Aron P G, Li S, Brooks J R, Welker J M, Levin N E
Department of Earth and Environmental Sciences, University of Michigan, Ann Arbor, MI, USA.
Now at Hazen and Sawyer, Baltimore, MD, USA.
Paleoceanogr Paleoclimatol. 2023 Mar 13;38(4). doi: 10.1029/2022pa004458.
Triple oxygen isotope ratios offer new opportunities to improve reconstructions of past climate by quantifying evaporation, relative humidity, and diagenesis in geologic archives. However, the utility of in paleoclimate applications is hampered by a limited understanding of how precipitation values vary across time and space. To improve applications of , we present , -excess, and data from 26 precipitation sites in the western and central United States and three streams from the Willamette River Basin in western Oregon. In this data set, we find that precipitation tracks evaporation but appears insensitive to many controls that govern variation in , including Rayleigh distillation, elevation, latitude, longitude, and local precipitation amount. Seasonality has a large effect on variation in the data set and we observe higher seasonally amount-weighted average precipitation values in the winter (40 ± 15 per meg [± standard deviation]) than in the summer (18 ± 18 per meg). This seasonal precipitation variability likely arises from a combination of sub-cloud evaporation, atmospheric mixing, moisture recycling, sublimation, and/or relative humidity, but the data set is not well suited to quantitatively assess isotopic variability associated with each of these processes. The seasonal pattern, which is absent in -excess and opposite in sign from , appears in other data sets globally; it showcases the influence of seasonality on values of precipitation and highlights the need for further systematic studies to understand variation in values of precipitation.
三重氧同位素比率为通过量化地质记录中的蒸发、相对湿度和成岩作用来改进过去气候重建提供了新机会。然而，由于对降水δ值如何随时间和空间变化的理解有限，其在古气候应用中的效用受到了阻碍。为了改进δ的应用，我们展示了美国西部和中部26个降水站点以及俄勒冈州西部威拉米特河流域三条溪流的δ、δ-过量和δ数据。在这个数据集中，我们发现降水δ跟踪蒸发，但对许多控制δ变化的因素不敏感，包括瑞利蒸馏、海拔、纬度、经度和当地降水量。季节性对数据集中的δ变化有很大影响，我们观察到冬季季节性加权平均降水δ值（每百万分率40±15[±标准差]）高于夏季（每百万分率18±18）。这种季节性降水δ变异性可能源于云下蒸发、大气混合、水分再循环、升华和/或相对湿度的综合作用，但该数据集不太适合定量评估与这些过程中每一个相关的同位素变异性。季节性δ模式在δ-过量中不存在且与δ符号相反，在全球其他数据集中也有出现；它展示了季节性对降水δ值的影响，并强调需要进一步进行系统研究以了解降水δ值的变化。
