留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

耦合模式FGOALS-g3对全球海洋潮汐的模拟评估

黄新禹 王彩霞 魏吉林 于子棚 田志伟 刘海龙

黄新禹,王彩霞,魏吉林,等. 耦合模式FGOALS-g3对全球海洋潮汐的模拟评估[J]. 海洋学报,2024,46(8):63–73 doi: 10.12284/hyxb2024091
引用本文: 黄新禹,王彩霞,魏吉林,等. 耦合模式FGOALS-g3对全球海洋潮汐的模拟评估[J]. 海洋学报,2024,46(8):63–73 doi: 10.12284/hyxb2024091
Huang Xinyu,Wang Caixia,Wei Jilin, et al. An assessment of global ocean tide simulation by a coupled climate model FGOALS-g3[J]. Haiyang Xuebao,2024, 46(8):63–73 doi: 10.12284/hyxb2024091
Citation: Huang Xinyu,Wang Caixia,Wei Jilin, et al. An assessment of global ocean tide simulation by a coupled climate model FGOALS-g3[J]. Haiyang Xuebao,2024, 46(8):63–73 doi: 10.12284/hyxb2024091

耦合模式FGOALS-g3对全球海洋潮汐的模拟评估

doi: 10.12284/hyxb2024091
基金项目: 国家自然科学基金(41931182);国家重点研发计划(2022YFC3104802)。
详细信息
    作者简介:

    黄新禹(1999—),男,河南省许昌市人,研究方向为海洋内潮数值模拟。E-mail: huangxinyu@stu.ouc.edu.cn

    通讯作者:

    刘海龙(1973—),男,山东省潍坊市人,研究员,主要从事海洋环流数值模拟。E-mail: lhl@lasg.iap.ac.cn

  • 中图分类号: P731.23

An assessment of global ocean tide simulation by a coupled climate model FGOALS-g3

  • 摘要: 潮汐在海洋能量的传递和混合过程中起着重要的作用,为维持全球热盐环流提供了主要的能量,影响着全球的海洋环流。此前已有工作在低分辨率的、单独的海洋模式中研究潮汐作用对海洋环流状态的敏感性,为进一步研究潮汐作用对环流和气候状态的敏感性,有必要将潮强迫引入到气候耦合模式中。本文成功地将8个主要平衡分潮显式地加入到耦合模式FGOALS-g3中,并评估了其对全球海洋潮汐的模拟能力,对于进一步研究潮汐对大尺度环流及气候状态的影响有重要意义。本文通过对模拟的海表面高度数据进行潮汐调和分析,得到各个分潮的调和常数,并将其与全球潮汐模型TPXO9和FES2014,以及开放海洋潮汐数据集st102进行对比。结果表明,FGOALS-g3耦合模式可以合理地模拟全球海洋中的正压潮,模拟结果与潮汐模型和实测数据集相比均比较接近。与这两套全球潮汐模型相比,均方误差均相对较小,且误差大多分布在振幅较大的区域。与st102数据集相比,FGOALS-g3模拟的8个主要分潮的平均振幅相对误差均在10%以内,且总均方误差均小于10 cm。
  • 图  1  TPXO9、FES2014和 FGOALS-g3试验M2分潮和K1分潮的振幅和迟角的空间分布

    图中M2分潮 (a−c) 和K1分潮 (d−f) 的等值线间隔分别为30°和60°

    Fig.  1  Spatial patterns of the amplitude and phase of the M2 and K1 constituents for TPXO9, FES2014 and FGOALS-g3

    The lines of the constant phase are plotted every 30° for M2 (a−c) and every 60°for K1 (d−f)

    图  2  FGOALS-g3相比于TPXO9的M2分潮和K1分潮的均方误差

    a, d. 振幅误差;b, e. 迟角误差;c, f. 总均方误差

    Fig.  2  Errors of the simulated M2 constituent (a–c) and K1 constituent (d–f) relative to TPXO9 in FGOALS-g3

    a, d. Amplitude error;b, e. phase error;c, f. total error

    图  3  FGOALS-g3的潮汐模式模拟的大潮和小潮的空间分布

    每列中相邻两幅图的时间间隔为6 h

    Fig.  3  Spatial patterns of the spring tides and neap tides for the FGOALS-g3 tidal module

    The interval between the rows is 6 h

    表  1  TPXO9 和 FGOALS-g3模拟的八大分潮的全球平均振幅,以及FGOALS-g3 相比于 TPXO9 的振幅误差、迟角误差和总均方误差

    Tab.  1  Global mean values of the amplitudes of the eight tidal constituents for TPXO9 and FGOALS-g3, and the amplitude, phase, and total errors of the eight tidal constituents for FGOALS-g3 compared with TPXO9

