论文标题

使用事件特定的GDAS氛围重建空气淋浴参数

Reconstructing air shower parameters with LOFAR using event specific GDAS atmospheres

论文作者

Mitra, P., Bonardi, A., Corstanje, A., Buitink, S., Krampah, G. K, Falcke, H., Hare, B. M., Hörandel, J. R., Huege, T., Mulrey, K., Nelles, A., Pandya, H., Rachen, J. P., Rossetto, L., Scholten, O., ter Veen, S., Trinh, T. N. G., Winchen, T.

论文摘要

大气参数(如湿度,压力,温度和折射率)的有限了解一直是从空气淋浴的无线电发射中重建最大淋浴最大深度的重要系统不确定性之一。当前的空气淋浴蒙特卡洛模拟代码,例如Corsika和无线电插件Coreas使用各种平均参数化气氛。但是,用于Lofar数据的宇宙射线分析方法需要时间依赖性和特定位置的大气模型。在那里,为每个检测到的宇宙射线使用专用的模拟集,以考虑测量时的实际大气条件。使用全球大气模型的全球数据同化系统(GDAS),我们在Corsika和Coreas实施了时间依赖,现实的大气概况。我们为所有使用Lofar测量的空气淋浴的事件特异性气氛产生了现实,这一事件设置跨越了几年,并且天气状况许多不同。对我们的数据集进行完整的重新分析表明,对于大多数数据,我们先前的校正因子的表现相当好。在重建的$ x _ {\ rm max} $中,我们发现只有2 g/cm $^2 $的小型系统偏移。但是,例如,在极端天气条件下,气压非常低,转移最高可达15 g/cm $^2 $。我们提供了一个校正公式,以确定$ x _ {\ rm max} $的变化,这是由于使用US-STD气氛和基于GDAS的氛围进行的模拟比较而产生的。

The limited knowledge of atmospheric parameters like humidity, pressure, temperature, and the index of refraction has been one of the important systematic uncertainties in reconstructing the depth of the shower maximum from the radio emission of air showers. Current air shower Monte Carlo simulation codes like CORSIKA and the radio plug-in CoREAS use various averaged parameterized atmospheres. However, time-dependent and location-specific atmospheric models are needed for the cosmic ray analysis method used for LOFAR data. There, dedicated simulation sets are used for each detected cosmic ray, to take into account the actual atmospheric conditions at the time of the measurement. Using the Global Data Assimilation System (GDAS), a global atmospheric model, we have implemented time-dependent, realistic atmospheric profiles in CORSIKA and CoREAS. We have produced realistic event-specific atmospheres for all air showers measured with LOFAR, an event set spanning several years and many different weather conditions. A complete re-analysis of our data set shows that for the majority of data, our previous correction factor performed rather well; we found only a small systematic shift of 2 g/cm$^2$ in the reconstructed $X_{\rm max}$. However, under extreme weather conditions, for example, very low air pressure, the shift can be up to 15 g/cm$^2$. We provide a correction formula to determine the shift in $X_{\rm max}$ resulting from a comparison of simulations done using the US-Std atmosphere and the GDAS-based atmosphere.

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