Editorial Type:
Article
Article Type:
Research Article

Interdecadal Climate Variations Controlling the Water Level of Lake Qinghai over the Tibetan Plateau

Lin Zhao Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, Gansu, China, and Department of Plants, Soils, and Climate, Utah State University, Logan, Utah

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S.-Y. Simon Wang Utah Climate Center, and Department of Plants, Soils, and Climate, Utah State University, Logan, Utah

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Jonathan Meyer Utah Climate Center, and Department of Plants, Soils, and Climate, Utah State University, Logan, Utah

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Print Publication:
01 Nov 2017
DOI:
https://doi.org/10.1175/JHM-D-17-0071.1
Page(s):
3013–3025
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Abstract

Using observed and reanalysis data, the pronounced interdecadal variations of Lake Qinghai (LQH) water levels and associated climate factors were diagnosed. From the 1960s to the early 2000s, the water level of LQH in the Tibetan Plateau has experienced a continual decline of 3 m but has since increased considerably. A water budget analysis of the LQH watershed suggested that the water vapor flux divergence is the dominant atmospheric process modulating precipitation and subsequently the lake volume change . The marked interdecadal variability in and was found to be related to the North Pacific (NP) and Pacific decadal oscillation (PDO) modes during the cold season (November–March). Through empirical orthogonal function (EOF) and regression analyses, the water vapor sink over the LQH watershed also responds significantly to the summer Eurasian wave train modulated by the low-frequency variability associated with the cold season NP and PDO modes. Removal of these variability modes (NP, PDO, and the Eurasian wave train) led to a residual uptrend in the hydrological variables of , , and precipitation, corresponding to the net water level increase. Attribution analysis using the Coupled Model Intercomparison Project phase 5 (CMIP5) single-forcing experiments shows that the simulations driven by greenhouse gas forcing produced a significant increase in the LQH precipitation, while anthropogenic aerosols generated a minor wetting trend as well.

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/JHM-D-17-0071.s1.

© 2017 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: Lin Zhao, zhaolin_110@lzb.ac.cn

Abstract

Using observed and reanalysis data, the pronounced interdecadal variations of Lake Qinghai (LQH) water levels and associated climate factors were diagnosed. From the 1960s to the early 2000s, the water level of LQH in the Tibetan Plateau has experienced a continual decline of 3 m but has since increased considerably. A water budget analysis of the LQH watershed suggested that the water vapor flux divergence is the dominant atmospheric process modulating precipitation and subsequently the lake volume change . The marked interdecadal variability in and was found to be related to the North Pacific (NP) and Pacific decadal oscillation (PDO) modes during the cold season (November–March). Through empirical orthogonal function (EOF) and regression analyses, the water vapor sink over the LQH watershed also responds significantly to the summer Eurasian wave train modulated by the low-frequency variability associated with the cold season NP and PDO modes. Removal of these variability modes (NP, PDO, and the Eurasian wave train) led to a residual uptrend in the hydrological variables of , , and precipitation, corresponding to the net water level increase. Attribution analysis using the Coupled Model Intercomparison Project phase 5 (CMIP5) single-forcing experiments shows that the simulations driven by greenhouse gas forcing produced a significant increase in the LQH precipitation, while anthropogenic aerosols generated a minor wetting trend as well.

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/JHM-D-17-0071.s1.

© 2017 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: Lin Zhao, zhaolin_110@lzb.ac.cn

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