For detecting below surface sources of deformation, strain measurements offer a very large advantage (orders of magnitude) in sensitivity over displacement measurements. On active volcanoes an intriguing open challenge is to measure the strain variations caused by the different types of eruptive activity with the highest possible precision in order to obtain advantages on the clear detecting of phenomena, their modeling and understanding. We present the updated main results obtained from the high precision strain recorded by the borehole dilatometer network on Mt. Etna volcano. The instruments, installed from the end of 2011, detected significant changes during different types of eruptive activity: several lava fountains during 2011-2014; two explosive sequences in 2015 and 2016; moderate effusive activity in 2017 and a dike intrusion in 2018. The strain changes provided powerful diagnostic information on the different ongoing processes, and allowed us to add key information on the different eruptive styles and sources. We also highlight how the recorded signals, with the associated modeling and interpretation, provide a powerful contribution to surveillance requirements on an active volcano. This report demonstrates that the borehole dilatometer network represents a useful tool both for the understanding of the volcano processes and for surveillance needs.

Key Points

Identifying and characterizing the dynamics of explosive activity is impelling to build tools for hazard assessment at open-conduit volcanoes: machine learning techniques are now a feasible choice. During the summer of 2019, Stromboli experienced two paroxysmal eruptions that occurred in two different volcanic phases, which gave us the possibility to conceive and test an early-warning algorithm on a real use case: the paroxysm on July, 3 was clearly preceded by smaller and less perceptible changes in the volcano dynamics, while the second paroxysm, on August 28 concluded the eruptive phase. Among the changes observed in the weeks preceding the July paroxysm one of the most significant is represented by the shape variation of the ordinary minor explosions, filtered in the very long period (VLP 2-50 s) band, recorded by the Sacks-Evertson strainmeter installed near the village of Stromboli. Starting from these observations, the usage of two independent methods (an unsupervised machine learning strategy and a cross-correlation algorithm) to classify strain transients falling in the ultra long period (ULP 50-200 s) frequency band, allowed us to validate the robustness of the approach. This classification leads us to establish a link between VLP and ULP shape variation forms and volcanic activity, especially related to the unforeseen 3 July 2019 paroxysm. Previous warning times used to precede paroxysms at Stromboli are of a few minutes only. For paroxysmal events occurring outside any long-lasting eruption, the initial success of our approach, although applied only to the few available examples, could permit us to anticipate this time to several days by detecting medium-term strain anomalies: this could be crucial for risk mitigation by prohibiting access to the summit. Our innovative analysis of dynamic strain may be used to provide an early-warning system also on other open conduit active volcanoes.

Optical imaging surveys measure both the galaxy density and the gravitational lensing-induced shear fields across the sky. Recently, the Dark Energy Survey (DES) Collaboration used a joint fit to two-point correlations between these observables to place tight constraints on cosmology (T. M. C. Abbott et al. (Dark Energy Survey Collaboration), Phys. Rev. D 98, 043526 (2018)). In this work, we develop the methodology to extend the DES Year 1 joint probes analysis to include cross-correlations of the optical survey observables with gravitational lensing of the cosmic microwave background as measured by the South Pole Telescope (SPT) and Planck. Using simulated analyses, we show how the resulting set of five two-point functions increases the robustness of the cosmological constraints to systematic errors in galaxy lensing shear calibration. Additionally, we show that contamination of the SPT+Planck cosmic microwave background lensing map by the thermal Sunyaev-Zel'dovich effect is a potentially large source of systematic error for two-point function analyses but show that it can be reduced to acceptable levels in our analysis by masking clusters of galaxies and imposing angular scale cuts on the two-point functions. The methodology developed here will be applied to the analysis of data from the DES, the SPT, and Planck in a companion work.

The combination of multiple observational probes has long been advocated as a powerful technique to constrain cosmological parameters, in particular dark energy. The Dark Energy Survey has measured 207 spectroscopically confirmed type Ia supernova light curves, the baryon acoustic oscillation feature, weak gravitational lensing, and galaxy clustering. Here we present combined results from these probes, deriving constraints on the equation of state, w, of dark energy and its energy density in the Universe. Independently of other experiments, such as those that measure the cosmic microwave background, the probes from this single photometric survey rule out a Universe with no dark energy, finding w = -0.80(-0.11)(+0.09). The geometry is shown to be consistent with a spatially flat Universe, and we obtain a constraint on the baryon density of Omega(b) = 0.069(-0.012)(+0.009) that is independent of early Universe measurements. These results demonstrate the potential power of large multiprobe photometric surveys and pave the way for order of magnitude advances in our constraints on properties of dark energy and cosmology over the next decade.

