New cosmic ray observations at Syowa Station in the Antarctic for space weather study

Kato, C.; Kihara, W.; Ko, Y.; Kadokura, Akira; Kataoka, Ryuho; Evenson, P. A.; Uchida, Satoru; Kaimi, So; Nakamura, Yoshiaki; Uchida, Herbert Akihito; Murase, Kiyoka; Munakata, K.

doi:10.1051/swsc/2021005

Cited by 5 publications

(5 citation statements)

References 28 publications

(39 reference statements)

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“…Kato et al (2021) reported how the coefficient for MMS is calculated with the obtained values. The corrections of barometric effects for both muons and neutrons are also reported by Kato et al (2021).…”

Section: Mass Weighted Temperature Correction For Muon Count Ratementioning

confidence: 85%

“…The correction based on the linear correlation between the TMSS and muon count rate is the best method for muon detector data (Mendonsa et al, 2016). In this study, we applied the same MSS method to the muon detector data at Syowa Station as Kato et al (2021) documented. To calculate the TMSS, the temperature data was obtained from GDAS (Global Data Assimilation System; https://www.ncei.noaa.gov/products/weather-climate-models/global-data-assimilation) at 925, 850, 700, 600, 500, 400, 300, 250, 200, 150, 100, 70, 50, 30, and 20 hPa.…”

Section: Mass Weighted Temperature Correction For Muon Count Ratementioning

confidence: 99%

“…We started neutron and muon measurements at Syowa Station in the Antarctic (69.01º S, 39.59 º E; the vertical cutoff rigidity is 0.4 GV) in February 2018 (Kato et al, 2021). The simultaneous measurements of neutron and muon flux offer a unique perspective relative to the other neutron monitors and muon detectors that do not share the same location.…”

Section: Introductionmentioning

confidence: 99%

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Local environmental effects on cosmic ray observations at Syowa Station in the Antarctic: PARMA-based snow cover correction for neutrons and machine learning approach for neutrons and muons

Kataoka¹,

Sato²,

Kato³

et al. 2022

J. Space Weather Space Clim.

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Solar modulation of galactic cosmic rays around the solar minimum in 2019-2020 looks different in the secondary neutrons and muons observed at the ground. To compare the solar modulation of primary cosmic rays in detail, we must remove the possible seasonal variations caused by the atmosphere and surrounding environment. As such surrounding environment effects, we evaluate the snow cover effect on neutron count rate and the atmospheric temperature effect on muon count rate, both simultaneously observed at Syowa Station in the Antarctic (69.01º S, 39.59º E). A machine learning technique, Echo State Network (ESN), is applied to estimate both effects hidden in the observed time series of the count rate. We show that the ESN with the input of GDAS data (temperature time series at 925, 850, 700, 600, 500, 400, 300, 250, 200, 150, 100, 70, 50, 30, and 20 hPa) at the local position can be useful for both the temperature correction for muons and snow cover correction for neutrons. The corrected muon count rate starts decreasing in late 2019, preceding the corrected neutron count rate which starts decreasing in early 2020, possibly indicating the rigidity-dependent solar modulation in the heliosphere.

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Section: Mass Weighted Temperature Correction For Muon Count Ratementioning

confidence: 85%

Section: Mass Weighted Temperature Correction For Muon Count Ratementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Local environmental effects on cosmic ray observations at Syowa Station in the Antarctic: PARMA-based snow cover correction for neutrons and machine learning approach for neutrons and muons

Kataoka¹,

Sato²,

Kato³

et al. 2022

J. Space Weather Space Clim.

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“…For another check of the analysis, we also include the data from a combined NM (SYOW) and MD (Syow-MD), which started simultaneous operations at the Antarctic Syowa Station in 2018 (Kato et al 2021). Since orbits of vertically incident cosmic rays tend to be aligned with the field line in the polar geomagnetic field, the asymptotic viewing directions of an NM and the vertical channel of MD are similar within ∼30°.…”

