Surface Upwelling off the Zhoushan Islands, East China Sea, from Himawari-8 AHI Data

被引:10
作者
Yin, Wenbin [1 ]
Ma, Youzhi [1 ]
Wang, Dian [1 ]
He, Shuangyan [2 ]
Huang, Daji [3 ]
机构
[1] Zhejiang Ocean Univ, Coll Marine Sci & Technol, Zhoushan 316022, Peoples R China
[2] Zhejiang Univ, Ocean Coll, Zhoushan 316021, Peoples R China
[3] Minist Nat Resources, Key Lab Trop Marine Ecosyst & Bioresources, Inst Oceanog 4, Beihai 536000, Peoples R China
基金
中国国家自然科学基金; 海南省自然科学基金;
关键词
surface upwelling; Zhoushan Islands; Himawari-8; SST; NORTHEAST;
D O I
10.3390/rs14143261
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The summer upwelling around the Zhoushan Islands is well-known. The previous concise review of (mostly) observational studies reveals that the present knowledge of the Zhoushan upwelling is unsatisfactory and has focused on seasonal variations. In this study, a sea surface temperature (SST) gradient-based upwelling detection algorithm was used. The Level 3 daily and hourly SST data from the geostationary satellite Himawari-8 were used to explore statistical features, seasonal variations, and short-term variations of the Zhoushan upwelling. Despite the duration period being like in previous studies, there is a new finding that the location of the upwelling center has a significant monthly migration. The statistical results show that the potential upwelling spots are clustered in the location with large topographic gradients and can be divided into four aggregation areas: between Gouqi Island and Lvhua Island, off Shengsi Island, around the Zhongjieshan Islands, and off the Taohua-Liuheng Islands. The core area of the Zhoushan upwelling is located at 122 degrees E-123 degrees E, 29.5 degrees N-31.15 degrees N with an irregular ellipse extending from southwest to northeast. The continuous cloud-free satellite images display that the lifecycle of the short-term variations was about 24 h and included two stages: intensification and decay. Meanwhile, the surface upwelling center has onshore-offshore movement under the advective transport of local tidal currents. A preliminary discussion suggests that the quasi-24 h periodic variations may be caused by the competing effect between tidal mixing and the stratification in the water column.
引用
收藏
页数:16
相关论文
共 50 条
  • [41] Integrating Machine Learning and a Spatial Contextual Algorithm to Detect Wildfire from Himawari-8 Data in Southwest China
    Liu, Chuanfeng
    Chen, Rui
    He, Binbin
    FORESTS, 2023, 14 (05):
  • [42] Fog Season Risk Assessment for Maritime Transportation Systems Exploiting Himawari-8 Data: A Case Study in Bohai Sea, China
    Du, Pei
    Zeng, Zhe
    Zhang, Jingwei
    Liu, Lu
    Yang, Jianchang
    Qu, Chuanping
    Jiang, Li
    Liu, Shanwei
    REMOTE SENSING, 2021, 13 (17)
  • [43] Cross-Comparison of channel parameters between FY-3E/MERSI-LL and Himawari-8/AHI in China
    Xie, Lianni
    Wu, Shuang
    Chen, Jie
    Zheng, Wei
    Yan, Hua
    Xu, Zuomin
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2022, 43 (12) : 4663 - 4681
  • [44] Time series retrieval of Multi-wavelength Aerosol optical depth by adapting Transformer (TMAT) using Himawari-8 AHI data
    She, Lu
    Li, Zhengqiang
    de Leeuw, Gerrit
    Wang, Weile
    Wang, Yujie
    Yang, Lu
    Feng, Zixian
    Yang, Chen
    Shi, Yun
    REMOTE SENSING OF ENVIRONMENT, 2024, 305
  • [45] Short-Term Variation of the Surface Flow Pattern South of Lombok Strait Observed from the Himawari-8 Sea Surface Temperature
    Taniguchi, Naokazu
    Kida, Shinichiro
    Sakuno, Yuji
    Mutsuda, Hidemi
    Syamsudin, Fadli
    REMOTE SENSING, 2019, 11 (12)
  • [46] Validation of Himawari-8 Sea Surface Temperature Retrievals Using Infrared SST Autonomous Radiometer Measurements
    Zhang, Haifeng
    Beggs, Helen
    Griffin, Christopher
    Govekar, Pallavi Devidas
    REMOTE SENSING, 2023, 15 (11)
  • [47] ESTIMATION OF DAILY GLOBAL SOLAR IRRADIANCE FROM HIMAWARI-8 PRODUCTS OVER CHINA
    Zhang, Yanli
    Chen, Linhong
    Liu, Jingfeng
    XXIV ISPRS CONGRESS: IMAGING TODAY, FORESEEING TOMORROW, COMMISSION III, 2022, 5-3 : 493 - 500
  • [48] Cloud Detection from the Himawari-8 Satellite Data Using a Convolutional Neural Network
    Andreev, A., I
    Shamilova, Yu A.
    IZVESTIYA ATMOSPHERIC AND OCEANIC PHYSICS, 2021, 57 (09) : 1162 - 1170
  • [49] Cloud Detection from the Himawari-8 Satellite Data Using a Convolutional Neural Network
    A. I. Andreev
    Yu. A. Shamilova
    Izvestiya, Atmospheric and Oceanic Physics, 2021, 57 : 1162 - 1170
  • [50] Retrieval of cloud microphysical properties from Himawari-8/AHI infrared channels and its application in surface shortwave downward radiation estimation in the sun glint region
    Tana, Gegen
    Ri, Xu
    Shi, Chong
    Ma, Run
    Letu, Husi
    Xu, Jian
    Shi, Jiancheng
    REMOTE SENSING OF ENVIRONMENT, 2023, 290