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Estimation of wet variable's background error information for regional model

机译:湿变量的区域模型背景错误信息估算

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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:为了提高WRF模型的湿度分析,已经引入了一种新的多变量平衡约束方案来估计来自一系列历史预测的湿变量的背景错误信息。新方案由三个关键程序组成:物理转换,垂直变换和水平变换。通过去除与其他控制变量相关联的平衡部分,相对湿度的不平衡部分用作新的湿法控制变量。统计结果表明,相对湿度的背景误差结构看起来明显局部化表征,其在垂直方向上的模型高电平上具有大的负值,并且在水平方向上稳定的特征长度尺度约20km。

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