SMOS卫星盐度数据在中国近岸海域的准确度评估

王新新; 杨建洪; 赵冬至; 王祥; 孙广轮

doi:10.3969/j.issn.0253-4193.2013.05.019

SMOS卫星盐度数据在中国近岸海域的准确度评估

doi: 10.3969/j.issn.0253-4193.2013.05.019

1.
大连海事大学环境科学与工程学院, 辽宁大连 116026;国家海洋局国家海洋环境监测中心, 辽宁大连 116023
2.
国家海洋局国家海洋环境监测中心, 辽宁大连 116023

基金项目: 海洋公益性行业科研专项经费项目(20090592)。

计量
- 文章访问数: 2145
- HTML全文浏览量: 18
- PDF下载量: 1843
- 被引次数: 0
出版历程
- 收稿日期: 2012-03-13

SMOS satellite salinity data accuracy assessment in the China coastal areas

1.
College of Environmental Science and Engineering, Dalian Maritime University, Dalian 116026, China;National Marine Environmental Monitoring Center, State Oceanic Administration, Dalian 116023, China
2.
National Marine Environmental Monitoring Center, State Oceanic Administration, Dalian 116023, China

摘要

摘要: 盐度是描述海洋的关键变量,对海表面盐度进行观测可以推进对全球水循环的理解。本文的主要目的是在中国近海海域对SMOS卫星盐度数据进行准确度评估。主要方法是将SMOS卫星L2海洋盐度数据产品(V317)与实测ARGO数据和走航数据进行匹配,并采用统计学的方法对SMOS卫星数据准确度进行评估。结果表明:匹配数据的线性关系不显著,SMOS卫星盐度数据(V317)在南海和东海的均方根误差分别约为1.2和0.7,应用海表面粗糙度修正模型得到的3组海表盐度数据准确度都相对较低,尤其在近岸强风场区域,海表盐度卫星数据相对于实测数据偏高,这可能是由于海表粗糙度和陆地射频干扰(RFI)作用影响的结果;SMOS卫星数据在东海的均方根误差比南海高0.5左右,这可能是由于东海海域为相对开阔海域,受陆地RFI影响相对南海较小;在中国近岸海域,应用SSS1和SSS3模型得到的盐度数据准确度相对较高,可以对模型进行地球物理参数修正,进行局地化改进,预计可以提高近岸海域盐度反演的准确度。
- 卫星遥感 /
- 海表盐度 /
- ARGO /
- 粗糙度修正模型 /
- 近岸影响
Abstract: The ocean salinity is a key variable to describe the ocean. Observing sea surface salinity (SSS) can promote the understanding of global water cycle. This paper main aims to carry out the accuracy assessment of SMOS satellite SSS data in the coastal waters of China. The main methods of this paper is that matching SMOS satellite L2 ocean salinity data products (V317) with the in-situ ARGO data and navigation data, evaluating SMOS satellite data using statistics method. The results show that the linear relationship of the matched data is not significant, and the RMSE of the SMOS SSS in South China Sea and East China Sea are 1.2 and 0.7 respectively. The three sets of SSS data, which are acquired applying three models in correcting the sea surface roughness are all with relatively low accuracy, especially in coastal strong wind areas,the SSS value observed by satellite is overestimated, and SMOS SSS retrieve may be seriously influenced by the sea surface roughness and land radio frequency. The RMSE of SMOS SSS data in South China Sea is higher than the East China Sea around 0.5.the degree of accuracy of salinity data using SSS1 and SSS3 are relatively high in the China seas. In further application, higher accuracy can be purchased by amending geophysical parametersand applying local improvement in China seas.
- satellite remote sensing /
- sea surface salinity /
- ARGO /
- roughness correction model /
- coastal effect

HTML全文

参考文献(22)

Talone M, Camps A, Sabia R, et al.Towards a coherent Sea Surface Salinity product from SMOS radiometric measurements and ARGO buoys[C]//Proceeding of International Geoscience and Remote Sensing Symposium,Barcelona,Spain,2007.Piscataway: Institute of Electrical and Electronics Engineers,2007:3959-3962.

Zine S, Boutin J, Font J, et al. Overview of the SMOS sea surface salinity prototype processor[J].IEEE Transactions on Geoscience and Remote Sensing,2008,46(3):621-644.

