Journal of Tropical Oceanography ›› 2023, Vol. 42 ›› Issue (4): 104-112.doi: 10.11978/2022215CSTR: 32234.14.2022215

• Marine Meteorology • Previous Articles     Next Articles

CALIOP remote sensing monitoring of the Fujian sea fog and spectral characteristics analysis of subcloud fog based on Himawari-8

HU Chenyue1(), QIU Zhongfeng1, LIAO Kuo2(), ZHAO Dongzhi1, WU Daomao3   

  1. 1. Nanjing University of Information Science and Technology, Nanjing 210044, China
    2. Fujian Institute of Meteorological Sciences, Fuzhou 350008, China
    3. Suqian Environmental Monitoring Center, Suqian 223800, China
  • Received:2022-10-09 Revised:2022-12-14 Online:2023-07-10 Published:2022-12-19
  • Supported by:
    National Natural Science Foundation of China(41976165)

Abstract:

Sea fog, as a hazard weather, affects maritime transportation and military activities. The coastal area of Fujian province is a national strategic area characterized by frequent sea fog. It is essential to monitor and study the sea fog in this area. cloud-aerosol lidar with orthogonal polarization (CALIOP) can detect the vertical structure characteristics of sea fog due to its vertical penetration through laser. Thus, it is very suitable for sea fog monitoring. In this paper, firstly, remote sensing monitoring of sea fog over the coastal area of Fujian was carried out through CALIOP L1 level 532 nm total attenuated backscattering and vertical feature mask (VFM) data. Based on the physical characteristics of sea fog, the detection range of sea fog was expanded. Secondly, the vertical characteristics of sea fog in this area were analyzed and it was found that subcloud fog occurred frequently. To explore the spectral characteristics of the subcloud fog and develop a high time coverage and large-scale synchronous sea fog monitoring algorithm. Besides, the spectral differences of cloud, pure fog, and subcloud fog were compared based on Himawari-8 data. According to the results, in the daytime, the spectral characteristics of pure fog and subcloud fog were not significantly different in each band, and the reflectance of bands 1~4 was much lower than that of cloud pixels; at night, the brightness temperature of pure fog at 3.9 μm band was generally lower than that of subcloud fog. It is expected to improve the monitoring accuracy of sea fog in Fujian Province by distinguishing cloud, pure fog, and subcloud fog based on the above spectral characteristics.

Key words: sea fog, satellite remote sensing, Fujian