基于Bootstrap算法的FY-3/MWRI北极海冰密集度反演
Arctic sea ice concentration retrieval study of FY-3/MWRI based on the bootstrap algorithm
- 2023年27卷第4期 页码：973-985
收稿：2022-07-08，
纸质出版：2023-04-07
DOI： 10.11834/jrs.20222336
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摘要
海冰作为全球气候系统的重要组成部分，不仅影响着大气与海洋环流，也是气候变化的重要指示器。海冰密集度是描述极地海冰极为重要的地球物理参数之一。本文基于风云三号卫星微波成像仪（MWRI）亮温数据开展北极海冰密集度反演研究，采用线性回归和阈值法确定了动态亮温系点值，利用天气滤波器和陆地污染修正法消除了天气和陆地对海冰密集度反演的影响，计算了2019年—2020年海冰范围和海冰面积并与同类产品进行了比对。结果表明，本研究获取的北极海冰密集度产品与NSIDC发布的海冰密集度产品有较高的相关性，海冰密集度的差异在冬季小于3%，夏季小于8%。利用SAR数据进行了不同产品的结果评估，结果表明本文算法的反演结果优于NASA Team算法，在冬季精度约有1%的提升，在夏季精度约有4%左右的提升。动态亮温系点值较好地反映了海冰辐射特性的季节变化。本研究为中国自主卫星的海冰密集度产品的业务化发布奠定了基础。
Abstract
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 km
2
and -0.401 ± 0.093 × 106 km
2
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.
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Keywords
references
Beitsch A , Kern S and Kaleschke L . 2015 . Comparison of SSM/I and AMSR-E sea ice concentrations with ASPeCt ship observations around antarctica . IEEE Transactions on Geoscience and Remote Sensing , 53 ( 4 ): 1985 - 1996 [ DOI: 10.1109/TGRS.2014.2351497 http://dx.doi.org/10.1109/TGRS.2014.2351497 ]
Brucker L , Cavalieri D J , Markus T and Ivanoff A . 2014 . NASA Team 2 sea ice concentration algorithm retrieval uncertainty . IEEE Transactions on Geoscience and Remote Sensing , 52 ( 11 ): 7336 - 7352 [ DOI: 10.1109/TGRS.2014.2311376 http://dx.doi.org/10.1109/TGRS.2014.2311376 ]
Cavalieri D J , Gloersen P and Campbell W J . 1984 . Determination of sea ice parameters with the NIMBUS 7 SMMR . Journal of Geophysical Research: Atmospheres , 89 ( D4 ): 5355 - 5369 [ DOI: 10.1029/JD089iD04p05355 http://dx.doi.org/10.1029/JD089iD04p05355 ]
Cavalieri D J , Parkinson C L , Gloersen P , Comiso J C and Zwally H J . 1999 . Deriving long-term time series of sea ice cover from satellite passive-microwave multisensor data sets . Journal of Geophysical Research: Oceans , 104 ( C7 ): 15803 - 15814 [ DOI: 10.1029/1999JC900081 http://dx.doi.org/10.1029/1999JC900081 ]
Cavalieri D J , Parkinson C L , Gloersen P and Zwally H J . 1997 . Arctic and Antarctic Sea Ice Concentrations from Multichannel Passive-Microwave Satellite Data Sets: October 1978-September 1995: User's Guide. NASA Technical Memorandum 104647 . NASA
Chen Y , Zhao X , Pang X P and Ji Q . 2022 . Daily sea ice concentration product based on brightness temperature data of FY-3D MWRI in the Arctic . Big Earth Data , 6 ( 2 ): 164 - 178 [ DOI: 10.1080/20964471.2020.1865623 http://dx.doi.org/10.1080/20964471.2020.1865623 ]
Cheung H H N , Keenlyside N , Omrani N E and Zhou W . 2018 . Remarkable link between projected uncertainties of Arctic sea-ice decline and winter Eurasian climate . Advances in Atmospheric Sciences , 35 ( 1 ): 38 - 51 [ DOI: 10.1007/s00376-017-7156-5 http://dx.doi.org/10.1007/s00376-017-7156-5 ]