Section: Cosmic-ray Datamentioning

confidence: 99%

Large-amplitude Bidirectional Anisotropy of Cosmic-Ray Intensity Observed with Worldwide Networks of Ground-based Neutron Monitors and Muon Detectors in 2021 November

Munakata

Kozai

Kato

et al. 2022

ApJ

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We analyze the cosmic-ray variations during a significant Forbush decrease observed with worldwide networks of ground-based neutron monitors and muon detectors during 2021 November 3–5. Utilizing the difference between primary cosmic-ray rigidities monitored by neutron monitors and muon detectors, we deduce the rigidity spectra of the cosmic-ray density (or omnidirectional intensity) and the first- and second-order anisotropies separately for each hour of data. A clear two-step decrease is seen in the cosmic-ray density with the first ∼2% decrease after the interplanetary shock arrival followed by the second ∼5% decrease inside the magnetic flux rope (MFR) at 15 GV. Most strikingly, a large bidirectional streaming along the magnetic field is observed in the MFR with a peak amplitude of ∼5% at 15 GV, which is comparable to the total density decrease inside the MFR. The bidirectional streaming could be explained by adiabatic deceleration and/or focusing in the expanding MFR, which have stronger effects for pitch angles near 90°, or by selective entry of GCRs along a leg of the MFR. The peak anisotropy and density depression in the flux rope both decrease with increasing rigidity. The spectra vary dynamically, indicating that the temporal variations of density and anisotropy appear different in neutron monitor and muon detector data.

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“…We started neutron and muon measurements at Syowa Station in the Antarctic (69.01 S, 39.59 E; the vertical cutoff rigidity is 0.4 GV) in February 2018 (Kato et al, 2021). The simultaneous observation of neutron and muon is a unique point compared to the other neutron monitors and muon detectors.…”

Section: Introductionmentioning

confidence: 99%

Machine-learning correction of the local effects on neutron monitor and muon detector count rates at Syowa Station in the Antarctic

Kataoka¹,

Sato²,

Kato³

et al. 2022

Preprint

Self Cite

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Solar modulation of galactic cosmic rays around the solar minimum in 2019-2020 looks different in the secondary neutrons and muons observed at the ground. To compare the solar modulation of primary cosmic rays in detail, we must remove the possible seasonal variations caused by the atmosphere and surrounding environment. As such surrounding environment effects, we evaluate the snow cover effect on neutron count rate and the atmospheric temperature effect on muon count rate, both simultaneously observed at Syowa Station in the Antarctic (69.01 S, 39.59 E). A machine learning technique, Echo State Network (ESN), is applied to estimate both effects hidden in the observed time series of the count rate. We show that the ESN with the input of ERA5 reanalysis data (temperature time series at 1000, 700, 500, 300, 200, 100, 70, 50, 30, 20, and 10 hPa) at the closet position can be useful for both the temperature correction for muons and snow cover correction for neutrons. The corrected muon count rate starts decreasing in late 2019, earlier than the corrected neutron count rate, which starts decreasing in early 2020, possibly indicating the rigidity-dependent solar modulation in the heliosphere.

show abstract

New cosmic ray observations at Syowa Station in the Antarctic for space weather study

Cited by 5 publications

References 28 publications

Local environmental effects on cosmic ray observations at Syowa Station in the Antarctic: PARMA-based snow cover correction for neutrons and machine learning approach for neutrons and muons

Local environmental effects on cosmic ray observations at Syowa Station in the Antarctic: PARMA-based snow cover correction for neutrons and machine learning approach for neutrons and muons

Large-amplitude Bidirectional Anisotropy of Cosmic-Ray Intensity Observed with Worldwide Networks of Ground-based Neutron Monitors and Muon Detectors in 2021 November

Machine-learning correction of the local effects on neutron monitor and muon detector count rates at Syowa Station in the Antarctic

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