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Analysis of applicability to build K-value model in southwest China

机译:西南西南部建立千千克价值模型的适用性分析

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Using the eleven Radiosonde Stations' data in southwestern of China from 2010 to 2013 to calculate the conversion coefficient K which is a reference value of Precipitable Water Vapor (PWV). Then build the EMARDSON model and the EMARDSON K model which introduced with elevation parameter and altitude. And to analysis the accuracy of the two models in the southwest China by radiosonde data in 2014. The results show: 1) The K value calculated by EMARDSON model has good adaptability in southwest region. 2) The method of spatial interpolation prediction by choosing 7 Radiosonde Stations' K value uniformity is more adaptable than using 11 Radiosonde Stations' K value to build basic model in the case of predicting 11 Radiosonde Stations' K value, and it has a certain accuracy when predicting by using spatial interpolation in some areas where lacking data. 3) The accuracy by using the A-EMARDSON model to predict K value was improved obviously. at the same time, when predicting K value by the method of spatial interpolation, both the precision of inner and the precision of outer are better than EMARDSON model. So it can be concluded that the altitude factor is an important factor to influence the K value prediction.
机译:在2010年至2013年,在中国西南部使用的十一射频电台数据以计算转换系数K,这是可降水水蒸气(PWV)的参考值。然后构建EMARDSON模型和带有高度参数和高度的emardson K模型。并在2014年通过无线电探测数据分析了中国西南两种模型的准确性。结果表明:1)Emardson模型计算的K值在西南地区具有良好的适应性。 2)通过选择7个无线电钻头站的空间插值预测方法比在预测11个无线电探测站的k值的情况下,更适应于在预测11个无线电电台站的情况下构建基本模型的基本模型更适应。它具有一定的准确性当在缺少数据的某些区域中使用空间插值时预测。 3)通过使用A-EMARDSON模型来预测k值的准确性显而易见。同时,当通过空间插值方法预测k值时,内部的精度和外部精度优于Emardson模型。因此,可以得出结论,高度因子是影响k值预测的重要因素。

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