Comiso J C . 1986 . Characteristics of Arctic winter sea ice from satellite multispectral microwave observations . Journal of Geophysical Research : Oceans , 91 ( C1 ): 975 - 994 [ DOI: 10.1029/JC091iC01p00975 http://dx.doi.org/10.1029/JC091iC01p00975 ]
Comiso J C and Zwally H J . 1982 . Antarctic sea ice concentrations inferred from Nimbus 5 ESMR and Landsat imagery . Journal of Geophysical Research : Oceans , 87 ( C8 ): 5836 - 5844 . [ DOI: 10.1029/JC087iC08p05836 http://dx.doi.org/10.1029/JC087iC08p05836 ]
Comiso J C . 1995 . SSM/I Sea Ice Concentrations Using the Bootstrap Algorithm. NASA Reference Publication 1380 . NASA
Comiso J C , Cavalieri D J , Parkinson C L and Gloersen P . 1997 . Passive microwave algorithms for sea ice concentration: a comparison of two techniques . Remote Sensing of Environment , 60 ( 3 ): 357 - 384 [ DOI: 10.1016/S0034-4257(96)00220-9 http://dx.doi.org/10.1016/S0034-4257(96)00220-9 ]
Comiso J C . 2017 . Bootstrap Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/I-SSMIS, Version 3 [Data Set] . Boulder, Colorado USA : NASA National Snow and Ice Data Center Distributed Active Archive Center [ DOI: 10.5067/7Q8HCCWS4I0R http://dx.doi.org/10.5067/7Q8HCCWS4I0R ]
Comiso J C , Meier W N and Gersten R . 2017 . Variability and trends in the Arctic Sea ice cover: results from different techniques . Journal of Geophysical Research: Oceans , 122 ( 8 ): 6883 - 6900 [ DOI: 10.1002/2017JC012768 http://dx.doi.org/10.1002/2017JC012768 ]
Kern S , Lavergne T , Notz D , Pedersen L T , Tonboe R T , Saldo R and Sørensen A M . 2019 . Satellite passive microwave sea-ice concentration data set intercomparison: closed ice and ship-based observations . The Cryosphere , 13 ( 12 ): 3261 - 3307 [ DOI: 10.5194/tc-13-3261-2019 http://dx.doi.org/10.5194/tc-13-3261-2019 ]
Kern S , Lavergne T , Notz D , Pedersen L T and Tonboe R . 2020 . Satellite passive microwave sea-ice concentration data set inter-comparison for Arctic summer conditions . The Cryosphere , 14 ( 7 ): 2469 - 2493 [ DOI: 10.5194/tc-14-2469-2020 http://dx.doi.org/10.5194/tc-14-2469-2020 ]
Kern S , Lavergne T , Pedersen L T , Tonboe R T , Bell L , Meyer M and Zeigermann L . 2022 . Satellite passive microwave sea-ice concentration data set intercomparison using Landsat data . The Cryosphere , 16 ( 1 ): 349 - 378 [ DOI: 10.5194/tc-16-349-2022 http://dx.doi.org/10.5194/tc-16-349-2022 ]
Knuth M A and Ackley S F . 2006 . Summer and early-fall sea-ice concentration in the Ross Sea: comparison of in situ ASPeCt observations and satellite passive microwave estimates . Annals of Glaciology , 44 : 303 - 309 [ DOI: 10.3189/172756406781811466 http://dx.doi.org/10.3189/172756406781811466 ]
Kwok R . 2018 . Arctic sea ice thickness, volume, and multiyear ice coverage: Losses and coupled variability (1958-2018) . Environmental Research Letters , 13 ( 10 ): 105005 [ DOI: 10.1088/1748-9326/aae3ec http://dx.doi.org/10.1088/1748-9326/aae3ec ]
