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From a global perspective, the stable isotope altitude effect is crucial for understanding climate information. However, the intensity of this effect can be influenced by the source of moisture, particularly in inland mountainous regions where the moisture sources are complex. Different combinations of moisture sources might affect the altitude effect. Focusing on the upper Shiyang River in the northern part of the Qilian Mountains in China, this study calculated the proportion of recycled moisture in precipitation and utilized the HYSPLIT model to determine the source of advective moisture. It explored the characteristics and mechanisms by which moisture sources affect the spatiotemporal variations in precipitation isotope effects within the study area. The findings indicated that: (a) The altitude effect follows a seasonal pattern: winter < autumn < spring < summer, with a reverse effect in winter. (b) As the contribution of recycled moisture to precipitation increases, the altitude effect of stable isotopes weakens, primarily due to the disruptive influence of recycled moisture on this effect. (c) The altitude effect of stable isotopes in precipitation is determined by the direction of the moisture source and its attributes. When the primary source of advective moisture runs perpendicular to the mountain range and the moisture migration speed is slow, the altitude effect is pronounced. Thus, although temperature directly causes the altitude effect, water vapor sources significantly influence it in inland mountainous regions. Key Points The altitude effect has significant seasonal variation, being strong in summer and weakest in winter The contribution of recirculating water vapor to precipitation is large, weakening the altitude effect The source of water vapor and the nature of the air masses contribute to the differences in elevation effects

Understanding and modeling precipitation isotope (δ18O and δD) patterns for large regions of the globe requires quantifying processes governing continental‐scale climatology and hydrology. In this study, we have evaluated the extent to which inclusion of monthly moisture source temperature and moisture source locations in the Rayleigh distillation model aid in reproducing the relationships between monthly time series of precipitation isotope (δ18O) values and temperature across the contiguous United States. The steepest isotope‐temperature slopes (0.5‰–0.6‰ δ18O/°C) and greatest δ18O value correlations with temperature (r2 = 0.5–0.8), derived from 5 continuous years of the data from the United States Network for Isotopes in Precipitation, occurred in the high altitudes of the Rocky Mountains and the upper Great Lakes region. The isotope‐temperature slopes derived from the site‐specific time series were consistently lower along the coastal regions of the United States as were the coefficients of determination. The low coastal isotope‐temperature slopes are not easily explained by the simple Rayleigh model that uses condensation temperatures as the primary driver of precipitation isotopes. However, the Raleigh model equipped with moisture source temperatures defined by seasonal temperature oscillations and migrating moisture source locations provides a robust replication of the δ18O‐temperature slopes along coastal regions. These findings emphasize the importance of moisture sources conditions when interpreting palaeoclimate proxies (i.e., tree rings, ice cores, etc.), and argue that moisture source dynamics should always be included in models that use isotopes as diagnostic tools in testing hydrologic models.

Studies about the hydrological cycle based on basin or regional scales often ignore the uniqueness of recycling moisture in mountain areas, and little effort has been made to understand the impact of the local recycled moisture on precipitation in mountain areas. We collected and analyzed a series of samples (stable isotope of precipitation, soil water, plant water, runoff, and groundwater) in the Qilian Mountains, northwest of China. Based on the isotopic mixing model, the characteristics of recycled moisture in the Qilian Mountains were evaluated. The results showed that lateral advection moisture is the primary source of precipitation (83.5~98.38%). The contribution rate of recycled moisture to precipitation was higher in the spring, summer, and autumn (2.05~16.5%), and lower in the winter (1.62~3.32%). The contribution of recycled moisture to precipitation in the high-elevation areas (>2400 m) was higher than that in the foothills area (2100~2400 m). The contribution of vegetation transpiration (fTr) to precipitation in the east of Qilian Mountain was higher than that of the land surface evaporation (fEv). These proved that in the eastern part of Qilian Mountain, the arge-scale water cycle has a greater impact on precipitation in the area. The influence of local circulating water on precipitation dominated in the summer half of the year. Understanding the contribution of local circulating water to precipitation in the eastern part of Qilian Mountain will help us to understand the local hydrothermal conditions better and provide a basis for rationally arranging local agricultural production activities.

