A local ensemble transform Kalman filter data assimilation system for the NCEP global model
A local ensemble transform Kalman filter data assimilation system for the NCEP global model
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DOI：
10.1111/j.1600-0870.2007.00274.x
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发表时间：
2008-01
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影响因子：
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通讯作者：
I. Szunyogh;E. Kostelich;G. Gyarmati;E. Kalnay;B. Hunt;E. Ott;Elizabeth A. Satterfield;J. Yorke
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文献类型：
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作者：
I. Szunyogh;E. Kostelich;G. Gyarmati;E. Kalnay;B. Hunt;E. Ott;Elizabeth A. Satterfield;J. Yorke
研究了在美国国家环境预报中心（NCEP）全球预报系统（GFS）2004年版模式组件上并行实现局部包络变换卡尔曼滤波（LETKF）同化方案的精度和计算效率。在模型分辨率T62 L28下进行了数值试验。除卫星辐射外，2004年NCEP业务同化的所有大气观测数据都被LETKF同化。LETKF分析的准确性进行了评估，通过比较它的光谱统计插值（SSI），这是业务的全球数据同化方案的NCEP在2004年。对于选定的一组观测数据，LETKF分析在南半球热带外地区比SSI分析更准确，在北方半球热带外地区和热带地区比SSI分析更准确。在3.6 GHz Xeon处理器的Beowulf集群上实现的计算挂钟时间使我们在NCEP GFS上实现的LETKF成为一个广泛适用的分析预测系统，特别是用于研究目的。例如，在NCAR-NCEP再分析（T62 L28）的分辨率下，使用40个处理器生成一个完整季节（90 d）的四个每日分析，所需的挂钟时间不到4 d。
The accuracy and computational efficiency of a parallel computer implementation of the Local Ensemble Transform Kalman Filter (LETKF) data assimilation scheme on the model component of the 2004 version of the Global Forecast System (GFS) of the National Centers for Environmental Prediction (NCEP) is investigated. Numerical experiments are carried out at model resolution T62L28. All atmospheric observations that were operationally assimilated by NCEP in 2004, except for satellite radiances, are assimilated with the LETKF. The accuracy of the LETKF analyses is evaluated by comparing it to that of the Spectral Statistical Interpolation (SSI), which was the operational global data assimilation scheme of NCEP in 2004. For the selected set of observations, the LETKF analyses are more accurate than the SSI analyses in the Southern Hemisphere extratropics and are comparably accurate in the Northern Hemisphere extratropics and in the Tropics. The computationalwall-clock times achieved on a Beowulf cluster of 3.6 GHz Xeon processors make our implementation of the LETKF on the NCEP GFS a widely applicable analysis-forecast system, especially for research purposes. For instance, the generation of four daily analyses at the resolution of the NCAR-NCEP reanalysis (T62L28) for a full season (90 d), using 40 processors, takes less than 4 d of wall-clock time.