Density of seawater is a critical property that controls ocean dynamics. Previous works suggest the use of the delta 18O calcite of foraminifera as a potential proxy for paleodensity. However, potential quantitative reconstructions were limited to the tropical and subtropical surface ocean and without an explicit estimate of the uncertainty in calibration model parameters. We developed the use of the delta 18Oc of planktonic foraminifera as a surface paleodensity proxy using Bayesian regression models calibrated to annual surface density. Predictive performance of the models improves when we account for inter-species specific differences.We investigate the additional uncertainties that could be introduced by potential evolution of the delta 18Oc-density relationship with time - from the last glacial maximum (LGM) to the preindustrial (PI) - through the combination of past isotope enabled climate model simulations and a foraminiferal growth module. We demonstrate that additional uncertainties are weak globally, except for the Nordic Seas region.We applied our Bayesian regression model to LGM and Late Holocene (LH) delta 18Oc foraminifera databases to reconstruct annual surface density during these periods. We observe stronger LGM density value changes at low latitudes compared to mid latitudes. These results will be used to evaluate numerical climate models in their ability to simulate ocean surface density during the extreme climatic period of the LGM.The new calibration has great potential to reconstruct the past temporal evolution of ocean surface density over the Quaternary. Under climates outside the Quaternary period and in ocean basins characterized by anti-estuary circulation, like the current Mediterranean Sea and Red Sea, our calibration could provide density estimates with larger uncertainty, a point that requires further investigations.

Antarctica is changing faster than our current observation networks can robustly assess or predict. Recent extreme events – major ice-shelf collapse, unprecedented heatwaves and abrupt, record-low winter sea ice – show that rare extremes can rapidly reshape the Antarctic system. These changes matter well beyond the polar regions: Antarctica influences global sea level, ocean circulation, and the whole climate system. This white paper sets out the case for Antarctica InSync (2027–2030) to deliver a four-year, coordinated observational baseline ahead of the International Polar Year 2031/32, so it is possible to distinguish temporary anomalies from long-term shifts, detect early warning signs of tipping points, and improve the evidence base for risk management.

Various proxy records have suggested widespread permafrost degradation in northern high latitudes during interglacial warm climates, including the mid Holocene (MH, 6000 years before present) and the last interglacial (LIG, 127 ka BP), and linked this to substantially warmer high-latitude climates compared to the pre-industrial period (PI). However, most Earth system models suggest only modest warming or even slight cooling in terms of annual mean surface temperatures during these interglacials, seemingly contradicting the reconstructions of widespread permafrost degradation. Here, we combine paleo climate simulations of the Alfred Wegener Institute's Earth system model version 2.5 (AWI-ESM-2.5) with the CryoGridLite permafrost model to investigate the ground thermal regime and freeze-thaw dynamics in northern high-latitude land areas during the MH and the LIG in comparison to the PI. Specifically, we decompose how the annual mean and seasonal amplitude (that is, the difference between the maximum and minimum monthly mean) of surface temperatures affect the occurrence of permafrost, seasonal frost, thaw depth and duration, and thermal contraction cracking activity. For the MH (LIG) AWI-ESM-2.5 simulated global-mean surface temperatures in the simulation domain to be about 0.1 K lower (0.4 K higher), and the global-mean seasonal amplitudes to be 2.9 K (7.4 K) higher than for the PI. With respect to interglacial permafrost characteristics, our simulations revealed that (i) local permafrost probabilities and global permafrost extent are predominantly determined by mean temperatures, (ii) maximum thaw depths are increasing with both annual mean and seasonal amplitudes, and (iii) thermal contraction cracking within the permafrost domain is almost solely driven by the seasonal amplitudes of surface temperatures. Thus, not only mean warming, but also the enhanced seasonal temperature amplitude due to a different orbital forcing have driven permafrost and ground ice dynamics during past interglacial climates. Our results provide an additional explanation of reconstructed periods of marked permafrost degradation in the past, which was driven by deep surficial thaw during summer, while colder winters allowed for permafrost persistence in greater depths. Our results further suggest that past interglacial climates have limited suitability as analogues for future permafrost thaw trajectories, as rising mean temperatures paralleled by decreasing seasonal amplitudes expose the northern permafrost region to magnitudes of thaw that are likely unprecedented since at least Marine Isotope Stage 11c (about 400 ka BP).

