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过去60年来南极冰盖近地面气温时空变化研究
引用本文:张雪影, 王叶堂, 宁文涛, 张悟颖, 董旭. 过去60年来南极冰盖近地面气温时空变化研究[J]. 第四纪研究, 2021, 41(3): 739-751. doi: 10.11928/j.issn.1001-7410.2021.03.10
作者姓名:张雪影  王叶堂  宁文涛  张悟颖  董旭
作者单位:山东师范大学地理与环境学院, 山东 济南 250014
基金项目:国家自然科学基金面上项目(批准号:41971081)、中国科学院(A类)战略性先导科技专项项目(批准号:XAD19070103)和山东省高等学校优秀青年创新团队项目(批准号:2019KJH011)共同资助
摘    要:

如何将十分有限的器测资料和再分析资料有机联系起来,充分借助它们各自的优势,分析南极冰盖气温时空变化具有重要意义。以CFSR(the Climate Forecast System Reanalysis)、ERA5(the European Centre for Medium-Range Weather Forecasts Fifth-generation Reanalysis)和MERRA-2(the Modern-Era Retrospective Analysis for Research and Applications,version 2)再分析资料分别作为背景场,利用南极冰盖具有超过50年连续观测的站点气温观测资料,分别重建了1960~2019年冰盖近地面月气温时空数据集,借助于未参与重建的70个站点观测资料进行了验证分析。在此基础上,利用精度最高的重建数据集探讨了冰盖过去60年来气温时空变化特征。精度验证结果表明:基于ERA5重建的月气温数据集精度最高,相关系数为0.70,均方根误差为0.49℃。1960~2019年,南极半岛和西南极冰盖呈现显著增温趋势,而且显著变暖延伸到60°~180°E的东南极内陆大部分区域。全球变暖停滞事件在南极半岛和西南极冰盖发生,且增温减缓程度更明显:1999~2019年间年和春季平均气温均呈明显降低趋势。1960~1998年,整个东南极冰盖气温没有显著变化,但是1999~2019年东南极冰盖内陆较大区域呈现了显著变暖趋势。这些结果有助于增进对不同时间尺度南极冰盖气温变化区域差异性的理解。



关 键 词:南极冰盖   近地面气温重建   再分析资料   时空演变
收稿时间:2020-12-30
修稿时间:2021-03-11

Spatiotemporal variations of near-surface air temperature over the Antarctic Ice Sheet during the past 60 years
ZHANG Xueying, WANG Yetang, NING Wentao, ZHANG Wuying, DONG Xu. Spatiotemporal variations of near-surface air temperature over the Antarctic Ice Sheet during the past 60 years[J]. Quaternary Sciences, 2021, 41(3): 739-751. doi: 10.11928/j.issn.1001-7410.2021.03.10
Authors:ZHANG Xueying  WANG Yetang  NING Wentao  ZHANG Wuying  DONG Xu
Affiliation:College of Geography and Environment, Shandong Normal University, Jinan 250014, Shangdong
Abstract:This study presents a reconstruction of monthly near-surface air temperature over the entire Antarctic Ice Sheet(AIS) from 1960 to 2019. This reconstruction uses the kriging technique to interpolate more than 50 a air temperature observational records, supplemented by the spatiotemporal temperature covariances of the three global reanalysis products including the Climate Forecast System Reanalysis(CFSR), the European Centre for Medium-Range Weather Forecasts fifth-generation reanalysis(ERA5), and the Modern-Era Retrospective Analysis for Research and Applications, version 2(MERRA-2). Comparison with the independent observations from 70 weather stations shows that the monthly temperature dataset reconstructed based on ERA 5 has the highest accuracy, with a correlation coefficient of 0.70 and a root mean square error of 0.49℃. Spatial changes in the linear trends in air temperature depend largely on the season and analyzed time spans. From 1960 to 2019, significant warming occurs in the Antarctic Peninsula(AP) and the West AIS, in terms of annual mean temperature, the AP and West AIS show significant increasing warming of 0.31℃/decade and 0.11℃/decade, respectively; From the perspective of seasonal variation, the AP shows significant warming trends in all seasons except spring, especially in autumn, when the warming trend reach 0.48℃/decade, and we also find significant warming in West AIS at 0.25℃/decade in spring. Different from the previous studies, our reconstruction reveals larger areas with the significantly increasing trends in the annual temperature, especially for most of the interior of the 60°~180°E sector, for the 1960~2019 period. The "global warming hiatus" event occurs in the AP and West AIS, with the decreasing trends in the annual mean temperature averaged at the respective region, at the rates of 0.16℃/decade and 0.024℃/decade, respectively, especially in summer, the AP shows significant cooling trend of 0.47℃/decade, during 1999~2019. From 1960 to 1998, there is no any significant air temperature changes throughout the year in the entire East AIS. However, during 1999~2019, significant warming trends occur in part of inland regions around the South Pole, especially in summer, the warming rate is more than 0.6℃/decade. These results are useful for the estimation of the spatial variability in air temperature on the different time scales over the AIS.
Keywords:Antarctic Ice Sheet  near-surface air temperature reconstruction  reanalysis products  spatiotemporal variability
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