Paleoclimate data assimilation: Its motivation, progress and prospects

被引:0
|
作者
FANG Miao [1 ,2 ]
LI Xin [1 ,3 ]
机构
[1] Cold and Arid Regions Environment and Engineering Research, Chinese Academy of Sciences
[2] University of Chinese Academy of Sciences
[3] Center for Excellence in Tibetan Plateau Earth Sciences, Chinese Academy of Sciences
基金
中国国家自然科学基金;
关键词
Climate reconstruction; Paleoclimate modeling; Proxies; Data assimilation;
D O I
暂无
中图分类号
P532 [古气候学];
学科分类号
摘要
Reconstructing past climate is beneficial for researchers to understand the mechanism of past climate change, recognize the context of modern climate change and predict scenarios of future climate change. Paleoclimate data assimilation(PDA), which was first introduced in 2000, is a promising approach and a significant issue in the context of past climate research. PDA has the same theoretical basis as the traditional data assimilation(DA) employed in the fields of atmosphere science, ocean science and land surface science. The main aim of PDA is to optimally estimate past climate states that are both consistent with the climate signal recorded in proxy and the dynamic understanding of the climate system through combining the physical laws and dynamic mechanisms of climate systems represented by climate models with climate signals recorded in proxies(e.g., tree rings, ice cores). After investigating the research status and latest advances of PDA abroad, in this paper, the background, concept and methodology of PAD are briefly introduced. Several special aspects and the development history of PAD are systematically summarized. The theoretical basis and typical cases associated with three frequently-used PAD methods(e.g., nudging, particle filter and ensemble square root filter) are analyzed and demonstrated. Finally, some underlying problems in current studies and key prospects in future research related to PDA are proposed to provide valuable thoughts on and a scientific basis for PDA research.
引用
收藏
页码:1817 / 1826
页数:10
相关论文
共 50 条
  • [21] Pliocene Warmth and Patterns of Climate Change Inferred From Paleoclimate Data Assimilation
    Tierney, Jessica E.
    King, Jonathan
    Osman, Matthew B.
    Abell, Jordan T.
    Burls, Natalie J.
    Erfani, Ehsan
    Cooper, Vincent T.
    Feng, Ran
    AGU ADVANCES, 2025, 6 (01):
  • [22] Reconstructing paleoclimate fields using online data assimilation with a linear inverse model
    Perkins, Walter A.
    Hakim, Gregory J.
    CLIMATE OF THE PAST, 2017, 13 (05) : 421 - 436
  • [23] Recent progress of data assimilation methods in meteorology
    Tsuyuki, Tadashi
    Miyoshi, Takemasa
    JOURNAL OF THE METEOROLOGICAL SOCIETY OF JAPAN, 2007, 85B : 331 - 361
  • [24] Data Assimilation and its Applications
    Sharan, Maithili
    Issartel, Jean Pierre
    PURE AND APPLIED GEOPHYSICS, 2012, 169 (03) : 309 - 310
  • [25] THE WINDPROOF SPRAYER - ITS PROGRESS AND PROSPECTS
    ROGERS, RB
    FORD, RJ
    AGRICULTURAL ENGINEERING, 1985, 66 (11): : 11 - 13
  • [26] Data assimilation and its applications
    Wang, B
    Zou, XL
    Zhu, J
    PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2000, 97 (21) : 11143 - 11144
  • [27] Some progress on ocean data assimilation in China: Introduction of the special section “Ocean Data Assimilation”
    Huizan Wang
    Yan Chen
    Weimin Zhang
    Acta Oceanologica Sinica, 2022, 41 : 1 - 2
  • [28] Data Assimilation and its Applications
    Maithili Sharan
    Jean Pierre Issartel
    Pure and Applied Geophysics, 2012, 169 : 309 - 310
  • [29] Some progress on ocean data assimilation in China: Introduction of the special section “Ocean Data Assimilation”
    Huizan Wang
    Yan Chen
    Weimin Zhang
    Acta Oceanologica Sinica, 2022, 41 (02) : 1 - 2
  • [30] Some progress on ocean data assimilation in China: Introduction of the special section "Ocean Data Assimilation"
    Wang, Huizan
    Chen, Yan
    Zhang, Weimin
    ACTA OCEANOLOGICA SINICA, 2022, 41 (02) : 1 - 2