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In the present paper, a 5-yr baseline integration for the period 1987–91 was carried out over a Pan-Canadian domain to validate the performance of the third-generation Canadian Regional Climate Model (CRCM). The CRCM simulated the large-scale circulation over North America well; it also correctly captured the seasonal variability of surface temperature and reproduced the winter precipitation over North America realistically. However, the CRCM systematically overestimated the summer precipitation over the continent when compared with the observed values. Extensive experiments have been conducted to trace down the sources of error of summer precipitation. Particular attention has been given to the water-vapor-related physical parameterization processes such as the mass flux convection scheme in the CRCM. Experiments involving spectral nudging of the specific humidity toward the values of large-scale driving data enabled the authors to link overestimation with abundant water vapor accumulated in the lower boundary layer resulting from an excessive amount of moisture stored in the soil. A strong boundary layer mixing process from the third generation of the Canadian Atmospheric General Circulation Model was then implemented into the CRCM along with an adjustment to the soil water holding capacity. A final analysis of a 14-month experiment showed that these modifications significantly improved the simulation of summer precipitation over North America without adversely affecting the simulation of winter precipitation. [ABSTRACT FROM AUTHOR]

Advanced operational four-dimensional variational data assimilation (4DVAR) schemes include a linearized version of moist convective parameterization and its adjoint. At the Meteorological Service of Canada, work is underway to implement 4DVAR for both global and regional operational data assimilation. Moreover, the Kain– Fritsch moist convective parameterization scheme is currently under operational testing for global and regional weather forecasting. Consequently, tangent linear and adjoint versions of this convective scheme have been developed. Sources of nonlinearities and accuracy of the tangent linear approximation of the convective scheme itself were examined. The procedure to test this latter aspect uses Monte Carlo simulations based on background error covariances from the operational three-dimensional variational data assimilation (3DVAR) system at the Canadian Meteorological Centre. It is shown that for a critical level of amplitudes of vertical perturbations of temperature or moisture greater than typically 0.1 K or 0.1 g kg-1, the tangent linear approximation becomes inaccurate (e.g., typical perturbation response having the wrong sign and amplitude errors larger than 100%). For such perturbation amplitudes, there is a rapid increase of convective points where the tangent linear convective approximation is very strongly in error. Deactivation of the Kain–Fritsch scheme becomes frequent and a significant source of invalid tangent linear approximation for input perturbations exceeding typically 0.3 K or 0.3 g kg-1. Potential implications of this study for linearized moist convection in the context of 4DVAR and moist singular vector computation are discussed. [ABSTRACT FROM AUTHOR]