We investigate the origin of the X-ray emission in low-luminosity AGNs (LLAGNs). predicted that the X-ray emission should originate from jets rather than from an advection-dominated accretion flow (ADAF) when the X-ray luminosity L X of the source is below a critical value of L X,crit ≈ 10 −6 L Edd . This prediction implies that the X-ray spectrum in such sources should be fitted by jets rather than ADAFs. Furthermore, below L X,crit the correlation between radio (L R ) and X-ray (L X ) luminosities and the black hole mass (M)-the so-called fundamental plane of black hole activity-should deviate from the general correlation obtained by Merloni, Heinz & Di Matteo (2003) and become steeper. The Merloni et al. correlation is described by logL R = 0.6logL X + 0.78logM + 7.33, while the predicted correlation is logL R = 1.23logL X + 0.25logM − 13.45. We collect data from the literature to check the validity of these two expectations. We find that among the 16 LLAGNs with good X-ray and radio spectra, 13 are consistent with the Yuan & Cui prediction. For the 22 LLAGNs with L X < L X,crit , the fundamental plane correlation is described by logL R = 1.22logL X + 0.23logM − 12.46, also in excellent agreement with the prediction.

We investigate the observed correlation between the 2-10 keV X-ray luminosity (in unit of the Eddington luminosity; l X ≡ L X /L Edd ) and the photon index (Γ) of the X-ray spectrum for both black hole X-ray binaries (BHBs) and active galactic nuclei (AGNs). We construct a large sample, with 10 −9 < ∼ l X < ∼ 10 −1 . We find that Γ is positively and negatively correlated with l X when l X > ∼ 10 −3 and 10 −6.5 < ∼ l X < ∼ 10 −3 respectively, while Γ is nearly a constant when l X < ∼ 10 −6.5 . We explain the above correlation in the framework of a coupled hot accretion flow -jet model. The radio emission always come from the jet while the X-ray emission comes from the accretion flow and jet when l X is above and below 10 −6.5 , respectively. More specifically, we assume that with the increase of mass accretion rate, the hot accretion flow develops into a clumpy and further a disc -corona two-phase structure because of thermal instability. We argue that such kind of two-phase accretion flow can explain the observed positive correlation.

Low-luminosity active galactic nuclei (LLAGNs) are generally believed to be powered by an inner radiatively inefficient, advection-dominated accretion flow (ADAF), an outer truncated thin disk, and a jet. Maoz (2007) recently challenged this picture based on the observation that the strength of ultraviolet emission relative to the X-ray and radio bands does not depart from empirical trends defined by more luminous sources. He advocates that AGNs across all luminosities have essentially the same accretion and radiative processes, which in luminous sources are described by a standard optically thick, geometrically thin disk. We calculate ADAF models and demonstrate that they can successfully fit the observed spectral energy distributions of the LLAGNs in Maoz's sample. Our model naturally accommodates the radio and X-ray emission, and the ultraviolet flux is well explained by a combination of the first-order Compton scattering in the ADAF, synchrotron emission in the jet, and black body emission in the truncated thin disk. It is premature to dismiss the ADAF model for LLAGNs. The UV data can be fit equally well using a standard thin disk, but an additional corona and jet would be required to account for the X-ray and radio emission. We argue that there are strong theoretical reasons to prefer the ADAF model over the thin disk scenario. We discuss testable predictions that can potentially discriminate between the two accretion models.

Despite the importance of mountain snowpack to understanding the water and energy cycles in North America's montane regions, no reliable mountain snow climatology exists for the entire continent. We present a new estimate of mountain snow water equivalent (SWE) for North America from regional climate model simulations. Climatological peak SWE in North America mountains is 1,006 km3, 2.94 times larger than previous estimates from reanalyses. By combining this mountain SWE value with the best available global product in nonmountain areas, we estimate peak North America SWE of 1,684 km3, 55% greater than previous estimates. In our simulations, the date of maximum SWE varies widely by mountain range, from early March to mid‐April. Though mountains comprise 24% of the continent's land area, we estimate that they contain ~60% of North American SWE. This new estimate is a suitable benchmark for continental‐ and global‐scale water and energy budget studies.

