Abstract

The presence of internal variability (IV) in ensembles of nested regional climate model (RCM) simulations is now widely acknowledged in the community working on dynamical downscaling. IV is defined as the inter-member spread between members in an ensemble of simulations performed by a given RCM driven by identical lateral boundary conditions (LBC), where different members are being initialised at different times. The physical mechanisms responsible for the time variations and structure of such IV have only recently begun to receive attention. Recent studies have shown empirical evidence of a close parallel between the energy conversions associated with the time fluctuations of IV in ensemble simulations of RCM and the energy conversions taking place in weather systems. Inspired by the classical work on global energetics of weather systems, we sought a formulation of an energy cycle for IV that would be applicable for limited-area domain. We develop here a novel formalism based on local energetics that can be applied to further our understanding IV. Prognostic equations for ensemble-mean kinetic energy and available enthalpy are decomposed into contributions due to ensemble-mean variables (EM) and those due to deviations from the ensemble mean (IV). Together these equations constitute an energy cycle for IV in ensemble simulations of RCM. Although the energy cycle for IV was developed in a context entirely different from that of energetics of weather systems, the exchange terms between the various reservoirs have a rather similar mathematical form, which facilitates some interpretations of their physical meaning.

Highlights

  • During the last decade, ensembles of dynamical downscaling climate simulations have been increasingly used to better understand our evolving climate at scales that are not resolved by global climate models (GCM)

  • internal variability (IV) is defined as the inter-member spread between members in an ensemble of simulations performed by a given regional climate model (RCM) driven by identical lateral boundary conditions (LBC), where different members are being initialised at different times

  • In an ensemble of simulations performed with a given RCM driven by the same external boundary conditions, but launched from different initial conditions (IC), individual simulations evolve into different weather sequences

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Summary

Introduction

Ensembles of dynamical downscaling climate simulations have been increasingly used to better understand our evolving climate at scales that are not resolved by global climate models (GCM). Nikiema and Laprise (2011a, b) established detailed prognostic equations for inter-member variance (or2IV =ot) of various atmospheric variables such as potential temperature and vorticity They applied these equations to perform diagnostic budget studies to quantify the various dynamical and diabatic contributions to the time variations of IV that took place in an ensemble of 20 simulations of the third-generation Canadian RCM (CRCM3) that differed only in their IC. A noteworthy result from these studies is that there appears to be an undeniable parallel between the energetics of IV in ensemble simulations of nested model and the energy conversions taking place in weather systems, with generation of potential energy by diabatic processes such as condensation, convection and radiation, and later conversion to kinetic energy (e.g., Lorenz 1955, 1967) This led the authors to conclude that RCM IV is a natural phenomenon arising from the chaotic nature of the atmosphere, and not a numerical artefact associated, for example, to the nesting technique.

Basic equations in the atmospheric system
The atmospheric energy equations
À Tr T
Ensemble-mean energy equations
Kinetic energy equations for KEM and KIV
Ensemble-mean energy cycle
Conclusions
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