浏览全部资源
扫码关注微信
纸质出版日期： 2017-9-15 ，
录用日期： 2017-5-22
扫 描 看 全 文
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
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
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。
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 (
T
v
) and horizontally (
T
h
) 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
s
). 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
T
v
and
T
h
of a flat sea water surface at L-band and obtain the derivatives of
T
v
and
T
h
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
T
v
and
T
h
when the
SST
is 5 ℃
and the brightness temperature is more sensitive to the
SSS
for
T
v
than
T
h
with increasing
SST
. When the
SST
increases to 30 ℃
the sensitivity is approximately 0.8 K/psu for
T
v
. 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.
海表盐度卫星遥感水温反演精度
sea surface salinitysatellite remote sensingwater temperatureretrieval accuracy
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
相关作者
相关机构
京公网安备11010802024621