Related papers: Bayesian Motion Estimation for Dust Aerosols
We present for the first time hourly variations of the spatial density gradient of 50 GeV cosmic rays within a sample solar rotation period in 2006. By inversely solving the transport equation, including diffusion, we deduce the gradient…
When the flow is sufficiently rarefied, a temperature gradient, for example, between two walls separated by a few mean free paths, induces a gas flow---an observation attributed to the thermo-stress convection effects at microscale. The…
We discuss a new phenomenon of turbulent thermal diffusion associated with turbulent transport of aerosols in the atmosphere and in laboratory experiments. The essence of this phenomenon is the appearance of a nondiffusive mean flux of…
This paper presents a new approach to the estimation of the deformation of an isotropic Gaussian random field on $\mathbb{R}^2$ based on dense observations of a single realization of the deformed random field. Under this framework we…
We present a stochastic method for reconstructing missing spatial and velocity data along the trajectories of small objects passively advected by turbulent flows with a wide range of temporal or spatial scales, such as small balloons in the…
Dust formation in brown dwarf atmospheres is studied by utilising a model for driven turbulence in the mesoscopic scale regime. We apply a pseudo-spectral method where waves are created and superimposed within a limited wavenumber interval.…
Dust emission is an important tool in studies of star-forming clouds, as a tracer of column density and indirectly via the dust evolution that is connected to the history and physical conditions of the clouds. We examine radiative transfer…
Ethane is the most abundant non-methane hydrocarbon in the Earth's atmosphere and an important precursor of tropospheric ozone through various chemical pathways. Ethane is also an indirect greenhouse gas (global warming potential),…
Desert surfaces are typically non uniform, with individual sand dunes generally surrounded by gravel or non-erodible beds. Similarly, beaches vary in composition and moisture that enhances cohesion between the grains. These bed…
Extreme weather events are projected to intensify global migration, increase resource competition, and amplify socio-spatial phenomena, including intergroup conflicts, socioeconomic inequalities, and unplanned displacements, among others.…
Global and mesoscale models represent the background (slowly varying) winds on Mars, but short timescale wind variability is not explicitly represented. The local wind erosion and dust deposition model can be useful for more accurate local…
Disturbance estimation for Micro Aerial Vehicles (MAVs) is crucial for robustness and safety. In this paper, we use novel, bio-inspired airflow sensors to measure the airflow acting on a MAV, and we fuse this information in an Unscented…
Take-off and landing are the periods of a flight where aircraft are most vulnerable to a ground based rocket attack by terrorists. While aircraft approach and depart from airports on pre-defined flight paths, there is a degree of…
The reconstruction from observations of high-dimensional chaotic dynamics such as geophysical flows is hampered by (i) the partial and noisy observations that can realistically be obtained, (ii) the need to learn from long time series of…
Pathogenic fungi are a leading cause of crop disease and primarily spread through microscopic, durable spores adapted differentially for both persistence and dispersal. Computational Earth System Models and air pollution models have been…
Machine learning is now used in many areas of astrophysics, from detecting exoplanets in Kepler transit signals to removing telescope systematics. Recent work demonstrated the potential of using machine learning algorithms for atmospheric…
We present a method for accurately and precisely inferring photometric dust extinction towards stars at mid-to-high Galactic latitudes using probabilistic machine learning to model the colour-magnitude distribution of zero-extinction stars…
Anomalous diffusion is present at all scales, from atomic to large scales. Some exemplary systems are; ultra-cold atoms, telomeres in the nucleus of cells, moisture transport in cement-based materials, the free movement of arthropods, and…
The Alaskan landscape has undergone substantial changes in recent decades, most notably the expansion of shrubs and trees across the Arctic. We developed a dynamic statistical model to quantify the impact of climate change on the structural…
This work provides two statistical Gaussian forecasting methods for predicting First Daily Departure Times (FDDTs) of everyday use electric vehicles. This is important in smart grid applications to understand disconnection times of such…