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Toward Unification of the Multiscale Modeling of the Atmosphere : Volume 11, Issue 1 (28/01/2011)

By Arakawa, A.

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Book Id: WPLBN0003995787
Format Type: PDF Article :
File Size: Pages 37
Reproduction Date: 2015

Title: Toward Unification of the Multiscale Modeling of the Atmosphere : Volume 11, Issue 1 (28/01/2011)  
Author: Arakawa, A.
Volume: Vol. 11, Issue 1
Language: English
Subject: Science, Atmospheric, Chemistry
Collections: Periodicals: Journal and Magazine Collection (Contemporary), Copernicus GmbH
Historic
Publication Date:
2011
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications

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Wu, C., Arakawa, A., & Jung, J. (2011). Toward Unification of the Multiscale Modeling of the Atmosphere : Volume 11, Issue 1 (28/01/2011). Retrieved from http://worldlibrary.org/


Description
Description: University of California, Los Angeles, California, USA. This paper suggests two possible routes to achieve the unification of model physics in coarse- and fine-resolution atmospheric models. As far as 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. ROUTE I for unification 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 for unification 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 gaps. An outline of the Q3-D algorithm and highlights of preliminary results are reviewed.

Summary
Toward unification of the multiscale modeling of the atmosphere

Excerpt
Arakawa, A.: The cumulus parameterization problem: Past, present, and future, J. Climate, 17, 2493–2525, 2004.; Arakawa, A. and Schubert, W. H.: Interaction of a cumulus cloud ensemble with the large-scale environment. Part I, J. Atmos. Sci., 31, 674–701, 1974.; Bjerknes, V.: Das Problem der Wettervorhersage, betrachtet vom Standpunkte der Mechanik und der Physik (The problem of weather prediction, considered from the viewpoints of mechanics and physics). – Meteorol. Z. 21, 1–7. (translated and edited by E. Volken and S. Brönimann, Meteorol. Z., {18}(2009), 663–667, 1904.; Buizza, R.: Horizontal resolution impact on short and long-range forecast error, Q. J. Roy. Meteorol. Soc., 136, 1020–1035, 2010.; Emanuel, K. A.: A scheme for representing cumulus convection in large-scale models, J. Atmos. Sci., 48, 2313–2335, 1991.; Tiedtke, M.: A comprehensive mass flux scheme for cumulus parameterization in large-scale models. Mon. Weather Rev., 117, 1779–1800, 1989.; Grabowski, W. W.: Coupling cloud processes with the large-scale dynamics using the cloud-resolving convective parameterization (CRCP), J. Atmos. Sci., 58, 978–997, 2001.; Grabowski, W. W. and Smolarkiewicz, P. K.: CRCP: a cloud resolving convective parameterization for modeling the tropical convective atmosphere, Phicica D, 133, 171–178, 1999.; Jung, J.-H. and Arakawa, A.: The resolution dependency of model physics: Illustrations from nonhydrostatic model experiments, J. Atmos. Sci., 61, 88–102, 2004.; Jung, J.-H. and Arakawa, A.: A three-dimensional anelastic model based on the vorticity equation, Mon. Weather Rev., 135, 276–294, 2008.; Jung, J.-H. and Arakawa, A.: Development of a quasi-3d multiscale modeling framework: motivation, basic algorithm and preliminary results, J. Adv. Model. Earth Syst., {2}(11), 31 pp., 2010.; Kain, J. S. and Fritsch, J. M.: A one-dimensional entraining detraining plume model and its application in convective parameterization, J. Atmos. Sci., {47,} 2784–2802, 1990.; Khairoutdinov, M. F., and Randall, D. A.: A cloud-resolving model as a cloud parameterization in the NCAR Community Climate System Model: Preliminary results, Geophys. Res. Lett., 28, 3617–3620, 2001.; Krueger, S. K.: Current Issues in Cumulus Parameterization. ECMWF Seminar on Key issues in the Parameterization of Subgrid Physical Processes, ECMWF, Reading, UK, 3–7 September 2001, 25–51, 2002.; Krueger, S. K. and Luo, Y.: Grid-size dependence of cumulus parameterization. Extended Abstracts, 20th Conference on Weather Analysis and Forecasting/16th Conference on Numerical Weather Prediction, Seattle, WA, Amer. Meteorol. Soc., 2004.; Randall, D. A., Khairoutdinov, M. F., Arakawa, A., and Grabowski, W. W.: Breaking the cloud parameterization deadlock, B. Am. Meteorol. Soc., 84, 1547–1564, 2003.; Skamarock, W. C. and Klemp, J. B.: Adaptive grid refinement for two-dimensional and three-dimensional nonhydrostatic atmospheric flow, Mon. Weather Rev., 121, 788–804, 1993.; Weisman, M. L., Skamarock, W. C., and Klemp, J. B.: The resolution dependence of explicitly modeled convective system, Mon. Weather Rev., 125, 527–548, 1997.; Williamson, D. L.: Convergence of atmospheric simulations with increasing horizontal resolution and fixed forcing scales. Tellus, 51A, 663–673, 1999.; Xu, K.-M. and Arakawa, A.: Semi-prognostic tests of the Arakawa-Schubert cumulus parameterization using simulated data, J. Atmos. Sci., 49, 2421–2436, 1992.; Yanai, M., Esbensen, S., and Chu, J.: Determination of bulk properties of tropical cloud clusters from large-scale heat and moisture budgets, J. Atmos. Sci., 30, 611–627, 1973.; Zhang, G. J. and McFarlane, N. A.: Sensitivity of climate simulations to the parameterization of cumulus convection in the Canadian Climate Center general circulation model, Atmos.-Ocean, {33,} 407–446, 1995.

 

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