Abstract

The summertime improvement resulting from the operational implementation of a new surface modeling and assimilation strategy into the Canadian regional weather forecasting system is described in this study. The surface processes over land are represented in this system using the Interactions between Soil–Biosphere–Atmosphere (ISBA) land surface scheme. Surface variables, including soil moisture, are initialized using a sequential assimilation technique in which model errors of low-level air temperature and relative humidity are used to determine analysis increments of surface variables. It was found that the magnitude and nature of the analysis increments applied to the surface variables depended on the surface and meteorological conditions observed in each region. In regions characterized by weak meteorological activity (i.e., no clouds or precipitation), model errors of low-level air characteristics are more likely to be related to an incorrect representation of surface processes due to either erroneous initial conditions or inaccurate parameterizations in the land surface scheme. In other regions characterized by more frequent and more intense precipitation events, surface corrections are mainly associated with inaccurate atmospheric forcing. Objective evaluation against observations from radiosondes and surface stations showed that the amplitude of the diurnal cycle of near-surface air temperature and humidity is larger with the new surface system, in better agreement with observations. This type of improvement was found to extend higher up in the boundary layer (up to 700 hPa) where cold and humid biases were significantly reduced by introducing the new surface system. The model precipitation was also found to be significantly influenced by the new representation of surface fluxes. The problematic increase of a positive bias in precipitation with integration time was found to be significantly reduced with the new system, due to the warmer and drier boundary layer.

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