关于表示太阳极紫外辐照度的广义加法模型

IF 3.7 2区 地球科学 Space Weather Pub Date : 2024-03-12 DOI:10.1029/2023sw003680
Daniel A. Brandt, Erick F. Vega, Aaron J. Ridley
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引用次数: 0

摘要

在空间天气预报方面,需要在多个时间尺度上对太阳极紫外辐照度进行说明,并进行相关的不确定性量化,以确定下游参数的准确性。辐照度的经验模型通常依赖于多个波段的辐照度与各种太阳指数之间的参数拟合。我们在这些经验模型的基础上,使用广义相加模型(GAM)来表示太阳辐照度。我们分两步应用 GAM 方法:(a) 在 FISM2 辐照度和太阳指数 F10.7、修订太阳黑子数以及莱曼-α 太阳指数之间拟合一个 GAM。(b) 根据 FISM2 辐照度拟合第二个 GAM,以模拟第一个 GAM 的残差。在太阳周期 24 期间,我们使用已知太阳指数驱动的 GAM 和使用自回归建模方法提前 3 天预测的 GAM 评估了这种方法的性能。我们证明了性能对太阳周期和季节的依赖可以忽略不计,我们还评估了 GAM 方法在不同波长上的功效。
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On Generalized Additive Models for Representation of Solar EUV Irradiance
In the context of space weather forecasting, solar EUV irradiance specification is needed on multiple time scales, with associated uncertainty quantification for determining the accuracy of downstream parameters. Empirical models of irradiance often rely on parametric fits between irradiance in several bands and various solar indices. We build upon these empirical models by using Generalized Additive Models (GAMs) to represent solar irradiance. We apply the GAM approach in two steps: (a) A GAM is fitted between FISM2 irradiance and solar indices F10.7, Revised Sunspot Number, and the Lyman-α solar index. (b) A second GAM is fit to model the residuals of the first GAM with respect to FISM2 irradiance. We evaluate the performance of this approach during Solar Cycle 24 using GAMs driven by known solar indices as well as those forecasted 3 days ahead with an autoregressive modeling approach. We demonstrate negligible dependence of performance on solar cycle and season, and we assess the efficacy of the GAM approach across different wavelengths.
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