Abstract
The inner Galaxy has hosted cosmic-ray burst events, including those responsible for the gamma-ray Fermi bubbles and the eROSITA bubbles in X-rays. In this work, we study the Alpha Magnetic ...Spectrometer positron fraction and find three features around 12, 21, and 48 GeV, of which the lowest energy has a 1.4–4.9
σ
significance, depending on astrophysical background assumptions. Using background simulations that explain the cosmic-ray positron fraction, positron flux, and electron plus positron flux by primary and secondary cosmic rays and cosmic rays from local pulsars, we test these spectral features as originating from electron/positron burst events from the inner Galaxy. We find the 12 GeV feature to be explained by an event of age
τ
≃ 3–10 Myr, in agreement with the proposed age of the Fermi bubbles. Furthermore, the energy in cosmic-ray electrons and positrons propagating along the Galactic disk and not within the Fermi bubbles volume is estimated to be 10
51.5
–10
57.5
erg, or O(10
−4
) − O(1) the cosmic-ray energy causing the Fermi bubbles. We advocate that these positron fraction features are the counterpart signals of the Fermi bubbles, or of substructures within them, or of the eROSITA bubbles.
Cosmic‐ray neutron sensors (CRNS) fill the gap between locally measured in‐situ soil moisture (SM) and remotely sensed SM by providing accurate SM estimation at the field scale. This is promising for ...improving hydrologic model predictions, as CRNS can provide valuable information on SM in the root zone at the typical scale of a model grid cell. In this study, SM measurements from a network of 12 CRNS in the Rur catchment (Germany) were assimilated into the Terrestrial System Modeling Platform (TSMP) to investigate its potential for improving SM, evapotranspiration (ET) and river discharge characterization and estimating soil hydraulic parameters at the larger catchment scale. The data assimilation (DA) experiments (with and without parameter estimation) were conducted in both a wet year (2016) and a dry year (2018) with the ensemble Kalman filter (EnKF), and later verified with an independent year (2017) without DA. The results show that SM characterization was significantly improved at measurement locations (with up to 60% root mean square error (RMSE) reduction), and that joint state‐parameter estimation improved SM simulation more than state estimation alone (more than 15% additional RMSE reduction). Jackknife experiments showed that SM at verification locations had lower and different improvements in the wet and dry years (an RMSE reduction of 40% in 2016 and 16% in 2018). In addition, SM assimilation was found to improve ET characterization to a much lesser extent, with a 15% RMSE reduction of monthly ET in the wet year and 9% in the dry year.
Key Points
Assimilation of soil moisture from a network of cosmic‐ray neutron sensors improves soil moisture characterization at the catchment scale
Soil moisture characterization improved more in a wet year than in a very dry year
Evapotranspiration and river discharge simulation are only slightly improved, despite better estimations of soil moisture
We report on measurements of the all-particle cosmic ray energy spectrum and composition in the PeV to EeV energy range using 3 years of data from the IceCube Neutrino Observatory. The IceTop ...detector measures cosmic ray induced air showers on the surface of the ice, from which the energy spectrum of cosmic rays is determined by making additional assumptions about the mass composition. A separate measurement is performed when IceTop data are analyzed in coincidence with the high-energy muon energy loss information from the deep in-ice IceCube detector. In this measurement, both the spectrum and the mass composition of the primary cosmic rays are simultaneously reconstructed using a neural network trained on observables from both detectors. The performance and relative advantages of these two distinct analyses are discussed, including the systematic uncertainties and the dependence on the hadronic interaction models, and both all-particle spectra as well as individual spectra for elemental groups are presented.
The Giant Radio Array for Neutrino Detection (GRAND) is a planned large-scale observatory of ultra-high-energy (UHE) cosmic particles, with energies exceeding 10
8
GeV. Its goal is to solve the ...long-standing mystery of the origin of UHE cosmic rays. To do this, GRAND will detect an unprecedented number of UHE cosmic rays and search for the undiscovered UHE neutrinos and gamma rays associated to them with unmatched sensitivity. GRAND will use large arrays of antennas to detect the radio emission coming from extensive air showers initiated by UHE particles in the atmosphere. Its design is modular: 20 separate, independent sub-arrays, each of 10000 radio antennas deployed over 10000 km
2
. A staged construction plan will validate key detection techniques while achieving important science goals early. Here we present the science goals, detection strategy, preliminary design, performance goals, and construction plans for GRAND.
Abstract
The Cosmic Ray Energetics And Mass for the International Space Station (ISS-CREAM) experiment successfully recorded data for 539 days from 2017 August to 2019 February. We report the energy ...spectrum of cosmic-ray protons from the ISS-CREAM experiment at energies from 1.60 × 10
3
to 6.55 × 10
5
GeV. The measured spectrum deviates from a single power law. A smoothly broken power-law fit to the data, including statistical and systematic uncertainties, shows the spectral index change at 9.0 × 10
3
GeV from 2.57 ± 0.03 to 2.82 ± 0.02 with a significance of greater than 3
σ
. This bump-like structure is consistent with a spectral softening recently reported by the balloon-borne CREAM, DAMPE, and NUCLEON, but ISS-CREAM extends measurements to higher energies.
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