Reconstructing tropical monthly sea surface temperature variability by assimilating coral proxy datasets

被引：0

作者：

Hu, Wenqing ^{[1
]}

Ning, Liang ^{[1
,2
,3
]}

Liu, Zhengyu ^{[4
]}

Liu, Jian ^{[1
,5
]}

Wu, Fen ^{[1
]}

Yan, Mi ^{[1
,3
]}

Jiang, Leilei ^{[6
]}

Lei, Lili ^{[7
,8
]}

Xing, Fangmiao ^{[1
]}

Sun, Haohao ^{[7
,8
]}

Chen, Kefan ^{[1
]}

Qin, Yanmin ^{[1
]}

Sun, Weiyi ^{[1
]}

Wen, Qin ^{[1
]}

Li, Benyue ^{[1
]}

机构：

[1] Nanjing Normal Univ, Jiangsu Ctr Collaborat Innovat Geog Informat Reso, State Key Lab Cultivat Base Geog Environm Evolut, Key Lab Virtual Geog Environm,Minist Educ,Sch Geo, Nanjing, Peoples R China

[2] Univ Massachusetts, Climate Syst Res Ctr, Dept Geosci, Amherst, MA 01002 USA

[3] Chinese Acad Sci, Inst Earth Environm, State Key Lab Loess & Quaternary Geol, Xian, Peoples R China

[4] Ohio State Univ, Dept Geog, Columbus, OH 43210 USA

[5] Nanjing Normal Univ, Sch Math Sci, Jiangsu Prov Key Lab Numer Simulat Large Scale Com, Nanjing, Peoples R China

[6] Guangxi Univ, Coral Reef Res Ctr China, Sch Marine Sci, Guangxi Lab Study Coral Reefs South China Sea, Nanning, Peoples R China

[7] Nanjing Univ, Key Lab Mesoscale Severe Weather, Minist Educ, Nanjing, Peoples R China

[8] Nanjing Univ, Sch Atmospher Sci, Nanjing, Peoples R China

来源：

NPJ CLIMATE AND ATMOSPHERIC SCIENCE | 2024年 / 7卷 / 01期

基金：

中国国家自然科学基金;

关键词：

EL-NINO/SOUTHERN OSCILLATION; SOUTH CHINA SEA; CLIMATE; PACIFIC; NINO; ENSO; RECORDS; REANALYSIS; DELTA-O-18; FRAMEWORK;

D O I：

10.1038/s41612-024-00816-w

中图分类号：

P4 [大气科学（气象学）];

学科分类号：

0706 ; 070601 ;

摘要：

Coral reconstruction often serves as a major proxy of high-resolution sea surface temperature (SST) variability beyond the instrumental era. However, coral reconstructions are sparse and are usually studied for interannual variability, with few studies on the monthly features. In this study, we reconstruct the monthly SST spatial field by applying the paleoclimate data assimilation method to the coral records of the latest CoralHydro2k data set for the instrument period of 1880-2000. A comparison with observed SST variability shows that our assimilated tropical SST variability performs reasonably well for the seasonal cycle and monthly ENSO characteristics, notably the phase-locking and onset timing, and more realistic spatial fields relative to the model simulations. This study suggests the feasibility of applying paleoclimate data assimilation to reconstruct the monthly SST in the historical period.

引用

页数：10

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