Citation: | Xia Liu, Qiang Wang, Mu Mu. Identifying the sensitive areas in targeted observation for predicting the Kuroshio large meander path in a regional ocean model[J]. Acta Oceanologica Sinica, 2022, 41(2): 3-14. doi: doi:10.1007/s13131-021-1838-7 |
[1] |
Farrara J D, Chao Yi, Li Zhijin, et al. 2013. A data-assimilative ocean forecasting system for the Prince William sound and an evaluation of its performance during sound Predictions 2009. Continental Shelf Research, 63(S1): S193–S208. doi: 10.1016/j.csr.2012.11.008
|
[2] |
Fujii Y, Tsujino H, Usui N, et al. 2008. Application of singular vector analysis to the Kuroshio large meander. Journal of Geophysical Research: Oceans, 113(C7): C07026. doi: 10.1029/2007JC004476
|
[3] |
Halliwell Jr R G, Srinivasan A, Kourafalou V, et al. 2014. Rigorous evaluation of a fraternal twin ocean OSSE system for the open Gulf of Mexico. Journal of Atmospheric and Oceanic Technology, 31(1): 105–130. doi: 10.1175/JTECH-D-13-00011.1
|
[4] |
Hayasaki M, Kawamura R, Mori M, et al. 2013. Response of extratropical cyclone activity to the Kuroshio large meander in northern winter. Geophysical Research Letters, 40(11): 2851–2855. doi: 10.1002/grl.50546
|
[5] |
Ishikawa Y, Awaji T, Komori N, et al. 2004. Application of sensitivity analysis using an adjoint model for short-range forecasts of the Kuroshio path south of Japan. Journal of Oceanography, 60(2): 293–301. doi: 10.1023/b:joce.0000038335.50080.ff
|
[6] |
Kawabe M. 1995. Variations of current path, velocity, and volume transport of the Kuroshio in relation with the large meander. Journal of Physical Oceanography, 25(12): 3103–3117. doi: 10.1175/1520-0485(1995)025<3103:VOCPVA>2.0.CO;2
|
[7] |
Langland R H. 2005. Issues in targeted observing. Quarterly Journal of the Royal Meteorological Society, 131(613): 3409–3425. doi: 10.1256/qj.05.130
|
[8] |
Li Yineng, Peng Shiqiu, Liu Duanling. 2014. Adaptive observation in the South China Sea using CNOP approach based on a 3-D ocean circulation model and its adjoint model. Journal of Geophysical Research: Oceans, 119(12): 8973–8986. doi: 10.1002/2014JC010220
|
[9] |
Liu Xia, Mu Mu, Wang Qiang. 2018a. The nonlinear optimal triggering perturbation of the Kuroshio large meander and its evolution in a regional ocean model. Journal of Physical Oceanography, 48(8): 1771–1786. doi: 10.1175/JPO-D-17-0246.1
|
[10] |
Liu Xia, Wang Qiang, Mu Mu. 2018b. Optimal initial error growth in the prediction of the Kuroshio large meander based on a high-resolution regional ocean model. Advances in Atmospheric Sciences, 35(11): 1362–1371. doi: 10.1007/s00376-018-8003-z
|
[11] |
Ma Xiaohui, Jing Zhao, Chang Ping, et al. 2016. Western boundary currents regulated by interaction between ocean eddies and the atmosphere. Nature, 535(7613): 533–537. doi: 10.1038/nature18640
|
[12] |
Miyazawa Y, Kagimoto T, Guo Xinyu, et al. 2008. The Kuroshio large meander formation in 2004 analyzed by an eddy-resolving ocean forecast system. Journal of Geophysical Research: Oceans, 113(C10): C10015. doi: 10.1029/2007JC004226
|
[13] |
Miyazawa Y, Yamane S, Guo Xinyu, et al. 2005. Ensemble forecast of the Kuroshio meandering. Journal of Geophysical Research: Oceans, 110(C10): C10026. doi: 10.1029/2004JC002426
|
[14] |
Mu Mu. 2013. Methods, current status, and prospect of targeted observation. Science China: Earth Sciences, 56(12): 1997–2005. doi: 10.1007/s11430-013-4727-x
|
[15] |
Mu Mu, Duan Wansuo, Wang B. 2003. Conditional nonlinear optimal perturbation and its applications. Nonlinear Processes in Geophysics, 10(6): 493–501. doi: 10.5194/npg-10-493-2003
|
[16] |
Mu Mu, Zhou Feifan, Wang Hongli. 2009. A method for identifying the sensitive areas in targeted observations for tropical cyclone prediction: conditional nonlinear optimal perturbation. Monthly Weather Review, 137(5): 1623–1639. doi: 10.1175/2008MWR2640.1
|
[17] |
