In this paper, we discuss the influence of meteorological effects
on the data of the ground installation CARPET, which is a detector of the
charged component of secondary cosmic rays (CRs). This device is designed in
the P.N. Lebedev Physical Institute (LPI, Moscow, Russia) and installed at
the Dolgoprudny scientific station (Dolgoprudny, Moscow region;
55.56
The CARPET installation is designed for permanent monitoring of charged component of secondary cosmic ray (CR) flux at the ground level. It allows analysis of secondary CR fluxes variations, caused by geomagnetic and solar activity on the processes affecting the behavior of cosmic rays in near-Earth space and Earth's atmosphere (Makhmutov et al., 2013, 2015).
The basis of the CARPET installation (Fig. 1) is the STS-6 gas-discharge Geiger–Müller counters, combined in 12 detector blocks of 10 counters each. The detector block consists of two layers: five upper and five lower counters, separated with an aluminum absorber (filter) 7 mm thick. Experimental data are recorded using three channels with a time resolution of 1 ms. The first channel (UP) corresponds to the integral count rate of charged particles passing through the top layer of 60 counters. The second channel (LOW) corresponds to the integral count of charged particles passing through the bottom layer of 60 counters. Particles simultaneously registered by both the upper and lower counters, i.e., passed through the filter, are registered in the coincidence channel – TEL.
CARPET-MOSCOW installation and its components.
In addition, there is a channel of auxiliary information (“telemetry”), which consists of the data on atmospheric pressure, temperature, and supply voltages.
The CARPET installation detects particles of the following energies: in the
UP and the LOW channels there are electrons and positrons with energies
Nowadays there is an international network of the CARPET installations: the first
module was launched in 2006 (De Mendonca et al., 2011, 2013; Mizin et al.,
2011) at CASLEO (San Juan, Argentina; 31.47
This paper investigates the influence of meteorological conditions on the data of the installation, which has been operating since 2017 at the Dolgoprudny Scientific Station of the Lebedev Physical Institute RAS.
Ground-based CARPET installations detect secondary charged particles, mainly
muons, generated in the interaction of primary CRs with nuclei in the
atmosphere. Muons are not nuclear-active particles (such as protons,
neutrons, and also charged pions and kaons) and lose energy for the
excitation and ionization of air atoms. Ionization losses depend on the
amount of matter above the detector; therefore, the barometric effect must
be taken into account. The altitude of muon generation in the
The barometric effect can be determined through variations in atmospheric
pressure at the level of CR registration (Eq. 1):
According to the data for 2019, hourly averaged average count rate and
atmospheric pressure for the CARPET-MOSCOW installation
For calculating the barometric coefficient
Relationship between
To prove that secondary CR variations associated with barometric effect
are more significant than variations of primary CR variations, we use
pressure-corrected data of the Moscow neutron monitor
(
Figure 3 shows neutron monitor count rate variations on the data of 2019. The
black horizontal line is the average count rate [pulses/min] according to
the annual data. Black vertical dashed lines are the boundaries of the
months. The names of the month are signed at the bottom. The standard
deviations for the data of each month are shown at the top. The relative
magnitude of the effect determined by the variations in primary CRs over a
given period of time can be estimated by the ratio
Pressure-corrected count rate variations of the Moscow neutron monitor for the period of 2019. The horizontal line is the average count rate. The vertical dashed lines are the boundaries of the months. The standard deviations for the data of each month are shown at the top.
Magnitude of the barometric effect of the CARPET-MOSCOW can be estimated as
The muon component of secondary CRs is characterized by a significant temperature effect (Yanke et al., 2011). To correct the CR measurements for this effect, it is necessary to carry out temperature measurements in the atmosphere close to the location of the CR instrument. The temperature effect has two components: negative and positive. The negative temperature effect is associated with a decrease in muon fluxes during heating and expansion of the atmosphere. The positive temperature effect is associated with the appearance of additional muons, due to a decrease in the density of the atmosphere and, in connection with this, a decrease in the probability of interaction of charged pions and kaons with air nuclei. As a consequence, the probability of decays of charged pions and kaons and the appearance of additional muons increases. These two effects (positive and negative) are competitive (Dorman, 1972, 2004, 2006; Yanke et al., 2011).
To estimate the temperature effect, we used data of the TEL channel of the CARPET-MOSCOW installation for 2019–2020. The altitude profiles of temperature and pressure were determined from the experimental data of the Central Aerological Observatory (CAO; Dolgoprudny).
