Envisat ASAR海浪谱资料的最优插值同化试验

doi:10.11978/j.issn.1009-5470.2010.05.017

Journal of Tropical Oceanography ›› 2010, Vol. 29 ›› Issue (5): 17-23.doi: 10.11978/j.issn.1009-5470.2010.05.017cstr: 32234.14.j.issn.1009-5470.2010.05.017

• Marine hydrology • Previous Articles Next Articles

Optimal interpolation assimilation experiments based on Envisat ASAR ocean wave spectral data

1. Institute of Oceanology, CAS, Qingdao 266071, China; 2. Graduate University of CAS, Beijing 100039, China; 3. First Institute of Oceanography, SOA, Qingdao 266061, China; 4. Key Laboratory of Marine Science and Numerical Modeling (MASNUM), SOA, Qingdao 266061, China

1. Institute of Oceanology, CAS, Qingdao 266071, China; 2. Graduate University of CAS, Beijing 100039, China; 3. First Institute of Oceanography, SOA, Qingdao 266061, China; 4. Key Laboratory of Marine Science and Numerical Modeling (MASNUM), SOA, Qingdao 266061, China

Received:2010-01-06 Revised:2010-03-23 Online:2010-10-30 Published:2011-10-10
About author:任启峰(1980—), 男, 山东省莱芜市人, 在读博士生, 主要从事海浪资料同化研究。E-mail: renqifeng@yeah.net
Supported by:
海洋公益性行业科研专项(200705027)

Abstract

Abstract:

With the third generation wave model named LAGFD-WAM, optimal interpolation assimilation experiments are performed based on Envisat Advanced Synthetic Aperture Radar (ASAR) ocean wave spectral data using four different iso-tropic background error correlation functions. The experiment results are compared with observation data from four different moored buoys. The results show that the optimal interpolation of ASAR wave spectral data can effectively improve the sig-nificant wave height (SWH) simulation of the wave model. The differences of assimilation effects among four experiments with different background error correlation functions are not obvious. The key to assimilation effects lies in the choice of cor-relation scale length. For the auto-regressive background error correlation function, the experiment results indicate that the assimilation effect is best when the correlation scale length is assumed to be from 400 to 500km, and that the root-mean-square error of model SWH data relatively decreases by 26% compared with that without assimilation.

Key words: ocean wave spectrum, optimal interpolation, background error correlation function, correlation scale length

. Institute of Oceanology,CAS,Qingdao 6607,China; . Graduate University o. Optimal interpolation assimilation experiments based on Envisat ASAR ocean wave spectral data[J].Journal of Tropical Oceanography, 2010, 29(5): 17-23.

References

[1] LIONELLO P, GÜNTHER H, JANSSEN P A E M. Assimilation of altimeter data in a global third-generation wave model[J]. J Geophys Res, 1992, 97(C9): 14453-14474.

[2] BENDER L C, GLOWACKI T. The assimilation of altimeter data into the Australian wave model[J]. Aust Meteorol Mag, 1996, 45: 41-48.

[3] GREENSLADE D J M. The assimilation of ERS-2 significant wave height data in the Australian region[J]. J Mar Syst, 2001, 28: 141-160.

[4] MASTENBROEK C, MAKIN V K, VOORRIPS A C, et al. Validation of ERS-1 altimeter wave height measurements and assimilation in a North Sea wave model[J]. Global Atmos Ocean Syst, 1994, 2: 143-161.

[5] YOUNG I R, GLOWACKI T J. Assimilation of altimeter wave height data into a spectral wave model using statistical interpolation[J]. Ocean Eng, 1996, 23(8): 667-689.

[6] BREIVIK L A, REISTAD M. Assimilation of ERS-1 altimeter wave heights in an operational numerical wave model[J]. Weather Forecast, 1994, 9: 440-451.

[7] BREIVIK L A, REISTAD M, SCHYBERG H, et al. Assimilation of ERS SAR wave spectra in an operational wave model[J]. J Geophys Res, 1998, 103(C4): 7 887-7 900.

[8] HASSELMANN S, LIONELLO P, HASSELMAN K. An optimal interpolation scheme for the assimilation of spectral wave data[J]. J Geophys Res, 1997, 102(C7): 15823-15836.

[9] VOORRIPS A C, MAKIN V K, HASSELMANN S. Assimilation of wave spectra from pitch-and-roll buoys in a North Sea wave model[J]. J Geophys Res, 1997, 102(C3): 5829-5849.

[10] AOUF L, LEFÈVRE J M, HAUSER D. Assimilation of directional wave spectra in the wave model WAM: An impact study from synthetic observations in preparation for the SWIMSAT satellite mission[J]. J Atmos Oceanic Technol, 2006, 23: 448-463.

