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The EPICA Dome C (EDC) ice core provides the longest continuous climatic record, covering the last 800 000 years (800 kyr). A unique opportunity to investigate decadal to millennial variability during past glacial and interglacial periods is provided by the high-resolution water isotopic record (δ18O and δD) available for the EDC ice core. We present here a continuous compilation of the EDC water isotopic record at a sample resolution of 11 cm, which consists of 27 000 δ18O measurements and 7920 δD measurements (covering, respectively, 94 % and 27 % of the whole EDC record), including published and new measurements (2900 for both δ18O and δD) for the last 800 kyr. Here, we demonstrate that repeated water isotope measurements of the same EDC samples from different depth intervals obtained using different analytical methods are comparable within analytical uncertainty. We thus combine all available EDC water isotope measurements to generate a high-resolution (11 cm) dataset for the past 800 kyr. A frequency decomposition of the most complete δ18O record and a simple assessment of the possible influence of diffusion on the measured profile shows that the variability at the multi-decadal to multi-centennial timescale is higher during glacial than during interglacial periods and higher during early interglacial isotopic maxima than during the Holocene. This analysis shows as well that during interglacial periods characterized by a temperature optimum at the beginning, the multi-centennial variability is strongest over this temperature optimum.

Global measurements of absorbing aerosol optical depth (AAOD) are scarce and mostly provided by the ground network AERONET (AErosol RObotic NETwork). In recent years, several satellite products of AAOD have been developed. This study's primary aim is to establish the usefulness of these datasets for AEROCOM (Aerosol Comparisons between Observations and Models) model evaluation with a focus on the years 2006, 2008 and 2010. The satellite products are super-observations consisting of 1∘×1∘×30 min aggregated retrievals. This study consists of two papers, the current one that deals with the assessment of satellite observations and a second paper (Schutgens et al., 2021) that deals with the evaluation of models using those satellite data. In particular, the current paper details an evaluation with AERONET observations from the sparse AERONET network as well as a global intercomparison of satellite datasets, with a focus on how minimum AOD (aerosol optical depth) thresholds and temporal averaging may improve agreement between satellite observations. All satellite datasets are shown to have reasonable skill for AAOD (three out of four datasets show correlations with AERONET in excess of 0.6) but less skill for SSA (single-scattering albedo; only one out of four datasets shows correlations with AERONET in excess of 0.6). In comparison, satellite AOD shows correlations from 0.72 to 0.88 against the same AERONET dataset. However, we show that performance vs. AERONET and inter-satellite agreements for SSA improve significantly at higher AOD. Temporal averaging also improves agreements between satellite datasets. Nevertheless multi-annual averages still show systematic differences, even at high AOD. In particular, we show that two POLDER (Polarization and Directionality of the Earth's Reflectances) products appear to have a systematic SSA difference over land of ∼0.04, independent of AOD. Identifying the cause of this bias offers the possibility of substantially improving current datasets. We also provide evidence that suggests that evaluation with AERONET observations leads to an underestimate of true biases in satellite SSA. In the second part of this study we show that, notwithstanding these biases in satellite AAOD and SSA, the datasets allow meaningful evaluation of AEROCOM models.

