Assimilating operational SST and sea ice analysis data into an operational circulation model for the coastal seas of China

JI Qiyan; ZHU Xueming; WANG Hui; LIU Guimei; GAO Shan; JI Xuanliang; XU Qing

doi:10.1007/s13131-015-0691-y

Volume 34 Issue 7

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Article Navigation > Acta Oceanologica Sinica > 2015 > 34(7): 54-64

JI Qiyan, ZHU Xueming, WANG Hui, LIU Guimei, GAO Shan, JI Xuanliang, XU Qing. Assimilating operational SST and sea ice analysis data into an operational circulation model for the coastal seas of China[J]. Acta Oceanologica Sinica, 2015, 34(7): 54-64. doi: 10.1007/s13131-015-0691-y

Citation:

JI Qiyan, ZHU Xueming, WANG Hui, LIU Guimei, GAO Shan, JI Xuanliang, XU Qing. Assimilating operational SST and sea ice analysis data into an operational circulation model for the coastal seas of China[J]. Acta Oceanologica Sinica, 2015, 34(7): 54-64. doi: 10.1007/s13131-015-0691-y

Citation:

JI Qiyan, ZHU Xueming, WANG Hui, LIU Guimei, GAO Shan, JI Xuanliang, XU Qing. Assimilating operational SST and sea ice analysis data into an operational circulation model for the coastal seas of China[J]. Acta Oceanologica Sinica, 2015, 34(7): 54-64. doi: 10.1007/s13131-015-0691-y

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Assimilating operational SST and sea ice analysis data into an operational circulation model for the coastal seas of China

doi: 10.1007/s13131-015-0691-y

1.
Key Laboratory of Ministry of Education for Coastal Disaster and Defence, Hohai University, Nanjing 210098, China
2.
Key Laboratory of Research on Marine Hazards Forecasting, National Marine Environmental Forecasting Center, State Oceanic Administration, Beijing 100081, China
3.
Key Laboratory of Ministry of Education for Coastal Disaster and Defence, Hohai University, Nanjing 210098, China;Key Laboratory of Research on Marine Hazards Forecasting, National Marine Environmental Forecasting Center, State Oceanic Administration, Beijing 100081, China

Received Date: 2015-01-23
Rev Recd Date: 2015-02-28

Abstract

Abstract

The prediction of sea surface temperature (SST) is an essential task for an operational ocean circulation model. A sea surface heat flux, an initial temperature field, and boundary conditions directly affect the accuracy of a SST simulation. Here two quick and convenient data assimilation methods are employed to improve the SST simulation in the domain of the Bohai Sea, the Yellow Sea and the East China Sea (BYECS). One is based on a surface net heat flux correction, named as Qcorrection (QC), which nudges the flux correction to the model equation; the other is ensemble optimal interpolation (EnOI), which optimizes the model initial field. Based on such two methods, the SST data obtained from the operational SST and sea ice analysis (OSTIA) system are assimilated into an operational circulation model for the coastal seas of China. The results of the simulated SST based on four experiments, in 2011, have been analyzed. By comparing with the OSTIA SST, the domain averaged root mean square error (RMSE) of the four experiments is 1.74, 1.16, 1.30 and 0.91℃, respectively; the improvements of assimilation experiments Exps 2, 3 and 4 are about 33.3%, 25.3%, and 47.7%, respectively. Although both two methods are effective in assimilating the SST, the EnOI shows more advantages than the QC, and the best result is achieved when the two methods are combined. Comparing with the observational data from coastal buoy stations, show that assimilating the high-resolution satellite SST products can effectively improve the SST prediction skill in coastal regions.
- sea surface temperature,
- data assimilation,
- ensemble optimal interpolation,
- quick correction,
- Bohai Sea

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References

Barnier B, Siefridt L, Marchesiello P. 1995. Thermal forcing for a global ocean circulation model using a three-year climatology of ECMWF analyses. Journal of Marine Systems, 6(4): 363-380

Carnes M R. 2009. Description and Evaluation of GDEM-V 3.0. Naval Research Laboratory, NRL/MR/7330-09-9165. Naval Research Laboratory, Stennis Space Center, MS, 1-27

