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The demanding precision of triple oxygen isotope (Δ17O) measurements in water has restricted their measurement to dual-inlet mass spectrometry until the recent development of commercially available infrared-laser analyzers. Laser-based measurements of triple oxygen isotope ratios are now increasingly performed by laboratories seeking to better constrain the source and history of meteoric waters. However, in practice, these measurements are subject to large analytical errors that remain poorly documented in scientific literature and by instrument manufacturers, which can effectively restrict the confident application of Δ17O to settings where variations are relatively large (~ 25-60 per meg). We present our operating method of a Picarro L2140-i cavity ringdown spectrometer during the analysis of low-latitude rainwaters where confidently resolving daily variations in Δ17O (differences of ~10-20 per meg) was desired. Our approach was optimized over ~3 years and uses a combination of published best-practices plus additional steps to combat spectral contamination of trace amounts of dissolved organics, which, for Δ17O, emerges as a much more substantial problem than previously documented, even in pure rainwater. We resolve the extreme sensitivity of the Δ17O measurement to organics through their removal via Picarro's micro-combustion module, whose performance is evaluated each sequence using alcohol-spiked standards. While correction for sample-to-sample memory and instrumental drift significantly improves traditional isotope metrics, these corrections have only marginal impact (0-1 per meg error reduction) on Δ17O. Our post-processing scheme uses the analyzer's high-resolution data, which improves δ2H measurement (0.25 ‰ error reduction) and allows for much more rich troubleshooting and data-processing compared to the default user-facing data output. In addition to competitive performance for traditional isotope metrics, we report a longterm, control standard root-mean-square-error for Δ17O of 11 per meg. Overall performance (Δ17O error of 7 per meg, calculated by averaging 3 replicates spread across distinct, independently calibrated sequences) is comparable to mass spectrometry and requires only ~6.3 h per sample. We demonstrate the impact of our approach using a rainfall dataset from Uganda and offer recommendations for other efforts that aim to measure meteoric Δ17O via CRDS. [ABSTRACT FROM AUTHOR]

Reconstructions of global hydroclimate during the Common Era (CE; the past ~ 2000 years) are important for providing context for current and future global environmental change. Stable isotope ratios in water are quantitative indicators of hydroclimate on regional to global scales, and these signals are encoded in a wide range of natural geologic archives. Here we present the Iso2k database, a global compilation of previously published datasets from a variety of natural archives that record the stable oxygen (δ18O) or hydrogen (δ²H) isotopic composition of environmental waters, which reflect hydroclimate changes over the CE. The Iso2k database contains 756 isotope records from the terrestrial and marine realms, including: glacier and ground ice (205); speleothems (68); corals, sclerosponges, and mollusks (145); wood (81); lake sediments and other terrestrial sediments (e.g., loess) (158); and marine sediments (99). Individual datasets have temporal resolutions ranging from sub-annual to centennial, and include chronological data where available. A fundamental feature of the database is its comprehensive metadata, which will assist both experts and non-experts in the interpretation of each record and in data synthesis. Key metadata fields have standardized vocabularies to facilitate comparisons across diverse archives and with climate model simulated fields. This is the first global-scale collection of water isotope proxy records from multiple types of geological and biological archives. It is suitable for evaluating hydroclimate processes through time and space using large-scale synthesis, model-data intercomparison and (paleo)data assimilation. The Iso2k database is available for download at: https://doi.org/10.6084/m9.figshare.11553162 (McKay and Konecky, 2020). [ABSTRACT FROM AUTHOR]