On the Importance of High-Resolution in Large-Scale Ocean Models

被引:1
|
作者
Eric P.CHASSIGNET [1 ]
Xiaobiao XU [1 ]
机构
[1] Center for Ocean-Atmospheric Prediction Studies (COAPS), Florida State University
关键词
ocean modeling; numerical models; horizontal resolution; boundary currents;
D O I
暂无
中图分类号
P73 [海洋基础科学];
学科分类号
0707 ;
摘要
Eddying global ocean models are now routinely used for ocean prediction, and the value-added of a better representation of the observed ocean variability and western boundary currents at that resolution is currently being evaluated in climate models. This overview article begins with a brief summary of the impact on ocean model biases of resolving eddies in several global ocean–sea ice numerical simulations. Then, a series of North and Equatorial Atlantic configurations are used to show that an increase of the horizontal resolution from eddy-resolving to submesoscale-enabled together with the inclusion of high-resolution bathymetry and tides significantly improve the models’ abilities to represent the observed ocean variability and western boundary currents. However, the computational cost of these simulations is extremely large, and for these simulations to become routine, close collaborations with computer scientists are essential to ensure that numerical codes can take full advantage of the latest computing architecture.
引用
收藏
页码:1621 / 1634
页数:14
相关论文
共 50 条
  • [21] On the Way to Large-Scale and High-Resolution Brain-Chip Interfacing
    Vassanelli, Stefano
    Mahmud, Mufti
    Girardi, Stefano
    Maschietto, Marta
    COGNITIVE COMPUTATION, 2012, 4 (01) : 71 - 81
  • [22] Large-Scale High-Resolution Groundwater Modelling using Grid Computing
    Berendrecht, W. L.
    Lourens, A.
    Snepvangers, J. J. J. C.
    Minnema, B.
    MODSIM 2007: INTERNATIONAL CONGRESS ON MODELLING AND SIMULATION: LAND, WATER AND ENVIRONMENTAL MANAGEMENT: INTEGRATED SYSTEMS FOR SUSTAINABILITY, 2007, : 1954 - 1958
  • [23] On the Way to Large-Scale and High-Resolution Brain-Chip Interfacing
    Stefano Vassanelli
    Mufti Mahmud
    Stefano Girardi
    Marta Maschietto
    Cognitive Computation, 2012, 4 : 71 - 81
  • [24] High-resolution coincidence counting system for large-scale photonics applications
    Hlousek, Josef
    Grygar, Jan
    Dudka, Michal
    Jezek, Miroslav
    PHYSICAL REVIEW APPLIED, 2024, 21 (02)
  • [25] Large-scale and high-resolution analysis of food purchases and health outcomes
    Luca Maria Aiello
    Rossano Schifanella
    Daniele Quercia
    Lucia Del Prete
    EPJ Data Science, 8
  • [26] Towards high-resolution large-scale multi-view stereo
    Hiep, Vu Hoang
    Keriven, Renaud
    Labatut, Patrick
    Pons, Jean-Philippe
    CVPR: 2009 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, VOLS 1-4, 2009, : 1430 - 1437
  • [27] Large-scale calculation of low-frequency-induced currents in high-resolution human body models
    Barchanski, Andreas
    Clemens, Markus
    Gjonaj, Erion
    De Gersem, Herbert
    Weiland, Thomas
    IEEE TRANSACTIONS ON MAGNETICS, 2007, 43 (04) : 1693 - 1696
  • [28] High-Resolution Imaging Capability of Large-Scale LEO Satellite Constellations
    Dorje, Lhamo
    Li, Xiaohua
    Chen, Yu
    Poredi, Nihal A.
    ICC 2024 - IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS, 2024, : 1594 - 1599
  • [29] A high-resolution large-scale dataset of pathological and normal white blood cells
    Bodzas, Alexandra
    Kodytek, Pavel
    Zidek, Jan
    SCIENTIFIC DATA, 2023, 10 (01)
  • [30] Classification of Large-Scale High-Resolution SAR Images With Deep Transfer Learning
    Huang, Zhongling
    Dumitru, Corneliu Octavian
    Pan, Zongxu
    Lei, Bin
    Datcu, Mihai
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2021, 18 (01) : 107 - 111