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首页> 外文期刊>Monthly Weather Review >Jet Stream Analysis and Forecast Errors Using GADS Aircraft Observations in the DAO, ECMWF, and NCEP Models
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Jet Stream Analysis and Forecast Errors Using GADS Aircraft Observations in the DAO, ECMWF, and NCEP Models

机译:在DAO,ECMWF和NCEP模型中使用GADS飞机观测数据进行射流分析和预测误差

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Peak analyzed jet stream wind speeds are compared with independent aircraft observations over Canada and the continental United States. The results permit a study of the accuracy of analyzed jet streak strength for the data-sparse 85% of the earth's surface versus the data-dense 15%. The observations come from the Global Aircraft Data Set (GADS) experiment, which since 1996 has collected flight data recorder information from every flight of 56 British Airways 747-400 aircraft. The study is timely because automated aircraft observations are reaching their near-asymptotic limits (there are not many uncovered commercial aircraft routes left), and we are about to enter a new, third-generation, satellite-sounding-instrument era. Future reanalyses will mix time periods from both eras. This study gives an estimate of the analysis accuracy of data assimilation using second-generation satellite systems. The results show that major current generation assimilation models have peak wind speed errors of -5% to -9% over data-sparse Canada compared with -2% to -5% over the data-dense continental United States. When these additional aircraft observations are assimilated as a part of the normal observational input data stream, a small but statistically significant improvement is shown for 1-month forecast experiments over two consecutive winters.
机译:将峰值分析的射流风速与加拿大和美国大陆上的独立飞机观测结果进行比较。结果允许对数据稀疏的85%的地球表面与数据密集的15%的分析的喷射条纹强度的准确性进行研究。这些观测结果来自全球飞机数据集(GADS)实验,该实验自1996年以来就从56架英国航空公司747-400飞机的每次飞行中收集了飞行数据记录器信息。这项研究是及时的,因为自动飞机观测已接近其渐近极限(几乎没有发现未发现的商用飞机路线),而且我们即将进入一个新的第三代卫星探测仪器时代。未来的重新分析将混合两个时代的时间段。这项研究估计了使用第二代卫星系统进行数据同化的分析准确性。结果表明,主要的当代同化模型在数据稀疏的加拿大的峰值风速误差为-5%至-9%,而在数据密集的美国大陆的峰值为-2%至-5%。当将这些额外的飞机观测结果作为正常观测输入数据流的一部分进行吸收时,对于连续两个冬季的1个月预报实验显示出很小但具有统计学意义的改进。

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