近500 年南极涛动指数重建及其变率分析
收稿日期: 2009-11-30
修回日期: 2010-01-17
网络出版日期: 2010-03-30
基金资助
国家自然科学基金项目(40675035); 公益性行业科研专项项目(GYHY200806010); 国家科技支撑计划 (2007BAC29B02)
Antarctic Oscillation Index Reconstruction since 1500 AD and Its Variability
Received date: 2009-11-30
Revised date: 2010-01-17
Online published: 2010-03-30
Supported by
National Natural Science Foundation of China, No.40675035; R&D Special Fund for Public Welfare Industry (Meteorology), No.GYHY200806010; National Key Science and Technology Project, No.2007bac29b02]
南极涛动是南半球大气环流的主要模态, 在多种尺度上对南半球及北半球部分地区的气候系统产生重要影响。在对树轮、珊瑚、冰芯等多种代用资料进行挑选与主成分分析的基础上，重建了公元1500 年以来南半球夏季(当年12 月-次年2 月) 的南极涛动指数。重建序列的解释方差(r2)、误差减少量(RE) 平均值分别为59.9%、0.47，较高的r2、RE表明重建具有了较高的可信度；而整体呈减少趋势的标准误差(SE) 表明代用资料的增多可以减少重建序列的不确定性。重建结果与其它研究给出的南极涛动指数有着较好的一致性。重建序列的功率谱分析表明，过去500 多年南极涛动年际变率突出的周期有2.4a、2.6a、6.3a，年代际变率突出的周期有24.1a、37.6a，均达到95%显著性水平。进一步的小波分析表明南极涛动在不同时间尺度上的变率及其周期有着随时间而演变的特征。
张自银1, 龚道溢1, 何学兆1, 雷杨娜2, 冯胜辉1 . 近500 年南极涛动指数重建及其变率分析[J]. 地理学报, 2010 , 65(3) : 259 -269 . DOI: 10.11821/xb201003001
The Antarctic Oscillation (AAO) is the dominant mode of atmospheric circulation variability over the southern hemisphere. It could not only play important roles in climate changes over southern hemisphere, but also exert lots of influences in some regions in northern hemisphere. Due to the lack of widespread instrumental records during historical periods, the understanding of the natural variability of AAO is limited. The purpose of this paper is to reconstruct an austral summer Antarctic Oscillation index (DJF-AAO) focusing on interannual-decadal variability since 1500 AD based on multiple proxies, such as tree-rings, corals, and ice-cores. A Marshall-AAO index derived from 12-station sea level pressure records since 1957 are selected as observational series for calibration. There are 263 variables retained after a series of screening criteria for proxies, to refine the major signatures contained in the proxies by applying principal component analysis, and then a series of screening criteria implemented again for the time coefficient (PC) corresponding to each eigenvector. After that, by applying multivariate regression method the observational AAO-PC relations were calibrated and cross-validated based on the period of 1957-1989, then regressions were employed to compute the DJF-AAO index in 1500-1956. In verification procedure we checked the explained variance (r2), reduction of error (RE), and the standard error (SE). The cross-validation was performed by applying a leave-one-out validation method. During the reconstruction period of 1500-1956, the mean of r2, RE, and SE are 59.9% , 0.47 and 0.67, respectively. These statistical data indicate that DJF-AAO reconstruction is relatively reasonable for the last 460 years approximately. The reconstruction is compared favorably with several existing shorter AAO indexes derived from station SLP records both on the interannual and decadal time scales. The leading periods of the DJF-AAO index are ~2.4, ~2.6, ~6.3, ~24.1, ~37.6 years during the last 500 years, which are all significant at the 95% level.
[1] Gong D Y, Wang S W. Definition of Antarctic oscillation index. Geophysical Research Letters, 1999, 26(4): 459-462.
[2] Thompson D W J, Wallace J M. Annular modes in the extratropical circulation. Part I: Month to month variability. Journal of Climate, 2000, 13(5): 1000-1016.
[3] Rogers J, Loon H V. Spatial variability of sea level pressure and 500mb height anomalies over the Southern Hemisphere. Monthly Weather Review, 1982, 110(10): 1375-1392.
