Resampling and requantization of band-limited Gaussian stochastic signals with flat power spectrum

A theoretical analysis, aimed at characterizing the degradation induced by the resampling and requantization processes applied to band-limited Gaussian signals with flat power spectrum, available through their digitized samples, is presented. The analysis provides an efficient algorithm for computing the complete {joint} bivariate discrete probability distribution associated to the true quantized version of the Gaussian signal and to the quantity estimated after resampling and requantization of the input digitized sequence. The use of Fourier transform techniques allows deriving {approximate} analytical expressions for the quantities of interest, as well as implementing their efficient computation. Numerical experiments are found to be in good agreement with the theoretical results, and confirm the validity of the whole approach.Comment: Submitted to Digital Signal Processin

The Northern Adriatic Forecasting System for Circulation and Biogeochemistry: Implementation and Preliminary Results

This paper described the implementation of a forecasting system of the coupled physical and biogeochemical state of the northern Adriatic Sea and discussed the preliminary results. The forecasting system is composed of two components: the NEMO general circulation model and the BFM biogeochemical model. The BFM component includes an explicit benthic pelagic coupling providing fluxes at the sediment-water interface and the dynamic of the major benthic state variables. The system is forced by atmospheric forcing from a limited-area model and by available land-based (river runoff and nutrient load) data. The preliminary results were validated against available remote and in situ observations. The validation effort indicated a good performance of the system in defining the basin scale characteristics, while locally the forecasting model performance seemed mostly impaired by the uncertainties in the definition of the land-based forcing

Coupling radio propagation and weather forecast models to maximize Ka-band channel transmission rate for interplanetary missions

Deep space (DS) missions for interplanetary explorations are aimed at acquiring information about the solar system and its composition. To achieve this result a radio link is established between the space satellite and receiving stations on the Earth. Significant channel capacity must be guaranteed to such spacecraft-to-Earth link considering their large separation distance as well. Terrestrial atmospheric impairments on the space-to-Earth propagating signals are the major responsible for the signal degradation thus reducing the link’s channel temporal availability. Considering the saturation and the limited bandwidth of the conventional systems used working at X-band (around 8.4 GHz), frequencies above Ku-band (12-18 GHz) are being used and currently explored for next future DS missions. For example, the ESA mission EUCLID, planned to be launched in 2020 to reach Sun-Earth Lagrange point L2, will use the K-band (at 25.5-27 GHz). The BepiColombo (BC) ESA mission to Mercury, planned to be launched in 2016, will use Ka-band (at 32-34 GHz) with some modules operating at X-band too. The W-band is also being investigated for space communications (Lucente et al., IEEE Systems J., 2008) as well as near-infrared band for DS links (Luini at al., 3rd IWOW, 2014; Cesarone et al., ICSOS, 2011). If compared with X-band channels, K-band and Ka-band can provide an appealing data rate and signal-to-noise ratio in free space due to the squared-frequency law increase of antenna directivity within the downlink budget (for the same physical antenna size). However, atmospheric path attenuation can be significant for higher frequencies since the major source of transmission outage is not only caused by convective rainfall, as it happens for lower frequencies too, but even non-precipitating clouds and moderate precipitation produced by stratiform rain events are detrimental. This means that accurate channel models are necessary for DS mission data link design at K and Ka band. A physical approach can offer advanced radiopropagation models to take into account the effects due to atmospheric gases, clouds and precipitation. The objective of this work is to couple a weather forecast numerical model with a microphysically- oriented radiopropagation model, providing a description of the atmospheric state and of its effects on a DS downlink. This work is developed in the framework of the RadioMeteorological Operations Planner (RMOP) program, aimed at performing a feasibility study for the BC mission (Biscarini et al., EuCAP 2014). The RMOP chain for the link budget computation is composed by three modules: weather forecast (WFM), radio propagation (RPM) and downlink budget (DBM). WFM is aimed at providing an atmospheric state vector. Among the available weather forecast models, for RMOP purposes we have used the Mesoscale Model 5. The output of the WFM is the input of the RPM for the computation of the atmospheric attenuation and sky-noise temperature at the receiving ground station antenna. RPM makes use of radiative transfer solver based on the Eddington approximations well as accurate scattering models. Time series of attenuation and sky-noise temperature coming from the RPM are converted into probability density functions and then ingested by the DBM to compute the received data volume (DV). Using the BC mission as a reference test case for the Ka-band ground station at Cebreros (Spain), this work will show the advantages of using a coupled WFM-RPM approach with respect to climatological statistics in a link budget optimization procedure. The signal degradation due to atmospheric effects in DS links in terms of received DV will be also investigated not only at Ka band, but also at X, K and W for intercomparison. The quality of the DS downlink will be given in terms of received DV and the results at different frequencies compared showing the respective advantages and drawbacks

