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Retrieval and validation of sea surface temperature from HY-1D COCTS

  • role： First author第一作者
  • Affiliation：

    College of Marine Technology, Faculty of Information Science and Engineering, Ocean University of China, Qingdao 266100, China

    Sarya Oceanographic Institution, Ocean University of China, Sanya 572024, China

    Laboratory for Regional Oceanography and Numerical Modeling, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266071, China

  • Email：liumingkun@ouc.edu.cn
  • Introduction：刘铭坤，研究方向为卫星海洋遥感。E-mail：liumingkun@ouc.edu.cn
LIU Mingkun123,  
  • role： Corresponding author通信作者
  • Affiliation：

    College of Marine Technology, Faculty of Information Science and Engineering, Ocean University of China, Qingdao 266100, China

    Sarya Oceanographic Institution, Ocean University of China, Sanya 572024, China

    Laboratory for Regional Oceanography and Numerical Modeling, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266071, China

  • Email：leiguan@ouc.edu.cn
  • Introduction：管磊，研究方向为卫星海洋遥感。E-mail：leiguan@ouc.edu.cn
GUAN Lei123*,  
  • Affiliation：

    Sarya Oceanographic Institution, Ocean University of China, Sanya 572024, China

    Laboratory for Regional Oceanography and Numerical Modeling, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266071, China

LIU Fanli23,  
  • Affiliation：

    National Satellite Ocean Application Service, Ministry of Natural Resources of China, Beijing 100081, China

    Key Laboratory of Space Ocean Remote Sensing and Application, Ministry of Natural Resources of China, Beijing 100081, China

LIU Jianqiang45

Resümee

HY-1D was launched in June 2020 as the first operational generation of Chinese marine satellite constellation with the launched HY-1C satellite for networking in the morning and afternoon. The Chinese Ocean Color and Temperature Scanner (COCTS) has two thermal infrared channels (10.30—11.40 and 11.40—12.50 µm) for observing Sea Surface Temperature (SST). In this work, the Bayesian cloud detection and optimal estimation algorithm are utilized for HY-1D COCTS SST retrieval in the Northwest Pacific based on the atmospheric radiative transfer model.COCTS is a whiskbroom scanner with eight parallel detectors along-track. The different spectral responses of these eight parallel detectors caused the sharp striped noise across the scan lines. The de-striping is carried out based on the unidirectional variational model. De-striping can be viewed as an optimization problem based on the minimization of a unidirectional variational model because striping can be assumed to be unidirectional noise because it does not affect the image horizontal gradient. The solution of the Euler-Lagrange equation is obtained based on a Gauss-Seidel fixed-point iterative scheme. The de-striped analysis show that the de-striping algorithm is successfully utilized in the HY-1D COCTS radiance data.Based on the simulated brightness temperature using the moderate resolution atmospheric transmission model, a Bayesian approach is utilized for the cloud detection of COCTS infrared brightness temperatures. Bayesian cloud detection is based on Bayes’ theorem, which determines a clear-sky probability given the satellite observations and prior background information. The COCTS brightness temperature images and the retrieved SST validation distributions show that the cloud detection is effective for SST retrieval.The optimal estimation algorithm is used for COCTS SST retrieval, based on the COCTS simulated brightness temperature and ERA5 SST as the prior SST. The HY-1D COCTS-retrieved SSTs are compared with the in situ SST and Visible Infrared Imaging Radiometer Suite (VIIRS) SST. The bias of the comparisons between the COCTS-retrieved SST and the in situ measurement is -0.04 ℃, and the standard deviation is 0.45 ℃. The bias and standard deviation of the COCTS newly retrieved SST minus SST from VIIRS are -0.05 ℃ and 0.49 ℃, respectively. Validation result shows that the accuracy of HY-1D COCTS SST in the Northwest Pacific reaches the equivalent level with international operational SST.

Schlüsselwort

remote sensing;HY-1D;COCTS;sea surface temperature;cloud detection;Retrieval;validation

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