[4] Reason C J C, Rouault M. Links between the Arctic Oscillation and winter rainfall over western South Africa. Geophysical Research Letters, 2005, 32, L07705, doi: 10.1029/2005GL022419.
[5] Cai W J, Shi G, Li Y. Multidecadal fluctuations of winter rainfall over southwest Western Australia simulated in the CSIRO Mark 3 coupled model. Geophysical Research Letters, 2005, 32, L12701, doi: 10.1029/2005GL022712.
[6] Lovenduski N S, Gruber N. Impact of the Southern Annular Mode on Southern Ocean circulation and biology. Geophysical Research Letters, 2005, 32, L11603, doi: 10.1029/2005GL022727.
[7] He Jinhai, Chen Lizhen. Quasi-40 day oscillations over the mid-latitude of the southern hemisphere with their relation to the summer monsoon over the northern hemisphere. Journal of Nanjing Institute of Meteorology, 1989, 12(1): 11-18.
[何金海, 陈丽臻. 南半球中纬度准40 天振荡及其与北半球夏季风的关系. 南京气象学院学报, 1989, 12(1): 11-18.]
[8] Gao Hui, Xue Feng, Wang Huijun. Influence of interannual variability of Antarctic oscillation on Jianghuai Meiyu along the Yangtze and Huaihe river valley and its importance to prediction. Chinese Science Bulletin, 2003, 48 267(suppl.2): 87-92.
[高辉, 薛峰, 王会军. 南极涛动年际变化对江淮梅雨的影响及预报意义. 科学通报, 2003, 48(增刊 2): 87-92.]
[9] Wang H J, Fan K. Central-north China precipitation as reconstructed from the Qing dynasty: Signal of the Antarctic atmospheric oscillation. Geophysical Research Letters, 2005, 32, L24705, doi: 10.1029/2005GL024562.
[10] Nan S N, Li J P. The relationship between the summer precipitation in the Yangtze River Valley and the boreal spring southern hemisphere annular mode. Geophysical Research Letters, 2003, 30(24): 2266, doi: 10.1029/2003GL018381.
[11] Bao Xuejun, Wang Panxing, Qin Jun. Time lag correlation analyses of Antarctic oscillations and Jianghuai Meiyu anomaly. Journal of Nanjing Institute of Meteorology, 2006, 29(3): 348-352.
[鲍学俊, 王盘兴, 覃军. 南极涛动与江淮 梅雨异常的时滞相关分析. 南京气象学院学报, 2006, 29(3): 348-352.]
[12] Fan Ke, Wang Huijun. Interannual variability of Antarctic Oscillation and its influence on East Asian climate during boreal winter and spring. Science in China: Series D, 2006, 49(5): 554-560.
[范可, 王会军. 南极涛动的年际变化及其 对东亚冬春季气候的影响. 中国科学: D辑, 2006, 36(4): 385-391.]
[13] Lang X M. Prediction model for spring dust weather frequency in North China. Science in China: Series D, 2008, 51 (5): 709-720.
[14] Jones J M, Widmann M. Instrument- and tree-ring-based estimates of the Antarctic oscillation. Journal of Climate, 2003, 16: 3511-3524.
[15] Moreno P I, François J P, Villa-Martínez R P et al. Millennial-scale variability in Southern Hemisphere westerly wind activity over the last 5000 years in SW Patagonia. Quaternary Science Reviews, 2009, 28: 25-38.
[16] Kalnay E, Kanamitsu M, Kistler R et al. The NCEP/NCAR 40-year reanalysis project. Bulletin of the American Meteorological Society, 1996, 77: 437-471.
[17] Uppala S M., Kållberg P W, Simmons A J et al. The ERA-40 reanalysis. Quarterly Journal of the Royal Meteorological Society, 2005, 131: 2961-3012.
[18] Allan R J, Ansell T J. A new globally complete monthly historical mean sea level pressure data set (HadSLP2): 1850-2004. Journal of Climate, 2004, 19: 5816-584.
