water in simple condensation-evaporation processes is considered quantitatively on the basis of the fractionation factors given in section 1.2.
Abstract: In chapter 2 the isotopic fractionation of water in some simple condensation-evaporation processes are considered quantitatively on the basis of the fractionation factors given in section 1.2. The condensation temperature is an important parameter, which has got some glaciological applications. The temperature effect (the δ's decreasing with temperature) together with varying evaporation and exchange appear in the “amount effect” as high δ's in sparse rain. The relative deuterium-oxygen-18 fractionation is not quite simple. If the relative deviations from the standard water (S.M.O.W.) are called δ D and δ 18 , the best linear approximation is δ D = 8 δ 18 . Chapter 3 gives some qualitative considerations on non-equilibrium (fast) processes. Kinetic effects have heavy bearings upon the effective fractionation factors. Such effects have only been demonstrated clearly in evaporation processes, but may also influence condensation processes. The quantity d = δ D −8 δ 18 is used as an index for non-equilibrium conditions. The stable isotope data from the world wide I.A.E.A.-W.M.O. precipitation survey are discussed in chapter 4. The unweighted mean annual composition of rain at tropical island stations fits the line δ D = 4.6 δ 18 indicating a first stage equilibrium condensation from vapour evaporated in a non-equilibrium process. Regional characteristics appear in the weighted means. The Northern hemisphere continental stations, except African and Near East, fit the line δ D = 8.0 δ 18 + 10 as far as the weighted means are concerned (δ D = 8.1 δ 18 + 11 for the unweighted) corresponding to an equilibrium Rayleigh condensation from vapour, evaporated in a non-equilibrium process from S.M.O.W. The departure from equilibrium vapour seems even higher in the rest of the investigated part of the world. At most stations the δ D and varies linearily with δ 18 with a slope close to 8, only at two stations higher than 8, at several lower than 8 (mainly connected with relatively dry climates). Considerable variations in the isotopic composition of monthly precipitation occur at most stations. At low latitudes the amount effect accounts for the variations, whereas seasonal variation at high latitudes is ascribed to the temperature effect. Tokyo is an example of a mid latitude station influenced by both effects. Some possible hydrological applications are outlined in chapter 5. DOI: 10.1111/j.2153-3490.1964.tb00181.x

7,081 citations


"A Review of Antarctic Surface Snow ..." refers background or methods in this paper

  • ...The second-order isotopic parameter deuterium excess d D 8 18O (Dansgaard 1964) is expected to be highly sensitive to kinetic effects occurring either during evaporation at the ocean surface or during atmospheric transport (e.g., reevaporation of droplets or ice crystal formation)....

    [...]

  • ...…the deuterium excess spatial variations. a. Description of the models and simulations Based on an open-system Rayleigh-type distillation scheme (Dansgaard 1964), simple cloud isotopic models are designed to represent the microphysical processes involved in the isotopic fractionation occurring…...

    [...]

Journal ArticleDOI
26 May 1961-Science
TL;DR: The relationship between deuterium and oxygen-18 concentrations in natural meteoric waters from many parts of the world has been determined with a mass spectrometer and shows a linear correlation over the entire range for waters which have not undergone excessive evaporation.
Abstract: The relationship between deuterium and oxygen-18 concentrations in natural meteoric waters from many parts of the world has been determined with a mass spectrometer. The isotopic enrichments, relative to ocean water, display a linear correlation over the entire range for waters which have not undergone excessive evaporation.

6,721 citations


"A Review of Antarctic Surface Snow ..." refers background in this paper

  • ...Since the 1950s, it has been observed that the stable isotopic composition of precipitation in the mid- and high latitudes is related to air temperature (Dansgaard 1953; Epstein and Mayeda 1953; Craig 1961)....

    [...]

  • ...Estonian traverse to Dome B This study Pits Glacier Lambert Australian traverses Delmotte (1997) 134 pits Transantarctica Dahe et al....

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Journal ArticleDOI
TL;DR: A number of marine water and fresh water samples were examined for the relative O18O16 ratio, and the variation of this ratio was determined to a precision of ± 1% as mentioned in this paper.

3,113 citations


"A Review of Antarctic Surface Snow ..." refers background in this paper

  • ...Since the 1950s, it has been observed that the stable isotopic composition of precipitation in the mid- and high latitudes is related to air temperature (Dansgaard 1953; Epstein and Mayeda 1953; Craig 1961)....

    [...]

Journal ArticleDOI
10 Jun 2004-Nature
TL;DR: The recovery of a deep ice core from Dome C, Antarctica, that provides a climate record for the past 740,000 years is reported, suggesting that without human intervention, a climate similar to the present one would extend well into the future.
Abstract: The Antarctic Vostok ice core provided compelling evidence of the nature of climate, and of climate feedbacks, over the past 420,000 years. Marine records suggest that the amplitude of climate variability was smaller before that time, but such records are often poorly resolved. Moreover, it is not possible to infer the abundance of greenhouse gases in the atmosphere from marine records. Here we report the recovery of a deep ice core from Dome C, Antarctica, that provides a climate record for the past 740,000 years. For the four most recent glacial cycles, the data agree well with the record from Vostok. The earlier period, between 740,000 and 430,000 years ago, was characterized by less pronounced warmth in interglacial periods in Antarctica, but a higher proportion of each cycle was spent in the warm mode. The transition from glacial to interglacial conditions about 430,000 years ago ( Termination V) resembles the transition into the present interglacial period in terms of the magnitude of change in temperatures and greenhouse gases, but there are significant differences in the patterns of change. The interglacial stage following Termination V was exceptionally long - 28,000 years compared to, for example, the 12,000 years recorded so far in the present interglacial period. Given the similarities between this earlier warm period and today, our results may imply that without human intervention, a climate similar to the present one would extend well into the future.

1,995 citations

Journal ArticleDOI
TL;DR: In this paper, a theoretical model is derived to account for the deuterium-oxygen 18 relationship measured in meteoric waters, where a steady state regime is assumed for the evaporation of water at the ocean surface and the subsequent formation of precipitation.
Abstract: A theoretical model is derived to account for the deuterium-oxygen 18 relationship measured in meteoric waters. A steady state regime is assumed for the evaporation of water at the ocean surface and the subsequent formation of precipitation. The calculations show that the deuterium and oxygen 18 content in precipitation can be taken as linearly related. From the slope and the intercept (known as the deuterium excess) of the δD-δ18O linear relationship for precipitation we compute the mean values on a global scale of the evaporating ocean surface temperature and the relative humidity of the air masses overlying the oceans. The deuterium excess is primarly dependent on the mean relative humidity of the air masses formed above the ocean surface. Paleoclimatic data may be obtained by this isotopic method from the analysis of old water and ice samples. A moisture deficit of the air over the ocean, equal to only 10%, in comparison to 20% for modern conditions, is deduced from the deuterium-oxygen 18 distribution measured in groundwater samples older than 20,000 years.

1,216 citations

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