Stable water isotopes are employed as hydrological tracers to quantify the diverse implications of atmospheric moisture for climate. They are widely used as proxies for studying past climate changes, e.g., in isotope records from ice cores and speleothems. Here, we present a new isotopic dataset of both near-surface vapour and ocean surface water from the North Pole to Antarctica, continuously measured from a research vessel throughout the Atlantic and Arctic Oceans during a period of two years. Our observations contribute to a better understanding and modelling of water isotopic composition. The observations reveal that the vapour deuterium excess within the atmospheric boundary layer is not modulated by wind speed, contrary to the commonly used theory, but controlled by relative humidity and sea surface temperature only. In sea ice covered regions, the sublimation of deposited snow on sea ice is a key process controlling the local water vapour isotopic composition.

Abstract. Continuous, in situ measurements of water vapor isotopic composition have been conducted in the North Atlantic, Bermuda Islands (32.26° N, 64.88° W) between November 2011 and June~2013, using a~cavity-ring-down-spectrometer water vapor isotope analyzer and an autonomous self-designed calibration system. Meticulous calibration allows us to reach an accuracy and precision on 10 min average of δ18O, δD, and d-excess of respectively 0.14 ‰, 0.85 ‰, and 1.1 ‰, verified using two parallel instruments with independent calibration. As a result of more than 500 days with 6 hourly data the relationships between deuterium excess, relative humidity (rh), sea surface temperature (SST), wind speed and direction are assessed. From the whole dataset, 84% of d-excess variance is explained by a strong linear relationship with relative humidity. The slope of this relationship (−42.6 ± 0.4 ‰ % (rh)) is similar to the theoretical prediction of Merlivat and Jouzel (1979) for SST between 20 °C and 30 °C. However, in contrast with theory, no effect of wind speed could be detected on the relationship between d-excess and relative humidity. Separating the dataset into winter, spring, summer, and autumn seasons reveals different linear relationships between d-excess and humidity. Changes in wind directions are observed to affect the relationships between d-excess and humidity. The observed seasonal variability in the relationship between d-excess and relative humidity underlines the importance of long-term monitoring to make accurate conclusions.

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