The stable oxygen isotope ratio (δ18O) measured in ice cores is widely used to reconstruct past climate variability on short and long timescales. Among synoptic processes, atmospheric rivers (ARs) play a key role in the poleward transport of moisture. ARs are long, narrow corridors of intense horizontal water vapour transport, typically associated with extratropical cyclones. They convey large amounts of moisture from distant, often low-latitude source regions together with warm air advection, thereby introducing a distinct isotopic signature into precipitation. Through snowfall, the isotopic composition of atmospheric water vapour is recorded in snow and ultimately preserved in ice cores. While several studies have examined the influence of ARs on δ18O variability in Antarctic ice cores, a comparable assessment for Greenland remains more limited until now.Here, we investigate the imprint of ARs on δ18O variability in Greenland ice cores using virtual firn cores (VFCs) derived from a new high-resolution (0.5°) simulation performed with the isotope-enabled atmospheric general circulation model ECHAM6-wiso nudged to ERA5 reanalyses. VFCs are generated for the Renland Ice Cap (RECAP) and Southeastern Dome (SED) sites and evaluated against their corresponding very high-resolution measured δ18O records.Our results show that ARs do not fundamentally change the δ18O variability. However, they exert a pronounced influence on seasonal and subseasonal δ18O variations during periods when AR-related snowfall contributes a substantial fraction of total precipitation. On the subseasonal timescale, individual AR events are found to increase δ18O values by approximately 3‰ on average, with extreme cases reaching up to 5‰.

Abstract. Speleothem oxygen isotopes provide key insights into Holocene monsoon variability, but the scale-dependent and regionally variable controls on precipitation δ18O remain poorly resolved. Here, we use a continuous 8.3 ka isotope-enabled transient simulation based on AWI-ESM2-wiso to investigate Holocene climatic and isotopic changes and quantify driving mechanisms for the isotopic variations via a four-predictor multiple linear regression (MLR) model. The simulation successfully reproduces the orbitally driven long-term weakening of Northern Hemisphere monsoons and the bipolar hydroclimatic response to the 8.2 ka freshwater perturbation, characterized by a southward Intertropical Convergence Zone (ITCZ) shift, Northern Hemisphere drying and isotopic enrichment, and Southern Hemisphere moistening and depletion. MLR results show that regional precipitation amount serves as the dominant and temporally stable control on monsoon δ18O. Secondary predictors including moisture transport, continental recycling, and source temperature exert regionally divergent and time-varying influences. Supplementary large-scale climate indices can improve model performance for specific monsoon domains. El Niño und die Southern Oscillation (ENSO) is the most widespread teleconnection affecting most monsoon domains, while Atlantic Meridional Overturning Circulation (AMOC) and South Atlantic Convergence Zone (SACZ) act as additional key controls over Southwestern South American Monsoon. Spatial correlation analyses further demonstrate that the precipitation amount effect is weak and spatially heterogeneous at local grid scales but becomes robust and uniform at the regional scale. This further indicates that individual speleothem records may misrepresent large-scale monsoon signals due to local spatial noise, while regional proxy ensembles effectively capture the dominant precipitation-isotope relationship.

Abstract. Water stable isotopologues, particularly H218O and HD16O, are valuable tracers of physical and dynamical processes within the hydrological cycle. These isotopologues have been widely incorporated into isotope-enabled atmospheric general circulation models to constrain moisture sources and transport pathways. However, comprehensive evaluations of such models over the Tibetan Plateau (TP), a region whose complex orography substantially modulates South Asian monsoon dynamics, remain scarce. Here, we systematically evaluate simulations of water vapor isotopic composition (δ18Ov) from the ECHAM6-wiso model against daily in-situ observations from four high‐altitude stations (Kathmandu, Lulang, Namco, and Muztag) on the Tibetan Plateau, spanning January 2020 to November 2021. The model successfully reproduces the spatial distribution and seasonal cycle of δ18Ov; however, probability density functions reveal a systematic underestimation of isotopic depletion. Through a multi‐scale temporal decomposition of the daily δ18Ov time series, we attribute over 50% of the simulation error to deficiencies in representing large-scale atmospheric circulations (periods ≥ 30 days), while the remaining error is linked to synoptic-scale processes (3–7 days) associated with fractionation, including cloud microphysics, post‐condensation effects, and surface evaporation. The model's inability to accurately simulate terrain-induced atmospheric moisture blocking over the TP results in bias in atmospheric circulation variations, thereby amplifying the contribution of circulation-related processes to the overall error. These findings underscore the significance of atmospheric circulation in water vapor isotopic simulations and highlight the value of high‐resolution water vapor isotopic datasets for improving our understanding of moisture source attribution and water‐cycle dynamics in regions of complex topography.

