Toward unification of the multiscale modeling of the atmosphere

被引:137
|
作者
Arakawa, A. [1 ]
Jung, J. -H. [2 ]
Wu, C. -M. [1 ]
机构
[1] Univ Calif Los Angeles, Los Angeles, CA 90095 USA
[2] Colorado State Univ, Ft Collins, CO 80523 USA
基金
美国国家科学基金会;
关键词
RESOLVING CONVECTION PARAMETERIZATION; CUMULUS PARAMETERIZATION; CLOUD PARAMETERIZATION; RESOLUTION DEPENDENCE; HORIZONTAL RESOLUTION; ARAKAWA-SCHUBERT; SCHEME; SIMULATIONS; ENSEMBLE;
D O I
10.5194/acp-11-3731-2011
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
As far as the representation of deep moist convection is concerned, only two kinds of model physics are used at present: highly parameterized as in the conventional general circulation models (GCMs) and explicitly simulated as in the cloud-resolving models (CRMs). Ideally, these two kinds of model physics should be unified so that a continuous transition of model physics from one kind to the other takes place as the resolution changes. With such unification, the GCM can converge to a global CRM (GCRM) as the grid size is refined. This paper suggests two possible routes to achieve the unification. ROUTE I continues to follow the parameterization approach, but uses a unified parameterization that is applicable to any horizontal resolutions between those typically used by GCMs and CRMs. It is shown that a key to construct such a unified parameterization is to eliminate the assumption of small fractional area covered by convective clouds, which is commonly used in the conventional cumulus parameterizations either explicitly or implicitly. A preliminary design of the unified parameterization is presented, which demonstrates that such an assumption can be eliminated through a relatively minor modification of the existing mass-flux based parameterizations. Partial evaluations of the unified parameterization are also presented. ROUTE II follows the "multi-scale modeling framework (MMF)" approach, which takes advantage of explicit representation of deep moist convection and associated cloud-scale processes by CRMs. The Quasi-3-D (Q3-D) MMF is an attempt to broaden the applicability of MMF without necessarily using a fully three-dimensional CRM. This is accomplished using a network of cloud-resolving grids with large gaps. An outline of the Q3-D algorithm and highlights of preliminary results are reviewed.
引用
收藏
页码:3731 / 3742
页数:12
相关论文
共 50 条
  • [1] A Variational Multiscale Method for Particle Dispersion Modeling in the Atmosphere
    Nishio, Y.
    Janssens, B.
    Limam, K.
    van Beeck, J.
    FDMP-FLUID DYNAMICS & MATERIALS PROCESSING, 2023, 19 (03): : 743 - 753
  • [2] Multiscale modeling of the moist-convective atmosphere - A review
    Arakawa, A.
    Jung, J. -H.
    ATMOSPHERIC RESEARCH, 2011, 102 (03) : 263 - 285
  • [3] Toward a Multiscale Approach for Computational Atmospheric Modeling
    Alam, Jahrul M.
    MONTHLY WEATHER REVIEW, 2011, 139 (12) : 3906 - 3922
  • [4] Toward Multiscale Modeling of Carbon Nanotube Transistors
    Guo, Jing
    Datta, Supriyo
    Lundstrom, Mark
    Anantam, M. P.
    INTERNATIONAL JOURNAL FOR MULTISCALE COMPUTATIONAL ENGINEERING, 2004, 2 (02) : 257 - 276
  • [5] TOWARD MULTISCALE MODELING OF WAVE PROPAGATION IN ARTERIES
    Raustin, Ryan
    Mohammadi, Hadi
    JOURNAL OF MECHANICS IN MEDICINE AND BIOLOGY, 2016, 16 (03)
  • [6] Toward a Complex Automata formalism for multiscale modeling
    Hoekstra, Alfons G.
    Lorenz, Eric
    Falcone, Jean-Luc
    Chopard, Bastien
    INTERNATIONAL JOURNAL FOR MULTISCALE COMPUTATIONAL ENGINEERING, 2007, 5 (06) : 491 - 502
  • [7] Polyphenotype multilevel behavior genetics modeling: a step toward unification
    Hunter, Michael
    Bard, David
    BEHAVIOR GENETICS, 2015, 45 (06) : 663 - 663
  • [8] Multiscale Modeling of Composites: Toward Virtual Testing … and Beyond
    J. LLorca
    C. González
    J. M. Molina-Aldareguía
    C. S. Lópes
    JOM, 2013, 65 : 215 - 225
  • [9] Toward a multiscale modeling framework for understanding serotonergic function
    Wong-Lin, KongFatt
    Wang, Da-Hui
    Moustafa, Ahmed A.
    Cohen, Jeremiah Y.
    Nakamura, Kae
    JOURNAL OF PSYCHOPHARMACOLOGY, 2017, 31 (09) : 1121 - 1136
  • [10] Toward Predictive Multiscale Modeling of Vascular Tumor Growth
    Oden, J. Tinsley
    Lima, Ernesto A. B. F.
    Almeida, Regina C.
    Feng, Yusheng
    Rylander, Marissa Nichole
    Fuentes, David
    Faghihi, Danial
    Rahman, Mohammad M.
    DeWitt, Matthew
    Gadde, Manasa
    Zhou, J. Cliff
    ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING, 2016, 23 (04) : 735 - 779