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Abstract Extreme rainfall events in the humid-tropical Luquillo Mountains, Puerto Rico export the bulk of suspended sediment and particulate organic carbon. Using 25 years of river carbon and suspended sediment data, which targeted hurricanes and other large rainstorms, we estimated biogenic particulate organic carbon yields of 65 ± 16 tC km⁻²yr⁻¹for the Icacos and 17.7 ± 5.1 tC km⁻²yr⁻¹for the Mameyes rivers. These granitic and volcaniclastic catchments function as substantial atmospheric carbon-dioxide sinks, largely through export of river biogenic particulate organic carbon during extreme rainstorms. Compared to other regions, these high biogenic particulate organic carbon yields are accompanied by lower suspended sediment yields. Accordingly, particulate organic carbon export from these catchments is underpredicted by previous yield relationships, which are derived mainly from catchments with easily erodible sedimentary rocks. Therefore, rivers that drain petrogenic-carbon-poor bedrock require separate accounting to estimate their contributions to the geological carbon cycle. 

Finite-fault models for the 2010 M w 8.8 Maule, Chile earthquake indicate bilateral rupture with large-slip patches located north and south of the epicenter. Previous studies also show that this event features significant slip in the shallow part of the megathrust, which is revealed through correction of the forward tsunami modeling scheme used in tsunami inversions. The presence of shallow slip is consistent with the coseismic seafloor deformation measured off the Maule region adjacent to the trench and confirms that tsunami observations are particularly important for constraining far-offshore slip. Here, we benchmark the method of Optimal Time Alignment (OTA) of the tsunami waveforms in the joint inversion of tsunami (DART and tide-gauges) and geodetic (GPS, InSAR, land-leveling) observations for this event. We test the application of OTA to the tsunami Green’s functions used in a previous inversion. Through a suite of synthetic tests we show that if the bias in the forward model is comprised only of delays in the tsunami signals, the OTA can correct them precisely, independently of the sensors (DART or coastal tide-gauges) and, to the first-order, of the bathymetric model used. The same suite of experiments is repeated for the real case of the 2010 Maule earthquake where, despite the results of the synthetic tests, DARTs are shown to outperform tide-gauges. This gives an indication of the relative weights to be assigned when jointly inverting the two types of data. Moreover, we show that using OTA is preferable to subjectively correcting possible time mismatch of the tsunami waveforms. The results for the source model of the Maule earthquake show that using just the first-order modeling correction introduced by OTA confirms the bilateral rupture pattern around the epicenter, and, most importantly, shifts the inferred northern patch of slip to a shallower position consistent with the slip models obtained by applying more complex physics-based corrections to the tsunami waveforms. This is confirmed by a slip model refined by inverting geodetic and tsunami data complemented with a denser distribution of GPS data nearby the source area. The models obtained with the OTA method are finally benchmarked against the observed seafloor deformation off the Maule region. We find that all of the models using the OTA well predict this offshore coseismic deformation, thus overall, this benchmarking of the OTA method can be considered successful. 

ABSTRACT We present chemical abundances for 21 elements (from Li to Eu) in 150 metal-poor Galactic stars spanning −4.1 < [Fe/H] < −2.1. The targets were selected from the SkyMapper survey and include 90 objects with [Fe/H] ≤ −3 of which some 15 have [Fe/H] ≤ −3.5. When combining the sample with our previous studies, we find that the metallicity distribution function has a power-law slope of Δ(log N)/Δ[Fe/H] = 1.51 ± 0.01 dex per dex over the range −4 ≤ [Fe/H] ≤ −3. With only seven carbon-enhanced metal-poor stars in the sample, we again find that the selection of metal-poor stars based on SkyMapper filters is biased against highly carbon-rich stars for [Fe/H] > −3.5. Of the 20 objects for which we could measure nitrogen, 11 are nitrogen-enhanced metal-poor (NEMP) stars. Within our sample, the high NEMP fraction (55 per cent ± 21 per cent) is compatible with the upper range of predicted values (between 12 per cent and 35 per cent). The chemical abundance ratios [X/Fe] versus [Fe/H] exhibit similar trends to previous studies of metal-poor stars and Galactic chemical evolution models. We report the discovery of nine new r-I stars, four new r-II stars, one of which is the most metal-poor known, nine low-α stars with [α/Fe] ≤ 0.15 as well as one unusual star with [Zn/Fe] = +1.4 and [Sr/Fe] = +1.2 but with normal [Ba/Fe]. Finally, we combine our sample with literature data to provide the most extensive view of the early chemical enrichment of the Milky Way Galaxy. 

