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Atmosphere Data Assimilation System for the Siberian Region with the WRF-ARW Model and Three-dimensional Variational Analysis WRF 3D-Var

机译:WRF-ARW模型和三维变分分析WRF 3D-Var用于西伯利亚地区的大气数据同化系统

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摘要

The system of the cyclic assimilation of data on atmospheric conditions used in the West Siberian Administration for Hydrometeorology and Environmental Monitoring is described. It is based on the WRF-ARW mesoscale atmospheric model and on the WRF 3D-Var system of the three-dimensional variational analysis of data. The system is verified when the first approximation data (6-hour forecast) and WRF-ARW forecasts with the lead time up to 24 hours are compared with the observational data. The problems of assimilation of observations from the AMSU-A and AIRS satellite instruments are considered. The effect of using AMSU-A and AIRS for the analysis in the Novosibirsk region is estimated. The experiments demonstrated that the cyclic data assimilation system operates successfully. The AMSU-A observations improve the quality of analyses and forecasts in winter. In summer the impact of satellite observations on the forecast skill scores is ambiguous. Good short-term forecasts are provided by the initial conditions obtained using the system of detailing of the NCEP large-scale analysis.
机译:描述了西伯利亚水文气象和环境管理局所使用的大气状况数据的循环同化系统。它基于WRF-ARW中尺度大气模型和WRF 3D-Var系统的三维数据变分分析。将最初的近似数据(6小时预报)和交货时间最长为24小时的WRF-ARW预报与观测数据进行比较,即可验证系统。考虑了来自AMSU-A和AIRS卫星仪器的观测的同化问题。估计在新西伯利亚地区使用AMSU-A和AIRS进行分析的效果。实验表明,循环数据同化系统可以成功运行。 AMSU-A观测提高了冬季分析和预报的质量。在夏季,卫星观测对预测技能得分的影响是模棱两可的。使用NCEP大规模分析详细系统获得的初始条件可以提供良好的短期预测。

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