Li X Q , Cheng X , Hui F M , Zhai M X and Zhang Y Y . 2016 . Analysis of sea ice conditions in the Arctic Northeast Passage in summer 2014 . Chinese Journal of Polar Research , 28 ( 1 ): 87 - 94
李新情 , 程晓 , 惠凤鸣 , 翟梦茜 , 张媛媛 . 2016 . 2014年夏季北极东北航道冰情分析 . 极地研究 , 28 ( 1 ): 87 - 94 [ DOI: 10.13679/j.jdyj.2016.1.087 http://dx.doi.org/10.13679/j.jdyj.2016.1.087 ]
Liu S , Zou B , Shi L J and Cui Y R . 2020 . Polar sea ice concentration retrieval based on FY-3C microwave radiation imager data . Acta Oceanologica Sinica , 42 ( 1 ): 113 - 122
刘森 , 邹斌 , 石立坚 , 崔艳荣 . 2020 . 基于FY-3C微波辐射计数据的极区海冰密集度反演方法研究 . 海洋学报 , 42 ( 1 ): 113 - 122 [ DOI: 10.3969/j.issn.0253-4193.2020.01.012 http://dx.doi.org/10.3969/j.issn.0253-4193.2020.01.012 ]
Liu Y X , Wang Z M and Liu T T . 2016 . Change analysis for antarctic and arctic sea ice concentration and extent . Remote Sensing Information , 31 ( 2 ): 24 - 29
刘艳霞 , 王泽民 , 刘婷婷 . 2016 . 1979~2014年南北极海冰变化特征分析 . 遥感信息 , 31 ( 2 ): 24 - 29 [ DOI: 10.3969/j.issn.1000-3177.2016.02.005 http://dx.doi.org/10.3969/j.issn.1000-3177.2016.02.005 ]
Markus T and Cavalieri D J . 2000 . An enhancement of the NASA Team sea ice algorithm . IEEE Transactions on Geoscience and Remote Sensing , 38 ( 3 ): 1387 - 1398 [ DOI: 10.1109/36.843033 http://dx.doi.org/10.1109/36.843033 ]
Matzler C , Ramseier R and Svendsen E . 1984 . Polarization effects in seaice signatures . IEEE Journal of Oceanic Engineering , 1984, 9 ( 5 ): 333 - 338 [ DOI: 10.1109/JOE.1984.1145646 http://dx.doi.org/10.1109/JOE.1984.1145646 ]
Parkinson C L , Comiso J C , Zwally H J , Cavalieri D J , Gloersen P and Campbell W J . 1987 . Arctic Sea Ice , 1973 - 1976 : Satellite Passive-Microwave Observations . Washington : Scientific and Technical Information Branch, National Aeronautics and Space Administration
Serreze M C , Barrett A P , Stroeve J C , Kindig D N and Holland M M . 2009 . The emergence of surface-based Arctic amplification . The Cryosphere , 3 ( 1 ): 11 - 19 [ DOI: 10.5194/tc-3-11-2009 http://dx.doi.org/10.5194/tc-3-11-2009 ]
Shi L J , Liu S , Shi Y N , Ao X , Zou B and Wang Q M . 2021 . Sea ice concentration products over polar regions with Chinese FY3C/MWRI data . Remote Sensing , 13 ( 11 ): 2174 [ DOI: 10.3390/rs13112174 http://dx.doi.org/10.3390/rs13112174 ]
Shi L J , Wang Q M , Zou B , Shi Y N and Jiao M . 2014 . Arctic sea ice concentration retrieval using HY-2 radiometer data . Chinese Journal of Polar Research , 26 ( 4 ): 410 - 417
石立坚 , 王其茂 , 邹斌 , 施英妮 , 焦敏 . 2014 . 利用海洋(HY-2)卫星微波辐射计数据反演北极区域海冰密集度 . 极地研究 , 26 ( 4 ): 410 - 417 [ DOI: 10.13679/j.jdyj.2014.4.410 http://dx.doi.org/10.13679/j.jdyj.2014.4.410 ]
Smith D M . 1996 . Extraction of winter total sea-ice concentration in the Greenland and Barents Seas from SSM/I data . International Journal of Remote Sensing , 17 ( 13 ): 2625 - 2646 [ DOI: 10.1080/01431169608949096 http://dx.doi.org/10.1080/01431169608949096 ]
