The influence of erroneous background, beam-blocking and microphysical non-linearity on the application of a four-dimensional variational Doppler radar data assimilation system for quantitative precipitation forecasts

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题名:	The influence of erroneous background, beam-blocking and microphysical non-linearity on the application of a four-dimensional variational Doppler radar data assimilation system for quantitative precipitation forecasts
作者:	廖宇慶;Chang, Shao‐Fan;Sun, Juanzhen;Liou, Yu‐Chieng;Tai, Sheng‐Lun;Yang, Ching‐Yu
贡献者:	地球科學學院大氣科學學系
关键词:	Data assimilation;Data collection;Doppler radar;forecasting;Mathematical models;Meteorology;modelling;Radar;Rain;remote sensing;Weather forecasting
日期:	2014-01-01
上传时间:	2026-04-21 13:53:46 (UTC+8)
出版者:	Wiley-Blackwell;Chichester, UK: Wiley
摘要:	摘要： A series of observation system simulation experiments (OSSEs) and a real case study are conducted to investigate the application of the Doppler radar data assimilation technique for numerical model quantitative precipitation forecasts (QPFs). A four‐dimensional variational Doppler radar analysis system (VDRAS) is adopted for all experiments. The first set of OSSEs demonstrates that when the background field contains the imperfect information predicted from a mesoscale model, the incorrect convective‐scale perturbations in the background can result in spurious scattered precipitation. However, a smoothing procedure can be used to remove the fine structures from the primitive model output in order to avoid this over‐prediction. Results from the second set of OSSEs indicate that the lack of low‐elevation data owing to radar scan and/or beam blockage could significantly alter the retrieved low‐level thermal and dynamical structures when a different number of data assimilation cycles is applied. These impacts could lower the rainfall forecast capability of the model. The third set of OSSEs shows that, when the rainwater is assimilated over a long assimilation window, the non‐linearity embedded in the microphysical process could lead the minimization algorithm in a wrong direction, causing a further degradation of the rainfall prediction. However, using multiple short assimilation cycles produces better minimization and forecast results than those obtained with a single long cycle. A real case experiment based on data collected during Intensive Operation Period (IOP) #8 of the 2008 Southwest Monsoon Experiment (SoWMEX) is conducted to provide a verification of the conclusions obtained from OSSEs under a realistic framework. 出版者： Chichester, UK: Wiley 出版日期： 2014-04 出處： Meteorological Applications, 2014-04, Vol.21 (2), p.444-458 資源來源： Alma/SFX Local Collection 版權： 2014 Royal Meteorological Society 版權： Copyright © 2014 Royal Meteorological Society 識別號： ISSN: 1350-4827 識別號： EISSN: 1469-8080 識別號： DOI: 10.1002/met.1439
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