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Global TEC maps based on GNNS data: 2. Model evaluation

机译:全球卫星系统数据进行基于TEC地图:2。评价

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The present paper presents a detailed statistical evaluation of the global empirical background TEC model built by using the CODE TEC data for full 13 years, 1999-2011, and described in Part 1. It has been found that the empirical probability density distribution resembles more the Laplace than the Gaussian distribution. A further insight into the nature and sources of the model's error variable led up to building of a new error model. It has been constructed by using a similar approach to that of the background TEC model. The spatial-temporal variability of the RMSE (root mean squares error) is presented as a multiplication of three separable functions which describe solar cycle, seasonal and LT dependences. The error model contains 486 constants that have been determined by least squares fitting techniques. The overall standard deviation of the predicted RMSE with respect to the empirical one is 0.7 TECU. The error model could offer a prediction approach on the basis of which the RMSE depending on the solar activity, season and LT is predicted.
机译:本文提出了一个详细的统计评估全球经验背景侦探模型由使用TEC数据的代码13年,1999 - 2011,第1部分中描述。已经发现,经验概率密度分布类似于拉普拉斯高斯分布。模型的性质和来源的错误变量导致建立一个新的误差模型。由使用一个类似的TEC背景模型的方法。RMSE(根的时空变异性作为一个展示了平均平方误差)三个可分离函数的乘法描述太阳活动周期,季节性和LT依赖性。常数决定的二乘拟合技术。RMSE对预测的偏差经验是0.7特。可以提供一个预测方法的基础上的RMSE取决于太阳活动,季节和LT预计。

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