...
首页> 外文期刊>Quarterly Journal of the Royal Meteorological Society >A simplified bi-dimensional variational analysis of soil moisture from screen-level observations in a mesoscale numerical weather-prediction model
【24h】

A simplified bi-dimensional variational analysis of soil moisture from screen-level observations in a mesoscale numerical weather-prediction model

机译:中尺度数值天气预报模型中基于屏幕水平观测的土壤水分的简化二维变分分析

获取原文
获取原文并翻译 | 示例
           

摘要

The analysis of soil moisture for the initialization of a mesoscale numerical weather-prediction (NWP) model is considered subject to operational constraints, both in terms of computational cost and data availability. A variational technique is used t o analyse the soil moisture by assimilating screen-level observations of temperature and relative humidity. We consider a simplified bi-dimensional (z and t) variational approach (simplified 2D-VAR), where the estimate of the observation operator is obta ined from extra integration(s) of the numerical model. The fundamental assumptions of the method are first evaluated: linearity of the observation operator, horizontal decoupling between grid points, and truncation of the control variable space (variable decoupling), that allow the simplified 2D formalism. Thus, the variational method is applied at each grid point separately and the gain matrix is computed from finite differences given the small dimension involved. The 2D-VAR technique keeps count of th e full physics of the model, so the corrections applied to the control variable are adapted to the current meteorological conditions and the grid-point characteristics (texture and vegetation), as well as to the previous soil state. The linear estimate o f the observation operator is studied in detail to optimize its evaluation. The validation of the method is shown with simulated observations, and the assimilation of real observations is performed with different time-windows. A sequential assimilation c ycle on a 6-hour time-window allows the comparison with the optimum interpolation technique, while a 24-hour window is considered to extend the temporal consistency of the assimilated observations in the analysis. Results from the performed analyses with the simplified 2D-VAR method show a good retrieval of soil moisture, and a comparison with other initialization methods is also provided.
机译:在计算成本和数据可用性方面,为中尺度数值天气预报(NWP)模型初始化而进行的土壤水分分析被认为受到操作限制。通过吸收屏幕级别的温度和相对湿度观测值,采用变分技术来分析土壤湿度。我们考虑一种简化的二维(z和t)变分方法(简化的2D-VAR),其中观测算子的估计值与数值模型的额外积分无关。首先评估该方法的基本假设:观察算子的线性,网格点之间的水平去耦以及控制变量空间的截断(变量去耦),从而可以简化2D形式。因此,将变分方法分别应用于每个网格点,并在涉及到较小尺寸的情况下,通过有限差分计算增益矩阵。 2D-VAR技术保留了模型的全部物理信息,因此应用于控制变量的校正适应于当前的气象条件和格点特征(纹理和植被)以及先前的土壤州。对观察算子的线性估计进行了详细研究,以优化其评估。模拟的观测结果表明了该方法的有效性,而真实观测的同化则是在不同的时间窗口内进行的。在6小时的时间窗口上的顺序同化循环可以与最佳插值技术进行比较,而24小时的窗口被认为可以扩展分析中同化观测的时间一致性。使用简化的2D-VAR方法进行的分析结果表明,土壤水分的恢复效果很好,并且还与其他初始化方法进行了比较。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号