Elise Fourré

Water isotopes in precipitation are a powerful tool to better understand the processes governing snowfall in Antarctica, which is essential to improve our knowledge of the Antarctic atmospheric water cycle and surface mass balance, and for the interpretation of past climate signals archived in ice cores. However, precipitation isotope observations in Antarctica rely on manual sampling, which is prone to fractionation under low accumulation rates and remains both time-consuming and logistically demanding, and thus restricted to stations and seasons where manual sampling is feasible. In this study, we present a novel method that enables autonomous, continuous, and combined measurements of water vapor and precipitation δ D, using a single laser spectrometer. This technique offers new observational capabilities to better capture the isotopic signature of snowfall events in polar environments. Compared to conventional manual sampling of precipitation, the technique is capable of analysing very small amounts of water, while avoiding post-depositional effects. In addition, it enables high-temporal-resolution observations and is well suited for long-term deployments in unmanned environments. The sampling system prototype has been deployed at Dumont d'Urville station, located on the coastal margin of East Antarctica, and evaluated during three precipitation events from February to June 2023. A dedicated post-processing algorithm was developed to retrieve the isotopic composition of precipitation from the surrounding vapor background. Comparisons with independently collected snow samples show a mean deviation of −5.4 ‰ in δ D, which is well below the observed intra-event signal amplitude of about 100 ‰. This demonstrates the reliability of both the sampling system and the retrieval algorithm to study the isotopic composition of precipitation at the event-scale. With this new dataset, two approaches are proposed to better understand the water vapor – precipitation relationship at Dumont d'Urville: (1) an evaluation of the LMDZ6iso general circulation model, and (2) a comparison with ground-based remote sensing instruments (ceilometer and micro rain radar) to explore the link between the Δ( δ D) metric and the vertical structure of precipitation. Beyond polar applications, the proposed method opens new possibilities for other types of observations, including liquid precipitation sampling or cloud water isotopes monitoring onboard aircraft.

The variability of water isotopes in Antarctic ice cores is of major interest for reconstructing past climate through changes in temperature and the hydrological cycle. Archived during the deposition of successive layers of snow, water molecules undergo various processes that can modify the isotopic signal initially imprinted in snowfall during the process of snow densification to ice (i.e. firn). Diffusion is a well-known effect that affects water isotope composition by smoothing the initial climate-related signal. Here, we focus on new water isotopes profiles of two firn cores from Little Dome C (LDC), dated thanks to sulphate concentration measurements, with the aim to identify the physical processes affecting the isotopic signal in the firn at the drilling site for the new Beyond Epica Oldest Ice (BELDC) deep ice core on the East Antarctic Plateau. We use a simple Virtual Firn Core model (VFC) to best fit our δ¹⁸O firn profiles. We conclude that the VFC should include a 8 cm surface mixing layer and that diffusion is overestimated below a depth of 3 meters.

The variability of water isotopes in Antarctic ice cores is of major interest for reconstructing past climate through changes in temperature and the hydrological cycle. Archived during the deposition of successive layers of snow, water molecules undergo various processes that can modify the isotopic signal initially imprinted in snowfall during the process of snow densification to ice (i.e. firn). Diffusion is a well-known effect that affects water isotope composition by smoothing the initial climate-related signal. Here, we focus on new water isotopes profiles of two firn cores from Little Dome C (LDC), dated thanks to sulphate concentration measurements, with the aim to identify the physical processes affecting the isotopic signal in the firn at the drilling site for the new Beyond Epica Oldest Ice (BELDC) deep ice core on the East Antarctic Plateau. We use a simple Virtual Firn Core model (VFC) to best fit our δ¹⁸O firn profiles. We conclude that the VFC should include a 8 cm surface mixing layer and that diffusion is overestimated below a depth of 3 meters.