Carton J A, Giese B S. 2008. A reanalysis of ocean climate using simple ocean data assimilation (SODA). Monthly Weather Review, 136(8): 2999-3017

Costa P, Gómez B, Venâncio A, et al. 2012. Using the regional ocean modelling system (ROMS) to improve the sea surface temperature predictions of the MERCATOR Ocean System. Scientia Marina, 76(S1): 165-175

Counillon F, Bertino L. 2009. Ensemble optimal interpolation: multivariate properties in the Gulf of Mexico. Tellus A, 61(2): 296-308

Diaz H, Folland C, Manabe T, et al. 2002. Workshop on advances in the use of historical marine climate data. WMO Bulletin, 51(4): 377-379

Donlon C J, Martin M, Stark J, et al. 2012. The operational sea surface temperature and sea ice analysis (OSTIA) system. Remote Sensing of Environment, 116: 140-158

Egbert G D, Erofeeva S Y. 2002. Efficient inverse modeling of barotropic ocean tides. Journal of Atmospheric and Oceanic Technology, 19(2): 183-204

Evensen G. 2003. The ensemble Kalman filter: theoretical formulation and practical implementation. Ocean Dynamics, 53(4): 343-367

Fairall C W, Bradley E F, Rogers D P, et al. 1996. Bulk parameterization of air-sea fluxes for tropical ocean-global atmosphere coupled-ocean atmosphere response experiment. Journal of Geophysical Research: Oceans, 101(C2): 3747-3764

Fu Weiwei, Zhu Jiang, Yan Changxiang. 2009. A comparison between 3DVAR and EnOI techniques for satellite altimetry data assimilation. Ocean Modelling, 26(3-4): 206-216

Gaspari G, Cohn S E. 1999. Construction of correlation functions in two and three dimensions. Quarterly Journal of the Royal Meteorological Society, 125(554): 723-757

Guan Bingxian. 1994. Patterns and structures of the currents in Bohai, Huanghai and East China Seas. In: Zhou Di, Liang Yuanbo, Zeng Chengkui, et al., eds. Oceanology of China Seas. Berlin: Springer Netherlands, 17-26

Hu Haoguo, Wang Jia, 2010. Modeling effects of tidal and wave mixing on circulation and thermohaline structures in the Bering Sea: process studies. Journal of Geophysical Research: Oceans, 115(C1): C01006, doi: 10.1029/2008JC005175

Ichikawa H, Beardsley R C. 2002. The current system in the Yellow and East China Seas. Journal of Oceanography, 58(1): 77-92

IOC, IHO, BODC, 2009. General Bathymetric Chart of the Oceans: The GEBCO_08 Grid, version 20091120. Liverpool, U.K: British Oceanographic Data Centre, 1-19

Kamachi M, Kuragano T, Ichikawa H, et al. 2004. Operational data assimilation system for the Kuroshio south of Japan: reanalysis and validation. Journal of Oceanography, 60(2): 303-312

Kourafalou V H, De Mey P, Hénaff M L, et al. 2015. Coastal ocean forecasting: system integration and evaluation. Journal of Operational Oceanography, 7(3): 129-148

Li Yineng, Peng Shiqiu, Wang Jia, et al. 2014. Impacts of nonbreaking wave-stirring-induced mixing on the upper ocean thermal structure and typhoon intensity in the South China Sea. Journal of Geophysical Research: Oceans, 19(8): 5052-5070

Li Wei, Xie Yuanfu, He Zhongjie, et al. 2008. Application of the multigrid Data Assimilation Scheme to the China Seas' temperature forecast. Journal of Atmospheric and Oceanic Technology, 25(11): 2106-2116

Li Xichen, Zhu Jiang, Xiao Yiguo, et al. 2010. A Model-based observation- thinning scheme for the assimilation of high-resolution SST in the shelf and coastal seas around China. Journal of Atmospheric and Oceanic Technology, 27(6): 1044-1058

Losa S N, Danilov S, Schröter J, et al. 2012. Assimilating NOAA SST data into the BSH operational circulation model for the North and Baltic Seas: inference about the data. Journal of Marine Systems, 105-108: 152-162