By fusing data obtained from finely spaced continental-scale, magnetotelluric (MT) measurements used for geophysical imaging of the electrical conductivity variations of the Earth's crust and mantle, real-time data of the geomagnetic field variations at a sparse network of fixed geomagnetic observatory and variometer stations, power transmission system sensor data such as neutral ground return current, synchrophasor and other sensor data, information on power grid topology and state, and by applying algorithms we have developed to project the real-time stream of magnetic observatory and variometer data through the frequency-dependent tensor impedances derived from the MT data at each temporary station, we calculate the anomalous voltages on power transmission substations induced by geomagnetically induced currents. Our solution accounts for the first-order impacts on the induced voltages that are due to the effects of 3-D variations in ground (Earth's crust and upper mantle) electrical conductivity structure. These effects when convolved with the path integral of the induced vector ground electric field along the transmission lines are the dominant term in determining the intensity of the geomagnetically induced currents in the system; considerably more so than geomagnetic latitude scaling effects. We discuss integration of real-time geophysical estimates of geomagnetic disturbance induced substation voltages with DC and AC power flow simulations on increasingly realistic models of the topology and state of regional power grids. We are integrating our workflow with the open source PowerModelsGMD.jl power flow simulator developed at Los Alamos National Laboratory, and describe simulations of real-time assessments of stress on critical assets of the power grid including reactive power loss, phase deviations, transformer heating and other metrics of transmission system stress. Such efforts to provide a real-time assessment of risk to critical assets can also inform statistical assessments of system vulnerabilities to "100-yr" or "Carrington" level geomagnetic disturbances. We will discuss how such efforts are informing the development of updated standards that may impact the future regulatory environment that governs efforts to maintain a resilient power transmission system. 

ABSTRACT In this work, we combine spectroscopic information from the SkyMapper survey for Extremely Metal-Poor stars and astrometry from Gaia DR2 to investigate the kinematics of a sample of 475 stars with a metallicity range of $$-6.5 \le \rm [Fe/H] \le -2.05$$ dex. Exploiting the action map, we identify 16 and 40 stars dynamically consistent with the Gaia Sausage and Gaia Sequoia accretion events, respectively. The most metal poor of these candidates have metallicities of $$\rm [Fe/H]=-3.31\, \mathrm{ and }\, -3.74$$, respectively, helping to define the low-metallicity tail of the progenitors involved in the accretion events. We also find, consistent with other studies, that ∼21 per cent of the sample have orbits that remain confined to within 3 kpc of the Galactic plane, that is, |Zmax| ≤ 3 kpc. Of particular interest is a subsample (∼11 per cent of the total) of low |Zmax| stars with low eccentricities and prograde motions. The lowest metallicity of these stars has [Fe/H] = –4.30 and the subsample is best interpreted as the very low-metallicity tail of the metal-weak thick disc population. The low |Zmax|, low eccentricity stars with retrograde orbits are likely accreted, while the low |Zmax|, high eccentricity pro- and retrograde stars are plausibly associated with the Gaia Sausage system. We find that a small fraction of our sample (∼4 per cent of the total) is likely escaping from the Galaxy, and postulate that these stars have gained energy from gravitational interactions that occur when infalling dwarf galaxies are tidally disrupted. 

