Gaoyuan qixiang (Dec 2022)
Blending Scheme with Mixed Truncation Scale and Its Application in Southwest Regional Model
Abstract
The complex and diverse topography of the southwest region generates disastrous weather systems with multi-scale characteristics, and fluctuation information of each scale affects the occurrence and development of the weather systems.In order to introduce the information from the background field of the global model in a timely and appropriate approach during the update cycle assimilation process, and to correct the bias of the regional model in the analysis and forecasting of large-scale waveform information, this paper takes the southwest region as the research background, setting the truncation scale of wind field and the truncation scale of temperature & humidity variables differently according to the length scale characteristics of different types of model variables.A blending scheme with mixed truncation scale is proposed, and a one-week continuous batch update cycle assimilation experiments and diagnostics of one case are carried out based on the southwest regional update cycle assimilation system.The results show that both the unified and mixed truncation scale blending schemes can reduce the analysis and forecast bias in the process of update cycle assimilation, while the mixed-truncation-scale blending scheme can further reduce the bias of regional background field by adopting different truncation scales for the dynamic, temperature, and humidity field, and introduce the global background field information that is more consistent with the scale characteristics of the dynamic, temperature, and humidity field, respectively.The continuous update cycle assimilation analysis and the accuracy of meteorological element forecasting are improved.In the analysis of precipitation case, the model shows significant precipitation misreporting and falling area bias in the steep topography area.The mixed truncation scale blending scheme can further reduce the false report rate of heavy precipitation, improve the forecast skill of precipitation magnitude and falling area, and increase the accuracy of precipitation forecast.
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