Year
Month
(Peer-Reviewed) Worldwide impacts of atmospheric vapor pressure deficit on the interannual variability of terrestrial carbon sinks
Bin He 何斌 ¹, Chen Chen ², Shangrong Lin ³, Wenping Yuan 袁文平 ³, Hans W Chen ⁴, Deliang Chen 陈德亮 ⁵, Yafeng Zhang 张亚峰 ¹, Lanlan Guo 郭兰兰 ¹ ⁶, Xiang Zhao 赵祥 ⁷, Xuebang Liu ¹, Shilong Piao 朴世龙 ⁸, Ziqian Zhong ¹, Rui Wang ¹, Rui Tang ¹
¹ State Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China
中国 北京 北京师范大学地表过程与资源生态国家重点实验室, 北京师范大学全球变化与地球系统科学研究院
² Twenty First Century Aerospace Technology Co., Ltd., Beijing 100723, China
中国 北京 二十一世纪空间技术应用股份有限公司
³ School of Atmospheric Sciences, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University, Zhuhai 519082, China
中国 珠海 中山大学南方海洋科学与工程广东省实验室(珠海)
⁴ Department of Physical Geography and Ecosystem Science, Lund University, Lund S-223 64, Sweden
⁵ Regional Climate Group, Department of Earth Sciences, University of Gothenburg, Gothenburg S-40530, Sweden
⁶ Academy of Disaster Reduction and Emergency Management, School of Geography, Beijing Normal University, Beijing 100875, China
中国 北京 北京师范大学地理科学学部减灾与应急管理研究院
⁷ State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
中国 北京 北京师范大学遥感科学国家重点实验室,北京师范大学地理科学学部
⁸ Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
中国 北京 北京大学中法地球系统科学中心,北京大学城市与环境学院
National Science Review, 2021-08-20
Abstract

Interannual variability of the terrestrial ecosystem carbon sink is substantially regulated by various environmental variables and highly dominates the interannual variation of atmospheric carbon dioxide (CO2) concentrations. Thus, it is necessary to determine dominating factors affecting the interannual variability of the carbon sink to improve our capability of predicting future terrestrial carbon sinks.

Using global datasets derived from machine learning methods and process-based ecosystem models, this study reveals that the interannual variability of the atmospheric vapor pressure deficit (VPD) was significantly negatively correlated with net ecosystem production (NEP) and substantially impacted the interannual variability of the atmospheric CO2 growth rate (CGR). Further analyses found widespread constraints of VPD interannual variability on terrestrial gross primary production (GPP), causing VPD to impact NEP and CGR.

Partial correlation analysis confirms the persistent and widespread impacts of VPD on terrestrial carbon sinks compared to other environmental variables. Current Earth system models underestimate the interannual variability in VPD and its impacts on GPP and NEP. Our results highlight the importance of VPD for terrestrial carbon sinks in assessing ecosystems’ responses to future climate conditions.
Worldwide impacts of atmospheric vapor pressure deficit on the interannual variability of terrestrial carbon sinks_1
Worldwide impacts of atmospheric vapor pressure deficit on the interannual variability of terrestrial carbon sinks_2
Worldwide impacts of atmospheric vapor pressure deficit on the interannual variability of terrestrial carbon sinks_3
Worldwide impacts of atmospheric vapor pressure deficit on the interannual variability of terrestrial carbon sinks_4
  • Halide perovskite-based metasurfaces: structure design, performance regulation, and optoelectronic applications
  • Junxue Liu, Ying Su, Zibo Gao, Yinghan Li, Jingyuan Jia, Dequn Zhang, Yijing Mao, Tun Cao
  • Opto-Electronic Manufacturing
  • 2026-09-25
  • Electrically switchable bright-field and interference-synthesized edge-enhanced imaging with a polarization-multiplexed metalens
  • Xiaotong Li, Junhwa Seong, Yeseul Kim, Kwang-Suk Oh, Shiqi Hu, Le Dai, Harit Keawmuang, Beomha Yang, Minseok Choi, Youngsun Jeon, Cherry Park, Weiyan Li, Tianxu Jia, Han Zhu, Xiaodong Cai, Qi Zheng, Jinhui Shi, Young-Ki Kim, Yuchuan Shao, Trevon Badloe, Junsuk Rho
  • Opto-Electronic Science
  • 2026-09-20
  • Multiphysics optimization framework for high-power fiber amplifiers
  • Wei Liu, Zan Cheng, Pengfei Ma, Yisha Chen, Huan Yang, Zhiyong Pan, Zefeng Wang, Jinbao Chen
  • Opto-Electronic Science
  • 2026-09-20
  • 3D-printed copper water cooling system assisted fabrication of 10.6-μm high-power CO₂ laser resistance reflectors
  • Hongfei Jiao, Binbin Jiang, Xinshang Niu, Yifan Wang, Dongdong Li, Jun Yu, Xiaochuan Ji, Jingjing Xia, Jinlong Zhang, Xinbin Cheng, Zhanshan Wang
  • Opto-Electronic Advances
  • 2026-09-15
  • Pixel-controlled programmable metasurface as phase-type spatial terahertz modulator
  • Guibin Li, Guanyi Li, Zehao He, Xinke Wang, Peter J. Klar, He Ma, Yan Zhang
  • Opto-Electronic Advances
  • 2026-09-15
  • Spatiotemporal beam stirring in a multicore fiber
  • Alena Y. Kolesnikova, Mikhail D. Gervaziev, Nikita V. Bochkarev, Denis S. Kharenko, Evgeniy V. Podivilov, Sergey A. Babin
  • Opto-Electronic Advances
  • 2026-09-15
  • Ultrafast all-optical modulation of wide-bandwidth pulses enabled by silicon-metasurfaces
  • Kaloyan Georgiev, Khosro Zangeneh Kamali, Anton A. Trifonov, Giulia Crotti, Lyuben Petrov, Stefan Georgiev, Hristo Iliev, Lei Xu, Unai Arregui Leon, Mohsen Rahmani, Giuseppe Della Valle, Ivan Buchvarov, Dragomir Neshev
  • Opto-Electronic Advances
  • 2026-09-15
  • Physics-informed neural fields enable blind aberration correction for partially coherent quantitative phase imaging
  • Shun Zhou, Xingyu Huang, Linpeng Lu, Habib Ullah, Kaiyu Du, Maciej Trusiak, Malgorzata Kujawinska, Yuzhen Zhang, Yao Fan, Qian Chen, Qinrong Zhang, Chao Zuo
  • Opto-Electronic Science
  • 2026-08-26
  • Programmable directional photonic spiking neuron based on a non-Hermitian silicon microresonator
  • Stefano Biasi, Bülent Aslan, Stefano Gretter, Davide Olivieri, Alessandro Foradori, Riccardo Franchi, Lorenzo Pavesi
  • Opto-Electronic Science
  • 2026-08-26
  • Mutual empowerment of artificial intelligence and metasurfaces: intelligent nanophotonics and optical intelligence
  • Yu Zhao, Zile Li, Yongquan Zeng, Shaohua Yu, Guoxing Zheng
  • Opto-Electronic Science
  • 2026-08-26



  • Neural Architecture Dilation for Adversarial Robustness                                From aniline to phenol: carbon-nitrogen bond activation via uranyl photoredox catalysis
    About
    |
    Contact
    |
    Copyright © PubCard