To better understand and characterize current uncertainties in the important observational constraint of climate models of aerosol optical depth (AOD), we evaluate and intercompare 14 satellite products, representing nine different retrieval algorithm families using observations from five different sensors on six different platforms. The satellite products (super-observations consisting of 1∘×1∘ daily aggregated retrievals drawn from the years 2006, 2008 and 2010) are evaluated with AErosol RObotic NETwork (AERONET) and Maritime Aerosol Network (MAN) data. Results show that different products exhibit different regionally varying biases (both under- and overestimates) that may reach ±50 %, although a typical bias would be 15 %–25 % (depending on the product). In addition to these biases, the products exhibit random errors that can be 1.6 to 3 times as large. Most products show similar performance, although there are a few exceptions with either larger biases or larger random errors. The intercomparison of satellite products extends this analysis and provides spatial context to it. In particular, we show that aggregated satellite AOD agrees much better than the spatial coverage (often driven by cloud masks) within the 1∘×1∘ grid cells. Up to ∼50 % of the difference between satellite AOD is attributed to cloud contamination. The diversity in AOD products shows clear spatial patterns and varies from 10 % (parts of the ocean) to 100 % (central Asia and Australia). More importantly, we show that the diversity may be used as an indication of AOD uncertainty, at least for the better performing products. This provides modellers with a global map of expected AOD uncertainty in satellite products, allows assessment of products away from AERONET sites, can provide guidance for future AERONET locations and offers suggestions for product improvements. We account for statistical and sampling noise in our analyses. Sampling noise, variations due to the evaluation of different subsets of the data, causes important changes in error metrics. The consequences of this noise term for product evaluation are discussed.

Recent years have seen the increasing inclusion of per-retrieval prognostic (predictive) uncertainty estimates within satellite aerosol optical depth (AOD) data sets, providing users with quantitative tools to assist in the optimal use of these data. Prognostic estimates contrast with diagnostic (i.e. relative to some external truth) ones, which are typically obtained using sensitivity and/or validation analyses. Up to now, however, the quality of these uncertainty estimates has not been routinely assessed. This study presents a review of existing prognostic and diagnostic approaches for quantifying uncertainty in satellite AOD retrievals, and it presents a general framework to evaluate them based on the expected statistical properties of ensembles of estimated uncertainties and actual retrieval errors. It is hoped that this framework will be adopted as a complement to existing AOD validation exercises; it is not restricted to AOD and can in principle be applied to other quantities for which a reference validation data set is available. This framework is then applied to assess the uncertainties provided by several satellite data sets (seven over land, five over water), which draw on methods from the empirical to sensitivity analyses to formal error propagation, at 12 Aerosol Robotic Network (AERONET) sites. The AERONET sites are divided into those for which it is expected that the techniques will perform well and those for which some complexity about the site may provide a more severe test. Overall, all techniques show some skill in that larger estimated uncertainties are generally associated with larger observed errors, although they are sometimes poorly calibrated (i.e. too small or too large in magnitude). No technique uniformly performs best. For powerful formal uncertainty propagation approaches such as optimal estimation, the results illustrate some of the difficulties in appropriate population of the covariance matrices required by the technique. When the data sets are confronted by a situation strongly counter to the retrieval forward model (e.g. potentially mixed land–water surfaces or aerosol optical properties outside the family of assumptions), some algorithms fail to provide a retrieval, while others do but with a quantitatively unreliable uncertainty estimate. The discussion suggests paths forward for the refinement of these techniques.

Satellite instruments provide a vantage point for studying aerosol loading consistently over different regions of the world. However, the typical lifetime of a single satellite platform is on the order of 5–15 years; thus, for climate studies, the use of multiple satellite sensors should be considered. Discrepancies exist between aerosol optical depth (AOD) products due to differences in their information content, spatial and temporal sampling, calibration, cloud masking, and algorithmic assumptions. Users of satellite-based AOD time-series are confronted with the challenge of choosing an appropriate dataset for the intended application. In this study, 16 monthly AOD products obtained from different satellite sensors and with different algorithms were inter-compared and evaluated against Aerosol Robotic Network (AERONET) monthly AOD. Global and regional analyses indicate that products tend to agree qualitatively on the annual, seasonal and monthly timescales but may be offset in magnitude. Several approaches were then investigated to merge the AOD records from different satellites and create an optimised AOD dataset. With few exceptions, all merging approaches lead to similar results, indicating the robustness and stability of the merged AOD products. We introduce a gridded monthly AOD merged product for the period 1995–2017. We show that the quality of the merged product is as least as good as that of individual products. Optimal agreement of the AOD merged product with AERONET further demonstrates the advantage of merging multiple products. This merged dataset provides a long-term perspective on AOD changes over different regions of the world, and users are encouraged to use this dataset.

