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Stéphane Bélair
,
André Méthot
,
Jocelyn Mailhot
,
Bernard Bilodeau
,
Alain Patoine
,
Gérard Pellerin
, and
Jean Côté

Abstract

The objective and subjective evaluations that led to the implementation of the Fritsch and Chappell (FC) convective scheme in the new 24-km Canadian operational regional model are described in this study. Objective precipitation scores computed for a series of 12 benchmark cases equally distributed throughout all seasons and for a parallel preimplementation run of the new version of the model during summer 1998 show the positive impact of increasing the horizontal resolution and of including the FC scheme (instead of the Kuo scheme used in the previous version of the operational model). The comparison is particularly in favor of the FC configuration for the summertime parallel preimplementation run, with improved biases and threat scores, while it is nearly neutral for the 12 benchmark cases comprised mostly of large-scale weather systems.

Examination of a summertime case study confirms the superiority of FC over Kuo for the numerical representation of the structure and evolution of mesoscale convective systems. A wintertime case study, on the other hand, reveals that precipitation patterns with the two model configurations are quite similar, even though the FC scheme is essentially inactive for weather systems organized on such large scales. In contrast with the Kuo simulation, most of the precipitation occurs on the grid scale when using FC. This different partitioning of precipitation into implicit and explicit components is more consistent with the mesoscale-resolving capabilities of the model. It is also observed that the new model physics gives rise to more realistic deepening of coastal large-scale depressions.

The different implicit/explicit partitioning for Kuo and FC is clearly exposed with precipitation statistics from the 12 benchmark cases. With Kuo, it is found that implicit precipitation is produced over areas as large as (and even larger than) that associated with grid-scale precipitation; it is also shown that with this configuration most of the precipitation occurs at weak rates and is mainly produced by the implicit scheme. The results with FC are more realistic, in the sense that convective precipitation only covers a small fraction of the model domain (i.e., 1%–2%) and that both precipitation schemes are dominant in their respective areas, that is, weak precipitation for the explicit scheme and more intense precipitation for the implicit scheme.

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Jean Côté
,
Sylvie Gravel
,
André Méthot
,
Alain Patoine
,
Michel Roch
, and
Andrew Staniforth

Abstract

An integrated forecasting and data assimilation system has been and is continuing to be developed by the Meteorological Research Branch (MRB) in partnership with the Canadian Meteorological Centre (CMC) of Environment Canada. Part I of this two-part paper motivates the development of the new system, summarizes various considerations taken into its design, and describes its main characteristics.

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Jean Côté
,
Jean-Guy Desmarais
,
Sylvie Gravel
,
André Méthot
,
Alain Patoine
,
Michel Roch
, and
Andrew Staniforth

Abstract

An integrated forecasting and data assimilation system has been and is continuing to be developed by the Meteorological Research Branch (MRB) in partnership with the Canadian Meteorological Centre (CMC) of Environment Canada. Part II of this two-part paper presents the objective and subjective evaluations of the intercomparison process that led to the operational implementation of the new Global Environmental Multiscale model. The results of a “proof of concept” experiment and those of a meso-γ-scale simulation further demonstrate the validity and versatility of this model.

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Ron McTaggart-Cowan
,
Leo Separovic
,
Martin Charron
,
Xingxiu Deng
,
Normand Gagnon
,
Pieter L. Houtekamer
, and
Alain Patoine

Abstract

The ability of a stochastically perturbed parameterization (SPP) approach to represent uncertainties in the model component of the Canadian Global Ensemble Prediction System was demonstrated in Part I of this investigation. The goal of this second step in SPP evaluation is to determine whether the scheme represents a viable alternative to the current operational combination of a multiphysics configuration and stochastically perturbed parameterization tendencies (SPPT). An assessment of the impact of each model uncertainty estimate in isolation reveals that, although the multiphysics configuration is highly effective at generating ensemble spread, it is often the result of differing biases rather than a reflection of flow-dependent error growth. Moreover, some of the members of the multiphysics ensemble suffer from large errors on regional scales as a result of suboptimal configurations. The SPP scheme generates a greater diversity of member solutions than the SPPT scheme in isolation, and it has an impact on forecast performance that is similar to that of current operational uncertainty estimates. When the SPP framework is combined with recent upgrades to the model physics suite that are only applicable in the stochastic perturbation context, the quality of global ensemble guidance is significantly improved.

Significance Statement

The stochastically perturbed parameterization (SPP) technique was introduced in Part I to represent model uncertainties in forecasts generated by an operational global ensemble prediction system. We focus here on the viability of this technique as a replacement for the system’s current uncertainty estimates: multiphysics and stochastic perturbations of physics tendencies. Despite the practical success of this combination, it suffers from physical inconsistencies and poor conservation properties. The adoption of SPP allows the ensemble to benefit from a recent set of model updates that couple with this new representation of model uncertainty to yield significant improvements in the quality of forecasts generated by the system.

Open access
Claude Girard
,
André Plante
,
Michel Desgagné
,
Ron McTaggart-Cowan
,
Jean Côté
,
Martin Charron
,
Sylvie Gravel
,
Vivian Lee
,
Alain Patoine
,
Abdessamad Qaddouri
,
Michel Roch
,
Lubos Spacek
,
Monique Tanguay
,
Paul A. Vaillancourt
, and
Ayrton Zadra

Abstract

The Global Environmental Multiscale (GEM) model is the Canadian atmospheric model used for meteorological forecasting at all scales. A limited-area version now also exists. It is a gridpoint model with an implicit semi-Lagrangian iterative space–time integration scheme. In the “horizontal,” the equations are written in spherical coordinates with the traditional shallow atmosphere approximations and are discretized on an Arakawa C grid. In the “vertical,” the equations were originally defined using a hydrostatic-pressure coordinate and discretized on a regular (unstaggered) grid, a configuration found to be particularly susceptible to noise. Among the possible alternatives, the Charney–Phillips grid, with its unique characteristics, and, as the vertical coordinate, log-hydrostatic pressure are adopted. In this paper, an attempt is made to justify these two choices on theoretical grounds. The resulting equations and their vertical discretization are described and the solution method of what is forming the new dynamical core of GEM is presented, focusing on these two aspects.

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