Extreme precipitation stable isotopic compositions reveal unexpected summer monsoon incursions in the Qilian Mountains

Zhao, Liang; Dong, Xiying; Liu, Xiaohong; Wang, Ninglian; Eastoe, Christopher J.; Wei, Na; Xie, Chunyi; Liu, Huan; Han, Chuntan; Hua, Ting; Wang, Lixin

doi:10.1016/j.scitotenv.2023.165743

Cited by 10 publications

(5 citation statements)

References 69 publications

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“…Furthermore, the spatial analysis revealed a steady extension of the temperature increase trend from north to south. The cooling area is mainly distributed in the Qaidam Basin, which is at a relatively low altitude, and the atmospheric circulation may be the main reason for the temperature decline [54]. During the study period, about 55.24% of the TP experienced an increase in precipitation, with a trend of 1.80 mm/10a.…”

Section: Correlation Between Ndvi and Climate Changementioning

confidence: 97%

Normal Difference Vegetation Index Simulation and Driving Analysis of the Tibetan Plateau Based on Deep Learning Algorithms

Liu,

Du,

et al. 2024

Forests

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Global climate warming has profoundly affected terrestrial ecosystems. The Tibetan Plateau (TP) is an ecologically vulnerable region that emerged as an ideal place for investigating the mechanisms of vegetation response to climate change. In this study, we constructed an annual synthetic NDVI dataset with 500 m resolution based on MOD13A1 products from 2000 to 2021, which were extracted by the Google Earth Engine (GEE) and processed by the Kalman filter. Furthermore, considering topographic and climatic factors, a thorough analysis was conducted to ascertain the causes and effects of the NDVI’s spatiotemporal variations on the TP. The main findings are: (1) The vegetation coverage on the TP has been growing slowly over the past 22 years at a rate of 0.0134/10a, with a notable heterogeneity due to its topography and climate conditions. (2) During the study period, the TP generally showed a “warming and humidification” trend. The influence of human activities on vegetation growth has exhibited a favorable trajectory, with a notable acceleration observed since 2011. (3) The primary factor influencing NDVI in the southeastern and western regions of the TP was the increasing temperature. Conversely, vegetation in the northeastern and central regions was mostly regulated by precipitation. (4) Combined with the principal component analysis, a PCA-CNN-LSTM (PCL) model demonstrated significant superiority in modeling NDVI sequences on the Tibetan Plateau. Understanding the results of this paper is important for the sustainable development and the formulation of ecological policies on the Tibetan Plateau.

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Section: Correlation Between Ndvi and Climate Changementioning

confidence: 97%

Normal Difference Vegetation Index Simulation and Driving Analysis of the Tibetan Plateau Based on Deep Learning Algorithms

Liu,

Du,

et al. 2024

Forests

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“…The deuterium excess (d‐excess = δ 2 H − 8 × δ 18 O) quantifies the non‐equilibrium isotopic fractionation (Dansgaard, 1964) and serves as an effective tracer of moisture conditions in moisture source region. Based on the coverage of the global network of isotopes of precipitation (GNIP), numerous studies have identified various factors affecting the variation of precipitation δ 18 O (δ 18 O p ), such as moisture source sites (Shi et al, 2021), atmospheric transport processes (Zhang et al, 2004), latitude (Liu, Song, et al, 2008; Liu, Tian, et al, 2008; Valdivielso et al, 2022), altitude (Yao et al, 2009), and local meteorological elements (Guo et al, 2017; Xie et al, 2022; Zhao et al, 2023). In addition, d‐excess mainly depends on the meteorological conditions (e.g., relative humidity, sea surface temperature, wind speed) at the oceanic moisture source (Gat et al, 2003), and more studies in recent years have shown that local evaporation and changes in the hydrological cycle also have an impact on it (Parkes et al, 2017; Tian et al, 2020; Wang et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

“…Previous research has revealed that the northward progression of the monsoon zone is highly variable in both the interannual and interdecadal term, influenced by fluctuations in monsoon intensity (Tan & Gong, 2022). The Indian summer monsoon has been observed to surmount the highlands and extend to the central Tibetan Plateau (Dai et al, 2021; Li et al, 2023; Yu et al, 2021), with some years of heightened activity even reaching the northeast (Gui et al, 2020; Li et al, 2015; Xie et al, 2022; Zhao et al, 2023). This process is accompanied by strong convection, leading to a significant depletion of stable isotopic compositions of precipitation and atmospheric vapour.…”

Section: Introductionmentioning

confidence: 99%

Stable isotopic compositions and controlling factors of precipitation and atmospheric vapour in the headwaters of the Shule River