Recovering liquid water from past precipitation on continental areas from mid- to low-latitude and analysing its water isotopes presents significant challenges. Paleoclimate archives such as groundwater, ice or speleothems provide direct access to paleowaters. Most of the paleoclimate reconstructions linked to past precipitation water isotopes are not directly based on analysis of paleo liquid water. They are measured, for instance, on carbonate, sediment or cellulose, all of which primarily derive from precipitation water, yet remain influenced by various fractionation processes during their formation.Speleothems are advantageous as they can be found in all karstic regions of the Earth, at every latitude and on every continent. They contain fluid inclusions that encapsulated fossil drip water, corresponding to a mixture of precipitation water that fell above the cave area approximately at the time the inclusions were formed. It therefore constitutes thus a unique window into the past hydroclimate cycle for mid- to low latitude. Having better access to paleowater at lower latitudes than those of polar regions allows us to gather global information and understand the behaviour of past meteoric water.Using published and novel speleothem fluid inclusion data from ~140 caves, we investigate the global behaviour of water isotopes in the past. We explore the spatial distribution of paleoprecipitation, construct a global meteoric water line and develop paleo-isotopic lapse rates for the Holocene and Pleistocene. Furthermore, we compare the speleothem data with observational stable isotope data and two model simulations, i.e. the AWI-ESM-wiso and the ECHAM6-wiso simulations.

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. Atmospheric circulation patterns and mean climate conditions lead to heterogeneity in water isotope–temperature relationships across Antarctica, and accounting for these effects allows for more robust interpretation of temperature proxy records from ice cores.

We present the first results of the Water Isotope Model Intercomparison Project (WisoMIP), with Phase 1 focused on modern simulations (1979-2023) from a suite of isotope-enabled atmospheric general circulation models nudged to ERA5 reanalyzes. Water sources, mixing, and rainout history influence the isotopic composition of vapor and precipitation, making these simulations powerful tools for tracing the global water cycle. By prescribing identical winds, sea surface temperatures, and sea ice conditions, we isolate differences in water isotope behavior across models, controlling for variability in atmospheric dynamics and mean climate. Our analyses show that the ensemble mean best matches observations, as individual model errors cancel out to yield a more accurate representation of Earth's isotope distributions. We also evaluate trends and responses to major climate modes during the recent warming period, highlighting regional and temporal sensitivities in the isotope signals. These diagnostics extend beyond traditional model evaluation metrics (e.g., temperature, precipitation) to reveal uncertainties in physical processes and guide improvements in model parameterizations. The resulting modern nudged ensemble data set serves as a benchmark for isotope-enabled model development, satellite product comparison, and understanding of water cycle changes in a warming climate. Given its standardized design and broad participation, WisoMIP provides a valuable "isotope reanalysis" product for applications ranging from paleoclimate reconstruction to model tuning. Our work demonstrates the importance of coordinated isotope model evaluation in advancing the use of water isotopes as a diagnostic tool in climate science.

During the early and mid-Holocene, the Sahara and Sahel experienced a humid phase, the so-called African Humid Period (AHP)1. The AHP started around 14.8 thousand years before present (kyr BP), peaked between 9.0 kyr BP and 6.0 kyr BP and experienced short-lived droughts of as yet poorly constrained age and duration2,3. Here we show that the AHP was punctuated by two droughts of decadal-scale duration, at about 9.3 kyr BP and 8.2 kyr BP, and another more tentatively identified drought at 6.3 kyr BP. Our findings arise from a multiproxy time series from the annually layered (varved) sedimentary archive of Lake Yoa in Chad, which covers the past 10.25 kyr continuously. During the more prominent drought at 8.2 kyr BP, pollen and diatom data, along with leaf-wax isotopes and geochemical source area indicators, imply that a reduction in local precipitation and fluvial supply to Lake Yoa caused a lake-level drop accompanied by an expansion of reed belts along the shore. The proxy data, together with our climate simulations, suggest that the 8.2 kyr BP drought event was a direct and rapid response to a potential weakening of the Atlantic Meridional Overturning Circulation (AMOC) owing to sudden freshwater input into the North Atlantic. The results underline the need for improved decadal predictions4 to better anticipate such drought risks in the future.

