A moisture‐incrementing operator for the assimilation of humidity‐ and cloud‐sensitive observations: formulation and preliminary results
A moisture‐incrementing operator for the assimilation of humidity‐ and cloud‐sensitive observations: formulation and preliminary results
复制标题
用于同化湿度和云敏感观测的湿度增量算子：公式和初步结果
DOI：
10.1002/qj.3216
复制
发表时间：
2018
影响因子：
8.9
通讯作者：
Bell, William
中科院分区：
文献类型：
--
作者：
Migliorini, Stefano;Lorenc, Andrew C.;Bell, William
能够同化受云和降水影响的卫星辐射是气象局的一个关键目标，因为它有望在全球范围内和英国各地的气象重要位置提供预报技能的改进。目前用于数据同化成本函数最小化的“控制”变量集包括一个单一的湿度变量，该变量考虑了由湿度敏感观测引起的总水分（即来自其所有阶段）增量。控制变量定义了一个总的水增量，它由一个适当设计的操作器划分为特定的湿度和云（液态或冻结）水增量，以添加到预报模型的短期预测中。在最小化过程中，这些递增的值被拟合到观测值，并用于开始下一次预报。本文讨论了一种新的增湿算子的设计和初步试验，该算子具有以下特点：（i）它与扰动预报（PF）模式状态线性相关;（ii）它的物理基础公式与PF模式中的云方案一致;和（iii）它经过统计学训练，以拟合来自气象局全球和区域包围预测系统（MOGREPS）的云水扰动，当操作员也从MOGREPS获得特定湿度和温度扰动时。本文中描述的增湿算子公式与气象中心有关，这些气象中心（计划）利用线性依赖于总（即蒸汽加云）水数据同化增量的湿度控制变量。新运营商的初步验证结果显示了中性影响，主要来自热带地区风力预测的变化。未来的工作将测试新的湿度增加算子的性能，包括云影响的微波辐射的一组观测。
Being able to assimilate satellite radiances that are affected by cloud and precipitation is a key goal for the Met Office, as it is expected to provide improvements to forecast skill both at global scale and over the UK, at locations that are meteorologically important. The set of ‘control’ variables currently used for the minimization of the data assimilation cost function includes a single moist variable that accounts for total water (i.e. from all its phases) increments arising from moisture‐sensitive observations. The control variable defines a total water increment, which is partitioned by a suitably designed operator into specific humidity and cloud (liquid or frozen) water increments to be added to the forecast model's short‐range predictions. These incremented values are fitted to the observations during the minimization procedure and used to start the next forecast. This article discusses the design and initial testing of a new moisture‐incrementing operator with the following characteristics: (i) it is linearly related to the perturbation forecast (PF) model state; (ii) its physically based formulation is consistent with that of the cloud scheme operating within the PF model; and (iii) it is trained statistically to fit cloud‐water perturbations from the Met Office Global and Regional Ensemble Prediction System (MOGREPS), when the operator is fed with specific humidity and temperature perturbations also from MOGREPS. The moisture‐incrementing operator's formulation described in this article is relevant to meteorological centres that (plan to) make use of moist control variables that are linearly dependent on total (i.e. vapour plus cloud) water data‐assimilation increments. The initial validation results of the new operator show a neutral impact, arising mostly from changes in wind forecasts in the Tropics. Future work will test the performance of the new moisture‐incrementing operator with a set of observations that include cloud‐affected microwave radiances.
大型模型云方案的行为低于理想的强迫场景
影响因子：
8.9
作者：
Damian R. Wilson;D. Gregory
通讯作者：
D. Gregory
使用非相切线性模型研究增量 4D-Var
影响因子：
8.9
作者：
A. Lawless;S. Gratton;N. Nichols
通讯作者：
N. Nichols
影响因子：
8.9
作者：
N. Ingleby;A. Lorenc;King Ngi Ngan;F. Rawlins;D. Jackson
通讯作者：
D. Jackson