Losa S N, Danilov S, Schröter J, et al. 2014. Assimilating NOAA SST data into BSH operational circulation model for the North and Baltic Seas: Part 2. Sensitivity of the fore cast's skill to the prior model error statistics. Journal of Marine Systems, 129: 259-270

Ma Jirui, Han Guijun, Li Dong. 2002. A study on the application of variational adjoint data assimilation for numerical prediction of sea surface temperature. Acta Oceanologica Sinica (in Chinese), 24(5): 1-7

Mellor G L, Yamada T. 1982. Development of a turbulence closure model for geophysical fluid problems. Reviews of Geophysics, 20(4): 851-875

Miyazawa Y, Murakami H, Miyama T, et al. 2013. Data assimilation of the high-resolution sea surface temperature obtained from the aqua-terra satellites (MODIS-SST) using an ensemble Kalman filter. Remote Sensing, 5(6): 3123-3139

O'dea E J, Arnold A K, Edwards K P, et al. 2012. An operational ocean forecast system incorporating NEMO and SST data assimilation for the tidally driven European North-West shelf. Journal of Operational Oceanography, 5(1): 3-17

Oke P R, Brassington G B, Griffin D A, et al. 2008. The Bluelink ocean data assimilation system (BODAS). Ocean Modelling, 21(1-2): 46-70

Powell B S, Moore A M, Arango H G, et al. 2009. Near real-time ocean circulation assimilation and prediction in the Intra-Americas Sea with ROMS. Dynamics of Atmospheres and Oceans, 48(1-3): 46-68

Reynolds R W, Smith T M, Liu Chunying, et al. 2007. Daily high-resolution- blended analyses for sea surface temperature. Journal of Climate, 20(22): 5473-5496

Saha S, Moorthi S, Pan Hualu, et al. 2010. The NCEP climate forecast system reanalysis. Bulletin of the American Meteorological Society, 91(8): 1015-1057

Schofield O, Glenn S, Bissett P W, et al. 2003. Development of regional coastal ocean observatories and the potential benefits to marine sanctuaries. Marine Technology Society Journal, 37(1): 54-67

Seo G -H, Choi B -J, Cho Y -K, et al. 2010. Assimilation of sea surface temperature in the Northwest Pacific Ocean and its marginal seas using the ensemble Kalman filter. Ocean Science Journal, 45(4): 225-242

Seo G -H, Kim S, Choi B -J, et al. 2009. Implementation of the ensemble Kalman filter into a Northwest Pacific Ocean circulation model. In: Park S K, Xu Liang, ed. Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications. Berlin Heidelberg: Springer, 341-351

Shchepetkin A F, McWilliams J C. 2003. A method for computing horizontal pressure-gradient force in an oceanic model with a nonaligned vertical coordinate. Journal of Geophysical Research: Oceans, 108(C3): 3090, doi: 10.1029/2001JC001047

Shchepetkin A F, McWilliams J C. 2005. The regional oceanic modeling system (ROMS): a split-explicit, free-surface, topographyfollowing- coordinate oceanic model. Ocean Modelling, 9(4): 347-404

Shu Yeqiang, Zhu Jiang, Wang Dongxiao, et al. 2009. Performance of four sea surface temperature assimilation schemes in the South China Sea. Continental Shelf Research, 29(11-12): 1489-1501

Song Yuhe, Haidvogel D. 1994. A semi-implicit ocean circulation model using a generalized topography-following coordinate system. Journal of Computational Physics, 115(1): 228-244

Stanev E V, Schulz-Stellenfleth J, Staneva J, et al. 2011. Coastal observing and forecasting system for the German Bight-estimates of hydrophysical states. Ocean Science, 7(5): 569-583

Stark J D, Donlon C J, Martin M J, et al. 2007. OSTIA: An operational, high resolution, real time, global sea surface temperature analysis system. In: OCEANS 2007-Europe. Aberdeen: IEEE, 1-4

Sun Ruili, Li Lei. 2011. Influence of assimilating remote sensing data on the predicting precision of sea surface temperature. Transactions of Oceanology and Limnology (in Chinese), (4): 25-31

Umlauf L, Burchard H. 2003. A generic length-scale equation for geophysical turbulence models. Journal of Marine Research, 61(2): 235-265

