海表温度对SMOS盐度遥感反演精度的影响

金旭晨; 朱乾坤; 潘德炉; 龚芳; 何贤强

doi:10.11834/jrs.20176261

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海表温度对SMOS盐度遥感反演精度的影响
Impact of sea surface temperature on sea surface salinity retrieval by SMOS microwave radiometer
2017年21卷第6期页码：939-947
收稿：2016-08-01，

录用：2017-5-22，

纸质出版：2017-09-15
DOI： 10.11834/jrs.20176261
稿件说明：

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金旭晨, 朱乾坤, 潘德炉, 龚芳, 何贤强. 2017. 海表温度对SMOS盐度遥感反演精度的影响. 遥感学报, 21(6): 939–947 DOI： 10.11834/jrs.20176261.

Jin X C, Zhu Q K, Pan D L, Gong F and He X Q. 2017. Impact of sea surface temperature on sea surface salinity retrieval by SMOS microwave radiometer. Journal of Remote Sensing, 21(6): 939–947 DOI： 10.11834/jrs.20176261.

摘要

利用星载微波辐射计对全球海表盐度的卫星遥感探测，其精度会受到多种环境因子的影响。采用广义加性模型GAM和偏最小二乘法PLS分析了水温对海表盐度遥感反演精度的影响，同时，利用ARGO观测数据对SMOS卫星反演的赤道太平洋和西北太平洋海表盐度进行精度检验。结果表明，水温对海表盐度反演精度具有显著影响，且Stokes矢量第一参数(总辐亮度)是海表盐度反演的最佳亮温参数。在平均水温约16 ℃时的均方误差约为0.9 psu，23 ℃水温下的均方误差约为0.7 psu，30 ℃水温下的均方误差约为0.4 psu，即高水温下盐度反演精度相对较高。

Abstract

Global sea surface salinity (

SSS

) is retrieved using satellite microwave radiometers

Currently. However

SSS

remote sensing with an L-band radiometer is still challenging due to the low sensitivity of its brightness temperature to

SSS

variation. Results show that the sensitivities of vertically (

) and horizontally (

) polarized brightness temperature range from 0.4 K/psu to 0.8 K/psu and from 0.2 K/psu to 0.6 K/psu

respectively

at different observing angles and sea surface temperatures (

SST

). Hence

high-accuracy measurements are required. However

the quantitative effect of Sea Surface Temperature (

SST

) on the satellite retrieval of

SSS

remains unknown. In this study

we investigate the effect of

SST

on the accuracy of salinity retrieval from the Soil Moisture and Ocean Salinity (SMOS). The dielectric constant model proposed by Klein and Swift has been used to estimate the

and

of a flat sea water surface at L-band and obtain the derivatives of

and

as a function of

SSS

to show the relative sensitivity at different incident angles (12.5° and 42.5°). Moreover

the Generalized Additive Model (GAM) and the Partial Least Squares (PLS) regression method were used to investigate the effect of

SST

on the accuracy of salinity retrieval from the SMOS. Furthermore

SMOS data are compared with Argo data to assess the quality of satellite-derived

SSS

data at different

SST

s by calculating the root-mean-square error (RMSE) of two regions of the Pacific Ocean far from land and ice. Results show that satellite-measured brightness temperature has high sensitivity to

SSS

variation and good accuracy of

SSS

retrieval with high

SST

. For most open oceans where surface salinity is typically greater than 32 psu

the sensitivity is approximately 0.2–0.25 K/psu for

and

when the

SST

is 5 ℃

and the brightness temperature is more sensitive to the

SSS

for

than

with increasing

SST

. When the

SST

increases to 30 ℃

the sensitivity is approximately 0.8 K/psu for

. Moreover

the RMSEs of SMOS-derived

SSS

data are approximately 0.9

0.7

and 0.4 psu in regions of the Pacific Ocean where the

SST

s are approximately 16 ℃

23 ℃

and 30 ℃

respectively. Results of the GAM and the PLS model indicate that satellite-measured brightness temperature highly correlates with in situ

SSS

at high

SST

s. In addition

validation results of Argo data suggest that water temperature significantly affects

SSS

retrieval accuracy and that accurate

SSS

retrieval can be achieved at high

SST

s. These results indicate that

SST

can significantly influence the retrieval accuracy of

SSS

. Hence

the development of a new

SSS

retrieval algorithm that adapts to low

SST

s is necessary.

