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Spatial and Seasonal Isotope Variability in Precipitation across China: Monthly Isoscapes Based on Regionalized Fuzzy Clustering

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  • 1 aCollege of Geography and Environmental Science, Northwest Normal University, Lanzhou, China
  • | 2 bKey Laboratory of Resource Environment and Sustainable Development of Oasis of Gansu Province, Lanzhou, China
  • | 3 cAustralian Nuclear Science and Technology Organisation, Kirrawee DC, New South Wales, Australia
  • | 4 dState Key Laboratory of Marine Geology, Tongji University, Shanghai, China
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Abstract

The spatial patterns of stable hydrogen and oxygen isotopes in precipitation (precipitation isoscapes) provide a geographic perspective to understand the atmospheric processes in modern environment and paleoclimate records. Here we compiled stable isotope data in modern precipitation at 223 sites across China and 48 in surrounding countries, and used regionalized fuzzy clustering to create monthly precipitation isoscapes for China (C-Isoscape). Based on regressions using spatial and climatic parameters for 12 months, the best-fitting equations were chosen for four climate clusters, and then the four layers were weighted using fuzzy membership. The moisture transportation path, controlled by the westerlies and the monsoon, results in different spatial and seasonal diversity of precipitation isotopes. Based on C-Isoscape, we determined a nationwide meteoric water line as δ2H = 7.4δ18O + 5.5 using least squares regression or δ2H = 8.0δ18O + 10.2 using precipitation weighted reduced major axis regression. Compared with previous global products, the C-Isoscape usually shows precipitation more enriched in 18O and 2H in summer and more depleted in winter for northwest China, while the C-Isoscape values are more enriched in heavy isotopes in most months for southwest China. The new monthly precipitation isoscapes provide an accurate and high-resolution mapping for Chinese precipitation isotopes, allowing for future intra-annual atmospheric process diagnostics using stable hydrogen and oxygen isotope in precipitation in the region.

© 2022 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Mingjun Zhang, mjzhang2004@163.com

Abstract

The spatial patterns of stable hydrogen and oxygen isotopes in precipitation (precipitation isoscapes) provide a geographic perspective to understand the atmospheric processes in modern environment and paleoclimate records. Here we compiled stable isotope data in modern precipitation at 223 sites across China and 48 in surrounding countries, and used regionalized fuzzy clustering to create monthly precipitation isoscapes for China (C-Isoscape). Based on regressions using spatial and climatic parameters for 12 months, the best-fitting equations were chosen for four climate clusters, and then the four layers were weighted using fuzzy membership. The moisture transportation path, controlled by the westerlies and the monsoon, results in different spatial and seasonal diversity of precipitation isotopes. Based on C-Isoscape, we determined a nationwide meteoric water line as δ2H = 7.4δ18O + 5.5 using least squares regression or δ2H = 8.0δ18O + 10.2 using precipitation weighted reduced major axis regression. Compared with previous global products, the C-Isoscape usually shows precipitation more enriched in 18O and 2H in summer and more depleted in winter for northwest China, while the C-Isoscape values are more enriched in heavy isotopes in most months for southwest China. The new monthly precipitation isoscapes provide an accurate and high-resolution mapping for Chinese precipitation isotopes, allowing for future intra-annual atmospheric process diagnostics using stable hydrogen and oxygen isotope in precipitation in the region.

© 2022 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Mingjun Zhang, mjzhang2004@163.com

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