Page 100 - 应用声学2019年第4期

560 2019 年 7 月

0.20 [4] Lorenz E N, Emanuel K A. Optimal sites for supplemen-
଍҄ᮕઑ tary weather observation sites: simulation with a small
0.18 ᫎᬦ8ܹ model[J]. Journal of Atmospheric Sciences, 1998, 55(3):
͜୧૯ܿکவಪឨࣀ/dB 0.14 ᫎᬦ2ܹ [5] Palmer T N, Gelaro R, Barkmeijer J, et al. Singular vec-
ᫎᬦ6ܹ
ᫎᬦ4ܹ
399–414.
0.16
tors, metrics, and adaptive observations[J]. Journal of At-
mospheric Sciences, 1998, 55(4): 633–653.
0.12
[6] Bishop C H, Etherton B J, Majumdar S J. Adaptive sam-
0.10
pling with the ensemble transform Kalman filter. Part
I: theoretical aspects[J]. Monthly Weather Review, 2001,
0.08
4 6 8 10 12 14 16 129(3): 420–436.
ᮕઑܹ஝/d
[7] Mu M, Duan W S, Wang B. Conditional nonlinear optimal
图 10 基于 ETKF 方法适应性观测对声场传播损 perturbation and its applications[J]. Nonlinear Processes
失预报的影响 in Geophysics, 2003, 10(6): 493–501.
[8] Toth Z, Kalnay E. Ensemble forecasting at NMC: the gen-
Fig. 10 Influence of adaptive observation based on
eration of perturbations[J]. Bulletin of the American Me-
ETKF method on prediction of sound field prop-
teorological Society, 1993, 74(12): 2317–2330.
agation loss [9] Toth Z, Kalnay E. Ensemble forecasting at NCEP and
the breeding method[J]. Monthly Weather Review, 1997,
3 总结与展望 125(12): 3297–3319.
[10] 关吉平, 张立凤, 马环宇. 基于增长模繁殖法的初始分析误差
环境敏感区诊断与适应性观测是近几年国际 计算及集合预报试验 [J]. 气象科学, 2009, 29(3): 317–322.
Guan Jiping, Zhang Lifeng, Ma Huanyu. Computation
上提出改善环境预报精度的有效方法，是当前环境
of initial analysis error and ensemble forecast based on
数值预报领域研究的前沿热点问题。虽然在大气和 the method of“BGM”[J]. Scientia Meteorological Sinica,
海洋领域有所涉及，但仍处在起步发展阶段，海洋水 2009, 29(3): 317–322.
[11] 王辉, 刘娜, 李本霞, 等. 海洋可预报性和集合预报研究综
声环境敏感区诊断及适应性观测研究是一项跨学
述 [J]. 地球科学进展, 2014, 29(11): 1212–1225.
科的前沿基础性研究，具有一定的难度和挑战。研 Wang Hui, Liu Na, Li Benxia, et al. An overview of ocean
究一旦取得突破，将对我国水声观测系统建设及优 predictability and ocean ensemble forecast[J]. Advances in
Earth Science, 2014, 29(11): 1212–1225.
化使用产生深远影响，颠覆当前水声环境保障的方
[12] Yang S C, Keppenne C, Rienecker M, et al. Application of
法和技术，促进我国水声行业的发展。 coupled bred vectors to seasonal-to-interannual forecast-
ing and ocean data assimilation[J]. Journal of Climate,
致谢 特别感谢李启虎院士在本项研究论证阶段 2009, 22(11): 2850–2870.
给予的大力支持和关注，谨以此文庆祝李启虎院士 [13] Yin X Q, Oey L Y. Bred-ensemble ocean forecast of
八十华诞。 loop current and rings[J]. Ocean Modelling, 2007, 17(4):
300–326.
[14] Xue Y, Cane M A, Zebiak S E, et al. Predictability of a
coupled model of ENSO using singular vector analysis[J].
参 考 文 献 Monthly Weather Review, 1997, 125(9): 2043–2056.

[15] Chen Y Q, Battisti D S, Palmer T N, et al. A study
[1] Schmidt H. AREA: adaptive rapid environment assess- of the predictability of tropical pacific SST in a cou-
ment[M]//Pace N G, Jensen F B. Impact of littoral pled atmosphere-ocean model using singular vector anal-
environmental variability on acoustic predictions and ysis: the role of the annual cycle and the ENSO cycle[J].
sonar performance. Kluwer Academic Publishers, 2002: Monthly Weather Review, 1997, 125(5): 831–845.
587–594. [16] 邹广安. POM 模式在日本南部黑潮路径变异研究中的应
[2] Riehl H, Haggard W H, Sanborn R W. On the prediction 用 [J]. 海洋科学, 2016, 40(2): 151–158.
of 24-hour hurricane motion[J] Journal of Atmospheric Zou Guang’an. Application of the POM model to study
Sciences, 1956, 13(5): 415–420. the path variations of Kuroshio currents in southern Japan
[3] 穆穆. 目标观测的方法、现状与发展展望 [J]. 中国科学: 地球 seas[J]. Marine Sciences, 2016, 40(2): 151–158.
科学, 2013, 43(11): 1717–1725. [17] 马旭林, 于月明, 姜胜, 等. 基于集合卡尔曼变换的目标观
Mu Mu. Methods, current status, and prospect of tar- 测敏感区识别系统优化及影响试验 [J]. 大气科学学报, 2014,
geted observation[J]. Science China: Earth Sciences, 2013, 37(6): 749–757.
43(11): 1717–1725. Ma Xulin, Yu Yueming, Jiang Sheng, et a1. Optimiza-