سابِق|تال

Arctic sea ice concentration retrieval study of FY-3/MWRI based on the bootstrap algorithm

  • role： First author第一作者
  • Affiliation：

    National Marine Environmental Forecasting Center, Beijing 100081, China

    National Satellite Ocean Application Service, Beijing 100081, China

  • Email：ted_shawn@163.com
  • Introduction：武苏辉，研究方向为海洋遥感。E-mail：ted_shawn@163.com
WU Suhui12,  
  • Affiliation：

    National Satellite Ocean Application Service, Beijing 100081, China

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

ZOU Bin23,  
  • role： Corresponding author通信作者
  • Affiliation：

    National Satellite Ocean Application Service, Beijing 100081, China

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

  • Email：shilj@mail.nsoas.org.cn
  • Introduction：石立坚，研究方向为海洋遥感应用。E-mail：shilj@mail.nsoas.org.cn
SHI Lijian23*,  
  • Affiliation：

    National Satellite Ocean Application Service, Beijing 100081, China

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

ZENG Tao23,  
  • Affiliation：

    National Satellite Ocean Application Service, Beijing 100081, China

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

ZHANG Xi23,  
  • Affiliation：

    National Marine Environmental Forecasting Center, Beijing 100081, China

    National Satellite Ocean Application Service, Beijing 100081, China

LU Dunwang12

ملخص

As an essential part of the global climate system, sea ice affects the atmosphere and ocean circulation. It is also an important indicator of climate change. Sea ice concentration is one of the most important geophysical parameters for describing polar sea ice. We conduct an inversion study of Arctic sea ice concentration based on a Microwave Radiation Imager (MWRI) carried by FY3 series satellites. The daily dynamic tie point of the brightness temperature is determined by linear regression and the threshold method. The influence of weather and land pollution on sea ice concentration retrieval is eliminated using a weather filter and land pollution correction methods. The trend of sea ice extent and sea ice area calculated from 2019 to 2020 has a strong correlation with the sea ice concentration products released by NSIDC. The mean differences in the sea ice extent and sea ice area are -0.052 ± 0.015 × 106 km2 and -0.401 ± 0.093 × 106 km2, respectively. The sea ice concentrations have negative differences, approximately -3% in winter with a mean absolute deviation of 2%—4% and negative deviations of approximately -8% in summer with a mean absolute deviation of approximately 10%. The accuracy of sea ice concentration datasets based on different algorithms of MWRI is evaluated using SAR data. Results show that the retrieval result of the bootstrap algorithm is better than that of the NASA team algorithm. The accuracy is improved by approximately 1% in winter and approximately 4% in summer. The dynamic tie points of the brightness temperature effectively reflect the seasonal variation of sea ice radiative characteristics. This research has laid a foundation for the business release of sea ice intensive products of China’s autonomous satellites, thereby guaranteeing the continuity of sea ice records in polar regions facing interruptions for more than 40 years.

مفهوم

remote sensing;Microwave radiometer;brightness temperature;sea ice concentration;FY-3;Arctic;bootstrap algorithm

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