Recently, the aerosol microphysics submodel MADE3 (Modal Aerosol Dynamics model for Europe, adapted for global applications, third generation) was introduced as a successor to MADE and MADE-in. It includes nine aerosol species and nine lognormal modes to represent aerosol particles of three different mixing states throughout the aerosol size spectrum. Here, we describe the implementation of the most recent version of MADE3 into the ECHAM/MESSy Atmospheric Chemistry (EMAC) general circulation model, including a detailed evaluation of a 10-year aerosol simulation with MADE3 as part of EMAC.We compare simulation output to station network measurements of near-surface aerosol component mass concentrations, to airborne measurements of aerosol mass mixing ratio and number concentration vertical profiles, to ground-based and airborne measurements of particle size distributions, and to station network and satellite measurements of aerosol optical depth. Furthermore, we describe and apply a new evaluation method, which allows a comparison of model output to size-resolved electron microscopy measurements of particle composition. Although there are indications that fine-mode particle deposition may be underestimated by the model, we obtained satisfactory agreement with the observations. Remaining deviations are of similar size to those identified in other global aerosol model studies.Thus, MADE3 can be considered ready for application within EMAC. Due to its detailed representation of aerosol mixing state, it is especially useful for simulating wet and dry removal of aerosol particles, aerosol-induced formation of cloud droplets and ice crystals as well as aerosol–radiation interactions. Besides studies on these fundamental processes, we also plan to use MADE3 for a reassessment of the climate effects of anthropogenic aerosol perturbations.

The last deglaciation represents the most recent example of natural global warming associated with large-scale climate changes. In addition to the long-term global temperature increase, the last deglaciation onset is punctuated by a sequence of abrupt changes in the Northern Hemisphere. Such interplay between orbital- and millennial-scale variability is widely documented in paleoclimatic records but the underlying mechanisms are not fully understood. Limitations arise from the difficulty in constraining the sequence of events between external forcing, high- and low- latitude climate, and environmental changes.Greenland ice cores provide sub-decadal-scale records across the last deglaciation and contain fingerprints of climate variations occurring in different regions of the Northern Hemisphere. Here, we combine new ice d-excess and 17O-excess records, tracing changes in the midlatitudes, with ice δ18O records of polar climate. Within Heinrich Stadial 1, we demonstrate a decoupling between climatic conditions in Greenland and those of the lower latitudes. While Greenland temperature remains mostly stable from 17.5 to 14.7 ka, significant change in the midlatitudes of the northern Atlantic takes place at ∼ 16.2 ka, associated with warmer and wetter conditions of Greenland moisture sources. We show that this climate modification is coincident with abrupt changes in atmospheric CO2 and CH4 concentrations recorded in an Antarctic ice core. Our coherent ice core chronological framework and comparison with other paleoclimate records suggests a mechanism involving two-step freshwater fluxes in the North Atlantic associated with a southward shift of the Intertropical Convergence Zone.