No abstract

Abstract. Although the knowledge of the gravity of the Earth has improved considerably with CHAMP, GRACE, and GOCE (see appendices for a list of abbreviations) satellite missions, the geophysical community has identified the need for the continued monitoring of the time-variable component with the purpose of estimating the hydrological and glaciological yearly cycles and long-term trends. Currently, the GRACE-FO satellites are the sole dedicated provider of these data, while previously the GRACE mission fulfilled that role for 15 years. There is a data gap spanning from July 2017 to May 2018 between the end of the GRACE mission and start the of GRACE-FO, while the Swarm satellites have collected gravimetric data with their GPS receivers since December 2013. We present high-quality gravity field models (GFMs) from Swarm data that constitute an alternative and independent source of gravimetric data, which could help alleviate the consequences of the 10-month gap between GRACE and GRACE-FO, as well as the short gaps in the existing GRACE and GRACE-FO monthly time series. The geodetic community has realized that the combination of different gravity field solutions is superior to any individual model and set up the Combination Service of Time-variable Gravity Fields (COST-G) under the umbrella of the International Gravity Field Service (IGFS), part of the International Association of Geodesy (IAG). We exploit this fact and deliver the highest-quality monthly GFMs, resulting from the combination of four different gravity field estimation approaches. All solutions are unconstrained and estimated independently from month to month. We tested the added value of including kinematic baselines (KBs) in our estimation of GFMs and conclude that there is no significant improvement. The non-gravitational accelerations measured by the accelerometer on board Swarm C were also included in our processing to determine if this would improve the quality of the GFMs, but we observed that is only the case when the amplitude of the non-gravitational accelerations is higher than during the current quiet period in solar activity. Using GRACE data for comparison, we demonstrate that the geophysical signal in the Swarm GFMs is largely restricted to spherical harmonic degrees below 12. A 750 km smoothing radius is suitable to retrieve the temporal variations in Earth's gravity field over land areas since mid-2015 with roughly 4 cm equivalent water height (EWH) agreement with respect to GRACE. Over ocean areas, we illustrate that a more intense smoothing with 3000 km radius is necessary to resolve large-scale gravity variations, which agree with GRACE roughly at the level of 1 cm EWH, while at these spatial scales the GRACE observes variations with amplitudes between 0.3 and 1 cm EWH. The agreement with GRACE and GRACE-FO over nine selected large basins under analysis is 0.91 cm, 0.76 cm yr−1, and 0.79 in terms of temporal mean, trend, and correlation coefficient, respectively. The Swarm monthly models are distributed on a quarterly basis at ESA's Earth Swarm Data Access (at https://swarm-diss.eo.esa.int/, last access: 5 June 2020, follow Level2longterm and then EGF) and at the International Centre for Global Earth Models (http://icgem.gfz-potsdam.de/series/02_COST-G/Swarm, last access: 5 June 2020), as well as identified with the DOI https://doi.org/10.5880/ICGEM.2019.006 (Encarnacao et al., 2019).

No abstract

Data from the Tropical Rainfall Measuring Mission (TRMM) have made great contributions to hydrometeorology from both a science and an operations standpoint. However, direct application of TRMM data to short-fuse hydrologic forecasting has been challenging because of the data refresh and latency issues inherent in an instrument in low Earth orbit (LEO). To evaluate their potential impact on low-latency satellite rainfall estimates, rain rates from both the TRMM Microwave Imager (TMI) and precipitation radar (PR) were ingested into a multisensor framework that calibrates high-refresh, low-latency IR brightness temperature data from geostationary platforms against the more accurate but low-refresh, higher-latency rainfall rates available from microwave (MW) instruments on board LEO platforms. The TRMM data were used in two ways: to bias adjust the other MW data sources to match the distribution of the TMI rain rates, and directly alongside the MW rain rates in the calibration dataset. The results showed a significant reduction in false alarms and also a significant reduction in bias for those pixels for which rainfall was correctly detected. The MW bias adjustment was found to have much greater impact than the direct use of the TMI and PR rain rates in the calibration data, but this is not surprising since the latter represented perhaps only 10% of the calibration dataset.