Search

The isotopic composition of water vapour provides integrated perspectives on the hydrological histories of air masses and has been widely used for tracing physical processes in hydrological and climatic studies. Over the last two decades, the infrared laser spectroscopy technique has been used to measure the isotopic composition of water vapour near the Earths surface. Here, we have assembled a global database of high temporal resolution stable water vapour isotope ratios (δ18O and δD) observed using this measurement technique. As of March 2018, the database includes data collected at 35 sites in 15 Köppen climate zones from the years 2004 to 2017. The key variables in each dataset are hourly values of δ18O and δD in atmospheric water vapour. To support interpretation of the isotopologue data, synchronized time series of standard meteorological variables from in situ observations and ERA5 reanalyses are also provided. This database is intended to serve as a centralized platform allowing researchers to share their vapour isotope datasets, thus facilitating investigations that transcend disciplinary and geographic boundaries.

We document the isotopic evolution of near-surface snow at the East Greenland Ice Core Project (EastGRIP) ice core site in northeast Greenland using a time-resolved array of 1 m deep isotope (δ18O , δD) profiles. The snow profiles were taken from May–August during the 2017–2019 summer seasons. An age–depth model was developed and applied to each profile, mitigating the impacts of stratigraphic noise on isotope signals. Significant changes in deuterium excess (d) are observed in surface snow and near-surface snow as the snow ages. Decreases in d of up to 5 ‰ occur during summer seasons after deposition during two of the three summer seasons observed. The d always experiences a 3 ‰–5 ‰ increase after aging 1 year in the snow due to a broadening of the autumn d maximum. Models of idealized scenarios coupled with prior work indicate that the summertime post-depositional changes in d (Δd) can be explained by a combination of surface sublimation, forced ventilation of the near-surface snow down to 20–30 cm , and isotope-gradient-driven diffusion throughout the column. The interannual Δd is also partly explained with isotope-gradient-driven diffusion, but other mechanisms are at work that leave a bias in the d record. Thus, d does not just carry information about source-region conditions and transport history as is commonly assumed, but also integrates local conditions into summer snow layers as the snow ages through metamorphic processes. Finally, we observe a dramatic increase in the seasonal isotope-to-temperature sensitivity, which can be explained solely by isotope-gradient-driven diffusion. Our results are dependent on the site characteristics (e.g., wind, temperature, accumulation rate, snow properties) but indicate that more process-based research is necessary to understand water isotopes as climate proxies. Recommendations for monitoring and physical modeling are given, with special attention to the d parameter. [ABSTRACT FROM AUTHOR]

A versatile vapor generation module has been developed for both field-based water vapor isotope calibrations and laboratory-based liquid water isotope measurements. The vapor generation module can generate a stream of constant vapor at a wide variety of humidity levels spanning 300 to 30 000 ppmv and is fully scalable, allowing in principle an unlimited number of standards or samples to be connected to a water vapor isotope analyzer. This versatility opens up the possibility for calibrating with multiple standards during field deployment, including examining instrument humidity–isotope dependence. Utilizing the ability to generate an uninterrupted constant stream of vapor, we document an Allan deviation for 17O -excess (Δ17O) of less than 2 per meg for an approximate 3 h averaging time. For similar averaging time, the Allan deviations for δ17O , δ18O , δ D, and d-excess are 0.004 ‰, 0.005 ‰, 0.01 ‰, and 0.04 ‰, respectively. Measuring unknown samples shows that it is possible to obtain an average standard deviation of 3 per meg for Δ17O and an average standard error (95 % confidence limit) of 5 per meg. Using the vapor generation module, we document that an increase in the Allan deviation above the white noise level for integration times between 10 min and 1 h is caused by cyclic variations in the cavity temperature, which if improved upon could result in an improvement in liquid sample measurement precision of up to a factor of 2. We further argue that increases in Allan deviation for longer averaging times could be a result of memory effects and not only driven by instrumental drifts as it is often interpreted. The vapor generation module as a calibration system has been documented to generate a constant water vapor stream for more than 90 h, showing the feasibility of being used to integrate measurements over much longer periods than achievable with syringe-based injections as well as allowing the analysis of instrument performance and noise. Using clean in-house standards, we have operated the vapor generation module daily for 1–3 h for more than 6 months without the need for maintenance, illustrating its potential as a field-deployed autonomous vapor isotope calibration unit. When operating the vapor generation module for laboratory-based liquid water isotope measurements, we document a more than 2 times lower memory effect compared to a standard autosampler system. [ABSTRACT FROM AUTHOR]

