基于变分理论的AVHRR海表温度反演应用及效果评估

陈靖扬; 陈耀登; 师春香; 李旭; 徐宾

doi:10.3969/j.issn.0253-4193.2018.02.003

基于变分理论的AVHRR海表温度反演应用及效果评估

doi: 10.3969/j.issn.0253-4193.2018.02.003

1.
南京信息工程大学气象灾害教育部重点实验室气候与环境变化国际合作联合实验室气象灾害预报预警与评估协同创新中心, 江苏南京 210044
2.
国家气象信息中心, 北京 100081
3.
NOAA Science Center, Research and Data Systems Corporation, USA Maryland 20746-4304

基金项目: 公益性行业（气象）科研专项（201506002）；国家重点研发计划（2017YFC1502100）；国家自然科学基金项目（41675102）；中国气象局"气象资料质量控制及多源数据融合与再分析"项目。

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出版历程
- 收稿日期: 2017-01-22

AVHRR SST retrieval using variation algorithm and evaluation

1.
Key Laboratory of Meteorological Disaster of Ministry of Education(KLME)/Joint International Research Laboratory of Climate and Environment Change(ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing 210044, China
2.
National Meteorological Information Center, Beijing 100081
3.
Research and Data Systems Corporation, NOAA Science Center, Maryland 20746-4304, USA

摘要

摘要: 基于变分理论算法实现了METOP-A卫星AVHRR传感器探测数据的海洋表面温度变分反演，进行了连续1个月的海表温度反演试验，并分别从全球、分纬度带和天气系统活跃区域3个方面，将变分反演结果（VAR SST）与利用统计回归方法反演相同卫星得到的海表温度产品（GBL SST）、其他海温融合产品（OISST）及实际浮标观测数据等进行一系列评估。从全球评估指标看出，以OISST为参照，VAR SST要优于GBL SST；以浮标观测为参照，VAR SST略逊于GBL SST，而且VAR SST还改进了GBL SST随时间波动大的缺点；从分纬度带对比看出，在与OISST对比时，VAR SST在低纬度地区和北半球中纬度地区的质量要优于GBL SST，海温反演精度较高。研究还表明，由于变分方法考虑了大气状态的变化，能够更加有效订正卫星遥感过程中大气的削弱作用，从而反演出精度更高的海表温度，尤其在天气系统较为复杂的区域效果明显。
- 海表温度 /
- 反演 /
- 变分理论 /
- 统计回归 /
- AVHRR
Abstract: METOP-A/AVHRR sea surface temperature (SST) retrieved by using variation algorithm. SST retrieval was done for one month. In this paper, the result of variation retrieval (VAR SST) was evaluated by the product which retrieved by using regression algorithm of the same sensor and satellite (GBL SST), OISST and the buoy observation. This evaluation was done in the global regional and the weather system active regional. According to the evaluation index, we know that VAR SST is better than GBL SST when they are compared with OISST and worse than it when they are compared with buoy observation. In addition, the VAR SST also improved the GBL SST shortcomings about time fluctuations. When the VAR SST and the GBL SST compared with OISST in different latitude zones, we discovered that the VAR SST, which with higher accuracy, is better than GBL SST in the low latitudes and the middle latitude of Southern Hemisphere. According to the research, variation algorithm can correct the atmospheric attenuation in satellite remote sensing more effectively and get a higher accurate SST, especially in the area of the complex weather system. That's because the atmospheric temperature and water vapor mixing ratio were considered in this algorithm.
- sea surface temperature /
- retrieval /
- variation algorithm /
- statistical regression /
- AVHRR

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参考文献(30)

Wentz F J, Gentemann C, Smith D, et al. Satellite measurements of sea surface temperature through clouds[J]. Science, 2000, 288(5467):847-50.

Hosoda K, Murakami H, Sakaida F, et al. Algorithm and validation of sea surface temperature observation using MODIS sensors aboard terra and aqua in the western North Pacific[J]. Journal of Oceanography, 2007, 63(2):267-280.

王素娟,陆风,张鹏,等. FY2海面温度产品质量检验方法与误差分析[J]. 气象,2013,10:1331-1336. Wang Sujuan, Lu Feng, Zhang Peng, et al. Quality validation methods and error analysis for FY2 sea surface temperature[J]. Meteorological Monthly,2013,10:1331-1336.

王素娟,崔鹏,冉茂农,等. FY3A/VIRR海面温度业务产品算法改进与质量检验[J]. 气象科技,2014,05:748-752. Wang Sujuan, Cui Peng, Ran Maonong, et al. Algorithm improvemnet and quality validation of operational FY3A/VIRR SST product[J]. Meteorological Science and Technology, 2014,05:748-752.

Mcclain E P, Pichel W G, Walton C C. Comparative performance of AVHRR-based multichannel sea surface temperatures[J]. Journal of Geophysical Research Oceans, 1985, 90(C6):11587-11601.

Walton C C. Nonlinear multichannel algorithms for estimating sea surface temperature with AVHRR satellite data[J]. Journal of Applied Meteorology, 1988, 27(2):115-124.

Walton C C, Pichel W G, Sapper J F, et al. The development and operational application of nonlinear algorithms for the measurement of sea surface temperatures with the NOAA polar-orbiting environmental satellites[J]. Journal of Geophysical Research Atmospheres, 1998, 103(C12):27999-28012.

Li X,Pichel W, Maturi E, et al. Deriving the operational nonlinear multichannel sea surface temperature algorithm coefficients for NOAA-15 AVHRR/3[J]. International Journal of Remote Sensing, 2001, 22(4):699-704.

