A SIMPLE PROGNOSTIC CLOSURE ASSUMPTION TO DEEP CONVECTIVE PARAMETERIZATION:I

来源 :Acta Meteorologica Sinica | 被引量 : 0次 | 上传用户:jonelove0000
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In this work,the problem of dependency of the predicted rainfall upon the grid-size in mesoscale numerical weatherprediction models is addressed.We argue that this problem is due to (i) the violation of the quasi-equilibrium assump-tion,which is underlying most existing convective parameterization schemes,and states that the convective activity maybe considered in instantaneous equilibrium with the larger-scale forcing;and (ii) the violation of the hydrostatic approx-imation,made in most mesoscale models,which would induce too large-scale circulation in occurrence of strong con-vection.On the contrary,meso-β and meso-α scale models,i.e.models with horizontal grid size ranging from 10 to 100km,have a capacity to resolve motions with characteristic scales close to the ones of the convective motions.Wehypothesize that a possible way to eliminate this problem is (i) to take a prognostic approach to the parameterization ofdeep convection,whereby the quantities that describe the activity of convection are no longer diagnosed from the instan-taneous value of the large-scale forcing,but predicted by time-dependent equations,that integrate the large-scale forc-ing over time;(ii)to introduce a mesoscale parameter which varies systematically with the grid size of the numericalmodel in order to damp large-scale circulation usually too induced when the grid size becomes smaller (from 100 km to10 kin).We propose an implementation of this idea in the frame of one existing scheme,already tested and used for along time at the French Weather Service.The results of the test through one-dimensional experiments with the Phase Ⅲof GATE data are reported in this paper;and the ones on its implementation in the three-dimensional model with theOSCAR data will be reported in a companion paper. In this work, the problem of dependency of the predicted rainfall upon the grid-size in mesoscale numerical weatherprediction models is addressed. We argue that this problem is due to (i) the violation of the quasi-equilibrium assump- tion, which is the underlying most existing convective parameterization schemes, and states that the convective activity maybe considered in instantaneous equilibrium with the larger-scale forcing; and (ii) the violation of the hydrostatic approximation, made in most mesoscale models, which would induce too large-scale In the occurrence of strong con-vection. On the contrary, meso-β and meso-α scale models, iemodels with horizontal grid size ranging from 10 to 100km, have a capacity to resolve motions with characteristic scales close to the ones of the convective motions.Wehypothesize that a possible way to eliminate this problem is (i) to take a prognostic approach to the parameterization ofde convection, whereby the quantities that describe the activity o f convection are no longer diagnosed from the instan-taneous value of the large-scale forcing, but predicted by time-dependent equations, that integrate the large-scale for c-ing over time; (ii) to introduce a mesoscale parameter which varies systematically with the grid size of the numerical model in order to damp large-scale circulation usually too induced when the grid size becomes smaller (from 100 km to 10 kin) .We propose an implementation of this idea in the frame of one existing scheme, already tested and used for along time at the French Weather Service. The results of the test through one-dimensional experiments with the Phase III of GATE data are reported in this paper; and the ones on its implementation in the three-dimensional model with the OSCAR data will be reported in a companion paper.
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