Nighttime sea fog recognition based on Himawari-8 data

Hao Shuxin; Hao Zengzhou; Huang Haiqing; Niu Rui; Pan Delu; Gu Jixing

doi:10.12284/hyxb2021158

Volume 43 Issue 11

Dec. 2021

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Hao Shuxin，Hao Zengzhou，Huang Haiqing, et al. Nighttime sea fog recognition based on Himawari-8 data[J]. Haiyang Xuebao，2021, 43(11)：166–180 doi: 10.12284/hyxb2021158

Citation:

Hao Shuxin，Hao Zengzhou，Huang Haiqing, et al. Nighttime sea fog recognition based on Himawari-8 data[J]. Haiyang Xuebao，2021, 43(11)：166–180 doi: 10.12284/hyxb2021158

Citation:

Hao Shuxin，Hao Zengzhou，Huang Haiqing, et al. Nighttime sea fog recognition based on Himawari-8 data[J]. Haiyang Xuebao，2021, 43(11)：166–180 doi: 10.12284/hyxb2021158

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Nighttime sea fog recognition based on Himawari-8 data

doi: 10.12284/hyxb2021158

Hao Shuxin^{1, 2, 3
,},
Hao Zengzhou^{2, 3
,
,},
Huang Haiqing^{2, 3},
Niu Rui²,
Pan Delu^{2, 3},
Gu Jixing⁴

1.
School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210023, China
2.
State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, China
3.
Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou 511458, China
4.
Yantai Marine Environmental Monitoring Center Station, State Oceanic Administration, Yantai 264006, China

Received Date: 2020-11-26
Rev Recd Date: 2021-02-24

Available Online: 2021-08-25

Publish Date: 2021-12-31

Abstract

Abstract

Sea fog is a kind of disastrous weather phenomenon which occurs on the sea surface. Mastering the distribution and dynamic changes of sea fog can effectively reduce the disasters caused by sea fog. Satellite remote sensing observation has the characteristics of near real time, wide coverage, continuous observation and so on. Especially the geostationary satellite remote sensing observation with high time resolution, which can continuously and dynamically track the occurrence, development and extinction of sea fog. The sea fog events in the Yellow Sea and Bohai Sea are taken from 2018 to 2019 as examples in this paper. Based on the analysis of the multi-channel bright temperature radiation characteristics of sea fog in the Yellow Sea and Bohai Sea by using Himawari-8 (H-8) geostationary satellite data, the separation index of sea fog and cloud, the separation index of sea fog and water, the slope index of multi-band brightness temperature difference and texture index of mid-infrared bright temperature are defined through the difference and ratio combination of different bands, and the night sea fog monitoring algorithm based on multi-exponential probability distribution is proposed to realize the automatic identification of sea fog at night. The algorithm is applied to H-8 and GEO-KOMPSAT2A (GK-2A) geostationary satellite data respectively. The position distribution and coverage area of sea fog identify by multi-time satellite observations of six sea fog events from February to June 2020 are compared to achieve mutual verification. The results show that the algorithm proposed in this paper can effectively recognize sea fog at night. The monitoring results every 10 minutes of continuous observations of H-8 and GK-2A at night on April 29, 2020 are selected to follow up and analyze the area where sea fog occurred, it shows the occurrence, development and evolution of the sea fog event clearly. It indicates that the algorithm can monitor the distribution of sea fog and track the development and change of fog. It can provide scientific basis and decision-making basis for the prevention and mitigation of sea fog.
- sea fog,
- infrared remote sensing,
- geostationary meteorological satellites,
- band combination

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References(34)

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