The westerlies moisture transport underpins water security for over two billion people dependent on the Asian water towers (AWTs). However, the mechanisms by which large-scale westerlies-advected moisture is integrated into the AWTs' atmospheric water budget remain poorly understood due to observational gaps. Here, we combine three-dimensional observations of atmospheric water vapor stable isotopes with isotope-enabled modeling. We identify the conveyor mechanism that regulates the vertical moisture transport under calm conditions during the winter-spring period when the westerlies are dominant. Sharp vertical isotopic gradients show that large-scale westerlies-advected moisture is predominantly confined aloft, while local residual moisture persists near the surface. Our results show the interplay of the westerlies' subsidence at night with thermodynamically distinct local residual air, yielding thermal inversions and condensation that suppresses vertical mixing and decouples moisture between the free troposphere and the atmospheric boundary layer. This process constitutes a primary pathway for integrating westerlies-advected moisture into the local moisture budget without precipitation, sustaining near-surface moisture accumulation. Our results provide critical benchmarks for improving atmospheric models, refining climate projections of the intensifying water cycle over the AWTs, and advancing interpretations of isotopic records in regional climatic archives.

Water stable isotope signals recorded in shallow firn cores are essential to constrain the variations of climate and atmospheric water cycle over the past decades to centuries. However, deposition and post-deposition effects add additional signal, often referred to as stratigraphic noise, to the isotopic signal. One way to reduce the local stratigraphic noise is to combine several firn cores at the same location. Here, we study the water isotopic composition and chemical records from 9 firn cores (20 to 40 m depth) drilled in 2016 at 3 sites (D47, Stop5 and Stop0) with high accumulation rates (∼ 200 mm w.e. yr−1) along a transect between the coast and the plateau in Adélie Land in Antarctica (100 to 385 km from the coastal station Dumont d'Urville). Each core covers at least the period from 1979 to 2016 and the high-resolution measurements permit to capture the seasonal variations in both chemical and isotopic records. At each site, similarities in the nssSO4 and δ18O variations between the different cores were used to combine the three isotopic records into a single stacked isotopic curve, thereby enhancing the signal-to-noise ratio. At two sites, we find a good agreement when comparing the water isotopic profiles recovered from the stacked records to those obtained as modeling output from virtual firn cores calculated using the two isotope-enabled atmospheric general circulation models, ECHAM6-wiso and LMDZ6iso over the period 1979–2016 which supports the good performances of the two models for the Adélie Land region. At the very windy site of D47, building a coherent signal from the 3 individual cores is not possible because the isotopic and impurities signals are much more affected by stratigraphic noise. This study confirms that, even if the benefit of stacking is limited at very windy sites, combining several cores is of primary importance to faithfully reconstruct water isotope variability at one site. We also show that the stacked record permits to identify some strong climate signals recorded in the water isotope profiles.

The stable isotopic composition of precipitation (delta 2HP, delta 18OP; "water isotopes") is a powerful tool for tracking water through the atmosphere, as well as fingerprinting land-surface water masses and identifying water cycle biases in isotope-enabled climate models. Water isotopes also underpin our understanding of multi-decadal to multi-centennial water cycle variability via their retrieval from palaeoclimate archives. Water isotopes thereby increase our understanding of past and present - and hence future - water cycle variability. Understanding the drivers of spatial and temporal water isotope variability is a critical first step in applying these tracers for a better understanding of the water cycle. However, water isotope observations are sparse in both space and time. Here we develop and apply a machine learning (random forest) approach to predict spatially continuous monthly delta 2HP and delta 18OP across the Australian continent at 0.25 degrees resolution from 1962-2023. We train the random forest models on monthly delta 2HP (n=5199) and delta 18OP (n=5217) observations from 60 sites across Australia. We also predict the deuterium excess of precipitation (dxsP, defined as delta 2HP-8x delta 18OP). Out-of-sample delta 2HP and delta 18OP prediction skill is high both geographically and temporally. Skill is slightly lower for the secondary parameter dxsP, likely reflecting the larger reliance of spatio-temporal dxsP variability on moisture source conditions. The random forest models accurately capture both the seasonal cycle of precipitation isotopic variability and long-term annual-mean precipitation isotopic variability across the continent, and outperform estimates from an isotope-enabled atmosphere general circulation model over an equivalent time period. We show that spatio-temporal variability in precipitation amount, precipitation intensity, and surface temperature are particularly important for monthly delta 2HP and delta 18OP variations across the continent, with local surface pressure also important for dxsP. Drivers of site-level delta 2HP, delta 18OP, and dxsP are more varied. Overall, the new random forest modelled dataset reveals clear spatial and temporal variability in delta 2HP, delta 18OP, and dxsP across the Australian continent over the past decades - providing a robust foundation for hydrology, ecology, and palaeoclimate research, as well as an accessible framework for predicting water isotope values in other locations.

