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Estimation of Wet Variable's Background Error Information for Regional Model

机译:区域模型中湿变量背景误差信息的估计

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In order to improve the humidity analysis of the WRF model, a new multivariable balance constraint scheme has been introduced to estimate wet variable's background error information from a series of historical forecasts. The new scheme consists of three critical procedures: physical transformation, vertical transformation and horizontal transformation. By removing the balanced part associated with other control variables, the unbalanced part of relative humidity is used as the new wet control variable. Statistical results show that relative humidity's background error structure appears an obviously localized characterization, which has a large negative value on model high level in the vertical direction and a stable characteristic length scales about 20km in the horizontal direction.
机译:为了改善WRF模型的湿度分析,引入了一种新的多变量平衡约束方案,以根据一系列历史预测估算湿变量的背景误差信息。新方案包括三个关键过程:物理变换,垂直变换和水平变换。通过删除与其他控制变量关联的平衡部分,相对湿度的不平衡部分将用作新的湿控制变量。统计结果表明,相对湿度的背景误差结构表现出明显的局部特征,在高模型垂直方向上具有较大的负值,在水平方向上具有约20km的稳定特征长度尺度。

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