Spreen G , Kaleschke L and Heygster G . 2008 . Sea ice remote sensing using AMSR-E 89-GHz channels . Journal of Geophysical Research : Oceans , 113 ( C2 ): C02 S 03 [ DOI: 10.1029/2005JC003384 http://dx.doi.org/10.1029/2005JC003384 ]
Stroeve J C , Markus T , Boisvert L , Miller J and Barrett A . 2014 . Changes in Arctic melt season and implications for sea ice loss . Geophysical Research Letters , 41 ( 4 ): 1216 - 1225 [ DOI: 10.1002/2013GL058951 http://dx.doi.org/10.1002/2013GL058951 ]
Svendsen E , Matzler C and Grenfell T C . 1987 . A model for retrieving total sea ice concentration from a spaceborne dual-polarized passive microwave instrument operating near 90 GHz . International Journal of Remote Sensing , 8 ( 10 ): 1479 - 1487 . [ DOI: 10.1080/01431168708954790 http://dx.doi.org/10.1080/01431168708954790 ]
Tonboe R T , Eastwood S , Lavergne T , Sørensen A M , Rathmann N , Dybkjær G , Pedersen L T , Høyer J L and Kern S . 2016 . The EUMETSAT sea ice concentration climate data record . The Cryosphere , 10 ( 5 ): 2275 - 2290 [ DOI: 10.5194/tc-10-2275-2016 http://dx.doi.org/10.5194/tc-10-2275-2016 ]
Wang Y R and Li X M . 2021 . Arctic sea ice cover data from spaceborne synthetic aperture radar by deep learning . Earth System Science Data , 13 ( 6 ): 2723 - 2742 [ DOI: 10.5194/essd-13-2723-2021 http://dx.doi.org/10.5194/essd-13-2723-2021 ]
Xi Y , Sun B and Li X . 2013 . Assessment of AMSR-E ASI sea ice concentration using ship observations and Landsat-7 ETM+imagery . Journal of Remote Sensing , 17 ( 3 ): 514 - 526
席颖 , 孙波 , 李鑫 . 2013 . 利用船测数据以及Landsat-7 ETM+影像评估南极海冰区AMSR-E海冰密集度 . 遥感学报 , 17 ( 3 ): 514 - 526 [ DOI: 10.11834/jrs.20132081 http://dx.doi.org/10.11834/jrs.20132081 ]
Xu S M , Zhou L , Liu J P , Lu H and Wang B . 2017 . Data synergy between altimetry and l-band passive microwave remote sensing for the retrieval of sea ice parameters—a theoretical study of methodology . Remote Sensing , 9 ( 10 ): 1079 [ DOI: 10.3390/rs9101079 http://dx.doi.org/10.3390/rs9101079 ]
Zhang S G . 2012 . Sea Ice Concentration Algorithm and Study on the Physical Process about Sea Ice and Melt-pond Change in Central Arctic . Qingdao : Ocean University of China
张树刚 . 2012 . 海冰密集度反演以及北极中央区海冰和融池变化物理过程研究 . 青岛 : 中国海洋大学
Zwally H J . 1983 . Antarctic Sea Ice , 1973 - 1976 : Satellite Passive-Microwave Observations . Washington : Scientific and Technical Information Branch, National Aeronautics and Space Administration
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孟治国 吉林大学 地球探测科学与技术学院
赵瑞 吉林大学 地球探测科学与技术学院;武警工程大学 信息工程学院
蔡占川 澳门科技大学 月球与行星科学国家重点实验室
张渊智 中国科学院国家天文台;中国科学院大学 天文与空间科学学院
邹猛 吉林大学 工程仿生教育部重点实验室
张小平 澳门科技大学 月球与行星科学国家重点实验室
王宝震 北京大学 地球与空间科学学院遥感与地理信息系统研究所
任华忠 北京大学 地球与空间科学学院遥感与地理信息系统研究所;空间信息集成与3S工程应用北京市重点实验室;教育部高校联合遥感应用研究中心
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吉林大学 地球探测科学与技术学院
武警工程大学 信息工程学院
澳门科技大学 月球与行星科学国家重点实验室
中国科学院国家天文台
中国科学院大学 天文与空间科学学院
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