The variability of water isotopes in Antarctic ice cores is of major interest for reconstructing past climate through changes in temperature and the hydrological cycle. Archived during the deposition of successive layers of snow, water molecules undergo various processes that can modify the isotopic signal initially imprinted in snowfall during the process of snow densification to ice (i.e. firn). Diffusion is a well-known effect that affects water isotope composition by smoothing the initial climate-related signal. Here, we focus on new water isotopes profiles of two firn cores from Little Dome C (LDC), dated thanks to sulphate concentration measurements, with the aim to identify the physical processes affecting the isotopic signal in the firn at the drilling site for the new Beyond Epica Oldest Ice (BELDC) deep ice core on the East Antarctic Plateau. We use a simple Virtual Firn Core model (VFC) to best fit our δ¹⁸O firn profiles. We conclude that the VFC should include a 8 cm surface mixing layer and that diffusion is overestimated below a depth of 3 meters.

The variability of water isotopes in Antarctic ice cores is of major interest for reconstructing past climate through changes in temperature and the hydrological cycle. Archived during the deposition of successive layers of snow, water molecules undergo various processes that can modify the isotopic signal initially imprinted in snowfall during the process of snow densification to ice (i.e. firn). Diffusion is a well-known effect that affects water isotope composition by smoothing the initial climate-related signal. Here, we focus on new water isotopes profiles of two firn cores from Little Dome C (LDC), dated thanks to sulphate concentration measurements, with the aim to identify the physical processes affecting the isotopic signal in the firn at the drilling site for the new Beyond Epica Oldest Ice (BELDC) deep ice core on the East Antarctic Plateau. We use a simple Virtual Firn Core model (VFC) to best fit our δ¹⁸O firn profiles. We conclude that the VFC should include a 8 cm surface mixing layer and that diffusion is overestimated below a depth of 3 meters.

The variability of water isotopes in Antarctic ice cores is of major interest for reconstructing past climate through changes in temperature and the hydrological cycle. Archived during the deposition of successive layers of snow, water molecules undergo various processes that can modify the isotopic signal initially imprinted in snowfall during the process of snow densification to ice (i.e. firn). Diffusion is a well-known effect that affects water isotope composition by smoothing the initial climate-related signal. Here, we focus on new water isotopes profiles of two firn cores from Little Dome C (LDC), dated thanks to sulphate concentration measurements, with the aim to identify the physical processes affecting the isotopic signal in the firn at the drilling site for the new Beyond Epica Oldest Ice (BELDC) deep ice core on the East Antarctic Plateau. We use a simple Virtual Firn Core model (VFC) to best fit our δ¹⁸O firn profiles. We conclude that the VFC should include a 8 cm surface mixing layer and that diffusion is overestimated below a depth of 3 meters.

Water isotopes serve as tracers of hydrological processes and as proxies for past climates archived in ice cores. The isotopic signal is acquired throughout the hydrological cycle—through evaporation over the oceans, precipitation, which occurs as moisture is transported from lower to higher latitudes, and during post-depositional processes in which isotopic exchange between snow and atmospheric moisture occurs. Owing to these multiple influences, the relationship between isotope ratios in ice and local temperature varies across Antarctica, and distinct relationships are found when evaluating isotope ratios and temperature across space (for example, in surface snow) compared with temporal correlations at the same site (for example, in precipitation). Here we report measurements of water vapour isotopic compositions from a traverse across East Antarctica, as well as at two fixed sites: the coastal station Dumont D’Urville and Dome C on the plateau. Combining snow and vapour isotopic data, we demonstrate that the temporal and spatial isotope–temperature relationships are distinct because of differences in how the rainout fraction varies across time and space. Our findings support a shift from thinking about the isotope–temperature relationship in terms of distinct temporal and spatial slopes to recognizing that the relationship varies along a continuum based on known dependencies between circulation dynamics and mean climate state. By distilling moisture along moist isentropic transport paths, we can predict the isotope–temperature relationship across either time or space using a physical understanding of large-scale moisture transport under different climatic conditions.

The variability of water isotopes in Antarctic ice cores is of major interest for reconstructing past climate through changes in temperature and the hydrological cycle. Archived during the deposition of successive layers of snow, water molecules undergo various processes that can modify the isotopic signal initially imprinted in snowfall during the process of snow densification to ice (i.e. firn). Diffusion is a well-known effect that affects water isotope composition by smoothing the initial climate-related signal. Here, we focus on new water isotopes profiles of two firn cores from Little Dome C (LDC), dated thanks to sulphate concentration measurements, with the aim to identify the physical processes affecting the isotopic signal in the firn at the drilling site for the new Beyond Epica Oldest Ice (BELDC) deep ice core on the East Antarctic Plateau. We use a simple Virtual Firn Core model (VFC) to best fit our δ¹⁸O firn profiles. We conclude that the VFC should include a 8 cm surface mixing layer and that diffusion is overestimated below a depth of 3 meters.

