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Towards assimilation of wind profile observations in the atmospheric boundary layer with a sub-kilometre-scale ensemble data assimilation system
Tellus A: Dynamic Meteorology and Oceanography ( IF 2.247 ) Pub Date : 2020-01-01 , DOI: 10.1080/16000870.2020.1764307
Tobias Sebastian Finn 1, 2, 3 , Gernot Geppert 4, 5 , Felix Ament 1, 6
Affiliation  

Abstract Wind profile observations near the surface are rarely assimilated into numerical weather prediction models. More and more ground-based remote sensing devices for wind profile observations are used to get profiles up to the hub height of wind turbines. However, an observation impact of LiDAR-like wind profile measurements on data assimilation in the atmospheric boundary layer is unknown. We show here the observation impact of boundary layer wind profile measurements on a sub-kilometre-scale data assimilation system for the metropolitan area of Hamburg. This data assimilation system is based on the Kilometre-scale ENsemble Data Assimilation system and the COnsortium for Small-scale MOdelling model. In three stably stratified test cases, we show a positive observation impact of wind profile observations on wind speed in analyses and for forecasts. The analysis improvements in wind speed are propagated to improvements in temperature at forecast time in two of three cases. Additional assimilation of temperature and relative humidity increases the mean absolute increments only by a small amount compared to increments due to wind profile observations. Wind profile observations in the atmospheric boundary layer have therefore valuable information for data assimilation on small scales.

中文翻译:

利用亚千米级集合数据同化系统同化大气边界层中的风廓线观测

摘要 地表附近的风廓线观测很少被同化到数值天气预报模型中。越来越多的用于风廓线观测的地基遥感设备被用于获取风轮机轮毂高度的廓线。然而,类似 LiDAR 的风廓线测量对大气边界层数据同化的观测影响尚不清楚。我们在这里展示了边界层风廓线测量对汉堡大都市区亚公里级数据同化系统的观测影响。该数据同化系统基于公里尺度 ENsemble 数据同化系统和小规模建模模型联盟。在三个稳定分层的测试用例中,我们在分析和预测中展示了风廓线观测对风速的积极观测影响。在三种情况中的两种情况下,风速的分析改进会传播到预测时间的温度改进。与风廓线观测引起的增量相比,温度和相对湿度的额外同化仅增加了少量的平均绝对增量。因此,大气边界层中的风廓线观测对于小尺度数据同化具有有价值的信息。与风廓线观测引起的增量相比,温度和相对湿度的额外同化仅增加了少量的平均绝对增量。因此,大气边界层中的风廓线观测对于小尺度数据同化具有有价值的信息。与风廓线观测引起的增量相比,温度和相对湿度的额外同化仅增加了少量的平均绝对增量。因此,大气边界层中的风廓线观测对于小尺度数据同化具有有价值的信息。
更新日期:2020-01-01
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