We perform a joint analysis of the counts and weak lensing signal of redMaPPer clusters selected from the Dark Energy Survey (DES) Year 1 dataset. Our analysis uses the same shear and source photometric redshifts estimates as were used in the DES combined probes analysis. Our analysis results in surprisingly low values for S-8 = sigma(8)(Omega(m)/0.3)(0.5) = 0.65 0.04, driven by a low matter density parameter, Omega(m) = 0.179(-0.038)(+0.031), with sigma(8) - Omega(m) posteriors in 2.4 sigma tension with the DES Y1 3x2pt results, and in 5.6 sigma with the Planck CMB analysis. These results include the impact of post-unblinding changes to the analysis, which did not improve the level of consistency with other data sets compared to the results obtained at the unblinding. The fact that multiple cosmological probes (supernovae, baryon acoustic oscillations, cosmic shear, galaxy clustering and CMB anisotropies), and other galaxy cluster analyses all favor significantly higher matter densities suggests the presence of systematic errors in the data or an incomplete modeling of the relevant physics. Cross checks with x-ray and microwave data, as well as independent constraints on the observable -mass relation from Sunyaev-Zeldovich selected clusters, suggest that the discrepancy resides in our modeling of the weak lensing signal rather than the cluster abundance. Repeating our analysis using a higher richness threshold (lambda >= 30) significantly reduces the tension with other probes, and points to one or more richness -dependent effects not captured by our model.

We present a catalog of 23,790 extended low-surface-brightness galaxies (LSBGs) identified in similar to 5000 deg(2) from the first three years of imaging data from the Dark Energy Survey (DES). Based on a single-component Sersic model fit, we define extended LSBGs as galaxies with g-band effective radii R-eff (g) > 2.'' 5 and mean surface brightness (mu) over bar (eff)(g) > 24.2 mag arcsec(-2). We find that the distribution of LSBGs is strongly bimodal in (g-r) versus (g-i) color space. We divide our sample into red (g-i >= 0.60) and blue (g-i<0.60) galaxies and study the properties of the two populations. Redder LSBGs are more clustered than their blue counterparts and are correlated with the distribution of nearby (z<0.10) bright galaxies. Red LSBGs constitute similar to 33% of our LSBG sample, and similar to 30% of these are located within 1 degrees of low-redshift galaxy groups and clusters (compared to similar to 8% of the blue LSBGs). For nine of the most prominent galaxy groups and clusters, we calculate the physical properties of associated LSBGs assuming a redshift derived from the host system. In these systems, we identify 41 objects that can be classified as ultradiffuse galaxies, defined as LSBGs with projected physical effective radii R-eff > 1.5 kpc and central surface brightness mu(0) g > 24.0 mag arcsec(-2). The wide-area sample of LSBGs in DES can be used to test the role of environment on models of LSBG formation and evolution.

Over the past decade, ocean acidification (OA) has emerged as a major concern in ocean science. The field of OA is based on certainties-update of carbon dioxide into the global ocean alters its carbon chemistry, and many marine organisms, especially calcifiers, are sensitive to this change. However, the field must accommodate uncertainties about the seriousness of these impacts as it synthesizes and draws conclusions from multiple disciplines. There is pressure from stakeholders to expeditiously inform society about the extent to which OA will impact marine ecosystems and the people who depend on them. Ultimately, decisions about actions related to OA require evaluating risks about the likelihood and magnitude of these impacts. As the scientific literature accumulates, some of the uncertainty related to single-species sensitivity to OA is diminishing. Difficulties remain in scaling laboratory results to species and ecosystem responses in nature, though modeling exercises provide useful insight. As recognition of OA grows scientists' ability to communicate the certainties and uncertainties of our knowledge on OA is crucial for interaction with decision makers. In this regard, there are a number of valuable practices that can be drawn from other fields, especially the global climate change community. A generally accepted set of best practices that scientists follow in their discussions of uncertainty would be helpful for the community engaged in ocean acidification.

At a proximal level, the physiological impacts of global climate change on ectothermic organisms are manifest as changes in body temperatures. Especially for plants and animals exposed to direct solar radiation, body temperatures can be substantially different from air temperatures. We deployed biomimetic sensors that approximate the thermal characteristics of intertidal mussels at 71 sites worldwide, from 1998-present. Loggers recorded temperatures at 10-30 min intervals nearly continuously at multiple intertidal elevations. Comparisons against direct measurements of mussel tissue temperature indicated errors of similar to 2.0-2.5 degrees C, during daily fluctuations that often exceeded 15 degrees-20 degrees C. Geographic patterns in thermal stress based on biomimetic logger measurements were generally far more complex than anticipated based only on 'habitat-level' measurements of air or sea surface temperature. This unique data set provides an opportunity to link physiological measurements with spatially-and temporally-explicit field observations of body temperature.