NUMERICAL RESULTS FROM A NINE-LEVEL GENERAL CIRCULATION MODEL OF THE ATMOSPHERE<sup>1</sup>

Smagorinsky, Joseph; Manabe, Syukuro; Holloway, J. Leith

doi:10.1175/1520-0493(1965)093<0727:nrfanl>2.3.co;2

Cited by 444 publications

(169 citation statements)

References 23 publications

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“…The resulting dynamical models draw strongly on the heritage of General Circulation Models (GCMs). First developed in the 1960s-1980s-see, for example, Smagorinsky et al 1965 for a very early example-and continually developed since, GCMs are identical in concept to NWP models-insofar as they represent a physical model of the system one is attempting to predict or understand-but as they include more physical processes and must be run over longer timescales, they typically use much coarser resolution grid boxes than NWP. As in NWP, the use of ensembles in climate model simulations is common.…”

Section: Dynamical Modelsmentioning

confidence: 99%

Weather, Climate and the Nature of Predictability

Brayshaw

2018

Weather &Amp; Climate Services for the Energy Industry

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The prediction and simulation of future weather and climate is a key ingredient in good weather risk management. This chapter briefly reviews the nature and underlying sources of predictability on timescales from hours-ahead to centuries-ahead. The traditional distinction between 'weather' and 'climate' predictions is described, and the role of recent scientific developments in driving a convergence of these two classic problems is highlighted. The chapter concludes by outlining and comparing the two main strategies used for creating weather and climate predictions, and discussing the challenges of using predictions in quantitative applications.

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Section: Dynamical Modelsmentioning

confidence: 99%

Weather, Climate and the Nature of Predictability

Brayshaw

2018

Weather &Amp; Climate Services for the Energy Industry

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“…The frictional force F (due to vertical mixing) in term 12 is determined by F = (∂ v τ/∂z)/ρ (Smagorinsky et al, 1965) with the absence of frictional stress at the top of z (referring to the thickness of the friction active layer which will be determined by parametrization experiments for best fit by consulting the planetary boundary layer (PBL) height data from the ECMWF NUMERICAL DIAGNOSTIC MODEL FOR FORCING OF GEOPOTENTIAL 2071 model). The frictional stress at the Earth's surface is given by v τ = ρC d |V sfc |V sfc (Lettau, 1959;Pedlosky, 1987, sections 2.8 and 3.12) with the drag coefficient C d = 2 × 10 −3 proposed by Delsol et al(1971) and Holloway and Manabe (1971).…”

Section: Derivation Of a Complete Geopotential Numerical Model And Scmentioning

confidence: 99%

The derivation of a numerical diagnostic model for the forcing of the geopotential

Zhang

Cheng

et al. 2008

Quart J Royal Meteoro Soc

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ABSTRACT:Simply applying the divergence operator to the horizontal velocity equation in spherical-isobaric coordinates yields a more solvable linear geopotential equation (than the geopotential tendency and the omega equations) for diagnosing the geopotential and its anomalies responsible for global floods and droughts. This geopotential model is freed from the zerodenominator problem caused by the observed neutral stability which affects the geopotential tendency and omega equations. The geopotential equation's forcing terms 2-5 (the direct operation results of the horizontal advection term in the velocity equation) can identify the synoptic signals mixed up by the classical divergence equation's quadratic and Jacobian terms (the manipulated results of the above terms 2-5). Solving this geopotential equation with the successive-over-relaxation method and the neutral stability as calculated from the reanalysis data produces reasonably good reconstructions of the global and local geopotential fields. The additional advantages of the present geopotential model over the geopotential tendency, omega and divergence models are that the geopotential model reveals and explains the following mechanisms which received less attention in previous studies. (1) The saddle patterns favour the high systems. (2) The equatorial easterlies favour the low systems. (3) The contributions of ageostrophic processes associated with jets and saddle flows to the transitions of weather patterns might be overlooked by the geopotential tendency model in which neutral stability and static instability in cold domes as well as jet-induced inertial instability are smoothed out artificially.

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“…Over land areas the surface fluxes are evaluated following relations similar to those given by Businger et al (1971). The vertical distribution of fluxes of momentum, heat and moisture between *=1 and * =0 .7 follows the mixing length concepts as in Smagorinsky et al (1965). Above the *=0.7 level, the fluxes vanish in this formulation.…”

Section: The Global Spectral Modelmentioning

confidence: 99%

Details of Low Latitude Medium Range Numerical Weather Prediction Using a Global

Krishnamurti

Pasch

Pan

et al. 1983

Journal of the Meteorological Society of Japan

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This study addresses the formation of a tropical depression over the northern Bay of Bengal. A medium range numerical wheather prediction experiment is carried out with the observations from the Global and the Monsoon Experiments during 1979. The global spectral model contains 11 vertical levels; horizontally it is described by 29 waves via the so-called rhomboidal truncation. In the present experiment all 29 waves of the nondivergent wind and only 5 waves of the irrotational wind define the initial state. The model physics include air-sea interaction, detailed radiation, cumulus parameterization, large scale condensation, dry convective adjustment and the effects of mountains via the usual sigma frame. The initial state for the case study selected here is on July 1, 1204GMT1979. A tropical depression forms by July 5, 1979 over the northern Bay of Bengal. The global model shows considerable skill in predicting its formation and subsequent westward motion. The predicted fields of the total motion field and the streamfunction appear reasonable to day 8 of prediction. On the other hand, the divergent part of the motion field exhibits considerable error beyond day 2, especially on the planetary scale. These errors on the scale of the depression are much smaller since mass and moisture convergence move westward with the stream function minimum. In this region Kuo's scheme prescribes very reasonable rainfall rates for the monsoon depression.Single-level models, run at 700mb up to 48 hours starting on day 3, fail to predict the formation of the monsoon depression. These are respectively based on the conservation of absolute and potential vorticity. In order to understand further the formation of this depression, calculations of detailed energetics of the multi-level spectral forecast are carried out over a limited domain. They show that during the formative stage the barotropic process was most important while the rapid growth and its maintenance is largely attributable to the role of cumulus convection. The storm forms at upper levels (near 500mb) and descends down to the surface in the initial period; this is shown by observation and is reasonably simulated by the prediction.The initial barotropic growth appears to occur over a deep lower tropospheric layer and vertical coupling seems to be an important feature that is not described by the single level experiments.Finally, we present a short summary of results obtained for this experiment over other parts of the globe as well as for other experiments, where some results of data sensitivity studies are addressed.

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NUMERICAL RESULTS FROM A NINE-LEVEL GENERAL CIRCULATION MODEL OF THE ATMOSPHERE¹

Cited by 444 publications

References 23 publications

Weather, Climate and the Nature of Predictability

Weather, Climate and the Nature of Predictability

The derivation of a numerical diagnostic model for the forcing of the geopotential

Details of Low Latitude Medium Range Numerical Weather Prediction Using a Global

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NUMERICAL RESULTS FROM A NINE-LEVEL GENERAL CIRCULATION MODEL OF THE ATMOSPHERE1

Cited by 444 publications

References 23 publications

Weather, Climate and the Nature of Predictability

Weather, Climate and the Nature of Predictability

The derivation of a numerical diagnostic model for the forcing of the geopotential

Details of Low Latitude Medium Range Numerical Weather Prediction Using a Global

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Product

Resources

About

NUMERICAL RESULTS FROM A NINE-LEVEL GENERAL CIRCULATION MODEL OF THE ATMOSPHERE¹