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FY-3B/MWRI北极海冰密集度ASI算法反演研究

Retrieval of the Arctic sea ice concentration from FY-3B/MWRI using ASI algorithm

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【作者】 李乐乐; 王晓雨; 陈海花; 苏洁; 管磊;

【Author】 LI Lele;WANG Xiaoyu;CHEN Haihua;SU Jie;GUAN Lei;Faculty of Information Science & Engineering,Ocean University of China;University Corporation for Polar Research;Key Laboratory of Physical Oceanography,Ministry of Education,Ocean University of China;Laboratory for Regional Oceanography and Numerical Modeling,Qingdao National Laboratory for Marine Science and Technology;

【通讯作者】 管磊;

【机构】 中国海洋大学信息科学与工程学部; 中国高校极地联合研究中心; 中国海洋大学物理海洋教育部重点实验室; 区域海洋动力学与数值模拟功能实验室青岛海洋科学与技术国家实验室;

【摘要】 近年来,由于“北极放大”的气候效应,使得北极海冰变化受到了越来越多的关注。而作为海冰被动微波遥感的主要参数,海冰密集度SIC (Sea Ice Concentration)能够表征海冰的主要状态,可用于指导极区走航以及进行不同尺度的海冰变化研究。通过该参数还可以计算出海冰面积、海冰范围等信息,对极区冰情预测以及气候变化研究具有重要意义。本研究探讨了如何利用FY-3B/MWRI (FY-3B/MicroWave Radiometer Imager)较高分辨率通道数据来反演北极地区海冰密集度。基于ASI (ARTIST (Arctic Radiation and Turbulence Interaction STudy) Sea Ice)算法,本研究通过改进算法系点值的方法反演了北极地区海冰密集度,并将反演结果与MWRI海冰密集度产品进行了对比。首先利用Aqua/MODIS (Moderate Resolution Imaging Spectroradiometer)反射率数据获得的海冰密集度对二者进行了验证。结果表明,本研究选用的新系点值ASI算法在全部数据集范围内的平均偏差与MWRI海冰密集度产品相当,但标准偏差和均方根误差均较之明显降低,且在海冰密集度低于95%时精度远高于MWRI产品;然后将二者与不莱梅大学的SIC_UB (Sea Ice Concentration from University of Bremen)海冰密集度产品进行了对比,其中本研究反演海冰密集度与SIC_UB产品的平均偏差和标准偏差分别为3.3%和10.6%,低于MWRI产品与SIC_UB产品之间的5.9%和16.4%;最后,对本研究反演结果、MWRI产品、NSIDC/AMSR-E(National Snow and Ice Data Center/Advanced Microwave Scanning Radiometer-EOS)产品以及SIC_UB产品的日均海冰密集度和海冰面积、海冰范围进行了时间序列对比,结果表明本研究反演海冰密集度的数值在3种统计方式下均显著低于MWRI产品,且较之更接近NSIDC/AMSR-E和SIC_UB产品。本研究利用国产卫星亮温数据反演的北极地区海冰密集度具有较高空间分辨率和较高精度,有利于北极地区气候变化的长时间序列研究。

【Abstract】 The change of Arctic sea ice has recently attracted much attention among climate researchers due to the climate effect of“Arctic Amplification”. Sea ice concentration, which is the main parameter of passive microwave remote sensing of sea ice, can characterize the sea ice conditions, which can be used to guide the polar navigation and study the sea ice change in different scales. The sea ice area and sea ice extent can also be calculated by using the sea ice concentration, which is of great significance for the forecast of polar sea ice conditions and the study of climate change. This work discusses how to use the high resolution channels of FY-3B/MWRI(FY-3B/Microwave Radiometer Imager) to retrieve the sea ice concentrations in the Arctic. Based on the ASI(ARTIST [Arctic Radiation and Turbulence Interaction Study]Sea Ice) algorithm, the Arctic sea ice concentration is calculated in this study by improving the tie points of the algorithm. According to the cross calibration of brightness temperatures between the FY-3B/MWRI and the Aqua/AMSR-E(Advanced Microwave Scanning Radiometer-EOS), the differences between the two brightness temperature data are between ±4 K, which will result in a maximum bright temperature difference of 8 K. Accordingly, this study first sets the variation range of the tie points for FY-3B/MWRI centered on the original values of the ASI algorithm to 11.7±8 K for sea ice and 47.0±8 K for open water, separately, with a step length of 1 K. After the combination, 289 series of point value combinations are obtained. Then, the sea ice concentrations corresponding to each set of tie points are compared with those of the AMSR-E L3 product. Meanwhile, the tie points corresponding to the smallest deviation of the two data sets are selected. According to the tie points determined above, this study calculated the Arctic sea ice concentrations based on the FY-3B/MWRI brightness temperatures, hereinafter referred to as the Retrieved Sea Ice Concentration(RSIC). The RSICs in this study are compared with the MWRI Level 2 sea ice concentration product(hereinafter referred to as MWRI). First, the sea ice concentrations obtained from the Aqua/MODIS(Moderate Resolution Imaging Spectroradiometer) reflectivity data from July to September 2011 are used to verify the two data sets. The results show that the bias of RSIC is comparable to that of the MWRI product. However, the standard deviation and root mean square error are significantly reduced. Meanwhile, the accuracy of RSIC is much higher than that of the MWRI product in the areas with a sea ice concentration lower than 95%. Then, the two sea ice concentration data sets are compared with the sea ice concentration product from the University of Bremen(SIC_UB). The bias and the standard deviation between RSIC and SIC_UB are 3.3% and 10.6%, which are lower than the values between the MWRI and the SIC_UB products: 5.9% and 16.4%, respectively. Finally, the time series of the daily averaged sea ice concentration, sea ice area, and sea ice extent from the RSIC, MWRI, SIC_UB, and NSIDC/AMSR-E(National Snow and Ice Data Center/Advanced Microwave Scanning Radiometer-E) sea ice concentration products are compared. The results show that the values of RSIC are significantly lower than those of the MWRI product in three statistical methods and much closer to the AMSR-E and SIC_UB products. In this study, the sea ice concentrations in the Arctic region are retrieved based on the brightness temperatures from the FY-3B/MWRI high frequency channels. The sea ice concentrations in this study have a higher spatial resolution and a better accuracy compared with the FY-3B/MWRI L2 sea ice concentration product, which is conducive to the long-time series study of climate change in the Arctic.

【基金】 国家重点研发计划课题(编号:2019YFA0607001,2018YFA0605903)~~
  • 【文献出处】 遥感学报 ,National Remote Sensing Bulletin , 编辑部邮箱 ,2022年11期
  • 【分类号】P715.7
  • 【下载频次】77
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