Understanding snow processes in the sea-ice system is essential to improving Arctic sea-ice predictions and climate modeling. We show that the winter snow cover on Arctic sea ice is strongly enriched in heavy isotopes near the snow-sea ice interface, unexplainable by snow metamorphism alone. During the MOSAiC expedition, stratigraphic investigations revealed that large temperature gradients drive water vapor transport and mass transfer from sea ice into the snowpack. We estimate the contributed snow depth equivalent as 39 ± 7 mm (cumulative mass redistribution) and 63 ± 21 mm (isotope two-source model). Despite uncertainties, both highlight the need for detailed snowpack vapor flux modeling. Recognizing this recrystallization process improves understanding of snow stratigraphy, gas exchange, atmospheric chemistry through snow impurity distributions (e.g., sea salt aerosol), and reduces uncertainties in snow mass balance and heat conductivity. With continued Arctic change, evolving snowpack temperature gradients and recrystallized sea-ice snow contributions will further shape these processes.

Extreme precipitation events (EPE), defined as the top 10% of daily precipitation amounts, play a major role in Antarctica surface mass balance as they account for more than 40% of the total annual precipitation across the continent. These EPEs are often associated with high temperatures and have major consequences on the Antarctic surface mass balance. Though, it is key to estimate their recent evolution in terms of frequency and intensity in the context of climate change. As water stable isotopic composition of firn cores is known to record the temperature signal modulated by precipitation intermittency, and to be imprinted as well as by the large-scale atmospheric circulation, we can ask if EPEs could be detected in firn cores thanks to a particular isotopic signature. In this study we construct Virtual Firn Cores (VFC) across Antarctica to investigate how winter EPEs can be misinterpreted as summer maxima in firn cores. We create VFC using (1) temperature, precipitation rate and a linear temperature-d18O relationship from atmospheric regional model MAR, (2) d18O in precipitation from ECHAM6-wiso and (3) d18O in precipitation from LMDZ6-iso, for the period 1979-2022. Additionally to standard VFCs, we generate a second set of VFCs excluding each year the highest winter precipitation event (5-days period). We then run a detection algorithm to find local maxima for both sets of VFCs. We observe some regions with nearly 20% more “summer” detected in standard VFCs compared to VFCs without the winter maximum precipitation event. We argue that firn cores drilled in those regions are more likely to contain isotopic signals that could be used to detect EPEs temporal variability.

Snow on sea ice is crucial in moderating sea ice and atmosphere interactions, yet fully grasping snow's isotopic composition and the processes shaping it presents substantial challenges, including sublimation and wind redistribution. This study utilizes a year of stable water isotope datasets from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in 2019/2020 to explore the complex interactions between snow deposition processes and postdepositional changes affecting snow on Arctic sea ice including seasonal and spatial dynamics. We compare snow data with water vapor isotope measurements by examining 911 individual snow isotope measurements and integrating these discrete snow samples with continuous water vapor isotope data. Autumn shows a pronounced 818O offset between snow and vapor. In winter, 818O and d-excess in surface snow and water vapor diverge sharply, indicating kinetic fractionation under extremely cold temperatures as research vessel Polarstern drifted from the Siberian to the Atlantic Arctic. While water vapor 818O responds rapidly to air temperature and humidity changes, surface snow 818O values are modulated by postdepositional processes like sublimation and wind redistribution. We found that these 2 processes play a key role in isotopic enrichment that is intensified by the snow's prolonged surface residence. Wind-driven snow redistribution, occurring during 67% of the winter period, leads to an average surface snow 818O of-22 parts per thousand across the sea ice by redistributing and mixing fresh snow with more metamorphosed snow. This study provides new insights into how wind-driven redistribution and prolonged surface residence not only alter isotopic values in surface snow but also obscure seasonal isotopic patterns, complicating the interpretation of snow isotope records in the Arctic. Our research to understand the differences between the isotopic values of vapor and the isotopic values of snow provides insight into interactions between snow and the atmosphere, as well as the processes that alter isotopic values internally within the Arctic snowpack. Our study highlights the complexity of surface snow isotope geochemistry across the Arctic from the eastern to the central basin during the MOSAiC expedition window and how the underlying processes of water vapor transport, temperature-isotope relations, and the role of secondary processes, including wind redistribution and sea ice formation all contribute to the horizontal and vertical geochemistry patterns.