Numerical prediction of aerosol particle properties has become an important activity at many research and operational weather centers. This development is due to growing interest from a diverse set of stakeholders, such as air quality regulatory bodies, aviation and military authorities, solar energy plant managers, climate services providers, and health professionals. Owing to the complexity of atmospheric aerosol processes and their sensitivity to the underlying meteorological conditions, the prediction of aerosol particle concentrations and properties in the numerical weather prediction (NWP) framework faces a number of challenges. The modeling of numerous aerosol-related parameters increases computational expense. Errors in aerosol prediction concern all processes involved in the aerosol life cycle including (a) errors on the source terms (for both anthropogenic and natural emissions), (b) errors directly dependent on the meteorology (e.g., mixing, transport, scavenging by precipitation), and (c) errors related to aerosol chemistry (e.g., nucleation, gas–aerosol partitioning, chemical transformation and growth, hygroscopicity). Finally, there are fundamental uncertainties and significant processing overhead in the diverse observations used for verification and assimilation within these systems. Indeed, a significant component of aerosol forecast development consists in streamlining aerosol-related observations and reducing the most important errors through model development and data assimilation. Aerosol particle observations from satellite- and ground-based platforms have been crucial to guide model development of the recent years and have been made more readily available for model evaluation and assimilation. However, for the sustainability of the aerosol particle prediction activities around the globe, it is crucial that quality aerosol observations continue to be made available from different platforms (space, near surface, and aircraft) and freely shared. This paper reviews current requirements for aerosol observations in the context of the operational activities carried out at various global and regional centers. While some of the requirements are equally applicable to aerosol–climate, the focus here is on global operational prediction of aerosol properties such as mass concentrations and optical parameters. It is also recognized that the term requirements is loosely used here given the diversity in global aerosol observing systems and that utilized data are typically not from operational sources. Most operational models are based on bulk schemes that do not predict the size distribution of the aerosol particles. Others are based on a mix of bin and bulk schemes with limited capability of simulating the size information. However the next generation of aerosol operational models will output both mass and number density concentration to provide a more complete description of the aerosol population. A brief overview of the state of the art is provided with an introduction on the importance of aerosol prediction activities. The criteria on which the requirements for aerosol observations are based are also outlined. Assimilation and evaluation aspects are discussed from the perspective of the user requirements.

Aerosol-layer height is essential for understanding the impact of aerosols on the climate system. As part of the European Space Agency Aerosol_cci project, aerosol-layer height as derived from passive thermal and solar satellite sensors measurements have been compared with aerosol-layer heights estimated from CALIOP measurements. The Aerosol_cci project targeted dust-type aerosol for this study. This ensures relatively unambiguous aerosol identification by the CALIOP processing chain. Dust-layer height was estimated from thermal IASI measurements using four different algorithms (from BIRA-IASB, DLR, LMD, LISA) and from solar GOME-2 (KNMI) and SCIAMACHY (IUP) measurements. Due to differences in overpass time of the various satellites, a trajectory model was used to move the CALIOP-derived dust heights in space and time to the IASI, GOME-2 and SCIAMACHY dust height pixels. It is not possible to construct a unique dust-layer height from the CALIOP data. Thus two CALIOP-derived layer heights were used: the cumulative extinction height defined as the height where the CALIOP extinction column is half of the total extinction column, and the geometric mean height, which is defined as the geometrical mean of the top and bottom heights of the dust layer. In statistical average over all IASI data there is a general tendency to a positive bias of 0.5–0.8 km against CALIOP extinction-weighted height for three of the four algorithms assessed, while the fourth algorithm has almost no bias. When comparing geometric mean height there is a shift of −0.5 km for all algorithms (getting close to zero for the three algorithms and turning negative for the fourth). The standard deviation of all algorithms is quite similar and ranges between 1.0 and 1.3 km. When looking at different conditions (day, night, land, ocean), there is more detail in variabilities (e.g. all algorithms overestimate more at night than during the day). For the solar sensors it is found that on average SCIAMACHY data are lower by −1.097 km (−0.961 km) compared to the CALIOP geometric mean (cumulative extinction) height, and GOME-2 data are lower by −1.393 km (−0.818 km).

