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Thomas Nehrkorn and Marina Živković

Abstract

The performance of several schemes for diagnosing cloud cover from forecast model output was tested using a global numerical weather prediction model and the operational USAF RTNEPH (real-time nephanalysis) cloud analysis. In the present study, schemes were developed from cloud cover statistics stratified by synoptic weather regime. The synoptic regime were defined in terms of vertical profiles of temperature, winds, and moisture. The meteorological significance of these regimes was illustrated by relating them to synoptic features. The simplest scheme (AVG) assigned the average cloud cover to each of the regimes; a variant of the cloud curve algorithm (CCA) technique was developed in which separate cloud-RH curves were derived for each regime by a mapping of the cumulative frequency distribution of RH and cloud cover. Their performance was compared against a number of other diagnostic schemes, including a multiple linear regression method that used global regression equations for cloud cover from a large number of atmospheric and geographic predictors; a version of the Slingo scheme; and simple persistence. Results indicate that the schemes with the lowest rms errors (AVG, and the regression scheme) also had highly unrealistic frequency distributions, with too few points that were close to either clear or overcast values. Persistence was found to provide competitive or superior forecasts out to 24–36 h. The applicability of these results to improved model and cloud observations is discussed.

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Marina Živković and Jean-François Louis

Abstract

In the present paper, we review a new method for relating cloud observations to large-scale variables of general circulation models. The method is based on an application of the cluster analysis to synoptic analyses Of prognostic model variables provided by the National Meteorological Center. Surface cloud observations are “clustered” according to the similarity of the principal-component loading scores of the corresponding vertical soundings. The method was tested by developing a simple cloud parameterization scheme, from the cluster-stratified cloud data, and comparing it with the observations.

Parameterization results are compared qualitatively against satellite imagery and surface analysis, and quantitatively against a scheme based on one variable only, the relative humidity. Qualitative comparison shows that the new approach generates cloud parameterization consistent with observations, especially with cloud structures related to various synoptic-scale flows. Quantitative comparisons indicate a possible advantage of the present method in the areas covered by limited observations. Overall, the results are suggestive of a possible alternative for upgrading and validating cloud schemes presently used in general circulation models.

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Marina Zivković and Ernest M. Agee

Abstract

In this paper we present the results of numerical investigation of a two-dimensional nonlinear set of Boussinesq equations governing Bénard–Rayleigh convection using spectral representation in the horizontal direction and finite-difference formulation in the vertical direction. Integrations were characterized by high resolution (up to 171 horizontal modes on 32 levels in the vertical direction) and large domain size (ten linear cells were represented). The results presented were obtained for moderate values of Rayleigh number (1150 < Ra < 33 000) that was varied in a near continuous fashion.

It is found that two-dimensional heat flux transitions lead to simulations of various temporal states when sufficient resolution and high aspect-ratio domain of integration are used. The change of slope of the time-averaged logarithmic heat flux curve (log Nu) is simulated in a gradual manner by means of a series of bifurcated solutions.

This study demonstrates that transition from steady to time-dependent convection in two-dimensional simulations is the generic property of the Boussinesq equations. The findings highlight the roles of scale truncation and large domain aspect-ratio in simulations of self-organizing properties of thermal convection. They also provide useful information for the application of nonlinear spectral models to the study of organized convection.

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Kerry A. Emanuel and Marina Živković-Rothman

Abstract

Cumulus convection is a key process in controlling the water vapor content of the atmosphere, which is in turn the largest feedback mechanism for climate change in global climate models. Yet scant attention has been paid to designing convective representations that attempt to handle water vapor with fidelity, and even less to evaluating their performance. Here the authors attempt to address this deficiency by designing a representation of cumulus convection with close attention paid to convective water fluxes and by subjecting the scheme to rigorous tests using sounding array data. The authors maintain that such tests, in which a single-column model is forced by large-scale processes measured by or inferred from the sounding data, must be carried out over a period at least as long as the radiative-subsidence timescale—about 30 days—governing the water vapor adjustment time. The authors also argue that the observed forcing must be preconditioned to guarantee integral enthalpy conservation, else errors in the single-column prediction may be falsely attributed to convective schemes.

Optimization of the new scheme’s parameters is performed using one month of data from the intensive flux array operating during the Tropical Ocean Global Atmosphere Coupled Ocean–Atmosphere Response Experiment, with the aid of the adjoint of the linear tangent of the single-column model. Residual root-mean-square errors, after optimization, are about 15% in relative humidity and 1.8 K in temperature. It is difficult to reject the hypothesis that the residual errors are due to noise in the forcing. Evaluation of the convective scheme is performed using Global Atmospheric Researh Program Atlantic Tropical Experiment data. The performance of the scheme is compared to that of a few other schemes used in current climate models. It is also shown that a vertical resolution better than 50 mb in pressure is necessary for accurate prediction of atmospheric water vapor.

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