    M2 S2 N2 K2 K1 O1 P1 Q1
    平均振幅(TPXO9)/cm 34.84 13.55 7.41 3.80 11.73 8.12 3.66 1.69
    平均振幅(FGOALS-g3)/cm 31.66 13.07 7.28 3.50 13.78 13.00 4.28 2.74
    振幅误差/cm 7.40 3.25 1.39 0.97 2.83 3.86 0.87 0.89
    迟角误差/(°) 8.79 3.52 1.97 0.99 3.27 2.30 1.01 0.43
    总均方误差/cm 12.79 5.31 2.67 1.53 4.83 4.89 1.49 1.08
    下载: 导出CSV

    表  2  FES2014和 FGOALS-g3模拟的八大分潮的全球平均振幅,以及FGOALS-g3 相比于FES2014的振幅误差、迟角误差和总均方误差

    Tab.  2  Global mean values of the amplitudes of the eight tidal constituents for FES2014 and FGOALS-g3, and the amplitude, phase, and total errors of the eight tidal constituents for FGOALS-g3 compared with FES2014

    M2 S2 N2 K2 K1 O1 P1 Q1
    平均振幅(FES2014)/cm 35.88 14.24 7.49 3.97 14.20 10.43 4.15 1.96
    平均振幅(FGOALS-g3)/cm 31.66 13.07 7.28 3.50 13.78 13.00 4.28 2.74
    振幅误差/cm 11.17 4.15 1.69 1.02 5.11 2.97 0.85 0.43
    迟角误差/cm 8.94 3.92 1.62 1.23 5.32 3.06 0.95 0.40
    总均方误差/cm 14.31 5.71 2.34 1.60 7.38 4.26 1.27 0.59
    下载: 导出CSV

    表  3  st102 和 FGOALS-g3 模拟的八大分潮的全球平均振幅和振幅相对误差,以及 FGOALS-g3 相比于st102 的振幅误差、迟角误差和总均方误差

    Tab.  3  Global mean values and the relative errors of the amplitudes of the eight tidal constituents for st102 and FGOALS-g3, and the amplitude, phase, and total errors of the eight tidal constituents for FGOALS-g3 compared with st102