[19] Bromwich D H, Fogt R L. Strong trends in the skill of the ERA-40 and NCEP/NCAR reanalyses in the high and middle latitudes of the southern hemisphere,1958-2001. Journal of Climate, 2004, 17: 4603-4619.
[20] Jones P D, Lister D H. Intercomparison of four different southern hemisphere sea level pressure datasets. Geophysical Research Letters, 2007, 34, L10704, doi: 10.1092/2007GL029251.
[21] Marshall G J. Trends in the southern annular mode from observations and reanalyses. Journal of Climate, 2003, 16 (24): 4134-4143.
[22] Fogt R L, Perlwitz J, Monaghan A J et al. Historical SAM variability (Part II): 20th century variability and trends from reconstructions, observations, and the IPCC AR4 Models. Journal of Climate, 2009, 22(20): 5346-5365.
[23] Visbeck M. A station-based Southern Annular Mode index from 1884 to 2005. Journal of Climate, 2009, 22, 940-950.
[24] Jones J M, Fogt R L, Widmann M et al. Historical SAM variability (Part I): Century length seasonal reconstructions. Journal of Climate, 2009, 22(20): 5319-5345.
[25] Gong D Y, Kim S J, Ho C H. Arctic and Antarctic Oscillation signatures in tropical coral proxies over the South China Sea. Annales Geophysicae, 2009, 27: 1979-1988.
[26] Mann M E, Zhang Z H, Hughes M K et al. Proxy-based reconstructions of hemispheric and global surface temperature variations over the past two millennia. Proceedings of the National Academy of Sciences of the United States of America, 2008, 105(36): 13252-13257.
[27] Fritts H C. Tree Rings and Climate. London: Academic Press, 1976.
[28] Villalba R, Cook E R, Jacoby G C et al. Tree-ring based reconstructions of northern Patagonia precipitation since AD 1600. The Holocene, 1998, 8(6): 659-674.
[29] Gong D Y, Luterbacher J. Variability of the low-level cross-equatorial jet of the western Indian Ocean since 1660 as derived from the coral proxies. Geophysical Research Letters, 2008, 35, doi: 1029/2007GL032409.
[30] Zhang Z Y, Gong D Y, He X Z et al. Reconstruction of the western Pacific warm pool SST since 1644AD and its relation to precipitation over East China. Science in China: Series D, 2009, 52(9): 1436-1446.
[31] Lorenz E N. Empirical orthogonal functions and statistical weather prediction. Statistical Forecasting Project Report No.1. Boston: Dept of Meteor MIT, 1956: 49.
[32] Miller R L, Schmidt G A, Shindell D T. Forced annular variations in the 20th century Intergovernmental Panel on Climate Change Fourth Assessment Report models. Journal of Geophysical Research, 2006, 111, doi: 10.1029/ 2005JD006323.
[33] Zhu Yali, Wang Huijun. The Arctic and Antarctic oscillations in the IPCC AR4 coupled models. Acta Meteorologica Sinica, 2008, 66(6): 993-1004.
[祝亚丽, 王会军. 基于IPCC AR4 耦合模式的南极涛动和北极涛动的模拟及未来变化预估. 气象学报, 2008, 66(6): 994-1004.]
[34] Torrence C, Compo G P. A practical guide to wavelet analysis. Bulletin of the American Meteorological Society, 1998, 79(1): 61-78.
[35] Thompson D W J, Solomon S. Interpretation of recent southern hemisphere climate change. Science, 2002, 296: 895-899.
[36] Shindell D T, Schmidt G A. Southern hemisphere climate response to ozone changes and greenhouse gas increases. Geophysical Research Letters, 2004, 31(18): L18209, doi: 10.1029/2004GL020724.
[37] Zhou T J, Yu R C. Sea-surface temperature induced variability of the Southern Annular Mode in an atmospheric general circulation model. Geophysical Research Letters, 2004, 31(24): L24206, doi: 10.1029/2004GL021473.
[38] Kuroda Y, Kodera K. Solar cycle modulation of the southern annular mode. Geophysical Research Letters, 2005, 32: L13802, doi: 10.1029/2005GL022516.
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