The temperature effect was determined in two ways: based on the effective generation level method and the integral method (Dmitrieva et al., 2013; Ganeva et al., 2013; Zazyan et al., 2015).
To eliminate the barometric effect, original data (Fig. 4a) were processed according to Eq. (1) (Fig. 4b). The barometric correction mainly compensates for the daily variations in the count rate.
Count rate variations of the CARPET-MOSCOW installation for the
period of 2020–2021:
The effective generation rate method is based on the assumption that muons
are mainly generated at a certain isobaric level, which is 100 hPa
(Dmitrieva et al., 2013). The height
Upper-air meteorological sondes are launched twice a day, at 11:30 and 23:30 UTC (Kochin et al., 2021). The picture of a typical MRZ-3AK1 sonde is presented in Fig. 5. Flights last, on average, about 1.5 h. Therefore, from the available data of the CARPET-MOSCOW installation, samples were made of hourly data from 12:00 to 13:00 and 00:00 to 01:00 UTC.
Upper air sonde MRZ-3AK1 (CAO; Dolgoprudny).
To calculate the contribution of the negative component of the temperature
effect, we define the linear relationship between
Relationship between
For the CARPET-MOSCOW installation,
The corrected data series (Fig. 4c) is calculated by the following equation:
To calculate the contribution of the positive component of the temperature
effect, we define the linear dependence between
Relationship between
Using the least squares method, we define the approximating line, whose
slope is
As seen in Fig. 7, there is a slight positive temperature effect. Corrected
data series is calculated by the following equation (Fig. 4d):
Consider the integral method for determining the temperature effect:
There are 16 isobaric surfaces commonly accepted while analyzing upper-air atmospheric effects: 1000, 925, 850, 700, 500, 400, 300, 250, 200, 150, 100, 70, 50, 30, 20, and 10 hPa. They are also used in observations by CAO. It was decided to exclude the surface of 10 hPa from the calculations, since for the time period 2019–2020 there are only 148 measurements for this isobaric surface pressure level.
Represent Eq. (6) as a sum:
Starting from the first isobaric surface (20 hPa), we will determine the
dependence between
The results are shown in Table 1: the first column is the atmospheric pressure on the given surface, the second column is the average temperature according to the data for 2019–2020, the third column is the standard deviation of the temperature, the fourth column is the temperature coefficient for the given isobaric surface, and the fifth column is number of measurements (number of launches at which the sound reached the required altitude). Figure 4e shows the count rate of the CARPET-MOSCOW installation, corrected with integral method, according to the data for 2019–2020.
The results of determining the temperature coefficient for each isobaric surface.
Comparison of Fig. 4c and d shows that the contribution of the positive temperature effect is small. Comparison of Fig. 4d and e demonstrates that the efficiency of data correction using the integral method is worse than using the effective generation method.
We can compare the efficiency of the correction for positive and negative
temperature effects by comparing the CARPET-MOSCOW data with the data of a
neutron monitor, which is practically not sensitive to the influence of
temperature. The correlation coefficient between the pressure-corrected
neutron monitor data for the period of 2019–2020 and the CARPET-MOSCOW data
corrected for pressure and the negative temperature effect is
This paper describes the CARPET installation, designed for detecting the
charged component of secondary CRs. The barometric coefficient was
determined using the built-in pressure sensor. The temperature coefficient
was determined by two methods using the data of the upper-air sounding. The
integral method for determining the temperature effect is the most accurate.
However, due to the lack of regular measurements at high altitudes (since
not all sounds reach high altitudes), it can be seen that the data processed
with this method are less accurate. It also shows less correlation with the
data of the Moscow neutron monitor. In this connection, it is more optimal
to use the method of the effective generation level, since it does not
require a complete temperature profile. Also, for the CARPET-MOSCOW
installation, it is possible to use only the negative component of the
temperature effect, since variations of the count rate have a good (
Data related to this article are available upon request to the corresponding authors.
MP was responsible for the conceptualization, methodology, software, electronics, data curation, and writing of the original draft. VM was responsible for the conceptualization, methodology, data curation, and writing of the original draft. GB was responsible for the conceptualization and prepared the writing of the original draft, FZ carried out the data curation and prepared the original draft. VF curated the data. YS was responsible for the conceptualization. AO participated in data curation.
The authors declare that they have no conflict of interest.
Publisher’s note: Copernicus Publications remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
The authors express their gratitude to the Neutron Monitor Database (NMDB)
team (
This paper was edited by Ciro Apollonio and reviewed by two anonymous referees.