Doppler radar radial winds in HIRLAM. Part II: optimizing the super-observation processing
Doppler radar radial winds in HIRLAM. Part II: optimizing the super-observation processing
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DOI：
10.1111/j.1600-0870.2008.00381.x
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发表时间：
2009-01
期刊：
影响因子：
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通讯作者：
K. Salonen;H. Järvinen;Günther Haase;S. Niemelä;R. Eresmaa
中科院分区：
文献类型：
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作者：
K. Salonen;H. Järvinen;Günther Haase;S. Niemelä;R. Eresmaa
摘要多普勒雷达径向风观测在数值天气预报中的模拟误差主要包括仪器误差、模拟误差和代表性误差。系统和随机建模误差可以通过仔细设计观测算子（第一部分）来减少。随机仪器误差和代表性误差的影响可以通过优化所谓的超级观测（原始测量的空间平均值;第二部分）的处理来减少。本文通过实验优化了超观测处理，确定了不同分辨率下超观测的最佳分辨率。使用HIRLAM数据同化和预报系统进行为期1个月的实验，用于径向风数据监测和产生观测减去背景（OMB）差异。OMB统计量表明，超观测处理降低了径向风速OMB差的标准差，而平均矢量风速OMB差有增大的趋势。最佳参数设置对应于50 km（100 km）的测量范围和1.7 km 2（7.3 km 2）的平均面积。总之，一个准确的和计算上可行的观测算子多普勒雷达径向风观测（第一部分）和超级观测处理系统进行了优化（第二部分）。
Abstract Doppler radar radial wind observations are modelled in numerical weather prediction (NWP) within observation errors which consist of instrumental, modelling and representativeness errors. The systematic and random modelling errors can be reduced through a careful design of the observation operator (Part I). The impact of the random instrumental and representativeness errors can be decreased by optimizing the processing of the so-called super-observations (spatial averages of raw measurements; Part II). The super-observation processing is experimentally optimized in this article by determining the optimal resolution for the super-observations for differentNWPmodel resolutions. A 1-month experiment with the HIRLAM data assimilation and forecasting system is used for radial wind data monitoring and for generating observation minus background (OmB) differences. The OmB statistics indicate that the super-observation processing reduces the standard deviation of the radial wind speedOmBdifference, while themean vectorwindOmBdifference tends to increase. The optimal parameter settings correspond at a measurement range of 50 km (100 km) to an averaging area of 1.7 km2 (7.3 km2). In conclusion, an accurate and computationally feasible observation operator for the Doppler radar radial wind observations is developed (Part I) and a super-observation processing system is optimized (Part II).