[11] VOORRIPS A C, HEEMINK A W, KOMEN G J. Wave data assimilation with the Kalman filter[J]. Journal of Marine Systems, 1999, 19: 267-291.

[12] PINTO J P, BERNARDINO M C, PIRES SILVA A. A Kalman filter application to a spectral wave model[J]. Nonlinear Processes Geophys, 2005, 12: 775-782.

[13] DE LAS HERAS M M, BURGERS G, JANSSEN P A E M. Variational wave data assimilation in a third-generation wave model[J]. Journal of Atmospheric and Oceanic Technology, 1994, 11: 1350-1369.

[14] DE LAS HERAS M M, BURGERS G, JANSSEN P A E M. Wave data assimilation in the WAM wave model[J]. Journal of Marine Systems, 1995, 6: 77-85.

[15] BAUER E, HASSELMANN K, YOUNG I R, et al. Assimilation of wave data into the wave model WAM using an impulse response function method[J]. J Geophys Res, 1996, 101: 3801-3816.

[16] HOLTHUIJSEN L H, BOOIJ N, VAN ENDT M, et al. Assimilation of buoy and satellite data in wave forecasts with integral control variables[J]. Journal of Marine Systems, 1997, 13: 21-31.

[17] HERSBACH L. Application of the adjoint of the WAM model to inverse wave modeling[J]. J Geophys Res, 1998, 103: 10 469-10 488.

[18] 王跃山, 黄润恒. 用插入观测法将高度计观测同化到海浪模式WAM中[J]. 海洋预报, 1999, 16(2): 1-17.

[19] 张志旭, 齐义泉, 施平, 等. 最优化插值同化方法在预报南海台风浪中的应用[J]. 热带海洋学报, 2003, 22(4): 34-41.

[20] 郭衍游, 侯一筠, 杨永增, 等. 利用WaveWatch III建立东中国海区域海浪同化系统[J]. 高技术通讯, 2006, 16(10): 1092-1096.

[21] YANG YONG-ZENG, YUAN YE-LI, ZHANG JIE, et al. Wave data assimilation using the adjoint variational method in the LAGFD-WAM wave numerical model[C]//Proceedings of the International Conference on Marine Disasters: Forecast and Reduction. Beijing: China Ocean Press, 1998: 77-82.

[22] YANG YONG-ZENG, ZHAO WEI, TENG YONG. A temporal sliding procedure for ocean wave variational data assimilation and its application[J]. Chin J Oceanol Limnol, 2006, 24(1): 35-41.

[23] 郭衍游. 东中国海区域海浪同化系统设计与研究[D]. 青岛: 中国科学院海洋研究所, 2006.

[24] BRÜNING C, HASSELMANN S, HASSELMANN K, et al. First evaluation of ERS-1 synthetic aperture radar wave mode data[J]. Global Atmos Ocean Systm, 1994, 2: 61－98.

[25] ENGEN G, BARSTOW S F, JOHNSON H, et al. Directional wave spectra by inversion of ERS-1 synthetic aperture radar ocean imagery[J]. IEEE Trans Geosci Remote Sens, 1994, 32(2): 340-352.

[26] HASSELMANN S, BRÜNING C, HASSELMANN K, et al. An improved algorithm for the retrieval of ocean wave spectra from synthetic aperture radar image spectra[J]. J Geophys Res, 1996, 101(C7): 16615-16629.

[27] JOHNSEN H, CHAPRON B, WALKER N, et al. The ASAR wave mode: level 1 and level 2 algorithms and products[R]. Envisat Calibration Review, Noordwijk: ESA-ESTEC, 2002.

[28] GREENSLADE D J M, YOUNG I R. Background errors in a global wave model determined from altimeter data[J]. J Geophys Res, 2004, 109, C09007, doi: 10.1029/2004JC002324.

[29] YUAN YE-LI, HUA FENG, PAN ZENG-DI, et al. LAGFD-WAM numerical wave model-I basic physical model[J]. Acta Oceanol Sinica, 1991a, 10: 483-488.

[30] YUAN YE-LI, PAN ZENG-DI, HUA FENG, et al. LAGFD-WAM numerical wave model-II characteristics inlaid scheme and its application[J]. Acta Oceanol Sinica, 1991b, 11: 13-23.

[31] JOHNSEN H, ENGEN G, COLLARD F, et al. Envisat ASAR wave mode products-quality assessment and algorithm upgrade[C]//Proc of SEASAR 2006, Frascati: ESA SP-613, 2006.

Optimal interpolation assimilation experiments based on Envisat ASAR ocean wave spectral data

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