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Use of Four-Dimensional Data Assimilation in a Limited-Area Mesoscale Model Part2: Effects of Data Assimilation within the Planetary Boundary Layer

机译:在有限区域中尺度模型中使用四维数据同化第2部分:行星边界层内数据同化的影响

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A four-dimensional data assimilation (FDDA) scheme based on Newtonian relaxationor nudging has been developed and evaluated in the Pennsylvania State University/National Center for Atmospheric Research (PSU/NCAR) Limited-Area Mesoscale Model. It was shown in Part I of the study that continuous assimilation of standard-resolution rawinsonde observations throughout a model integration, rather than at only the initial time, can successfully limit large-scale model error growth (amplitude and phase errors) while the model maintains intervariable consistency and generates realistic mesoscale structures not resolved by the data. The purpose of the paper is to further refine the previously reported FDDA strategy used to produce 'dynamic analyses' of the atmosphere by investiating the effects of data assimilation within the planetary boundary layer (PBL). The data used for assimilation include conventional synoptic-scale rawinsonde data and mesoalpha-scale surface data. The main objective of the study is to determine how to effectively utilize the combined strength of these two simple data systems while avoiding their individual weaknesses. Ten experiments, which use a 15-layer version of the model, are evaluated for two midlatitude, real-data cases. (Copyright (c) 1991 American Meteorological Society.)

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