Kerr Y H, Waldteufel P, Wigneron J P, et al. soil moisture retrieval from space: the soil moisture and ocean salinity (SMOS) mission[J]. IEEE Transactions on Geoscience and Remote Sensing,2001,39(8):1729-1735.

Sonia Z, Jacqueline B, Philippe W, et al.Issues about retrieving Sea Surface Salinity in coastal areas from SMOS data[J]. IEEE Transactions on Geoscience and Remote Sensing,2007,45(7):2061-2072.

Marco T. Contribution to the improvement of the soil moisture and ocean salinity (SMOS) mission sea surface salinity retrieval algorithm. Barcelona: Universitat Politecnica de Catalunya (UPC), 2010.

Talone M, Sabia R, Gourrion J. Simulated SMOS Levels 2 and 3 products: the effect of introducing ARGO data in the processing chain and its impact on the error induced by the vicinity of the coast[J]. IEEE Transactions on Geoscience and Remote Sensing,2009,47(9):3041-3049.

Yueh S, Wilson W, Li F. Modeling of wind direction signals in polarimetric Sea Surface Brightness Temperatures[J]. IEEE Transactions on Geoscience and Remote Sensing,1997,35(6):1400-1418.

Gabarró C. Study of salinity retrieval errors for the SMOS mission[D]. Barcelona: Universitat Politècnica de Catalunya,2004:103-136.

Voronovich A.Small-slope approximation for electromagnetic wave scattering at a rough surface of two dielectric half spaces[J].Waves in Random Media,1994,4:337-367.

Reul N, Chapron B.A model of sea-foam thickness distribution for passive microwave remote sensing applications[J].Journal of Geophysical Research,2003,108(C10): 1-14.

Burrage D, Wang D, Wesson J,et al.SMOS observations of the Gulf of Mexico and Caribbean Sea: evaluating Surface Salinity retrieval and roughness correction performance[G]//Vienna: European Geosciences Union General Assembly,2011.

Banks C, Gommenginger C, Srokosz M, et al. Validating SMOS ocean surface salinity in the Atlantic with Argo and operational ocean model data[J]. IEEE Transactions on Geoscience and Remote Sensing,2012,50(5):1688-1702.

Boutin J, Reul N, Font J.Sea Surface Salinity from SMOS satellite: complementarity to In Situ observations[C/OL]//World Climate Research Programme Open Science Conference-Climate Research in Service to Society. Geneva: World Meteorological Organization,2011. http://conference2011.wcrp-climate.org/posters/C14/C14_boutin_T25A.pdf

Yueh S, West R, William W, et al. Error sources and feasibility for microwave remote sensing of ocean surface salinity[J]. IEEE Transactions on Geoscience and Remote Sensing,2001,39(5):1049-1060.

刘春霞,何溪澄.QuikSCAT散射计矢量风统计特征及南海大风遥感分析[J].热带气象学报,2003,19(增刊):107-117.

Gabarró C, Cames A, Font J. Retrieved Sea Surface Salinity and Wind Speed from L-band measurements for WISE and EuroSTARRS Campaigns[C]//Proceedings of the First Results Workshop on Euro STARRS, WISE, LOSAC Campaigns. Toulouse: Center for the Study of the Biosphere from Space (CESBIO),2003:163-171.

王杰,矫玉田,曹勇,等.海表面盐度遥感技术的发展与应用[J].海洋技术,2006,36(10):968-976.

Sabia R. Impact on Sea surface salinity retrieval of different auxiliary data within the SMOS mission[J]. IEEE Transactions on Geoscience and Remote Sensing,2006,44(10):2769-2778.

Biswas S,Jones L, Khan S. MWR and WindSat inter-satellite radiometric calibration plan[C]//Proceeding of 11 th Specialist Meeting on Microwave Radiometry and Remote Sensing of the Environment (MicroRad), Washington DC,USA, 2010.Piscataway: Institute of Electrical and Electronics Engineers, 2010 :266-271.

Hollinger J P. Passive microwave measurements of sea surface roughness[J]. IEEE Transactions on Geoscience Electronics, GE-9(3):1971,165-169.

王杰.微波遥感海水盐度的算法和影响因素分析[D].青岛:国家海洋局第一海洋研究所,2007.

殷晓斌.海面风矢量、温度和盐度的被动微波遥感及风对温盐遥感的影响研究[D].青岛:中国海洋大学,2007.

施引文献

资源附件(0)

访问统计