Nakamura H, Nishina A, Minobe S. 2012. Response of storm tracks to bimodal Kuroshio path states south of Japan. Journal of Climate, 25(21): 7772–7779. doi: 10.1175/JCLI-D-12-00326.1
|
[18] |
Qin Xiaohao, Mu Mu. 2011. A study on the reduction of forecast error variance by three adaptive observation approaches for tropical cyclone prediction. Monthly Weather Review, 139(7): 2218–2232. doi: 10.1175/2010MWR3327.1
|
[19] |
Shao Quanqin, Ma Weiwei, Chen Zhuoqi, et al. 2005. Relationship between Kuroshio meander pattern and Ommastrephes bartrami CPUE in northwest Pacific Ocean. Oceanologia et Limnologia Sinica, 36(2): 111–122
|
[20] |
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
|
[21] |
Shchepetkin A F, McWilliams J C. 2005. The regional oceanic modeling system (ROMS): a split-explicit, free-surface, topography-following-coordinate oceanic model. Ocean Modelling, 9(4): 347–404. doi: 10.1016/j.ocemod.2004.08.002
|
[22] |
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. doi: 10.1006/jcph.1994.1189
|
[23] |
Taft B A. 1972. Characteristics of the flow of the Kuroshio south of Japan. In: Stommel H, Yoshida K, eds. Kuroshio-Its Physical Aspects. Tokyo, Japan: University of Tokyo Press, 165–216
|
[24] |
Tang Youmin, Kleeman R, Moore A M. 2004. SST assimilation experiments in a tropical Pacific Ocean model. Journal of Physical Oceanography, 34(3): 623–642. doi: 10.1175/3518.1
|
[25] |
Tsujino H, Usui N, Nakano H. 2006. Dynamics of Kuroshio path variations in a high-resolution general circulation model. Journal of Geophysical Research: Oceans, 111(C11): C11001. doi: 10.1029/2005JC003118
|
[26] |
Usui N, Tsujino H, Nakano H. 2008. Formation process of the Kuroshio large meander in 2004. Journal of Geophysical Research: Oceans, 113(C8): C08047. doi: 10.1029/2007JC004675
|
[27] |
Wang Qiang, Ma Libin, Xu Qiangqiang. 2013a. Optimal precursor of the transition from Kuroshio large meander to straight path. Chinese Journal of Oceanology and Limnology, 31(5): 1153–1161. doi: 10.1007/s00343-013-2301-1
|
[28] |
Wang Qiang, Mu Mu, Dijkstra H A. 2012. Application of the conditional nonlinear optimal perturbation method to the predictability study of the Kuroshio large meander. Advances in Atmospheric Sciences, 29(1): 118–134. doi: 10.1007/s00376-011-0199-0
|
[29] |
Wang Qiang, Mu Mu, Dijkstra H A. 2013b. The similarity between optimal precursor and optimally growing initial error in prediction of Kuroshio large meander and its application to targeted observation. Journal of Geophysical Research: Oceans, 118(2): 869–884. doi: 10.1002/jgrc.20084
|
[30] |
Wang Qiang, Mu Mu, Dijkstra H A. 2013c. Effects of nonlinear physical processes on optimal error growth in predictability experiments of the Kuroshio Large Meander. Journal of Geophysical Research: Oceans, 118(12): 6425–6436. doi: 10.1002/2013JC009276
|
[31] |
Xia Ruibin, Liu Qinyu, Xu Lixiao. 2013. Formation mechanisms of the three Kuroshio large meanders. Periodical of Ocean University of China, 43(5): 1–7
|
[32] |
Xu Haiming, Tokinaga H, Xie Shangping. 2010. Atmospheric effects of the Kuroshio large meander during 2004–05. Journal of Climate, 23(17): 4704–4715. doi: 10.1175/2010JCLI3267.1
|
[33] |
Yang Yang, Liang Xiangsan. 2019. New perspectives on the generation and maintenance of the Kuroshio large meander. Journal of Physical Oceanography, 49(8): 2095–2113. doi: 10.1175/JPO-D-18-0276.1
|
[34] |
Zhang Kun, Mu Mu, Wang Qiang. 2017. Identifying the sensitive area in adaptive observation for predicting the upstream Kuroshio transport variation in a 3-D ocean model. Science China: Earth Sciences, 60(5): 866–875. doi: 10.1007/s11430-016-9020-8
|
[35] |
Zou Guangan, Wang Qiang, Mu Mu. 2016. Identifying sensitive areas of adaptive observations for prediction of the Kuroshio large meander using a shallow-water model. Chinese Journal of Oceanology and Limnology, 34(5): 1122–1133. doi: 10.1007/s00343-016-4264-5
|