    M2 S2 N2 K2 K1 O1 P1 Q1
    平均振幅(st102)/cm 40.40 15.15 8.11 3.97 12.57 8.73 3.84 1.77
    平均振幅(FGOALS-g3)/cm 36.79 14.17 8.48 3.75 13.14 9.07 4.02 1.91
    振幅相对误差/% 8.94 6.49 4.50 5.58 4.53 3.89 4.69 7.91
    振幅误差/cm 5.43 2.27 1.12 0.77 2.01 3.14 0.72 0.84
    迟角误差/cm 7.34 3.22 1.68 0.84 3.05 2.19 0.93 0.45
    总均方误差/cm 9.35 4.12 2.09 1.22 3.25 3.84 1.14 1.03
    下载: 导出CSV
  • [1] Huang Ruixin. Mixing and energetics of the oceanic thermohaline circulation[J]. Journal of Physical Oceanography, 1999, 29(4): 727−746. doi: 10.1175/1520-0485(1999)029<0727:MAEOTO>2.0.CO;2
    [2] MacKinnon J. Mountain waves in the deep ocean[J]. Nature, 2013, 501(7467): 321−322. doi: 10.1038/501321a
    [3] Munk W, Wunsch C. Abyssal recipes II: energetics of tidal and wind mixing[J]. Deep Sea Research Part I: Oceanographic Research Papers, 1998, 45(12): 1977−2010. doi: 10.1016/S0967-0637(98)00070-3
    [4] Wang Xiaowei, Liu Zhiyu, Peng Shiqiu. Impact of tidal mixing on water mass transformation and circulation in the South China Sea[J]. Journal of Physical Oceanography, 2017, 47(2): 419−432. doi: 10.1175/JPO-D-16-0171.1
    [5] Wunsch C, Ferrari R. Vertical mixing, energy, and the general circulation of the oceans[J]. Annual Review of Fluid Mechanics, 2004, 36: 281−314. doi: 10.1146/annurev.fluid.36.050802.122121
    [6] EgbertG D, Gary R D. Semi-diurnal and diurnal tidal dissipation from TOPEX/Poseidon altimetry[J]. Geophysical Research Letters, 2003, 30(17): 1907.
    [7] Jayne S R, St. Laurent L C. Parameterizing tidal dissipation over rough topography[J]. Geophysical Research Letters, 2001, 28(5): 811−814. doi: 10.1029/2000GL012044
    [8] Bryan K. A numerical method for the study of the circulation of the world ocean[J]. Journal of Computational Physics, 1997, 135(2): 154−169. doi: 10.1006/jcph.1997.5699
    [9] Cox M D. A primitive equation 3-dimensional model of the ocean[R]. Princeton: Princeton University, 1984.
    [10] Killworth P D, Webb D J, Stainforth D, et al. The development of a free-surface bryan-cox-semtner ocean model[J]. Journal of Physical Oceanography, 1991, 21(9): 1333−1348. doi: 10.1175/1520-0485(1991)021<1333:TDOAFS>2.0.CO;2
    [11] St. Laurent L C, Simmons H L, Jayne S R. Estimating tidally driven mixing in the deep ocean[J]. Geophysical Research Letters, 2002, 29(23): 2106.
    [12] Simmons H L, Jayne S R, St. Laurent L C, et al. Tidally driven mixing in a numerical model of the ocean general circulation[J]. Ocean Modelling, 2004, 6(3/4): 245−263.
    [13] Yu Yi, Liu Hailong, Lan Jian. The influence of explicit tidal forcing in a climate ocean circulation model[J]. Acta Oceanologica Sinica, 2016, 35(9): 42−50. doi: 10.1007/s13131-016-0931-9
    [14] Saenko O A, Merryfield W J. On the effect of topographically enhanced mixing on the global ocean circulation[J]. Journal of Physical Oceanography, 2005, 35(5): 826−834. doi: 10.1175/JPO2722.1
    [15] Jayne S R. The impact of abyssal mixing parameterizations in an ocean general circulation model[J]. Journal of Physical Oceanography, 2009, 39(7): 1756−1775. doi: 10.1175/2009JPO4085.1
    [16] Melet A, Hallberg R, Legg S, et al. Sensitivity of the ocean state to the vertical distribution of internal-tide-driven mixing[J]. Journal of Physical Oceanography, 2013, 43(3): 602−615. doi: 10.1175/JPO-D-12-055.1
    [17] Song Pengyang, Sidorenko D, Scholz P, et al. The tidal effects in the Finite-volumE Sea ice–Ocean Model (FESOM2.1): a comparison between parameterised tidal mixing and explicit tidal forcing[J]. Geoscientific Model Development, 2023, 16(1): 383−405. doi: 10.5194/gmd-16-383-2023
    [18] Thomas M, Sündermann J, Maier-Reimer E. Consideration of ocean tides in an OGCM and impacts on subseasonal to decadal polar motion excitation[J]. Geophysical Research Letters, 2001, 28(12): 2457−2460. doi: 10.1029/2000GL012234
    [19] Schiller A. Effects of explicit tidal forcing in an OGCM on the water-mass structure and circulation in the Indonesian through flow region[J]. Ocean Modelling, 2004, 6(1): 31−49. doi: 10.1016/S1463-5003(02)00057-4
    [20] Schiller A, Fiedler R. Explicit tidal forcing in an ocean general circulation model[J]. Geophysical Research Letters, 2007, 34(3): L03611.
    [21] Müller M, Haak H, Jungclaus J H, et al. The effect of ocean tides on a climate model simulation[J]. Ocean Modelling, 2010, 35(4): 304−313. doi: 10.1016/j.ocemod.2010.09.001
    [22] Jin Jiangbo, Guo Run, Zhang Minghua, et al. Formulation of a new explicit tidal scheme in revised LICOM2.0[J]. Geoscientific Model Development, 2022, 15(10): 4259−4273. doi: 10.5194/gmd-15-4259-2022
    [23] Arbic B K, Wallcraft A J, Metzger E J. Concurrent simulation of the eddying general circulation and tides in a global ocean model[J]. Ocean Modelling, 2010, 32(3/4): 175−187.
