Valérie Masson-Delmotte

Water isotopes are a key tool to reconstruct past climate variations from ice core records. At sites with low precipitation amounts, such as in Central Antarctica, redistribution by wind and post-depositional processes can alter the snow isotopic signal. This causes a shift in mean isotopic composition and adds stratigraphic noise, with a large spatial variability at the meter scale. In turn, this can modify the isotope-temperature relationship at inter-annual timescales. Here, we present a new dataset of water stable isotope measurements performed on 39 simultaneous 1.5 m deep snow pits dug along a 50 m trench in December 2019 at Dome C. It is combined to timeseries of observed isotopic composition in precipitation and surface-snow conducted over the last decade in order to study the isotope transfer function during snow archival processes. The trench isotopic records covering about 20 years depict no annual cycle and no correlation with local temperature, contrary to precipitation and surface snow time-series. Trench profiles show a very large spatial variability of the inter-annual signal archived in snow. The trench mean δ 18 O values show a a +7 ‰ offset (-6 ‰ for d-excess) compared to mean precipitation values, and +2 ‰ offset for δ 18 O (-1 ‰ for d-excess) compared to surface snow, indicating vapour exchanges acting beyond the surface snow layer. The power spectra of trench profiles imply a stronger smoothing at high frequencies than predicted by classical diffusion models. Individual trench profiles are dominated by stratigraphic noise, with a signal-to-noise ratio less than 0.35 across frequencies. This signal-to-noise ratio can be enhanced by up to 50 % by inter-profile alignment based on chemical tracers. The aligned core stack signal shows a multi-annual signal with some features not reproduced by a simple precipitation stacking model, hinting to a contribution of post-depositional effects in this common signal.

Water isotopes are a key tool to reconstruct past climate variations from ice core records. At sites with low precipitation amounts, such as in Central Antarctica, redistribution by wind and post-depositional processes can alter the snow isotopic signal. This causes a shift in mean isotopic composition and adds stratigraphic noise, with a large spatial variability at the meter scale. In turn, this can modify the isotope-temperature relationship at inter-annual timescales. Here, we present a new dataset of water stable isotope measurements performed on 39 simultaneous 1.5 m deep snow pits dug along a 50 m trench in December 2019 at Dome C. It is combined to timeseries of observed isotopic composition in precipitation and surface-snow conducted over the last decade in order to study the isotope transfer function during snow archival processes. The trench isotopic records covering about 20 years depict no annual cycle and no correlation with local temperature, contrary to precipitation and surface snow time-series. Trench profiles show a very large spatial variability of the inter-annual signal archived in snow. The trench mean δ 18 O values show a a +7 ‰ offset (-6 ‰ for d-excess) compared to mean precipitation values, and +2 ‰ offset for δ 18 O (-1 ‰ for d-excess) compared to surface snow, indicating vapour exchanges acting beyond the surface snow layer. The power spectra of trench profiles imply a stronger smoothing at high frequencies than predicted by classical diffusion models. Individual trench profiles are dominated by stratigraphic noise, with a signal-to-noise ratio less than 0.35 across frequencies. This signal-to-noise ratio can be enhanced by up to 50 % by inter-profile alignment based on chemical tracers. The aligned core stack signal shows a multi-annual signal with some features not reproduced by a simple precipitation stacking model, hinting to a contribution of post-depositional effects in this common signal.

Water isotopes are a key tool to reconstruct past climate variations from ice core records. At sites with low precipitation amounts, such as in Central Antarctica, redistribution by wind and post-depositional processes can alter the snow isotopic signal. This causes a shift in mean isotopic composition and adds stratigraphic noise, with a large spatial variability at the meter scale. In turn, this can modify the isotope-temperature relationship at inter-annual timescales. Here, we present a new dataset of water stable isotope measurements performed on 39 simultaneous 1.5 m deep snow pits dug along a 50 m trench in December 2019 at Dome C. It is combined to timeseries of observed isotopic composition in precipitation and surface-snow conducted over the last decade in order to study the isotope transfer function during snow archival processes. The trench isotopic records covering about 20 years depict no annual cycle and no correlation with local temperature, contrary to precipitation and surface snow time-series. Trench profiles show a very large spatial variability of the inter-annual signal archived in snow. The trench mean δ 18 O values show a a +7 ‰ offset (-6 ‰ for d-excess) compared to mean precipitation values, and +2 ‰ offset for δ 18 O (-1 ‰ for d-excess) compared to surface snow, indicating vapour exchanges acting beyond the surface snow layer. The power spectra of trench profiles imply a stronger smoothing at high frequencies than predicted by classical diffusion models. Individual trench profiles are dominated by stratigraphic noise, with a signal-to-noise ratio less than 0.35 across frequencies. This signal-to-noise ratio can be enhanced by up to 50 % by inter-profile alignment based on chemical tracers. The aligned core stack signal shows a multi-annual signal with some features not reproduced by a simple precipitation stacking model, hinting to a contribution of post-depositional effects in this common signal.

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.

In a rapidly changing climate, evidence-based decision-making benefits from up-to-date and timely information. We track twelve key sets of indicators of the state of the climate system, closely following Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment report (AR6) methods, to produce our fourth annual publication. One of the indicators, the Earth's energy imbalance (EEI) provides a crucial integrative measure of the overall heating of the planet and the pace of climate change – this has more than doubled since the 1976–1995 period. A newly added indicator of temperature extremes, the number of days experiencing marine heatwaves, has more than tripled between 1991 and 2025. For the 2016–2025 decade average, observed warming relative to 1850–1900 was 1.26 [1.13 to 1.36] °C, of which 1.24 [1.0 to 1.5] °C was human-induced. Human-induced warming reached 1.37 °C relative to 1850–1900 in the year 2025, increasing at a rate of 0.27 [0.2–0.4] °C per decade over 2016–2025. This high rate of warming, which matches the all-time high seen last year in the instrumental record, was caused by a combination of greenhouse gas emissions being at an all-time high of 54.6 ± 5.5 GtCO ₂ e yr ⁻¹ over the last decade (2015–2024), as well as reductions in the strength of aerosol cooling. Despite this, there is evidence that CO ₂ emission growth is slowing. The continuation of these annual updates could track decreases or increases in the rate of human influence and climatic changes presented here, reflecting the outcomes of societal choices during the critical 2020s decade. The data presented herein can provide a useful reference point for the drafting of the IPCC seventh assessment report. In total, we employ analysis from over 40 global datasets (https://doi.org/10.5281/zenodo.20499280, Smith et al., 2026a). Future monitoring of these indicators, such as ocean and satellite measurements of the Earth's energy imbalance, are threatened by geopolitical and public funding decisions. Our ability to consistently track many of the indicators requires the continuity of observation programs and coordination mechanisms, including the Global Climate Observing System (GCOS) program, that enable their effective integration and use.