关键词

Keywords

references

Corbella I, Durán I, Wu L, Torres F, Duffo N, Khazâal A and Martín-Neira M. 2015a. Impact of correlator efficiency errors on SMOS land-sea contamination. IEEE Geoscience and Remote Sensing Letters, 12(9): 1813–1817

Corbella I, Wu L, Torres F, Duffo N and Martín-Neira M. 2015b. Faraday rotation retrieval using SMOS radiometric data. IEEE Geoscience and Remote Sensing Letter, 12(3): 458–461

Ellison W, Balana A, Delbos G, Lamkaouchi K, Eymard L, Guillou C and Prigent C. 1998. New permittivity measurements of seawater. Radio Science, 33(3): 639–648

Hwang P A. 2012. Foam and roughness effects on passive microwave remote sensing of the ocean. IEEE Transactions on Geoscience and Remote Sensing, 50(8): 2978–2985

Kerr Y H, Waldteufel P, Wigneron J P, Delwart S, Cabot F, Boutin J, Escorihuela M J, Font J, Reul N, Gruhier C, Juglea S E, Drinkwater M R, Hahne A, Martín-Neira M and Mecklenburg S. 2010. The SMOS mission: New tool for monitoring key elements of the global water cycle. Proceedings of the IEEE, 98(5): 666–687

Klein L A and Swift C. 1977. An improved model for the dielectric constant of sea water at microwave frequencies. IEEE Transactions on Antennas and Propagation, 25(1): 104–111

Koblinsky C J, Hildebrand P, LeVine D, Pellerano F, Chao Y, Wilson W, Yueh S and Lagerloef G. 2003. Sea surface salinity from space: science goals and measurement approach. Radio Science, 38(4): 8064

Lagerloef G. 2012. Satellite mission monitors ocean surface salinity. EOS-Transactions American Geophysical Union, 93(25): 233–234

Meissner T, Wentz F J, Scott J and Vazquez-Cuervo J. 2016. Sensitivity of ocean surface salinity measurements from spaceborne L-band radiometers to ancillary sea surface temperature. IEEE Transactions on Geoscience and Remote Sensing, 54(12): 7105–7111

Oliva R, Daganzo E, Kerr Y H, Mecklenburg S, Nieto S, Richaume P and Gruhier C. 2012. SMOS radio frequency interference scenario: status and actions taken to improve the RFI environment in the 1400-1427-MHz passive band. IEEE Transactions on Geoscience and Remote Sensing, 50(5): 1427–1439

Sabia R, Camps A, Vall-Llossera M and Reul N. 2006. Impact on sea surface salinity retrieval of different auxiliary data within the SMOS mission. IEEE Transactions on Geoscience and Remote Sensing, 44(10): 2769–2778

Sabia R, Camps A, Talone M, Vall-llossera M and Font J. 2010. Determination of the sea surface salinity error budget in the soil moisture and ocean salinity mission. IEEE Transactions on Geoscience and Remote Sensing, 48(4): 1684–1693

殷晓斌, 王振占. 2013. 太阳对SMOS卫星海表亮温偏差年际变化的影响. 遥感学报, 17(5): 1049–1059

Yin X B and Wang Z Z. 2013. Effect of the sun on biases in SMOS brightness temperature over ocean surfaces. Journal of Remote Sensing, 17(5): 1049–1059 (

Yueh S H. 1997. Modeling of wind direction signals in polarimetric sea surface brightness temperatures. IEEE Transactions on Geoscience and Remote Sensing, 35(6): 1400–1418

Yueh S H, West R, Wilson W J, Li F K, Njoku E G and Rahmat-Samii Y. 2001. Error sources and feasibility for microwave remote sensing of ocean surface salinity. IEEE Transactions on Geoscience and Remote Sensing, 39(5): 1049–1060

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