大气与环境光学学报 ›› 2023, Vol. 18 ›› Issue (6): 569-584.doi: 10.3969/j.issn.1673-6141.2023.06.006

• 光学遥感 • 上一篇    下一篇

2001―2021年东亚地区CTP时空模态特征分析

孙乐 1,2, 唐超礼 2*, 魏圆圆 3, 黄友锐 2   

  1. 1 安徽理工大学计算机科学与工程学院, 安徽 淮南 232001; 2 安徽理工大学电气与信息工程学院, 安徽 淮南 232001; 3 安徽大学互联网学院, 安徽 合肥 230039
  • 收稿日期:2022-03-22 修回日期:2022-05-08 出版日期:2023-11-28 发布日期:2023-12-04
  • 通讯作者: E-mail: chltang@mail.ustc.edu.cn E-mail:chaolitang@163.com
  • 作者简介:孙 乐 (1997- ), 硕士研究生, 主要从事大数据分析。E-mail: sunle0605@163.com
  • 基金资助:
    安徽高校自然科学研究重点项目 (KJ2019A0103), 国家重点研发计划项目 (2017YFD0700501), 国家自然科学基金 (61772033)

Spatial-temporal mode analysis of cloud top pressure over East Asia during 2001―2021

SUN Le 1,2, TANG Chaoli 2*, WEI Yuanyuan 3, HUANG Yourui 2   

  1. 1 Department of Computer Science and Engineering, Anhui University of Science and Technology, Huainan 232001, China; 2 Institute of Electrical & Information Engineering, Anhui University of Science and Technology, Huainan 232001, China; 3 School of Internet, Anhui University, Hefei 230039, China
  • Received:2022-03-22 Revised:2022-05-08 Online:2023-11-28 Published:2023-12-04
  • Contact: 超礼 唐 E-mail:chaolitang@163.com

摘要: 基于2001 年1 月至2021 年12 月期间MODIS和AIRS遥感反演数据, 利用经验正交函数 (EOF)、MK趋势分析、 最小二乘法等方法研究了东亚地区近21 年的云顶气压 (CTP) 时空模态特征及变化趋势。结果表明: 东亚地区CTP从 东北到西南呈逐渐递减趋势; 四季变化差异性较大, 呈现“√”字型变化, 表现为冬季气压值最高、夏季最低; 受地理位 置和纬度带影响, CTP的高值区在一年四季均分布在东北地区上空, 低值区始终位于青藏高原地区。在中国的广西、 广东和缅甸、印度等地属于热带季风区, 在冬季受干冷气流的影响, 容易形成CTP高值区。东亚地区主要以中云分布 为主, 低云区主要集中在中国东北、京津冀、朝鲜半岛和中纬度海洋地区, 在中国中原地区、南方地区 (广西、广东和长 江中下游各省地区) 以及新疆部分地区以中云为主, 高云主要出现在中国青藏高原和塔克拉玛干沙漠。通过趋势分析 发现, 在2001 年至2021 年间, CTP在中国的新疆、印度半岛、缅甸、蒙古和贝加尔湖等区域呈现较高的增长趋势, 而在 中国的青藏高原、南部沿海等部分区域以及东部海域均呈较明显的下降趋势。东亚地区部分区域的CTP与地表温度、 湿度、水汽和云量均呈现较为显著的相关性, 因此CTP的变化可以在一定程度上反应区域性天气变化情况。

关键词: 云顶气压, 经验正交函数, MK趋势分析, 最小二乘法

Abstract: Based on MODIS and AIRS remote sensing data from January 2001 to December 2021, the temporal and spatial modal characteristics and variation trend of cloud top pressure (CTP) over East Asia in recent 21 years were studied using empirical orthogonal function (EOF), MK trend analysis and least square method. The results show that the CTP in east Asia shows a gradually decreasing trend from northeast to southwest, and large differences in seasonal changes with a tick font shape, manifested as the highest pressure value in winter and the lowest in summer. Affected by geographical position and latitudes, the high value areas of CTP are distributed in northeast region throughout the four seasons in one year, while the low value area is always located in the Qinghai-Tibet plateau area. Guangxi and Guangdong in China, Myanmar, India and other places belong to the tropical monsoon region, they are affected by cold and dry air in winter and easy to form CTP high value area. The East Asian region is mainly dominated by medium cloud distribution. Specifically, the low cloud areas are mainly concentrated in Northeast China, Beijing-Tianjin-Hebei, the Korean Peninsula, and mid latitude marine areas. The meduim cloud areas are mainly distributed in the Central Plains region, southern regions (Guangxi, Guangdong, and various provinces in the middle and lower reaches of the Yangtze River), as well as some regions of Xinjiang in China. And high clouds mainly appear in the Qinghai-Tibet Plateau and Taklamakan Desert of China. The trend analysis shows that CTP in Xinjiang of China, Indian Peninsula, Myanmar, Mongolia and Lake Baikal significantly increases from 2001 to 2021, while that in Qinghai-Tibet Plateau, southern coastal areas and eastern sea of China shows a significant downward trend. Generally, CTP is significantly correlated with surface temperature, humidity, water vapor and cloud cover in some regions of East Asia. Therefore, the change of CTP can reflect regional weather changes to a certain extent.

Key words: cloud top pressure, empirical orthogonal function, MK trend analysis, least square method

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