The question of how to derive and present uncertainty information in climate data records (CDRs) has received sustained attention within the European Space Agency Climate Change Initiative (CCI), a programme to generate CDRs addressing a range of essential climate variables (ECVs) from satellite data. Here, we review the nature, mathematics, practicalities, and communication of uncertainty information in CDRs from Earth observations. This review paper argues that CDRs derived from satellite-based Earth observation (EO) should include rigorous uncertainty information to support the application of the data in contexts such as policy, climate modelling, and numerical weather prediction reanalysis. Uncertainty, error, and quality are distinct concepts, and the case is made that CDR products should follow international metrological norms for presenting quantified uncertainty. As a baseline for good practice, total standard uncertainty should be quantified per datum in a CDR, meaning that uncertainty estimates should clearly discriminate more and less certain data. In this case, flags for data quality should not duplicate uncertainty information, but instead describe complementary information (such as the confidence in the uncertainty estimate provided or indicators of conditions violating the retrieval assumptions). The paper discusses the many sources of error in CDRs, noting that different errors may be correlated across a wide range of timescales and space scales. Error effects that contribute negligibly to the total uncertainty in a single-satellite measurement can be the dominant sources of uncertainty in a CDR on the large space scales and long timescales that are highly relevant for some climate applications. For this reason, identifying and characterizing the relevant sources of uncertainty for CDRs is particularly challenging. The characterization of uncertainty caused by a given error effect involves assessing the magnitude of the effect, the shape of the error distribution, and the propagation of the uncertainty to the geophysical variable in the CDR accounting for its error correlation properties. Uncertainty estimates can and should be validated as part of CDR validation when possible. These principles are quite general, but the approach to providing uncertainty information appropriate to different ECVs is varied, as confirmed by a brief review across different ECVs in the CCI. User requirements for uncertainty information can conflict with each other, and a variety of solutions and compromises are possible. The concept of an ensemble CDR as a simple means of communicating rigorous uncertainty information to users is discussed. Our review concludes by providing eight concrete recommendations for good practice in providing and communicating uncertainty in EO-based climate data records.

Basal ice is a common expression to describe bottom ice layers of glaciers, ice caps and ice sheets in which the ice is primarily conditioned by processes operating at the bed. It is chemically and/or physically distinct from the ice above and can be characterized by a component of basally derived sediments. The study of basal ice properties provides a rare opportunity to improve our understanding of subglacial environments and processes and to refine ice sheet behaviour modelling. Here, we present and discuss the results of water stable isotopes (δ18O and δD), ice fabrics, debris weight/size distribution and gas content of the basal part of the NEEM (North Greenland Eemian Ice Drilling Project) ice core. Below a depth of 2533.85 m, almost 10 m of basal debris-rich material was retrieved from the borehole, and regular occurrence of frozen sediments with only interstitial ice lenses in the bottom 5 m suggest that the ice–bedrock interface was reached. The sequence is composed of an alternation of three visually contrasting types of ice: clear ice with specks (very small amounts) of particulate inclusions, stratified debris-rich layers and ice containing dispersed debris. The use of water stable isotope signatures (δ18O and δD), together with other parameters, allows discrimination between the different types of ice and to unravel the processes involved in their formation and transformation. The basal debris-rich material presents δ18O values [−39.9 ‰; −34.4 ‰] within the range of the above last 300 m of unaltered meteoric ice [−44.9 ‰; −30.6 ‰] spanning a glacial-interglacial range of values. This rules out the hypothesis of a basal ice layer originating from pre-ice sheet ice overridden by the growing ice sheet, as previously suggested e.g. in the case of GRIP (Greenland Ice Core Project). We show that clear basal ice with specks corresponds to altered meteoric glacial ice where some of the climatic signal could have been preserved. However, the stratified debris-rich layers and the ice containing dispersed debris layers respectively express an “open” or “closed” system melting/refreezing signature, somewhat blurred by mixing processes in the upper part of the sequence. Climatic reconstruction is therefore prohibited from these ice types. We propose a first interpretative framework for the build-up of the NEEM basal ice sequence, based on the origin of the various ice types.

