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Reconstructing air shower parameters with LOFAR using event specific GDAS atmospheres

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.

preprint2020arXivOpen access
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