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Original Articles

Predictability experiments with a baroclinic model

Pages 77-89 | Received 25 Aug 1980, Published online: 15 Nov 2010
 

Abstract

A series of model predictability experiments has been performed using the baroclinic primitive equation spectral model developed by Staniforth and Daley (1977). These experiments were designed to show the difference in predictability decay rates for geostrophic and ageostrophic initial perturbations. The difference in predictability decay rates has implications for the optimal specification of the initial state as discussed in Daley (1980).

The results showed that the predictability decay rates from initial ageostrophic perturbations were smaller than those from geostrophic perturbations for large vertical scale. The predictability decay rates of the two types of initial perturbations tended to be similar for vertical scales smaller than 100 m. Results from a model containing a moist convective adjustment parameterization indicated a larger predictability decay rate from initial ageostrophic perturbations.

Résumé

Une série d'expériences en prévision a été faite avec le modèle spectral barocline d'équations primitives de Staniforth et Daley (1977), dans le but de démontrer la différence entre le taux de croissance de l'erreur dans la prévision des perturbations initiales géostrophiques et non‐géostrophiques. Il faut tenir compte de cette différence pour une spécification optimale des conditions initiales (Daley, 1980).

Les résultats indiquent que verticalement, sur grande échelle, le taux de croissance de l'erreur est plus bas dans la prévision des perturbations initiales non‐géostrophiques que dans celle des perturbations géostrophiques. Le taux de croissance de l'erreur est similaire dans le cas d'échelles verticales inférieures à 100 m. Dans le cas d'un modèle tenant compte des processus humides, le taux de croissance de l'erreur pour les modes non‐géostrophiques s'est avérée plus grande.

Notes

The National Center for Atmospheric Research is sponsored by the National Science Foundation.

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