Anding D, Kauth R. Estimation of sea surface temperature from space[J]. Remote Sensing of Environment, 1970, 1(4):217-220.

Mcmillin L M, Crosby D S. Theory and validation of the multiple window sea surface temperature technique[J]. Journal of Geophysical Research, 1984, 89(89):3655-3662.

王其茂, 金振刚, 孙从容. "海洋一号"(HY-1)卫星数据的海面温度反演[J]. 海洋预报, 2003, 20(3):53-59. Wang Qimao, Jin Zhengang, Sun Congrong. Sea surface temperature retrieval using the HY-1 satellite data[J].Marine Forecasts, 2003, 20(3):53-59.

周旋, 杨晓峰, 程亮,等. 单通道物理法反演海表温度的参数敏感性分析及验证[J]. 红外与毫米波学报, 2012, 31(1):91-96. Zhou Xuan, Yang Xiaofeng, Cheng Liang,et at. Sensitivity analysis and validation of the single channel physical method for retrieving sea surface temperature[J]. Journal of Infrared and Millimeter Waves, 2012, 31(1):91-96.

Akihiro U, Hiroshi F, Toshiro Y. Estimate of sea surface temperature using infrared image data of geostationary meteorological satellite (GMS)[J]. Meteorological Satellite Center Technical Note, 1987,15:43-65.

李万彪, 朱元竞, 赵柏林. 气象卫星遥感西北太平洋海温的研究[J]. 气象学报, 1997(1):43-54. Li Wanbiao, Zhu Yuanjing, Zhao Bailin. Study on SST in the Northwestern Pacific Ocean with satellite observation[J]. Acta Meteorol Sin, 1997(1):43-54.

Ma X L, Schmit T J, Smith W L. A nonlinear physical retrieval algorithm-Its application to the GOES-8/9 Sounder[J]. Journal of Applied Meteorology, 1999, 38(5):501-513.

Koner P, Harris A. Improved quality of MODIS sea surface temperature retrieval and data coverage using physical deterministic methods[J]. Remote Sensing, 2016, 8(6):454.

何明元, 马卫明, 史卫, 等. "FY3A"卫星资料在海面温度反演中的应用[C]//济南:全国水动力学研讨会. 2009. He Mingyuan, Ma Weiming, Shi Wei, et al. Sea Surface Temperature Retrieval Using FY3A Satellite Data[C].Ji'nan:National Congress on Hydrodynamics,2009.

Gemmill W,Katz B,Li X. Burroughs The daily real-time, global sea surface temperature high resolution analysis:RTG_SST_HR. http://docs.lib.noaa.gov/rescue/wb_technical_procedures_bulletin/MMAB_TPB/MMAB_TPB_2006-01.pdf

"GFS Presentation", https://vlab.ncep.noaa.gov/web/gfs/home/-/document_library_display(2016/07/12).

官元红, 周广庆, 陆维松,等. 资料同化方法的理论发展及应用综述[J]. 气象与减灾研究, 2007, 30(4):1-8. Guan Yuanhong, Zhou Guangqing, Lu Weisong, et al.Theory development and application of data assimilation methods[J]. Meteorology and Disaster Reduction Research, 2007, 30(4):1-8.

陆燕. 欧洲下一代气象卫星及其红外遥感仪器概要[J]. 红外, 2013, 34(11):1-7. Lu Yan. Survey of the nest-generation meterorlogical satellites and infrared sensors of RUMETSAT/ESA[J]. Infrared, 2013, 34(11):1-7.

"Advanced Very High Resolution Radiometer-AVHRR", http://noaasis.noaa.gov/NOAASIS/ml/avhrr.html (2016/04/05).

http://www.osi-saf.org/lml/#pres_SST.

Kilpatrick K A, Podestá G P, Evans R. Overview of the NOAA/NASA Advanced Very High Resolution Radiometer Pathfinder algorithm for sea surface temperature and associated matchup database[J]. J Geophys Res,2001, 106(C5):9179-9197.

Casey K S, Brandon T B, Cornillon P, et al. The Past, Present and Future of the AVHRR Pathfinder SST Program, in Oceanography from Space[M]//Oceanography from Space, Springer, 2010:273-287.

蒋兴伟,奚萌,宋清涛. 六种遥感海表温度产品的比对分析[J]. 海洋学报, 2013,35(4):88-97. Jiang Xingwei, Xi Meng, Song Qingtao. A comparison of six sea temperature analyses[J]. Haiyang Xuebao,2013,35(4):88-97.

刘瑞霞,师春香,刘杰. 直方变差图理论在卫星产品质量检验空间配准中的应用[J]. 遥感学报,2009,02:307-312. Liu Ruixia, Shi Chunxiang, Liu Jie. The application of Histo_variogram method in spatial matching of satellite data validation[J]. Journal of Remote Sensing, 2009,02:307-312.

李明, 刘骥平, 张占海,等. 利用南大洋漂流浮标数据评估AMSR-E SST[J]. 海洋学报, 2010, 32(6):47-55. Li Ming, Liu Jiping, Zhang Zhanhai, et al. Evaluation of AMSR-E SST in the Southern Ocean using drifting buoy data[J]. Haiyang Xuebao,2010, 32(6):47-55.

Kawai Y, Wada A. Diurnal sea surface temperature variation and its impact on the atmosphere and ocean:A review[J]. Journal of Oceanography, 2007, 63(5):721-744.

Eyre J R, Menzel W P. Retrieval of cloud parameters from satellite Sounder data:A simulation study[J]. Journal of Applied Meteorology, 1989, 28(4):267-275.

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