| 基于多种资料的青藏高原地表感热的对比分析 |
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| 引用本文： | 武正敏,陈权亮.基于多种资料的青藏高原地表感热的对比分析[J].高原山地气象研究,2018,38(1):1-10. |
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| 作者姓名： | 武正敏 陈权亮 |
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| 作者单位： | 成都信息工程大学大气科学学院/高原大气与环境四川重点实验室, 成都 610225 |
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| 基金项目： | 国家自然科学基金项目:青藏高原深对流活动及其对大气成分的输送过程研究(41475037),青藏高原地-气水热平衡和高原低值系统对东亚夏季风的影响(91537214) |
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| 摘 要： | 青藏高原地表感热通量是高原热源的主要分量之一,对高原局地天气系统、我国天气气候以及亚洲季风等都有着重要影响。选取1980～2016年青藏高原的站点资料和ERA-Interim、NCEP1、NCEP2再分析资料,计算高原地表感热通量的分布状况和时间变化特征并对不同资料得到的结果进行比较分析,结果表明:4种资料在夏季的空间分布、年际变化,高原中部的年际变化,以及长期变化趋势上具有较好的一致性,其中ERA-Interim感热资料较优于其他两种再分析资料。青藏高原的地表感热通量分布呈西高东低的特征,年均最大值出现在柴达木盆地,最小值位于贡山;区域平均值春季最大,冬季最小。感热逐月变化呈单峰型分布,不同分区的年际变化均在2001年或2003年由减弱趋势转变为增强趋势。
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| 关 键 词： | 青藏高原 地表感热通量 资料对比 |
| 收稿时间： | 2018-01-20 |
Comparison and Analysis of Surface Sensible Heat Flux in the Tibetan Plateau Based on a Variety of Data |
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| Affiliation: | College of Atmospheric Science, Chengdu University of Information Technology/Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, Chengdu 610225, China |
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| Abstract: | The surface sensible heat flux (SSHF) of the Tibetan Plateau (TP) is one of the major components of the heat source in the TP, with an important impact on the plateau local weather system, China's weather and the Asian monsoon. Based on the site data from 1980 to 2016, the monthly mean SSHF is calculated to analyze the characteristics of spatial distribution and temporal variability of the SSHF in the plateau. The results, compared with the ERA-Interim, NCEP1 and NCEP2 reanalysis datasets, show that four kinds of data have good consistency in the spatial distribution and the interannual variations of summer, interannual variations of central TP (CTP) , and long-term trend. The SSHF of ERA-Interim is superior to the other two reanalysis datasets. The distribution of SSHF over the TP is characterized with high values in the western Plateau and low eastern Plateau. The annual maximum of SSHF appears in the Qaidam basin and the minimum is located in Gongshan. The regional average value of SSHF is the highest in spring and the lowest in winter. The monthly change of SSHF shows a unimodal distribution. The interannual variations in different subregions switch from decreasing to increasing in 2001 or 2003. |
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