首页> 外文期刊>Tellus, Series A. Dynamic meteorology & oceanography >Towards assimilation of wind profile observations in the atmospheric boundary layer with a sub-kilometre-scale ensemble data assimilation system
【24h】

Towards assimilation of wind profile observations in the atmospheric boundary layer with a sub-kilometre-scale ensemble data assimilation system

机译:通过亚千米级集合数据同化系统同化大气边界层中的风剖面观测

获取原文
           

摘要

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.
机译:表面附近的风力分布观测很少被同化为数字天气预报模型。用于风剖面观测的越来越多的地面遥感装置用于使曲线沿着风力涡轮机的轮毂高度。然而,LiDar样风轮廓测量对大气边界层中数据同化的观察影响是未知的。我们在这里展示了边界层风力测量对汉堡大都市区的亚千米级数据同化系统的观测影响。该数据同化系统基于公正级集合数据同化系统和小型建模模型的联盟。在三种稳定分层的测试用例中,我们对风谱观测的阳性观察对速度分析和预测进行了阳性观察影响。风速的分析改进繁殖以在三种情况下预测时间的温度提高。与由于风剖面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平均绝对增量的少量。因此,大气边界层中的风剖面观测因此对小尺度进行数据同化的有价值信息。

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