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过去一千年南亚夏季风指数的树木年轮重建。

A tree-ring reconstruction of the South Asian summer monsoon index over the past millennium.

作者信息

Shi Feng, Li Jianping, Wilson Rob J S

机构信息

State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China.

1] College of Global Change and Earth System Science (GCESS), Beijing Normal University, Beijing 100875, China [2] Joint Center for Global Change Studies, Beijing 100875, China.

出版信息

Sci Rep. 2014 Oct 23;4:6739. doi: 10.1038/srep06739.

Abstract

The South Asian summer monsoon (SASM) is a major atmospheric synoptic climate system affecting nearly a quarter of the human population. Climate proxy data derived from tree rings, ice cores, speleothems, and other sources can all contribute to an understanding of SASM variability prior to instrumental period. Here, we develop an optimal information extraction (OIE) method, which we use to reconstruct the SASM index (SASMI) over the last millennium using 15 tree-ring chronologies. The record generated is significantly correlated (r = 0.7, p < 0.01) with the instrumental SASMI record on annual timescales; this correlation is higher than that obtained in any previous study. The reconstructed SASMI captures 18 of 26 (69%) reordered historical famine events in India over the last millennium; notably, 11 of 16 short events with durations of 1-3 years are accurately depicted in our reconstruction. Moreover, the reconstructed SASMI is positively correlated with variations in total solar irradiance (TSI) on multi-decadal timescales implying that variations in solar activity may influence the SASM. Based on the response of SASM to 34 significant volcanic events using the superposed epoch analysis, the volcanic forcing may drive a weak SASM in the second year of an eruption.

摘要

南亚夏季风(SASM)是一个主要的大气天气气候系统,影响着近四分之一的世界人口。来自树木年轮、冰芯、洞穴石笋和其他来源的气候代用数据都有助于了解仪器观测时期之前的SASM变率。在此,我们开发了一种最优信息提取(OIE)方法,并用该方法利用15个树木年轮年表重建了过去一千年的SASM指数(SASMI)。生成的记录在年时间尺度上与仪器观测的SASMI记录显著相关(r = 0.7,p < 0.01);这种相关性高于以往任何研究。重建的SASMI捕捉到了过去一千年印度26次重新排序的历史饥荒事件中的18次(69%);值得注意的是,我们的重建准确描绘了16次持续时间为1 - 3年的短期事件中的11次。此外,重建的SASMI在数十年时间尺度上与总太阳辐照度(TSI)的变化呈正相关,这意味着太阳活动的变化可能影响SASM。基于利用叠加时代分析得出的SASM对34次重大火山事件的响应,火山强迫可能在火山喷发后的第二年驱动较弱的SASM。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e40d/4206867/b1a974c1874e/srep06739-f1.jpg

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