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V. Masson-Delmotte, S. Hou, A. Ekaykin, J. Jouzel, A. Aristarain, R. T. Bernardo, D. Bromwich, O. Cattani, M. Delmotte, S. Falourd, M. Frezzotti, H. Gallée, L. Genoni, E. Isaksson, A. Landais, M. M. Helsen, G. Hoffmann, J. Lopez, V. Morgan, H. Motoyama, D. Noone, H. Oerter, J. R. Petit, A. Royer, R. Uemura, G. A. Schmidt, E. Schlosser, J. C. Simões, E. J. Steig, B. Stenni, M. Stievenard, M. R. van den Broeke, R. S. W. van de Wal, W. J. van de Berg, F. Vimeux, and J. W. C. White

control their distribution, such as the shortest distance to the coast, latitude, and elevation. A study of the linear relationships between geographical parameters and isotopic data ( Table 3 ) makes it possible to propose multiple linear regression models, which account for 85% of the δ D and 88% of the δ 18 O spatial variance: with δ D in ‰, λ the latitude, H the elevation (m), and D the distance to the nearest coast (including ice shelves; km), In this linear analysis, the site elevation

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Y. Govender, E. Cuevas, L. D. S. Sternberg, and M. R. Jury

the next sampling period. A subsample of the rainwater samples was tested for salinity using a Brix refractometer at the time of collection. Vacutainers were stored in a refrigerator (4°C) in the laboratory until analysis at the Laboratory of Stable Isotope Ecology in Tropical Ecosystems (University of Miami). A total of 49 rainwater samples were analyzed in triplicate for δ 18 O and δD by mass spectrometry using methods described by Vendramini and Sternberg ( Vendramini and Sternberg 2007

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Tim Kerr, M. S. Srinivasan, and Jeremy Rutherford

characterization efforts have been carried out in the glacierized regions of the Southern Alps ( Anderton 1976 ; Purdie et al. 2010 ; Ruddell and Budd 1990 ). Anderton (1976) found seasonal variations of 18 O concentrations in snow, precipitation, stream water, and spring water in a glacier-dominated Southern Alps catchment with winter water more depleted in 18 O than summer water. A more extensive analysis of alpine isotope concentrations was carried out by Ruddell and Budd (1990) to assess the value

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Heather Guy, Anton Seimon, L. Baker Perry, Bronwen L. Konecky, Maxwell Rado, Marcos Andrade, Mariusz Potocki, and Paul A. Mayewski

essential to understand the controls on modern-day subseasonal spatiotemporal variability of precipitation isotopes, and whether or not these signals are preserved in the ice. In response to these current limitations and opportunities in the analysis of tropical Andean ice cores, the goals of this study are to 1) to identify subseasonal signals of isotopes in precipitation on the northeastern flank of the Altiplano, and their spatiotemporal characteristics, 2) to determine the dominant meteorological

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Catherine E. Finkenbiner, Stephen P. Good, Scott T. Allen, Richard P. Fiorella, and Gabriel J. Bowen

applications. 2. Data and methods a. Site information and tracer datasets Daily precipitation stable water isotope time series were downloaded from the International Atomic Energy’s (IAEA) Global Network of Isotopes in Precipitation (GNIP) and Water Isotope System of Data Analysis, Visualization and Electronic Retrieval (WISER) database ( IAEA 2020 ). Each time series was filtered to ensure precipitation values were greater than zero and had corresponding δ 2 H and δ 18 O isotope ratios. All time series

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Michael P. Meredith, Hugh J. Venables, Andrew Clarke, Hugh W. Ducklow, Matthew Erickson, Melanie J. Leng, Jan T. M. Lenaerts, and Michiel R. van den Broeke

. During this cruise, samples were drawn routinely for isotope analysis from the underway water supply (5-m depth), and also from Niskin bottles closed at various depths during concurrent profiling with a SeaBird 911plus conductivity–temperature–depth (CTD) instrument. The spatial pattern of sampling and data coverage is indicated by the distributions of salinity and δ 18 O shown in Fig. 2 . Accuracy of the Pal-LTER salinity data is around 0.002. Fig . 2. (a) Salinity at the locations from which near

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Joseph Galewsky

very low δ values measured on Chajnantor were set within a fully glaciated cloud under conditions that were supersaturated with respect to ice. We now return to the isotopic data to evaluate the extent to which these processes were preserved in the observations and to explore how we can use simple models applied to the isotopic data to generate constraints on the last-saturation conditions. d. Isotopic modeling The picture that emerges from the data and analysis thus far is that the very low δ

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Douglas Lowenthal, A. Gannet Hallar, Ian McCubbin, Robert David, Randolph Borys, Peter Blossey, Andreas Muhlbauer, Zhiming Kuang, and Mary Moore

virtual impactor that excludes cloud droplets. Ice water content (IWC) was derived from the wind speed and the diameter of the tubes. Snow samples were transferred to a storage bag and stored in a freezer. After the study, aliquots of cloud and snow water samples were sent to the Institute of Arctic and Alpine Research (INSTAAR) in Boulder, Colorado, for analysis of stable isotopes of water ( Lowenthal et al. 2011 ). A weather station measured 5-min average temperature, relative humidity (RH), and

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Joshua Rambo, Chun-Ta Lai, James Farlin, Matt Schroeder, and Ken Bible

1. Introduction Isotope-enabled general circulation models (GCMs) are a unique tool to compare the stable isotope ratios in precipitation ( δ 18 O and δ 2 H) in contemporary and paleoclimatic conditions ( Joussaume et al. 1984 ). GCMs are able to simulate regional distributions of atmospheric water vapor and its stable isotope ratios ( δ 18 O v and δ 2 H v ), but these model simulations are difficult to validate, and rarely do so, because of the scarcity of direct and continuous δ 18 O v

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M. M. Helsen, R. S. W. Van de Wal, and M. R. Van den Broeke

-yr period over the entire Antarctic continent. This approach is summarized in Fig. 1 and section 2 . We first calculated backward trajectories for all snowfall events over the Antarctic continent using the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) dataset as the meteorological input for the trajectory model. For this reason, we describe some relevant features of ERA-40 in the Antarctic region ( section 3a ). Then, we simulated isotopic distillation

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