The Operational CMC–MRB Global Environmental Multiscale (GEM) Model. Part II: Results

Jean Côté Meteorological Research Branch, Atmospheric Environment Service, Dorval, Quebec, Canada

Search for other papers by Jean Côté in
Current site
Google Scholar
PubMed
Close
,
Jean-Guy Desmarais Canadian Meteorological Centre, Atmospheric Environment Service, Dorval, Quebec, Canada

Search for other papers by Jean-Guy Desmarais in
Current site
Google Scholar
PubMed
Close
,
Sylvie Gravel Meteorological Research Branch, Atmospheric Environment Service, Dorval, Quebec, Canada

Search for other papers by Sylvie Gravel in
Current site
Google Scholar
PubMed
Close
,
André Méthot Canadian Meteorological Centre, Atmospheric Environment Service, Dorval, Quebec, Canada

Search for other papers by André Méthot in
Current site
Google Scholar
PubMed
Close
,
Alain Patoine Canadian Meteorological Centre, Atmospheric Environment Service, Dorval, Quebec, Canada

Search for other papers by Alain Patoine in
Current site
Google Scholar
PubMed
Close
,
Michel Roch Meteorological Research Branch, Atmospheric Environment Service, Dorval, Quebec, Canada

Search for other papers by Michel Roch in
Current site
Google Scholar
PubMed
Close
, and
Andrew Staniforth Meteorological Research Branch, Atmospheric Environment Service, Dorval, Quebec, Canada

Search for other papers by Andrew Staniforth in
Current site
Google Scholar
PubMed
Close
Restricted access

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.

Corresponding author address: Dr. Jean Côté, Recherche en Prévision Numérique, 2121 Route Transcanadienne, Dorval, PQ H9P 1J3, Canada.

Email: jean.cote@ec.gc.ca

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.

Corresponding author address: Dr. Jean Côté, Recherche en Prévision Numérique, 2121 Route Transcanadienne, Dorval, PQ H9P 1J3, Canada.

Email: jean.cote@ec.gc.ca

Save
  • Benoit, R., M. Desgagné, P. Pellerin, S. Pellerin, Y. Chartier, and S. Desjardins, 1997: The Canadian MC2: A semi-Lagrangian, semi-implicit wideband atmospheric model suited for finescale process studies and simulation. Mon. Wea. Rev.,125, 2382–2415.

  • Chouinard, C., J. Mailhot, H. L. Mitchell, A. Staniforth, and R. Hogue, 1994: The Canadian regional data assimilation system: Operational and research applications. Mon. Wea. Rev.,122, 1306–1325.

  • Côté, J., M. Roch, A. Staniforth, and L. Fillion, 1993: A variable-resolution semi-Lagrangian finite-element global model of the shallow-water equations. Mon. Wea. Rev.,121, 231–243.

  • ——, S. Gravel, A. Méthot, A. Patoine, M. Roch, and A. Staniforth, 1997: Preliminary results from a dry global variable-resolution primitive equations model. The André J. Robert Memorial Volume, C. Lin, R. Laprise, H. Ritchie, Eds., Canadian Meteorological and Oceanographic Society, 245–259.

  • ——, ——, ——, ——, ——, and ——, 1998: The operational CMC–MRB Global Environmental Multiscale (GEM) model: Part I. Design considerations and formulation. Mon. Wea. Rev.,126, 1373–1395.

  • Fillion, L., H. L. Mitchell, H. Ritchie, and A. Staniforth, 1995: The impact of a digital filter finalization technique in a global data assimilation system. Tellus,47A, 304–323.

  • Mailhot, J., R. Sarrazin, B. Bilodeau, N. Brunet, and G. Pellerin, 1997: Development of the 35-km version of the operational regional forecast system. Atmos.Ocean,35, 1–28.

  • ——, ——, ——, ——, A. Méthot, G. Pellerin, C. Chouinard, L. Garand, C. Girard, and R. Hogue, 1995: Changes to the Canadian regional forecast system: description and evaluation of the 50-km version. Atmos.Ocean,33, 55–80.

  • Mitchell, H. L., C. Chouinard, C. Charette, R. Hogue, and S. J. Lambert, 1996: Impact of a revised analysis algorithm on an operational data assimilation system. Mon. Wea. Rev.,124, 1243–1255.

  • Rabier, F., A. McNally, E. Andersson, P. Courtier, P. Unden, J. Eyre, A. Hollingsworth, and F. Bouttier, 1998: The ECMWF implementation of three dimensional variational (3D-Var). Part II: Structure functions. Quart. J. Roy. Meteor. Soc., in press.

  • Ritchie, H., and C. Beaudoin, 1994: Approximations and sensitivity experiments with a baroclinic semi-Lagrangian spectral model. Mon. Wea. Rev.,122, 2391–2399.

  • Staniforth, A., 1997: Regional modeling: A theoretical discussion. Meteor. Atmos. Phys.,63, 15–29.

  • Verret, R., 1987: Development of a “perfect prog” system to forecast probability of precipitation and sky cover. CMC Tech. Doc. 29, 28 pp. [Available from the Canadian Meteorological Center, Dorval, PQ H9P 1J3, Canada.].

  • WMO, 1998: Weather reporting. WMO Publ. 9, Vol. A. [Availablefrom WMO, Case Postale 2300, CH-1211 Geneva 2, Switzerland;or online from http://www.wmo.ch/web/ddbs/publicat.html.].

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 838 218 17
PDF Downloads 421 124 10