Zhang,

Zhao,

Wang

et al. 2024

Hydrological Processes

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Stable isotopic compositions of precipitation (δ18Op, δ2Hp and d‐excessp) and atmospheric vapour (δ18Ov, δ2Hv and d‐excessv) with high spatial–temporal resolution are crucial in revealing hydrologic cycle. Based on the variation characteristics of δ18Op/δ18Ov, δ2Hp/δ2Hv and d‐excessp/d‐excessv in the headwaters of the Shule River (HSR) on hourly and daily scales from June to September 2018, this study analysed the relationships between δ18Op/δ2Hp and δ18Ov/δ2Hv combined with the equilibrium fractionation model, as well as δ18Op/δ18Ov and meteorological factors. The slopes of local meteoric water line (LMWL) and the δ2Hv‐δ18Ov fitting equation were similar (7.96 and 7.94) with both intercepts exceeding 10, reflecting the great contribution of recycling moisture. The values of δ18Ov/δ2Hv were lower than δ18Op/δ2Hp but with consistent variation patterns throughout the period. The equilibrium simulation results suggested that precipitation and atmospheric vapour almost approached isotopic equilibrium state, especially during monsoon intrusion period. Affected by monsoon intrusion, the slopes and intercepts of the LMWLs and the δ2Hv‐δ18Ov fitting equations were smaller than those during non‐monsoon period and d‐excess and δ18O were negatively correlated. Relative humidity had significant negative correlations with δ18Op and δ18Ov in the whole period, however, the positive correlations between δ18Op/δ18Ov and temperature were observed during non‐monsoon and monsoon intrusion period, respectively. Our results demonstrated that precipitation and atmospheric vapour isotopic compositions exhibited consistency under the influence of diverse moisture sources, while more complex relationships were found between δ18Op/δ18Ov and meteorological factors. This research provided evidence for using the isotopic compositions of atmospheric vapour to indicate moisture sources, and can improve understanding of the water cycle and eco‐hydrological process from the perspective of the interaction between water and gas phases of the inland river basin in northwest China.

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“…Isotope tracer methods, which pay attention to different stable isotopes of hydrogen (δ 2 H) and oxygen (δ 18 O) in water samples, have also been developed to study moisture sources (Yu et al, 2014). Given the differences in isotopic characteristics of regions, isotope tracer methods can distinguish moisture sources for regional precipitation (Zhao et al, 2023). In the meantime, it is noted that isotopic analysis can be hindered by the lack of spatiotemporally consistent data due to limited stations for collecting precipitation samples (Lykoudis & Argiriou, 2011).…”

Section: Introductionmentioning

confidence: 99%

Moisture sources of precipitation over the Pearl River Basin in South China

Liu,

Guo,

Zhang

et al. 2024

Intl Journal of Climatology

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Moisture sources and transport processes play a critical part in hydrological cycle and determine regional precipitation. This paper utilizes the Water Accounting Model‐2layers (WAM‐2layers) and the ERA5 reanalysis data to track the sources of precipitation over the Pearl River Basin (PRB). The contribution of external moisture and the role of local recycling are investigated. The results show that during the period from 1980 to 2020, oceanic sources including the western North Pacific and Indian Oceans serve as the primary moisture sources of precipitation over the PRB. The contributions to total seasonal precipitation are respectively 62.57% in MAM, 54.79% in JJA, 43.70% in SON and 60.88% in DJF. By contrast, the contribution of local recycling is generally below 5.50%. In the dry years of 1994, 1997 and 2001, the contribution of terrestrial sources is about 19.22%; in the wet years of 1989, 2009 and 2011, the contribution is about 16.31%. The summer precipitation anomalies are mainly attributable to moisture anomalies from the Equatorial Indian Ocean in the wet years and from Southeast Asia in the dry years. Furthermore, vertically integrated moisture flux anomalies over the boundaries of the PRB are generally the result of anomalous wind rather than anomalous moisture. In the wet years, low‐pressure systems induce strong cyclonic moisture transports, increasing the PRB precipitation. In the dry years, high‐pressure anomalies over the PRB block the moisture transports from the Indian Ocean and western North Pacific.

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Extreme precipitation stable isotopic compositions reveal unexpected summer monsoon incursions in the Qilian Mountains

Cited by 10 publications

References 69 publications

Normal Difference Vegetation Index Simulation and Driving Analysis of the Tibetan Plateau Based on Deep Learning Algorithms

Normal Difference Vegetation Index Simulation and Driving Analysis of the Tibetan Plateau Based on Deep Learning Algorithms

Stable isotopic compositions and controlling factors of precipitation and atmospheric vapour in the headwaters of the Shule River

Moisture sources of precipitation over the Pearl River Basin in South China

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