A high time resolution 2 m 2 tracking detector, based on timing Resistive Plate Chamber (tRPC) cells, has been installed at the Faculty of Physics of the University of Santiago de Compostela (Spain) in order to improve our understanding of the cosmic rays arriving at the Earth's surface. Following a short commissioning of the detector, a study of the atmospheric temperature effect of the secondary cosmic ray component was carried out. To take into account this effect, temperature coefficients, W T (h), were obtained from cosmic ray data using a method based on Principal Component Analysis (PCA). The results obtained show good agreement with the theoretical expectation. The method successfully removes the correlation present between the different atmospheric layers, which would be dominant otherwise. We briefly describe the initial calibration and pressure correction procedures, essential to isolate the temperature effect. Overall, the measured cosmic ray rate displays the expected anticorrelation with the effective atmospheric temperature, through the coefficient α T = −0.279±0.051%/K. Rates follow the seasonal variations, and unusual short-term events are clearly identified too.

A priori, cosmic‐ray measurements offer a unique capability to determine the vertical profile of atmospheric temperatures directly from ground. However, despite the increased understanding of the impact of the atmosphere on cosmic‐ray rates, attempts to explore the technological potential of the latter for atmospheric physics remain very limited. In this paper, we examine the intrinsic limits of the process of cosmic‐ray data inversion for atmospheric temperature retrieval, by combining a detection station at ground with another one placed at an optimal depth, and making full use of the angular information. With that aim, the temperature‐induced variations in cosmic rays (c.r.) rates have been simulated resorting to the theoretical temperature coefficients WT(h, θ, Eth) and the temperature profiles obtained from the ERA5 atmospheric reanalysis. Muon absorption and Poisson statistics have been included to increase realism. The resulting c.r. sample has been used as input for the inverse problem and the obtained temperatures compared to the input temperature data. Relative to early simulation works, performed without using angular information and relying on underground temperature coefficients from a suboptimal depth, our analysis shows a strong improvement in temperature predictability for all atmospheric layers up to 50 hPa, nearing a factor 2 error reduction. Furthermore, the temperature predictability on 6‐h intervals stays well within the range 0.8–2.2 K. Most remarkably, we show that it can be achieved with small‐area m2‐scale muon hodoscopes, amenable nowadays to a large variety of technologies. For mid‐latitude locations, the optimal depth of the underground station is around 20 m.

<p>The ionization caused by Cosmic Rays (CR) in the atmosphere can influence the growth of aerosols that will modify the density of cloud-condensation nuclei (CCN). In fact, the flux of CR in the atmosphere has been reported to correlate with cloud and aerosol properties. Several mechanisms have been proposed and tested to explain this effect, leading to the conclusion that the induced effects were minor. Still, these studies did not completely disprove the link between CR and clouds (i.e., climate). Since then, different mechanisms that could be relevant to aerosol growth have been proposed. One of them is the diffusion-charging mechanism by which aerosols acquire charges by diffusion of atmospheric ions onto their surface.  Charging and aerosol coagulation can influence each other and impact the particle charge and size distributions in the atmosphere. Previous works have developed approaches to explicitly solve all the equations governing charge and size distribution in particles. However, since aerosols can acquire a large number of charges, the number of equations to solve would be immense and very computationally expensive. Fortunately, other approaches have also been developed that allow diffusion charging to be implemented more efficiently. In this work, we use for the very first time a global chemistry transport model (GEOS-Chem) to implement the effects of diffusion charging from CR on the microphysical development of aerosols following those approaches. We compare the variations of CCN concentrations between the solar maximum and the solar minimum (i.e., different atmospheric ionization scenarios) to test the sensitivity of the effect. Results indicate that the influence of diffusion charging can be relevant under several atmospheric conditions. In such cases, the change in the concentrations of CCN between the solar maximum (high cosmic-ray flux) and the solar minimum (low cosmic-ray flux) is found to be larger than 1%, which may become relevant for cloud formation. </p>

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Analysis of the atmospheric effect on the TRAGALDABAS high resolution Cosmic Ray detector I. Riádigos 1 2 for the Tragaldabas Collaboration *