GPS Calendar

Liquid water availability decreased with geological time on Mars. There is abundant geological evidence for large amounts of liquid water forming fluvial features and hydrated minerals early in Martian history. However, it is still unclear how much water was present at different periods in Mars' history and what subsequently happened to that water. We develop a model that simulates volcanic degassing, atmospheric escape, and crustal hydration and computes the global Martian D/H and water budget evolution through geological time. Simulation results are compatible with early Noachian water reservoirs of 100-1500 global equivalent layers (GEL), comparable to what has been proposed for pre-Noachian contributors to the Martian protoatmosphere. Our simulations show that the water availability decreases drastically during the Noachian. The Hesperian provides an interval where both a wet and dry Mars is possible. During the Amazonian, water availability was similar to today. The model results show that 30-96% of water was lost through crustal hydration. This highlights crustal hydration as the major water sink through Mars history and the role of irreversible crustal sinks in reducing habitability of terrestrial planets.

In 2017, the Cassini spacecraft dove between Saturn's rings and the tops of its clouds. Flying only a few miles above Saturn's atmosphere, the spacecraft's orbital motion was affected by exquisitely fine details of Saturn's gravity field. Most of Saturn's gravity field was more or less what we expected, but traditional techniques failed to account for a significant component of the measured signal. In this work, we model how global seismic oscillations on Saturn warp its gravity field in time. We find good agreement with the data if Saturn tremors at unexpectedly high frequencies, singing a song we can only hear through its minute effect on gravity in the vacuum of space.

We propose an analytic function for the bond albedo of an airless or near-airless magma ocean planet (AMOP). We generated multiple 1D fractal surfaces with varying compositions unto which we individually bombarded 10,000 light rays. Using an approximate form of the Fresnel equations we measured how much of the incident light was reflected. Having repeated this algorithm on varying surface roughnesses we find the albedo as a function of the Hurst exponent, the geochemical composition of the magma, and the wavelength. As a proof of concept, we used our model on Kepler-10 b to demonstrate the applicability of our approach. We present the albedos of different lava compositions and multiple tests that can be applied to observational data in order to determine their characteristics. Currently, there is a strong degeneracy in the surface composition of AMOPS due to the large uncertainties in their measured albedos. In spite of this, when applied to Kepler-10 b we show that the high albedo could be caused by a moderately wavy ocean that is rich in oxidised metallic species such as FeO, Fe2O3, Fe3O4. This would imply that Kepler-10 b is a coreless or near-coreless body.

Accumulative observations of global earthquakes in decades have shown a great amount of variability of rupture behaviors; to what extent that large earthquakes share common rupture characteristics remains unclear. Here, by applying a machine learning approach, i.e. variational autoencoder, to global source time function (STF) databases, we extract a generic spectrum of earthquake STF shapes along with their population density. The spectrum reveals the popularity of events with slow onset and rapid termination, which contests a long-lingering perception that isosceles triangular and long-tailed shapes are more standard. The spectrum also highlights a special class of complex earthquakes that are located at shallow depth (<40 km) but pervasive in different faulting environments, likely implying depth dependence of fault properties. Finally, we show that the deviation from the spectrum can serve as a detector for earthquakes with unusual characteristics. Our results provide a self-sufficing framework to evaluate the variability of temporal rupture characteristics of global earthquakes.