期刊名称：Journal of Advances in Modeling Earth Systems
电子版ISSN：1942-2466
出版年度：2019
卷号：11
期号：3
页码：752-770
DOI：10.1029/2018MS001546
出版社：John Wiley & Sons, Ltd.
摘要：To account for model error on multiple scales in convective‐scale data assimilation, we incorporate the small‐scale additive noise based on random samples of model truncation error and combine it with the large‐scale additive noise based on random samples from global climatological atmospheric background error covariance. A series of experiments have been executed in the framework of the operational Kilometre‐scale ENsemble Data Assimilation system of the Deutscher Wetterdienst for a 2‐week period with different types of synoptic forcing of convection (i.e., strong or weak forcing). It is shown that the combination of large‐ and small‐scale additive noise is better than the application of large‐scale noise only. The specific increase in the background ensemble spread during data assimilation enhances the quality of short‐term 6‐hr precipitation forecasts. The improvement is especially significant during the weak forcing period, since the small‐scale additive noise increases the small‐scale variability which may favor occurrence of convection. It is also shown that additional perturbation of vertical velocity can further advance the performance of combination.
关键词：additive noise;model truncation error;multiscale;radar data assimilation;probabilistic forecasts
