Although the interplanetary magnetic field variability has been extensively investigated in situ by means of data coming from several space missions, the newly launched missions providing high-resolution measures and approaching the Sun, offer the possibility to study the multiscale variability in the innermost solar system. Here by means of the Parker Solar Probe measurements we investigate the scaling properties of solar wind magnetic field fluctuations at different heliocentric distances. The results show a clear transition at distances close to say 0.4 au. Closer to the Sun fluctuations show a f^-3/2 frequency power spectra and regular scaling properties, while for distances larger than 0.4 au fluctuations show a Kolmogorov spectrum f^-5/3 and are characterized by anomalous scalings. The observed statistical properties of turbulence suggests that the solar wind magnetic fluctuations, in the late stage far form the Sun, show a multifractal behaviour typical of turbulence and described through intermittency, while in the early stage, when leaving the solar corona, a breakdown of these properties are observed, thus showing a statistical monofractal global self-similarity. Physically the breakdown observed close to the Sun should be due either to a turbulence with regular statistics or to the presence of intense stochastic fluctuations able to cancel out correlations necessary for the presence of anomalous scaling.

中文翻译：

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穿过内日光层的磁场波动的标度特性

尽管已经通过来自多个太空任务的数据在原位广泛研究了行星际磁场变化，但新发射的提供高分辨率测量和接近太阳的任务为研究最内部太阳系的多尺度变化提供了可能性。在这里，通过帕克太阳探测器的测量，我们研究了不同日心距离处太阳风磁场波动的标度特性。结果显示在接近 0.4 au 的距离处有明显的转变。靠近太阳的波动显示 af^-3/2 频率功率谱和规则的缩放特性，而对于大于 0.4 au 的距离，波动显示 kolmogorov 谱 f^-5/3 并以异常缩放为特征。观测到的湍流统计特性表明，在远离太阳的后期，太阳风磁波动表现出湍流的典型多重分形行为，并通过间歇性描述，而在早期，当离开日冕时，观察到这些特性，从而显示出统计的单分形全局自相似性。从物理上讲，在靠近太阳的地方观察到的崩溃应该是由于定期统计的湍流，或者是由于存在强烈的随机波动，能够抵消异常尺度存在所必需的相关性。当离开日冕时，观察到这些特性的分解，从而显示出统计上的单分形全局自相似性。从物理上讲，在靠近太阳的地方观察到的崩溃应该是由于定期统计的湍流，或者是由于存在强烈的随机波动，能够抵消异常尺度存在所必需的相关性。当离开日冕时，观察到这些特性的分解，从而显示出统计上的单分形全局自相似性。从物理上讲，在靠近太阳的地方观察到的崩溃应该是由于定期统计的湍流，或者是由于存在强烈的随机波动，能够抵消异常尺度存在所必需的相关性。