Whereas ice cores from high-accumulation sites in coastal Antarctica clearly demonstrate annual layering, it is debated whether a seasonal signal is also preserved in ice cores from lower-accumulation sites further inland and particularly on the East Antarctic Plateau. In this study, we examine 5 m of early Holocene ice from the Dome Fuji (DF) ice core at a high temporal resolution by continuous flow analysis. The ice was continuously analysed for concentrations of dust, sodium, ammonium, liquid conductivity, and water isotopic composition. Furthermore, a dielectric profiling was performed on the solid ice. In most of the analysed ice, the multi-parameter impurity data set appears to resolve the seasonal variability although the identification of annual layers is not always unambiguous. The study thus provides information on the snow accumulation process in central East Antarctica. A layer counting based on the same principles as those previously applied to the NGRIP (North Greenland Ice core Project) and the Antarctic EPICA (European Project for Ice Coring in Antarctica) Dronning Maud Land (EDML) ice cores leads to a mean annual layer thickness for the DF ice of 3.0 ± 0.3 cm that compares well to existing estimates. The measured DF section is linked to the EDML ice core through a characteristic pattern of three significant acidity peaks that are present in both cores. The corresponding section of the EDML ice core has recently been dated by annual layer counting and the number of years identified independently in the two cores agree within error estimates. We therefore conclude that, to first order, the annual signal is preserved in this section of the DF core. This case study demonstrates the feasibility of determining annually deposited strata on the central East Antarctic Plateau. It also opens the possibility of resolving annual layers in the Eemian section of Antarctic ice cores where the accumulation is estimated to have been greater than in the Holocene.

Combined records of snow accumulation rate, δ18O and deuterium excess were produced from several shallow ice cores and snow pits at NEEM (North Greenland Eemian Ice Drilling), covering the period from 1724 to 2007. They are used to investigate recent climate variability and characterise the isotope–temperature relationship. We find that NEEM records are only weakly affected by inter-annual changes in the North Atlantic Oscillation. Decadal δ18O and accumulation variability is related to North Atlantic sea surface temperature and is enhanced at the beginning of the 19th century. No long-term trend is observed in the accumulation record. By contrast, NEEM δ18O shows multidecadal increasing trends in the late 19th century and since the 1980s. The strongest annual positive δ18O values are recorded at NEEM in 1928 and 2010, while maximum accumulation occurs in 1933. The last decade is the most enriched in δ18O (warmest), while the 11-year periods with the strongest depletion (coldest) are depicted at NEEM in 1815–1825 and 1836–1846, which are also the driest 11-year periods. The NEEM accumulation and δ18O records are strongly correlated with outputs from atmospheric models, nudged to atmospheric reanalyses. Best performance is observed for ERA reanalyses. Gridded temperature reconstructions, instrumental data and model outputs at NEEM are used to estimate the multidecadal accumulation–temperature and δ18O–temperature relationships for the strong warming period in 1979–2007. The accumulation sensitivity to temperature is estimated at 11 ± 2 % °C−1 and the δ18O–temperature slope at 1.1 ± 0.2 ‰ °C−1, about twice as large as previously used to estimate last interglacial temperature change from the bottom part of the NEEM deep ice core.

Glacial climate was characterised by two types of abrupt events. Greenland ice cores record Dansgaard–Oeschger events, marked by abrupt warming in-between cold, stadial phases. Six of these stadials appear related to major Heinrich events (HEs), identified from ice-rafted debris (IRD) and large excursions in carbon- and oxygen-stable isotopic ratios in North Atlantic deep sea sediments, documenting major ice sheet collapse events. This finding has led to the paradigm that glacial cold events are induced by the response of the Atlantic Meridional Overturning Circulation to such massive freshwater inputs, supported by sensitivity studies conducted with climate models of various complexities. These models also simulate synchronous Greenland temperature and lower-latitude hydrological changes. To investigate the sequence of events between climate changes at low latitudes and in Greenland, we provide here the first 17O-excess record from a Greenland ice core during Dansgaard–Oeschger events 7 to 13, encompassing H4 and H5. Combined with other ice core proxy records, our new 17O-excess data set demonstrates that stadials are generally characterised by low 17O-excess levels compared to interstadials. This can be interpreted as synchronous change of high-latitude temperature and lower-latitude hydrological cycle (relative humidity at the oceanic source of evaporation or change in the water mass trajectory/recharge) and/or an influence of local temperature on 17O-excess through kinetic effect at snow formation. As an exception from this general pattern, stadial 9 consists of three phases, characterised first by Greenland cooling during 550 ± 60 years (as shown by markers of Greenland temperature δ18O and δ15N), followed by a specific lower-latitude fingerprint as identified from several proxy records (abrupt decrease in 17O-excess, increase in CO2 and methane mixing ratio, heavier δD-CH4 and δ18Oatm), lasting 740 ± 60 years, itself ending approximately 390 ± 50 years prior to abrupt Greenland warming. We hypothesise that this lower-latitude signal may be the fingerprint of Heinrich event 4 in Greenland ice cores. The proposed decoupling between stable cold Greenland temperature and low-latitude climate variability identified for stadial 9 provides new targets for benchmarking climate model simulations and testing mechanisms associated with millennial variability.

