The Stokes drag force and the gravity force are usually sufficient to describe the behavior of sub-Kolmogorovsize (or pointlike) heavy particles in turbulence, in particular when the particle-to-fluid density ratio rho(p)/rho(integral) greater than or similar to 10(3) (with rho(p) and rho(f) the particle and fluid density, respectively). This is, in general, not the case for smaller particle-to-fluid density ratios, in particular not for rho(p)/rho(f) greater than or similar to 10(2).

We present the results of a comparative study performed with three numerical methods applied to a flow in a three-dimensional geometry characterized by weak compressibility and large rarefaction effects. The employed methods, all based on the kinetic theory of gases, are the Lattice Boltzmann Method (LBM) in a regularized formulation, the Direct Simulation Monte Carlo (DSMC) approach and a hybrid method coupling the LBM and the DSMC recently developed by Di Staso et al., in this contribution extended to the case of simulations involving many particles and three-dimensional geometries.

In this work we present a methodology for the mapping of Snow Water Equivalent (SWE) temporal variations based on the Synthetic Aperture Radar (SAR) Interferometry technique and Sentinel-1 data. The shift in the interferometric phase caused by the refraction of the microwave signal penetrating the snow layer is isolated and exploited to generate maps of temporal variation of SWE from coherent SAR interferograms.

To reduce the data acquisition time and the high-level sidelobes produced by conventional focusing methods for ground-based synthetic aperture radar interferometry, we present a new method to provide accurate displacement maps based on the dimension-reduced compressive sensing (CS) method combined with the multiple measurement vectors (MMVs) model. The proposed CS method consists in selecting the supported area of targets, estimated by the fast conventional method with undersampled data. The following sparse reconstruction is applied only to the selected areas.

In this work, we study the capability of the ground surface to generate Persistent Scatterers (PS) based on the lithology, slope and aspect angles. These properties affect the scattering behavior of the Synthetic Aperture Radar (SAR) signal, the interferometric phase stability and, as a consequence, the PS generation. Two-time series of interferometric SAR data acquired by two different SAR sensors in the C-band are processed to generate independent PS datasets. The region north of Lisbon, Portugal, characterized by sparse vegetation and lithology diversity, is chosen as study area.

We study the imaging and interferometric performances of a MIMO radar on board of an airship as alternative to airborne and spaceborne SAR remote sensing techniques. Four different MIMO radar arrays are designed working in L, C, X and Ku frequency bands. A frequency bandwidth of 250 MHz has been considered for the MIMO radars. The spatial resolution is 0.6 m in range and 0.3 degree in azimuth. The imaging and interferometric performances of the MIMO radar are analyzed in terms of the airship stability.

In this work, we study the problem of assimilating high resolution Precipitable Water Vapor (PWV) maps using the Weather Research and Forecast 3D Variational Data assimilation system (WRF-3DVar). The PWV maps are obtained using the Sentinel-1 Synthetic Aperture Radar (SAR) images and the SAR interferometry (InSAR) technique. The influence of the high resolution PWV data on the initial condition of WRF and during the next 12 hours is studied.

Very high resolution precipitable water vapor maps obtained by the Sentinel-1 A synthetic aperture radar (SAR), using the SAR interferometry (InSAR) technique, are here shown to have a positive impact on the performance of severe weather forecasts.