Sub-cloud evaporation changes the isotopic composition of precipitation, which greatly reduces the reliability of precipitation isotopic data as precipitation simulation data. This study employed the precipitation isotope datasets of Haikou in northern Hainan Island from June 2020 to February 2024 to quantitatively study the influence of sub-cloud evaporation on precipitation isotopes in tropical islands. Due to the sub-cloud evaporation, the slope of the local meteoric water line (LMWL: δ2H = 8.33δ18O + 14.33) is lower than the average slope of the theoretical LMWL (8.48). The average value of the residual ratios of raindrop after evaporation (f) is 86%. The complex and unstable sources of water vapor result in no obvious seasonal variations in the atmospheric humidity, which in turn leads to no obvious seasonal variations in Δd and f. The humid and hot environmental conditions reduced the impact of sub-cloud evaporation on precipitation isotopes. The two main uncertainties in the simulation of below-cloud evaporation are the influence of recycled water vapor on precipitation isotopes and the Stewart model’s assumption that raindrops at the cloud base achieve isotopic equilibrium with the surrounding water vapor, as it is difficult to realize. The results of this study are of great significance for improving the accuracy of precipitation simulation in tropical monsoon islands.

The ratio between the heavy and light stable isotopes in precipitation ( ) is an effective tool in answering questions in hydrology, climatology, biogeochemistry and other disciplines, but only if spatiotemporally sufficient data is available provided by precipitation monitoring networks. However, when gathered into large databases this can contain errors that can severely impact research outcomes. The present study aims to systematically identify and propose, for the first time, a screening procedure and possible adequate solution(s) to database errors detected in precipitation stable isotope monitoring networks in a reproducible way. The proposed approach is a distance-based outlier detection variant heavily relying on empirical inspection of spatially clustered time series. The core of the methodology consisted of screening the (i) O vs. H cross plot and (ii) station time-series, and comparing them to their neighbors by organizing the monitoring stations into spatial domains. Potential errors were categorized into (i) point anomalies (isolated erroneous data points) and (ii) interval anomalies (sustained errors over time). The approach is demonstrated on the Austrian Network for Isotopes in Precipitation, a data base that collects data on a monthly basis since 1972 with more than 70 active stations at its peak in 2014. In this sense, it is a crucial backbone for understanding hydrological processes in Central Europe. At 10 stations only point anomalies were found, at six stations only interval anomalies (Achenkirch, Bad Bleiberg, Hütten, Lahn, Salzburg, Schoppernau), and at five (Apetlon, Podersdorf, Saalfelden, Villacher Alps, Weyregg) both kind of anomalies were detected. By addressing these errors case-by-case the reliability of a precipitation isotope database for hydrological and climatological research could be enhanced.

Precipitation isoscapes have provided supporting data for numerous studies of water stable isotopes, alleviating the lack of observation data. However, the applicability of simulation data from global models to specific regional contexts remains a subject requiring further investigation, particularly concerning d-excess—an aspect often overlooked by prediction models. To bridge this gap, this study evaluates the performance of three mainstream precipitation isoscapes (OIPC3.2, RCWIP1, and RCWIP2) for the prediction of average annual δ[sup.2]H, δ[sup.18]O, and d-excess based on observations from the CHNIP database. The results show that while all three models can accurately reproduce δ[sup.2]H and δ[sup.18]O values, none are able to accurately match d-excess values. This disparity can be attributed to the absence of water-vapor source information in the models’ input variables, a key determinant influencing d-excess outcomes. Additionally, it is noteworthy that OIPC3.2 stands out as the optimal choice for δ[sup.2]H and δ[sup.18]O estimations, while RCWIP2 exhibits progressive enhancements over RCWIP1 in d-excess estimations. This highlights the significance of selecting highly pluralistic information variables and recognizing the impact of error propagation in such models. As a result, the advancement of isoscapes in accurately and precisely depicting precipitation isotopes, particularly d-excess, necessitates further refinement. Future avenues for improvement might involve the incorporation of water-vapor source-clustering methodologies, the selection of information-rich variables, and the autonomous construction of a dedicated d-excess simulation. This research provides valuable insights for the further refining of isoscape modeling in the future.