The Northeast Greenland Ice Stream (NEGIS) is the sole interior Greenlandic ice stream. Fast flow initiates near the summit dome, and the ice stream terminates approximately 1000 km downstream in three large outlet glaciers that calve into the Greenland Sea. To better understand this important system, in the summer of 2012 we drilled a 67 m firn core and conducted ground-based radio-echo sounding (RES) and active-source seismic surveys at a site approximately 150 km downstream from the onset of streaming flow (NEGIS firn core, 75°37.61' N, 35°56.49' W). The site is representative of the upper part of the ice stream, while also being in a crevasse-free area for safe surface operations. Annual cycles were observed for insoluble dust, sodium and ammonium concentrations and for electrolytic conductivity, allowing a seasonally resolved chronology covering the past 400 yr. Annual layer thicknesses averaged 0.11 m ice equivalent (i.e.) for the period 1607–2011, although accumulation varied between 0.08 and 0.14 m i.e., likely due to flow-related changes in surface topography. Tracing of RES layers from the NGRIP (North Greenland Ice Core Project) ice core site shows that the ice at NEGIS preserves a climatic record of at least the past 51 kyr. We demonstrate that deep ice core drilling in this location can provide a reliable Holocene and late-glacial climate record, as well as helping to constrain the past dynamics and ice–lithosphere interactions of the Greenland Ice Sheet.

Ice cores at Siple Dome, West Antarctica, receive the majority of their precipitation from Pacific Ocean moisture sources. Pacific climate patterns, particularly the El Niño–Southern Oscillation (ENSO) and the Southern Annular Mode (SAM), affect local temperature, atmospheric circulation, snow accumulation, and water isotope signals at Siple Dome. We examine borehole temperatures, accumulation, and water isotopes from a number of shallow ice cores recovered from a 60 km north–south transect of the dome. The data reveal spatial gradients partly explained by orographic uplift, as well as microclimate effects that are expressed differently on the Pacific and inland flanks. Our analyses suggest that while an ENSO and SAM signal are evident at Siple Dome, differences in microclimate and possible postdepositional movement of snow makes climate reconstruction problematic, a conclusion which should be considered at other West Antarctic coastal dome locations.

Water stable isotopes in Greenland ice core data provide key paleoclimatic information, and have been compared with precipitation isotopic composition simulated by isotopically enabled atmospheric models. However, post-depositional processes linked with snow metamorphism remain poorly documented. For this purpose, monitoring of the isotopic composition (δ18O, δD) of near-surface water vapor, precipitation and samples of the top (0.5 cm) snow surface has been conducted during two summers (2011–2012) at NEEM, NW Greenland. The samples also include a subset of 17O-excess measurements over 4 days, and the measurements span the 2012 Greenland heat wave. Our observations are consistent with calculations assuming isotopic equilibrium between surface snow and water vapor. We observe a strong correlation between near-surface vapor δ18O and air temperature (0.85 ± 0.11‰ °C−1 (R = 0.76) for 2012). The correlation with air temperature is not observed in precipitation data or surface snow data. Deuterium excess (d-excess) is strongly anti-correlated with δ18O with a stronger slope for vapor than for precipitation and snow surface data. During nine 1–5-day periods between precipitation events, our data demonstrate parallel changes of δ18O and d-excess in surface snow and near-surface vapor. The changes in δ18O of the vapor are similar or larger than those of the snow δ18O. It is estimated using the CROCUS snow model that 6 to 20% of the surface snow mass is exchanged with the atmosphere. In our data, the sign of surface snow isotopic changes is not related to the sign or magnitude of sublimation or deposition. Comparisons with atmospheric models show that day-to-day variations in near-surface vapor isotopic composition are driven by synoptic variations and changes in air mass trajectories and distillation histories. We suggest that, in between precipitation events, changes in the surface snow isotopic composition are driven by these changes in near-surface vapor isotopic composition. This is consistent with an estimated 60% mass turnover of surface snow per day driven by snow recrystallization processes under NEEM summer surface snow temperature gradients. Our findings have implications for ice core data interpretation and model–data comparisons, and call for further process studies.