    [24] Shriver J F, Arbic B K, Richman J G, et al. An evaluation of the barotropic and internal tides in a high-resolution global ocean circulation model[J]. Journal of Geophysical Research: Oceans, 2012, 117(C10): C10024.
    [25] Müller M, Cherniawsky J Y, Foreman M G G, et al. Global M2 internal tide and its seasonal variability from high resolution ocean circulation and tide modeling[J]. Geophysical Research Letters, 2012, 39(19): L19607.
    [26] Müller M. On the space-and time-dependence of barotropic-to-baroclinic tidal energy conversion[J]. Ocean Modelling, 2013, 72: 242−252. doi: 10.1016/j.ocemod.2013.09.007
    [27] Li Lijuan, Yu Yongqiang, Tang Yanli, et al. The flexible global ocean-atmosphere-land system model grid-point version 3 (FGOALS-g3): description and evaluation[J]. Journal of Advances in Modeling Earth Systems, 2020, 12(9): e2019MS002012. doi: 10.1029/2019MS002012
    [28] Li Lijuan, Dong Li, Xie Jinbo, et al. The GAMIL3: model description and evaluation[J]. Journal of Geophysical Research: Atmospheres, 2020, 125(15): e2020JD032574. doi: 10.1029/2020JD032574
    [29] Xie Zhenghui, Wang Longhuan, Wang Yan, et al. Land surface model CAS-LSM: model description and evaluation[J]. Journal of Advances in Modeling Earth Systems, 2020, 12(12): e2020MS002339. doi: 10.1029/2020MS002339
    [30] Lin Pengfei, Yu Zhipeng, Liu Hailong, et al. LICOM model datasets for the CMIP6 ocean model intercomparison project[J]. Advances in Atmospheric Sciences, 2020, 37(3): 239−249. doi: 10.1007/s00376-019-9208-5
    [31] Craig A P, Vertenstein M, Jacob R. A new flexible coupler for earth system modeling developed for CCSM4 and CESM1[J]. The International Journal of High Performance Computing Applications, 2012, 26(1): 31−42. doi: 10.1177/1094342011428141
    [32] Wang Yaqi, Yu Zipeng, Lin Pengfei, et al. FGOALS-g3 model datasets for CMIP6 flux-anomaly-forced model intercomparison project[J]. Advances in Atmospheric Sciences, 2020, 37(10): 1093−1101. doi: 10.1007/s00376-020-2045-8
    [33] Lin Pengfei, Zhao Bowen, Wei Jilin, et al. The super-large ensemble experiments of CAS FGOALS-g3[J]. Advances in Atmospheric Sciences, 2022, 39(10): 1746−1765. doi: 10.1007/s00376-022-1439-1
    [34] Zheng Weipeng, Yu Yongqiang, Luan Yihua, et al. CAS-FGOALS datasets for the two interglacial epochs of the holocene and the last interglacial in PMIP4[J]. Advances in Atmospheric Sciences, 2020, 37(10): 1034−1044. doi: 10.1007/s00376-020-9290-8
    [35] Wei Jilin, Liu Hailong, Zhao Yan, et al. Simulation of the climate and ocean circulations in the Middle Miocene Climate Optimum by a coupled model FGOALS-g3[J]. Palaeogeography, Palaeoclimatology, Palaeoecology, 2023, 617: 111509. doi: 10.1016/j.palaeo.2023.111509
    [36] Pu Ye, Liu Hongbo, Yan Ruojing, et al. CAS FGOALS-g3 model datasets for the CMIP6 scenario model intercomparison project (ScenarioMIP)[J]. Advances in Atmospheric Sciences, 2020, 37(10): 1081−1092. doi: 10.1007/s00376-020-2032-0
    [37] Griffies S M, Biastoch A, Böning C, et al. Coordinated ocean-ice reference experiments (COREs)[J]. Ocean Modelling, 2009, 26(1/2): 1−46.
    [38] Hendershott M C. The effects of solid earth deformation on global ocean tides[J]. Geophysical Journal International, 1972, 29(4): 389−402. doi: 10.1111/j.1365-246X.1972.tb06167.x
    [39] Eyring V, Bony S, Meehl G A, et al. Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization[J]. Geoscientific Model Development, 2016, 9(5): 1937−1958. doi: 10.5194/gmd-9-1937-2016
    [40] Egbert G D, Erofeeva S Y. Efficient inverse modeling of barotropic ocean tides[J]. Journal of Atmospheric and Oceanic Technology, 2002, 19(2): 183−204. doi: 10.1175/1520-0426(2002)019<0183:EIMOBO>2.0.CO;2
    [41] Lyard F H, Allain D J, Cancet M, et al. FES2014 global ocean tide atlas: design and performance[J]. Ocean Science, 2021, 17(3): 615−649. doi: 10.5194/os-17-615-2021
    [42] Shum C K, Woodworth P L, Andersen O B, et al. Accuracy assessment of recent ocean tide models[J]. Journal of Geophysical Research: Oceans, 1997, 102(C11): 25173−25194. doi: 10.1029/97JC00445
    [43] von Storch JS, Hertwig E, Lüschow V, et al. Open-ocean tides simulated by ICON-O, version icon-2.6.6[J]. Geoscientific Model Development, 2023, 16(17): 5179−5196. doi: 10.5194/gmd-16-5179-2023
    [44] Arbic B K. Incorporating tides and internal gravity waves within global ocean general circulation models: a review[J]. Progress in Oceanography, 2022, 206: 102824. doi: 10.1016/j.pocean.2022.102824
  • 加载中
图(3) / 表(3)
计量
  • 文章访问数:  161
  • HTML全文浏览量:  39
  • PDF下载量:  23
  • 被引次数: 0
出版历程
  • 收稿日期:  2024-01-18
  • 修回日期:  2024-07-30
  • 网络出版日期:  2024-08-12
  • 刊出日期:  2024-09-26

目录

    /

    返回文章
    返回