针对SMOS和Aquarius海表盐度误差分析没有区分不同空间频谱信噪特征的问题,基于6种主要的遥感盐度分析产品,根据定性图像、纬向波数谱、均方根误差等指标,分析产品的有效分辨率并探讨其原因机制。研究表明:CATDS-0.25°分析产品所描述的盐度场中小尺度结构失真,其较高谱能量密度在热带海域以噪音为主,而在西边界流等海域以信号为主;BEC-L3-0.25°有着较小的均方根误差、清晰的盐度图像、显著的中尺度能量,最适于描绘中尺度(25~100 km)盐度特征;BEC-L4-0.25°被奇异谱分析方法过度平滑了盐度场;Aquarius-V2-1.00°通过局部平滑处理,在描述大尺度(＞100 km)盐度现象方面表现较好;Aquarius-CAP-1.00°通过主动-被动联合算法(CAP)减小了均方根误差,但图像中卫星轨道形态明显;CATDS-1.00°的图像形态、能量分布和误差特征与Aquarius-V2-1.00°相当。这些结论可为用户正确使用产品进行地球物理学研究提供参考。
Abstract
The effective resolutions of six remotely sensed reanalysis products of sea surface salinity(SSS) from the soil moisture and ocean salinity (SMOS) and Aquarius/SAC-D missions were studied, in terms of the qualitative map, zonal wavenumber spectra, and root mean square (RMS) error. The mechanisms behind their differences also are studied. It suggests that the CATDS-0.25° reanalysis is unable to capture the small-scale structures in SSS and performs the worst in representing spatial variability in SSS. Its higher spectral energy is mostly a reflection of noises in the tropics while those in regions such as along the western boundary flows are signals. The BEC-L3-0.25° reanalysis, which has small RMS errors, clear salinity maps, and remarkable mesoscale energy, is the best fit for portraying mesoscale (25-100 km) SSS features. The SSS in the BEC-L4-0.25° reanalysis is overly attenuated by its singularity analysis remapping method. The Aquarius-V2-1.00° reanalysis, with an additional smoothing procedure, performs well in depicting large-scale (＞100 km) salinity phenomena. The Aquarius-CAP-1.00° reanalysis generates the smallest RMS errors benefiting from its combined active-passive (CAP) algorithm, however, and leads to a somewhat noisy, artificial pattern with unreasonable along-track strips. The CATDS-1.00° reanalysis is roughly equivalent to the Aquarius-V2-1.00° in terms of pattern, energy, and error features.
关键词
SMOS /
Aquarius /
海表盐度 /
遥感分析产品 /
有效分辨率
Key words
SMOS /
Aquarius /
sea surface salinity /
remotely sensed reanalysis product /
effective resolution
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
参考文献
[1] KERR Y, WALDTEUFEL P, WIGNERON J P, et al. The SMOS mission: New tool for monitoring key elements of the global water cycle[J]. P IEEE, 2010, 98(5): 666-687.
[2] KERR Y, MECKLENBURG S, DELWART S, et al. SMOS after five years in operations: from tentative research to operational applications[J]. Theor Appl Genet, 2015, 99(1-2): 289-295.
[3] LE-VINE D M, LAGERLOEF G S, TORRUSIO S E. Aquarius and remote sensing of sea surface salinity from space[J]. P IEEE, 2010, 98(5): 688-703.
[4] LE-VINE D M, DINNAT E P, LAGERLOEF G S E, et al. Aquarius: Status and recent results[J]. Radio Sci, 2016, 49(9): 709-720.
[5] DINNAT E P, VINE D M L, PIEPMEIER J R, et al. Aquarius L-band radiometers calibration using cold sky observations[J]. IEEE J-STARS, 2016, 8(12): 5 433-5 449.
[6] PABLOS M, PILES M, GONZÁLEZ-GAMBAU V, et al. SMOS and Aquarius radiometers: inter-comparison over selected targets[J]. IEEE J-STARS, 2014, 7(9): 3 833-3 844.
[7] TORRES F, CORBELLA I, WU L, et al. Minimization of image distortion in SMOS brightness temperature maps over the ocean[J]. IEEE Geosci Remote S, 2011, 9(1): 18-22.
[8] CAMPS A, VALL-LLOSSERA M, BATRES L, et al. Retrieving sea surface salinity with multiangular L-band brightness temperatures: Improvement by spatiotemporal averaging[J]. Radio Sci, 2016, 40(2): 1-13.
[9] HEJAZIN Y, JONES W L, SANTOS-GARCIA A, et al. A roughness correction for Aquarius sea surface salinity using the CONAE microwave radiometer[J]. IEEE J-STARS, 2016, 8(12): 5 500-5 510.
[10] MEISSNER T, WENTZ F, RICCIARDULLI L. The emission and scattering of L-band microwave radiation from rough ocean surfaces and wind speed measurements from the Aquarius sensor[J]. J Geophys Res: Oceans, 2014, 119(8): 6 499-6 522.
[11] YUEH S, TANG W, FORE A, et al. Aquarius geophysical model function and combined active passive algorithm for ocean surface salinity and wind retrieval[J]. J Geophys Res: Oceans, 2014, 119(8): 5 360-5 379.