The isotopic composition of water vapor can be used to track atmospheric hydrological processes and to evaluate numerical models simulating the water cycle. Accurate model–observation comparisons require understanding the spatial and temporal variability of tropospheric water vapor isotopes. The challenging task of obtaining highly resolved water vapor isotopic observations is typically addressed through airborne measurements performed aboard conventional aircraft, but these offer limited microscale insights. This study uses ultralight aircraft observations to investigate water vapor isotopic composition in the lower troposphere over southern France in late summer 2021. Combining observations with models, we identify key drivers of isotopic variability and detect short-lived, small-scale processes. The key findings of this study are that (i) at hourly and sub-daily scales, vertical mixing is the primary driver of isotopic variability in the lowermost troposphere above the study site; (ii) evapotranspiration significantly impacts the boundary layer water vapor isotopic signature, as revealed by the δ18O–δD relationship; and (iii) while water vapor isotopes generally follow large-scale humidity patterns, with separation distances that might range up to 100–300 km, they also reveal distinct small-scale structures (approximately hundreds of meters) that are not fully explained by humidity variations alone, highlighting sensitivity of water vapor isotopic composition to additional fine-scale processes. The latter are particularly evident for δD, which also exhibit the largest differences in horizontal and vertical gradients. Combined with other airborne datasets, our results support a simple model driven by surface observations to simulate tropospheric δD vertical profiles, improving surface–satellite comparisons.

Water stable isotopes signals recorded in snow, firn and ice cores were successfully used to investigate past temperatures on glacial/interglacial scales. However, many uncertainties hampered the interpretation of water isotope records at sub-annual to decadal resolution as a proxy of past temperature variations only. Condensation, sublimation and/or redistribution of snow triggered by strong katabatic winds as well as diffusion within firn lessen the representativeness of a single isotopic profile to reconstruct past temperature in this region. In order to mitigate the non-representativeness of a single isotopic profile, a solution consists of averaging several records to increase signal to noise ratios. In this study, we present an analysis of 3 stacked δ18O temporal series from the coast-to-plateau transition in Adélie land. Each of these stacks was built from three shallow firn cores (~20 m-long) drilled at 3 locations (so called D47, Stop5 and Stop0) with high accumulation rates (~200 mm w.eq ·yr-1) during the ASUMA campaign in December 2016 - January 2017. The sites feature different elevations (from 1516 m to 2416 m above sea level) and katabatic winds influence. We present a comparison of each of these stacks with virtual firn cores produced from the outputs of two atmospheric general circulation models including isotopes, ECHAM6wiso and LMDZ6iso for the period 1979 - 2016. In particular, we show how much of the climatic information we can retrieve from our δ18O stacked series.

In diesem Versuch wird die Spektralanalyse analoger Signale durch die FFT vorgestellt. Da die FFT ein blockorientiertes Verfahren ist, d.h. es wird in der Regel nur ein kurzer Block oder Ausschnitt eines Signals verarbeitet, spricht man von einer Kurzzeit-Spektralanalyse. Die Art und Weise wie die Blöcke aus dem Signal herausgeschnitten werden, im Weiteren Fensterung genannt, hat einen großen Einfluss auf das resultierende Spektrum. Nach einer theoretischen Einführung werden in der Versuchsdurchführung häufig verwendete Fensterfunktionen genauer untersucht.