Water isotopes in precipitation are a powerful tool to better understand the processes governing snowfall in Antarctica, which is essential to improve our knowledge of the Antarctic atmospheric water cycle and surface mass balance, and for the interpretation of past climate signals archived in ice cores. However, precipitation isotope observations in Antarctica rely on manual sampling, which is prone to fractionation under low accumulation rates and remains both time-consuming and logistically demanding, and thus restricted to stations and seasons where manual sampling is feasible. In this study, we present a novel method that enables autonomous, continuous, and combined measurements of water vapor and precipitation δD, using a single laser spectrometer. This technique offers new observational capabilities to better capture the isotopic signature of snowfall events in polar environments. Compared to conventional manual sampling of precipitation, the technique is capable of analysing very small amounts of condensed water, while avoiding post-depositional effects. In addition, it enables high-temporal-resolution observations and is well suited for long-term deployments in unmanned environments. The sampling system prototype has been deployed at Dumont d’Urville station, located on the coastal margin of East Antarctica, and evaluated during three precipitation events from February to June 2023. A dedicated post-processing algorithm was developed to retrieve the isotopic composition of precipitation from the surrounding vapor background. Comparisons with independently collected snow samples show a mean deviation of -5.4 ‰ in δD, which is well below the observed intra-event signal amplitude of about 100 ‰. This demonstrates the reliability of both the sampling system and the retrieval algorithm to study the isotopic composition of precipitation at the event-scale. With this new dataset, two applications are proposed to better understand the water vapor – precipitation relationship at Dumont d’Urville: (1) an evaluation of the LMDZ6iso general circulation model, and (2) a comparison with ground-based remote sensing instruments (ceilometer and micro rain radar) to explore the potential of the Δ(δD) metric as a proxy for snow formation altitude. Beyond polar applications, the proposed method opens new possibilities for other types of observations, including liquid precipitation sampling or cloud water isotopes monitoring onboard aircraft.

Water isotopes in precipitation are a powerful tool to better understand the processes governing snowfall in Antarctica, which is essential to improve our knowledge of the Antarctic atmospheric water cycle and surface mass balance, and for the interpretation of past climate signals archived in ice cores. However, precipitation isotope observations in Antarctica rely on manual sampling, which is prone to fractionation under low accumulation rates and remains both time-consuming and logistically demanding, and thus restricted to stations and seasons where manual sampling is feasible. In this study, we present a novel method that enables autonomous, continuous, and combined measurements of water vapor and precipitation δD, using a single laser spectrometer. This technique offers new observational capabilities to better capture the isotopic signature of snowfall events in polar environments. Compared to conventional manual sampling of precipitation, the technique is capable of analysing very small amounts of condensed water, while avoiding post-depositional effects. In addition, it enables high-temporal-resolution observations and is well suited for long-term deployments in unmanned environments. The sampling system prototype has been deployed at Dumont d’Urville station, located on the coastal margin of East Antarctica, and evaluated during three precipitation events from February to June 2023. A dedicated post-processing algorithm was developed to retrieve the isotopic composition of precipitation from the surrounding vapor background. Comparisons with independently collected snow samples show a mean deviation of -5.4 ‰ in δD, which is well below the observed intra-event signal amplitude of about 100 ‰. This demonstrates the reliability of both the sampling system and the retrieval algorithm to study the isotopic composition of precipitation at the event-scale. With this new dataset, two applications are proposed to better understand the water vapor – precipitation relationship at Dumont d’Urville: (1) an evaluation of the LMDZ6iso general circulation model, and (2) a comparison with ground-based remote sensing instruments (ceilometer and micro rain radar) to explore the potential of the Δ(δD) metric as a proxy for snow formation altitude. Beyond polar applications, the proposed method opens new possibilities for other types of observations, including liquid precipitation sampling or cloud water isotopes monitoring onboard aircraft.