[12] MELNICHENKO O, HACKER P, MAXIMENKO N, et al. Optimum interpolation analysis of Aquarius sea surface salinity[J]. J Geophys Res: Oceans, 2016, 121(1): 602-616.
[13] XIE P, BOYER T, BAYLER E, et al. An in situ-satellite blended analysis of global sea surface salinity[J]. J Geophys Res: Oceans, 2014, 119(9): 6 140-6 160.
[14] BOUTIN J, MARTIN N, REVERDIN G, et al. Sea surface salinity under rain cells: SMOS satellite and in situ drifters observations[J]. J Geophys Res: Oceans, 2014, 119(8): 5 533-5 545.
[15] DRUCKER R, RISER S C. Validation of Aquarius sea surface salinity with Argo: analysis of error due to depth of measurement and vertical salinity stratification[J]. J Geophys Res: Oceans, 2014, 119(7): 4 626-4 637.
[16] HERNANDEZ O, BOUTIN J, KOLODZIEJCZYK N, et al. SMOS salinity in the subtropical North Atlantic salinity maximum: 1. Comparison with Aquarius and in situ salinity[J]. J Geophys Res: Oceans, 2014, 119(12): 8 878-8 896.
[17] REAGAN J, BOYER T, ANTONOV J, et al. Comparison analysis between Aquarius sea surface salinity and World Ocean Database in situ analyzed sea surface salinity[J]. J Geophys Res: Oceans, 2014, 119(11): 8 122-8 140.
[18] TANG Wen-qing, YUEH S H, FORE A G. A Hayashi Validation of Aquarius sea surface salinity with in situ measurements from Argo floats and moored buoys[J]. J Geophys Res: Oceans, 2014, 119(9): 6171-6189
[19] LAGERLOEF G, KAO H Y, MEISSNER T, et al. Aquarius salinity validation analysis; data version 4.0[R]. 2015. ftp://podaac.jpl.nasa.gov/allData/aquarius/docs/v4/AQ-014-PS-0016 _Aquarius Salinity Data ValidationAnalysis_DatasetVersion4.0 and3.0 .pdf.
[20] MANNSHARDT E, SUCIC K, FUENTES M, et al. Comparison of distributional statistics of Aquarius and Argo sea surface salinity measurements[J]. J Atmos Oceanic Technol, 2015, 33(1): 151117145230002.
[21] LEE T. Consistency of Aquarius sea surface salinity with Argo products on various spatial and temporal scales[J]. Geophys Res Lett, 2016, 43(8): 3 857-3 864.
[22] BHASKAR T U, JAYARAM C. Evaluation of Aquarius sea surface salinity with Argo sea surface salinity in the tropical Indian Ocean[J]. IEEE Geosci Remote S, 2015, 12(6): 1 292-1 296.
[23] TZORTZI E, SROKOSZ M, GOMMENGINGER C, et al. Spatial and temporal scales of variability in tropical Atlantic sea surface salinity from the SMOS and Aquarius satellite missions[J]. Remote Sens Environ, 2016, 180: 418-430.
[24] BINGHAM F M, LEE T. Space and time scales of sea surface salinity and freshwater forcing variability in the global ocean[J]. J Geophys Res: Oceans, 2016, 122(4),doi: 10.1002/2016JC012216.
[25] VINOGRADOVA N T, PONTE R M. Small-scale variability in sea surface salinity and implications for satellite-derived measurements[J]. J Atmos Oceanic Technol, 2013, 30(11): 2 689-2 694.
[26] VINOGRADOVA N T, PONTE R M. Assessing temporal aliasing in satellite-based surface salinity measurements[J]. J Atmos Oceanic Technol, 2012, 29: 1 391-1 400.
[27] JOHNSON J T, ZHANG M. Theoretical study of the small slope approximation for ocean polarimetric thermal emission[J]. IEEE T Geosci Remote, 1999, 37(5): 2 305-2 316.
[28] GUIMBARD S, GOURRION J, PORTABELLA M, et al. SMOS semi-empirical ocean forward model adjustment[J]. IEEE T Geosci Remote, 2012, 50(5): 1 676-1 687.
[29] TURIEL A, NIEVES V, GARCÍA-LADONA E, et al. The multifractal structure of satellite sea surface temperature maps can be used to obtain global maps of streamlines[J]. Ocean Sci, 2009, 5(4): 447-460.
[30] MEISSNER T, WENTZ F, HILBURN K, et al. The Aquarius salinity retrieval algorithm[R]. IGARSS, 2012.
[31] YUEH S, CHAUBELL J. Sea surface salinity and wind retrieval using combined passive and active L-band microwave observations[J]. IEEE T Geosci Remote, 2012, 50(4): 1 022-1 032.
[32] REYNOLDS R W, CHELTON D B. Comparisons of daily sea surface temperature analyses for 2007-08[J]. J Climate, 2010, 23(13): 3 545-3 562.
基金
国家自然科学基金项目资助(41706021)
PDF(3938 KB)