Wang Jia. 1996. Global linear stability of the two-dimensional shallow- water equations: An application of the distributive theorem of roots for polynomials on the unit circle. Monthly Weather Review, 124(6): 1301-1310

Wang Cizhen, Li Xuhua, Qi Jianhua, et al. 1998. A numerical model for predicting offshore SST anomaly in the East China Sea I. Establishment of model. Haiyang Xuebao (in Chinese), 20(2): 27-34

Wang Cizhen, Li Xuhua, Qi Jianhua, et al. 1998. A numerical model for predicting offshore SST anomaly in the East China Sea II. Factor analyses and experiment forecast. Haiyang Xuebao (in Chinese), 20(3): 19-26

Wang Cizhen, Su Yusong. 1990. A model of SST prediction for limited region I, the dynamical equations. Oceanologia et Limnologia Sinica (in Chinese), 21(5): 418-424

Wang Cizhen, Su Yusong. 1991. A model of SST prediction for limited region II. the model's physical equation. Oceanologia et Limnologia Sinica (in Chinese), 22(1): 69-77

Wilkin J L, Arango H G, Haidvogel D B, et al. 2005. A regional ocean modeling system for the long-term ecosystem observatory. Journal of Geophysical Research: Oceans, 110(C6): C06S91

Xie Jiping, Counillon F, Zhu Jinang, et al. 2011. An eddy resolving tidal- driven model of the South China Sea assimilating alongtrack SLA data using the EnOI. Ocean Science, 7(5): 609-627

Xie Jiping, Zhu Jiang. 2010. Ensemble optimal interpolation schemes for assimilating Argo profiles into a hybrid coordinate ocean model. Ocean Modelling, 33(3-4): 283-298

Xie Jiping, Zhu Jiang, Li Yan. 2008. Assessment and inter-comparison of five high-resolution sea surface temperature products in the shelf and coastal seas around China. Continental Shelf Research, 28(10-11): 1286-1293

Xue Huijie, Shi Lei, Cousins S. 2004. SST assimilation and assessment of the predicted temperature from the GoMOOS nowcast/forecast system. In: Malcolm L, Spaulding P E, eds. Proceedings of the 8th International Conference on Coastal &Estuarine Modeling, ASCE, Monterey, California:128-143

Xue Huijie, Shi Lei, Cousins S. 2005. The GoMOOS Nowcast/Forecast System. Continental Shelf Research, 25(17):2122-2146

Ye Dong, Xie Jiping. 2011. Data assimilation experiment in the northern South China Sea based on ensemble optimal interpolation method. Marine Science Bulletin (in Chinese), 30(4): 377-386, 396

Yu Xiaolin, Wang Fan, Tang Xiaohui. 2012. Future projection of East China Sea temperature by dynamic downscaling of the IPCC_AR4 CCSM3 model result. Chinese Journal of Oceanology and Limnology, 30(5): 826-842

Zhang Jianhua, Su Jie, Li Lei, et al. 2005. A numerical model for prediction short dated SST in the China Sea. Marine Forecasts (in Chinese), 22(S1): 122-127

Zheng Fei, Zhu Jiang. 2008. Balanced multivariate model errors of an intermediate coupled model for ensemble Kalman filter data assimilation. Journal of Geophysical Research: Oceans, 113(C7): C07002, doi: 10.1029/2007JC004621

Zheng Fei, Zhu Jiang, Zhang Ronghua, et al. 2006. Ensemble hindcasts of SST anomalies in the tropical Pacific using an intermediate coupled model. Geophysical Research Letters, 33(19): L19604, doi: 10.1029/2006GL026994.

Zhu Xueming, Liu Guimei, Wang Jia, et al. 2015. A numerical study on the relationships of the variations of volume transport around the China Seas. Journal of Marine Systems, 145:15-36. http://dx.doi.org/10.1016/j.jmarsys.2014.12.003

Zhu Jiang, Xu Qichun, Wang Cizhen, et al. 1995. Data assimilation experiments on sea surface temperature numerical forecast: I. the optimal interpolation method experiments of objective analysis. Haiyang Xuebao (in Chinese), 17(6): 9-20

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