东亚及西太平洋地表温度时空模态分析及预测研究*

doi:10.11978/2022009

热带海洋学报 ›› 2022, Vol. 41 ›› Issue (6): 183-192.doi: 10.11978/2022009CSTR: 32234.14.2022009

• 海洋气象学 • 上一篇

东亚及西太平洋地表温度时空模态分析及预测研究^*

唐超礼¹^,², 陶鑫华¹(), 魏圆圆³, 戴聪明⁴, 魏合理⁴

1.安徽理工大学电气与信息工程学院, 安徽淮南 232001
2.中国科学院空间天气学国家重点实验室, 北京100190
3.安徽大学互联网学院, 安徽合肥 230039
4.中国科学院合肥物质科学研究院安徽光学精密机械研究所, 中国科学院大气光学重点实验室, 安徽合肥 230031

收稿日期:2022-01-18 修回日期:2022-03-24 出版日期:2022-11-10 发布日期:2022-03-21
通讯作者: 陶鑫华
作者简介:唐超礼(1980—), 男, 教授, 博士, 硕士生导师, 主要从事大气数据与信息技术研究
基金资助:
空间天气学国家重点实验室专项基金资助项目(201909);安徽高校自然科学研究重点项目(KJ2019A0103);安徽理工大学高层次引进人才科研启动基金(13190007);国家重点研发计划课题(2019YFA0706004);安徽理工大学研究生创新基金项目(2021CX2082)

Spatiotemporal modal analysis and prediction of surface temperature in East Asia and the Western Pacific^*

TANG Chaoli¹^,², TAO Xinhua¹(), WEI Yuanyuan³, DAI Congming⁴, WEI Heli⁴

1. School of Electrical & Information Engineering, Anhui University of Science and Technology, Huainan 232001, China
2. State Key Laboratory of Space Weather, Chinese Academy of Sciences, Beijing 100190, China
3. School of Internet, Anhui University, Hefei 230039, China
4. Key Laboratory of Atmospheric Optics, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei 230031, China

Received:2022-01-18 Revised:2022-03-24 Online:2022-11-10 Published:2022-03-21
Contact: TAO Xinhua
Supported by:
Specialized Research Fund for State Key Laboratories(201909);University Natural Science Research Project of Anhui Province of China(KJ2019A0103);Scientific Research Start-up Fund for High-level Introduced Talents of Anhui University of Science and Technology(13190007);National Key Research and Development Program(2019YFA0706004);Graduate Innovation Foundation of Anhui University of Science and Technology(2021CX2082)

摘要/Abstract

摘要：

地表温度(land surface temperature, LST)是地球表面(海洋和陆地)水循环和大气环境互通的重要参数, 也是海、陆能量传输的重要体现。本文利用2003—2020年卫星反演的LST数据, 通过M-K(Mann-Kendall)突变检验、线性回归、经验正交分解(empirical orthogonal function, EOF)等方法分析LST时空模态特征, 并运用季节自回归移动平均(seasonal autoregression integrated moving average, SARIMA)模型预测LST的变化趋势。发现春、秋、冬三季沿海温度高, 内陆温度低, 由南向北(10°N—60°N), 由东向西(70°E—140°E)递减; 而夏季相反。EOF第一模态贡献率为29.58%, 空间分布以昆仑山脉、秦岭为分界线。预计2020年以后, LST的变化范围在-5~35℃。结果表明: (1)由于纬度的增加及海陆位置的差异, 导致日本的LST幅度小, 蒙古国的LST幅度大, 其余地区变化幅度平稳; (2)春、秋季温差不大, 夏、冬季温差大, 主要原因是太阳辐射; 其次, 季风气候显著。内陆高山多, 沿海平原多, 陆地升温效应小于水体的降温效应也会影响温差; (3)东亚及西太平洋地区LST的变化与人类活动、火山爆发等事件有关。

关键词: 地表温度, 时空变化, 经验正交分解, M-K突变检验

Abstract:

Land surface temperature (LST) is an important parameter of water cycle and atmospheric environment interworking on the earth's surface (ocean and land), and it is also an essential embodiment of energy transmission between sea and land. Using the LST data retrieved from satellites from 2003 to 2020, this paper analyzes the temporal and spatial modal characteristics of LST by M-K (Mann-Kendall) mutation test, linear regression and empirical orthogonal function (EOF), and uses the seasonal autoregression integrated moving average (SARIMA) model to predict the change trend of LST. It is found that the coastal temperature is high and the inland temperature is low in spring, autumn and winter, decreasing from south to north (10°N—60°N) and from east to west (70°E—140°E); while summer is the opposite. The first mock exam rate of EOF is 29.58%, and the spatial distribution is the Kunlun mountain and Qinling Mountains. It is predicted that after 2020, the range of LST will be -5 ~ 35℃. The results show that: (1) with the increase of latitude and the difference of sea and land location, the LST amplitude in Japan is small, in Mongolia is large, and that in other regions fluctuates stably. (2) The temperature difference between spring and autumn is not significant, and the temperature difference between summer and winter is large, mainly due to solar radiation; Secondly, the monsoon climate is significant. There are many inland mountains and coastal plains, and the land heating effect is less than the water-cooling effect, which will also affect the temperature difference. (3) The changes of LST in East Asia and the Western Pacific are related to human activities, volcanic eruptions and other events.

Key words: land surface temperature, temporal and spatial variation, empirical orthogonal function, Mann-Kendall test

中图分类号:

P423

唐超礼, 陶鑫华, 魏圆圆, 戴聪明, 魏合理. 东亚及西太平洋地表温度时空模态分析及预测研究^*[J]. 热带海洋学报, 2022, 41(6): 183-192.

TANG Chaoli, TAO Xinhua, WEI Yuanyuan, DAI Congming, WEI Heli. Spatiotemporal modal analysis and prediction of surface temperature in East Asia and the Western Pacific^*[J]. Journal of Tropical Oceanography, 2022, 41(6): 183-192.

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东亚及西太平洋地表温度时空模态分析及预测研究^*

Spatiotemporal modal analysis and prediction of surface temperature in East Asia and the Western Pacific^*

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东亚及西太平洋地表温度时空模态分析及预测研究*

Spatiotemporal modal analysis and prediction of surface temperature in East Asia and the Western Pacific*

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东亚及西太平洋地表温度时空模态分析及预测研究^*

Spatiotemporal modal analysis and prediction of surface temperature in East Asia and the Western Pacific^*