We present here surface water vapor isotopic measurements conducted from June to August 2010 at the NEEM (North Greenland Eemian Drilling Project) camp, NW Greenland (77.45° N, 51.05° W, 2484 m a.s.l.). Measurements were conducted at 9 different heights from 0.1 m to 13.5 m above the snow surface using two different types of cavity-enhanced near-infrared absorption spectroscopy analyzers. For each instrument specific protocols were developed for calibration and drift corrections. The inter-comparison of corrected results from different instruments reveals excellent reproducibility, stability, and precision with a standard deviations of ~ 0.23‰ for δ18O and ~ 1.4‰ for δD. Diurnal and intraseasonal variations show strong relationships between changes in local surface humidity and water vapor isotopic composition, and with local and synoptic weather conditions. This variability probably results from the interplay between local moisture fluxes, linked with firn–air exchanges, boundary layer dynamics, and large-scale moisture advection. Particularly remarkable are several episodes characterized by high (> 40‰) surface water vapor deuterium excess. Air mass back-trajectory calculations from atmospheric analyses and water tagging in the LMDZiso (Laboratory of Meteorology Dynamics Zoom-isotopic) atmospheric model reveal that these events are associated with predominant Arctic air mass origin. The analysis suggests that high deuterium excess levels are a result of strong kinetic fractionation during evaporation at the sea-ice margin.

The Toba eruption that occurred some 74 ka ago in Sumatra, Indonesia, is among the largest volcanic events on Earth over the last 2 million years. Tephra from this eruption has been spread over vast areas in Asia, where it constitutes a major time marker close to the Marine Isotope Stage 4/5 boundary. As yet, no tephra associated with Toba has been identified in Greenland or Antarctic ice cores. Based on new accurate dating of Toba tephra and on accurately dated European stalagmites, the Toba event is known to occur between the onsets of Greenland interstadials (GI) 19 and 20. Furthermore, the existing linking of Greenland and Antarctic ice cores by gas records and by the bipolar seesaw hypothesis suggests that the Antarctic counterpart is situated between Antarctic Isotope Maxima (AIM) 19 and 20. In this work we suggest a direct synchronization of Greenland (NGRIP) and Antarctic (EDML) ice cores at the Toba eruption based on matching of a pattern of bipolar volcanic spikes. Annual layer counting between volcanic spikes in both cores allows for a unique match. We first demonstrate this bipolar matching technique at the already synchronized Laschamp geomagnetic excursion (41 ka BP) before we apply it to the suggested Toba interval. The Toba synchronization pattern covers some 2000 yr in GI-20 and AIM-19/20 and includes nine acidity peaks that are recognized in both ice cores. The suggested bipolar Toba synchronization has decadal precision. It thus allows a determination of the exact phasing of inter-hemispheric climate in a time interval of poorly constrained ice core records, and it allows for a discussion of the climatic impact of the Toba eruption in a global perspective. The bipolar linking gives no support for a long-term global cooling caused by the Toba eruption as Antarctica experiences a major warming shortly after the event. Furthermore, our bipolar match provides a way to place palaeo-environmental records other than ice cores into a precise climatic context.