ABSTRACT We report the discovery of the closest known black hole candidate as a binary companion to V723 Mon. V723 Mon is a nearby ($$d\sim 460\, \rm pc$$), bright (V ≃ 8.3 mag), evolved (Teff, giant ≃ 4440 K, and Lgiant ≃ 173 L⊙) red giant in a high mass function, f(M) = 1.72 ± 0.01 M⊙, nearly circular binary (P = 59.9 d, e ≃ 0). V723 Mon is a known variable star, previously classified as an eclipsing binary, but its All-Sky Automated Survey, Kilodegree Extremely Little Telescope, and Transiting Exoplanet Survey Satellite light curves are those of a nearly edge-on ellipsoidal variable. Detailed models of the light curves constrained by the period, radial velocities, and stellar temperature give an inclination of $$87.0^{\circ ^{+1.7^\circ }}_{-1.4^\circ }$$, a mass ratio of q ≃ 0.33 ± 0.02, a companion mass of Mcomp = 3.04 ± 0.06 M⊙, a stellar radius of Rgiant = 24.9 ± 0.7 R⊙, and a giant mass of Mgiant = 1.00 ± 0.07 M⊙. We identify a likely non-stellar, diffuse veiling component with contributions in the B and V band of $${\sim }63{{\ \rm per\ cent}}$$ and $${\sim }24{{\ \rm per\ cent}}$$, respectively. The SED and the absence of continuum eclipses imply that the companion mass must be dominated by a compact object. We do observe eclipses of the Balmer lines when the dark companion passes behind the giant, but their velocity spreads are low compared to observed accretion discs. The X-ray luminosity of the system is $$L_{\rm X}\simeq 7.6\times 10^{29}~\rm ergs~s^{-1}$$, corresponding to L/Ledd ∼ 10−9. The simplest explanation for the massive companion is a single compact object, most likely a black hole in the ‘mass gap’. 

Context. We present our findings on 18 previously known ZZ Ceti stars observed by the TESS space telescope in 120 s cadence mode during the survey observation of the southern ecliptic hemisphere. Aims. We focus on the frequency analysis of the space-based observations, comparing the results with findings of previous ground-based measurements. The frequencies detected by the TESS observations can serve as inputs for future asteroseismic analyses. Methods. We performed standard pre-whitening of the data sets to derive the possible pulsation frequencies of the different targets. In some cases, we fit Lorentzians to the frequency groups that emerged as the result of short-term amplitude or phase variations that occurred during the TESS observations. Results. We detected more than 40 pulsation frequencies in seven ZZ Ceti stars observed in the 120 s cadence by TESS, with precision better than 0.1  μ Hz. We found that HE 0532−5605 may be a new outbursting ZZ Ceti. Ten targets do not show any significant pulsation frequencies in their Fourier transforms, due to a combination of their intrinsic faintness and/or crowding on the large TESS pixels. We also detected possible amplitude or phase variations during the TESS observations in some cases. Such behaviour in these targets was not previously identified from ground-based observations. 

The operation of the electric power grid is foundational to the health, safety, and economic well-being of the nation, yet it is increasingly fragile and exposed to risk from exogenous factors. When power disruptions are widespread, prolonged, or impact critical services, the consequences can be grave. GMDs) can impact electric power transmission grids through premature ageing and transformer failure, which can lead to cascading failures and extended power disruptions. Geomagnetically induced currents (GICs) arising from geomagnetic disturbances (GMD mitigation poses a challenging problem to grid operators due to the nature of its impact. Space weather events arising from solar coronal mass ejections (CMEs) that intersect Earth's orbit occur on a continuum of timescales and levels of severity. Moderately sized CMEs, such as the 1989 event that lead to the failure of the HydroQuebec system, illustrate the risk to the power grid. Even larger space weather events that have the potential for profound impacts and prolonged power disruptions on a continental scale are thought to happen approximately storm has occurred during the existence of electric infrastructure. At the other end of the severity spectrum, recent evidence has shown that GICs flow at low levels continuously on the grid even in the every one hundred years; however, no such absence of a solar storm. This behavior may cause eventual, but slow to manifest breakdown of grid assets misattributed to non-GMD causes. In either case, it is difficult for utilities to justify the costly installation of sensors and telemetry to monitor this phenomenon. This paper details a system to augment human operators with two new abilities—(1) the real-time prediction of GICs flowing on their system and (2) the real-time monitoring of GMD grid manifestations—without installing new sensors. The system will do this by fusing a “top-down” approach using physics-based modeling driven by detailed 3-D Earth conductivity measurements and real-time magnetic observatory data with a “bottom-up” approach using artificial intelligence techniques driven by synchrophasor data. This hybrid methodology will enable utility operators to identify the best strategies to modify grid voltages and topology to mitigate damage and deal with a changing federal regulatory framework that requires GMD monitoring and mitigation efforts.