Based on 360 event-based precipitation samples collected at six stations on the North Tibetan Plateau (NTP) in 2019–2020, we analyzed the influence of meteorological parameters, sub-cloud evaporation, moisture sources, and moisture transmission pathways on precipitation and its seasonal variations. The results show that precipitation δ18O, δ2H, and d-excess values show obvious seasonal variations, being depleted in winter and enriched in summer. Although temperature is an important variable that affects the change in δ18O values of precipitation, the results of the sub-cloud evaporation effect and moisture tracing show that differences in moisture sources caused by seasonal changes in large-scale water moisture transport are an important cause of seasonal changes in δ18O and d-excess of precipitation at NTP. Depleted δ18O and enriched d-excess in winter represent the source of moisture transported by the westerlies from the Mediterranean area and Central Asia. Enriched δ18O and d-excess values in summer precipitation are related to the temperature effect. In addition, the meridional motion of the atmospheric flow has an effect on the precipitation isotope values in the NTP. When the meridional circulation is enhanced, the water vapour from low latitudes is easily transported northwards, enriching the summer precipitation isotope values in the central and eastern parts of the plateau. This provides a new insight into the explanation of stable oxygen isotopes in climate proxies across the westerlies-dominated Tibetan Plateau.

To further our understanding of the Asian monsoon system, particularly the onset dates of monsoon sub-systems over their respective East Asian domains, we present an 8-year (2007–2014) dataset of oxygen isotopes of precipitation (δ18Op) from three stations, Lulang and Nuxia in southeastern Tibetan Plateau (SETP) and Guangzhou in southeastern coastal China (SECN). The general agreement between isotopically identified monsoon onset dates with those identified by the meridional temperature gradient suggests that the initially sustained isotopic depletion is sensitive to the evolving thermal contrast between the Eurasian continent and the Indian Ocean. The 850 hPa meridional wind over nearby oceans is an efficient bridge linking isotopic variations in both regions with their respective monsoon sub-systems. The intensity of the South Asian High and tropical cyclone frequencies show stronger effects on isotopic depletion in the SECN than in the SETP and on monsoon onset timing over the South China Sea. Tibetan Plateau snow cover anomalies are significantly correlated with δ18Op in both regions on monthly timescales.

A review of the isotopic composition of precipitation sampled from October 2020 to January 2022 at four locations in the Magadan oblast at a distance to 300 km from the shore of the Sea of Okhotsk is presented. It is shown that the isotopic composition of precipitation on the coast (the city of Magadan) differs significantly from the inland one in both values and  and   ratios. The air-mass back-trajectory analysis revealed that these differences are primarily caused by varying roles of different moisture sources forming precipitation.

This study presents a stable oxygen isotope (δ 18 O) record in daily precipitation from two sites located to the northeast of the Tibetan Plateau (TP): Yushu on the eastern TP and Xi'an on the eastern Chinese Loess Plateau. It attempts to reveal the unique features associated with variations in atmospheric circulation patterns over inland China. For δ 18 O in daily precipitation at both stations, temperature effect is significant (p < 0.01) only during non-monsoon, while amount effect is significant only during monsoon. This suggests the coexistence of local recycling with large-scale atmospheric circulation on regional precipitation, which is further verified by the significant correlation of relative humidity with δ 18 O at both stations during monsoon season. The similarity of δ 18 O in regions under the supposedly same atmospheric circulation streams is tested for Yushu with that at Lhasa, Lulang and Delingha, demonstrating the lag days of δ 18 O depletion at Yushu with that at Lulang as varying from 15 to 25 d. This confirms the Bay of Bengal monsoon dominance over Yushu. Daily δ 18 O at Xi'an is compared with contemporary data at Changsha and Guangzhou, featuring a close correlation with the East Asian summer monsoon evolution processes over eastern China, and reflecting the Meiyu-Baiu front influence during July. Back-trajectory analysis in October-November at Xi'an identified the combined effect of cooling of the atmospheric column by the colder air from the west and the lifting of the warmer air from the east, which coexists with local water vapour source. Interactions of the three result in condensation at lower temperatures that is coupled with the long-distance transport of 2/3 of the available water vapour, thus leading to extremely low δ 18 O values in the post-monsoon precipitation.