On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ∼ 1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40 − 8 + 8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 M ⊙ . An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ∼ 40 Mpc ) less than 11 hours after the merger by the One-Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ∼10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ∼ 9 and ∼ 16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC 4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta.

Observations of supernova remnants (SNRs) are a powerful tool for investigating the later stages of stellar evolution, the properties of the ambient interstellar medium, and the physics of particle acceleration and shocks. For a fraction of SNRs, multi-wavelength coverage from radio to ultrahigh-energies has been provided, constraining their contributions to the production of Galactic cosmic rays. Although radio emission is the most common identifier of SNRs and a prime probe for refining models, high-resolution images at frequencies above 5 GHz are surprisingly lacking, even for bright and well-known SNRs such as IC443 and W44. In the frameworks of the Astronomical Validation and Early Science Program with the 64-m single-dish Sardinia Radio Telescope, we provided, for the first time, single-dish deep imaging at 7 GHz of the IC443 and W44 complexes coupled with spatially-resolved spectra in the 1.5 − 7 GHz frequency range. Our images were obtained through on-the-fly mapping techniques, providing antenna beam oversampling and resulting in accurate continuum flux density measurements. The integrated flux densities associated with IC443 are S 1.5GHz = 134 ± 4 Jy and S 7GHz = 67 ± 3 Jy. For W44, we measured total flux densities of S 1.5GHz = 214 ± 6 Jy and S 7GHz = 94 ± 4 Jy. Spectral index maps provide evidence of a wide physical parameter scatter among different SNR regions: a flat spectrum is observed from the brightest SNR regions at the shock, while steeper spectral indices (up to ∼ 0.7) are observed in fainter cooling regions, disentangling in this way different populations and spectra of radio/gamma-ray-emitting electrons in these SNRs.

No abstract

Seasonal changes in grass cover impact the generation of surface runoff due to the effects of grass roots on soil hydrologic properties and processes (i.e., infiltration). Using a rainfall simulator in a grass field site, we broadly investigated the influence of different initial conditions of soil moisture and grass growth stages on rainfall–runoff transformations. To parameterize the stages of grass growth, we used the height of the vegetation hveg, which is related to the leaf area index. Surprisingly, typical characteristics of runoff formation (peak flow and time to peak flow) were conditioned mainly by hveg. The runoff coefficient decreased about 40% when grass reached its maximum growth and was inversely and significantly related to the height of grass in general. Using the rainfall simulator experiments, we estimated the saturated soil hydraulic conductivity ks, a key parameter of infiltration models. We found strong relationships between ks and hveg when the Philip infiltration model was used, and we proposed a linear relationship between ks and hveg, making ks vary in time with grass growth (i.e., hveg). We compared predictions of hydrologic models at plot scale using ks varying with grass growth with predictions using a constant ks, as hydrological models commonly assume. Neglecting ks variability with grass growth can lead to errors up to 100% in surface runoff predictions at an event time scale and up to 87% at a monthly time scale. Ecohydrological models for runoff predictions should take into account the influence of grass growth dynamics on soil infiltration parameters.

No abstract