Water stable isotope records in polar ice cores have been largely used to reconstruct past local temperatures and other climatic information such as evaporative source region conditions of the precipitation reaching the ice core sites. However, recent studies have identified post-depositional processes taking place at the ice sheet's surface modifying the original precipitation signal and challenging the traditional interpretation of ice core isotopic records. In this study, we use a combination of existing and new datasets of the precipitation, snow surface and subsurface isotopic compositions (δ18O and d-excess), meteorological parameters, ERA5 reanalyses, outputs from the isotope-enabled climate model ECHAM6-wiso, and a simple modelling approach to investigate the transfer function of water stable isotopes from precipitation to the snow surface and subsurface at Dome C, in East Antarctica. We first show that water vapor fluxes at the surface of the ice sheet result in a net annual sublimation of snow, from 3.1 to 3.7 mm water equivalent per year between 2018 and 2020, corresponding to 12 to 15 % of the annual surface mass balance. We find that the precipitation isotopic signal cannot fully explain the mean, nor the variability of the isotopic composition observed in the snow, from annual to intra-monthly timescales. We observe that the mean effect of post-depositional processes over the study period enriches the snow surface in δ18O by 3.3 ‰ to 6.6 ‰ and lowers the snow surface d-excess by 3.5 ‰ to 7.6 ‰ compared to the incoming precipitation isotopic signal. We also show that the mean isotopic composition of the subsurface snow is not statistically different from that of the surface snow, indicating the preservation of the mean isotopic composition of the surface snow in the top centimetres of the snowpack. This study confirms previous findings about the complex interpretation of the water stable isotopic signal in the snow and provides the first quantitative estimation of the impact of post-depositional processes on the snow isotopic composition at Dome C, a crucial step for the accurate interpretation of isotopic records from ice cores. [ABSTRACT FROM AUTHOR]

We document the isotopic evolution of near-surface snow at the EastGRIP ice core site in the Northeast Greenland National Park using a time-resolved array of 1-m deep isotope (δ18 O , δ D) profiles. The snow profiles were taken from May–August during the 2017–2019 summer seasons. An age-depth model was developed and applied to each profile mitigating the impacts of stratigraphic noise on isotope signals. Significant changes in deuterium excess (d) are observed in surface snow and near-surface snow as the snow ages. Decreases in d of up to 5 ‰ occurs during summer seasons after deposition during two of the three summer seasons observed. The d always experiences a 3–5 ‰ increase in d after aging one year in the snow due to a broadening of the autumn d maximum. Models of idealized scenarios coupled with prior work (Wahl et al., 2022) indicate that the summertime post-depostional changes in d (Δ d) can be explained with surface sublimation, forced ventilation of the near-surface snow down to 20–30 cm, and isotope-gradient-driven (IGD) diffusion throughout the column. The interannual Δ d is also partly explained with IGD diffusion, but other mechanisms are at work that leave a bias in the d record. Thus, d does not just carry information about source region conditions and transport history as is commonly assumed, but also integrates local conditions into summer snow layers as the snow ages. Finally, we observe a dramatic increase in the seasonal isotope-to-temperature sensitivity occurs, which can be explained solely by IGD diffusion. Our results are dependent on the site characteristics (e.g. wind, temperature, accumulation rate), but indicate that more process-based research is necessary to understand water isotopes as climate proxies. Recommendations for monitoring and physical modeling are given, with special attention to the d parameter. [ABSTRACT FROM AUTHOR]

Surface processes alter the water stable isotope signal of the surface snow after deposition. However, it remains an open question to which extent surface post‐depositional processes should be considered when inferring past climate information from ice core records. Here, we present simulations for the Greenland Ice Sheet, combining outputs from two climate models with an isotope‐enabled snowpack model. We show that surface vapor exchange and associated fractionation imprint a climate signal into the firn, resulting in an increase in the annual mean value of δ18O by +2.3‰ and a reduction in d‐excess by −6.3‰. Further, implementing isotopic fractionation during surface vapor exchange improves the representation of the observed seasonal amplitude in δ18O from 65.0% to 100.2%. Our results stress that surface vapor exchange is important in the climate proxy signal formation and needs consideration when interpreting ice core climate records. Plain Language Summary: The climate information contained in falling snow is modified by exchange processes with the atmosphere after the snow has fallen to the surface. It is important to understand how this modification affects the interpretation of past climate information from ice core isotope records. In this study, we combined outputs from two climate models to simulate the climate signal in a snow core on the Greenland Ice Sheet. We evaluate the snow core model using snow observations from the Greenland Ice Sheet. By simulating snow cores with and without the modification at the surface, we find a considerable impact of the surface modification on the climate signal in the snow core. Further, considering the surface modification causes an improved representation of the seasonal changes compared to observations. Our findings highlight the importance of surface processes in forming climate information contained in ice cores and underscore the need to include these processes in the ice core interpretation. Key Points: Water isotopic fractionation during vapor exchange significantly affects the simulated annual and seasonal isotope climate signal in ice coresThe simulated seasonal amplitude of the δ18O signal in the snowpack improves when including surface vapor exchange induced fractionationA phase shift in the simulated seasonal maximum in d‐excess toward early autumn is induced by vapor exchange, consistent with observations [ABSTRACT FROM AUTHOR]

Stable water isotopes stored in snow, firn and ice are used to reconstruct environmental parameters. The imprint of these parameters at the snow surface as well as their preservation in the upper snowpack is determined by a number of processes influencing the recording of the environmental signal. Here, we present a dataset of approximately 3800 snow samples analysed for their stable water isotope composition which were obtained during the summer season at the deep drilling site of the East Greenland Ice Core Project in northeast Greenland. Sampling was carried out every third day between 14 May and 3 August 2018 along a 39 m long transect. Three depth intervals in the top 10 cm were sampled on 30 positions with a higher resolution closer to the surface (0 - 1 cm and 1 - 4 cm depth vs. 4 - 10 cm). The sample analysis was carried out at two renowned stable water isotope laboratories and produced isotope data with an overall highest uncertainty of 0.09° for δ18O and 0.8° for δD. This unique dataset shows strongest δ18O variability closest to the surface, damped and delayed variations in the lowest layer and a trend towards increasing homogeneity towards the end of the season, especially in the deepest layer. Additional information on the snow height and its temporal changes suggests a non-uniform spatial imprint of the seasonal climatic information in this area potentially following the stratigraphic noise of the surface. The data can be used to study the relation between snow height (changes) as well as the imprint and preservation of the isotopic composition at a site with 10 - 14 cmw.eq. yr-1 accumulation. The high temporal resolution sampling allows additional analyses on (post-)depositional processes, such as vapour-snow exchange. The data can be accessed at https://doi.pangaea.de/10.1594/PANGAEA.956626 (Zuhr et al., 2023). [ABSTRACT FROM AUTHOR]

A versatile vapor generation module has been developed for the purpose of both field water vapor isotope calibrations and laboratory liquid water isotope measurements. The vapor generation module is fully scalable allowing in principle an unlimited number of standards or samples to be connected, opening up the possibility for calibrating with multiple standards during field deployment. Compared to a standard autosampler system, the vapor generation module has a more than 2 times lower memory effect. The vapor generation module can in principle generate a constant stream of vapor with constant isotopic composition indefinitely. We document an Allan Deviation for 17O-excess (Δ17O) of less than 2 per meg for an approximate 3 hour averaging time. For similar averaging time the Allan Deviation for δ17O, δ18O, δD, d-excess is 0.004, 0.006, 0.01, 0.03 %. Measuring unknown samples show that it is possible to obtain an average standard deviation of 3 per meg leading to an average standard error (95 % confidence limit) using 4–5 replicates of 5 per meg. Using the vapor generation module we document that an enhancement in the Allan Deviation above the white noise level for integration times between 10 minutes and 1 hour is caused by cyclic variations in the cavity temperature. We further argue that increases in Allan Deviation for longer averaging times could be a result of memory effects and not only driven by instrumental drifts as it is often interpreted as. The vapor generation module as a calibration system have been document to generate a constant water vapor stream for a period of more than 90 hours showing the feasibility of being used as an autonomous field vapor isotope calibration unit for more than 3 months. [ABSTRACT FROM AUTHOR]

The Jurupa Unified School District in Southern California recently partnered with Microsoft, Dell and the Zone Integration Group for the implementation of a School Interoperability Framework (SIF) database repository model throughout the district (Magner 2002). A two-week project--the Integrated District Education Applications System, better known as New IDEAS--targeted the effective adoption of an integrated IT platform that would enable the district to automate routine tasks, integrate data across the district's core applications and drive process improvements. Budget constraints, coupled with increasing demands from local, state and federal requirements for data reporting, made it imperative that the district carefully maximize all investments in upgraded technologies. By optimizing processes in order to incorporate the ability to aggregate and share data across core systems, as well as by making this information readily available to all constituent groups throughout the district, technological and budgetary goals would be met. The results of this project are detailed in this article.