Mesoscale high-resolution meteorological and radiative transfer models for satellite downlink budget design at millimeter-wave frequencies

Deep space (DS) missions for interplanetary explorations are aimed at acquiring information about the solar system and its composition. To achieve this result a radio link is established between the space satellite and receiving stations on the Earth. Significant channel capacity must be guaranteed to such spacecraft-to-Earth link considering their large separation distance as well. Terrestrial atmospheric impairments on the space-to-Earth propagating signals are the major responsible for the signal degradation thus reducing the link’s channel temporal availability. Considering the saturation and the limited bandwidth of the conventional systems used working at X-band (around 8.4 GHz), frequencies above Ku-band (12-18 GHz) are being used and currently explored for next future DS missions. For example, the ESA mission EUCLID, planned to be launched in 2020 to reach Sun-Earth Lagrange point L2, will use the K-band (at 25.5-27 GHz). The BepiColombo (BC) ESA mission to Mercury, planned to be launched in 2016, will use Ka-band (at 32-34 GHz) with some modules operating at X-band too. The W-band is also being investigated for space communications (Lucente et al., IEEE Systems J., 2008) as well as near-infrared band for DS links (Luini at al., 3rd IWOW, 2014; Cesarone et al., ICSOS, 2011). If compared with X-band channels, higher frequency bands can provide an appealing data rate and signal-to-noise ratio in free space due to the squared-frequency law increase of antenna directivity within the downlink budget (for the same physical antenna size). In particular, W-band (75–110 GHz) can be one valid alternative to K- and Ka-bands; theoretically, W-band should provide high channel capacities due to the large bandwidth availability and a more robust immunity to signal interference. However, atmospheric path attenuation can be significant for higher frequencies since the major source of transmission outage is not only caused by convective rainfall, as it happens for lower frequencies too, but even non-precipitating clouds and moderate precipitation produced by stratiform rain events are detrimental. This means that accurate channel models are necessary for DS mission data link design. A physical approach can offer advanced radiopropagation models to take into account the effects due to atmospheric gases, clouds and precipitation. The objective of this work is to couple a weather forecast numerical model with a microphysically-oriented radiopropagation model, providing a description of the atmospheric state and of its effects on a DS downlink. This work is the continuation of a study developed in the framework of the RadioMeteorological Operations Planner (RMOP) program, aimed at performing a feasibility study for the BC mission (Biscarini et al., EuCAP 2014). The RMOP chain for the link budget computation is composed by three modules: weather forecast (WFM), radio propagation (RPM) and downlink budget (DBM). WFM is aimed at providing an atmospheric state vector. Among the available weather forecast models, for RMOP purposes we have used the Mesoscale Model 5. The output of the WFM is the input of the RPM for the computation of the atmospheric attenuation and sky-noise temperature at the receiving ground station antenna. RPM makes use of radiative transfer solver, based on the Eddington approximations well as accurate scattering models. Time series of attenuation and sky-noise temperature coming from the RPM are converted into probability density functions and then ingested by the DBM to compute the received data volume (DV). RMOP project was originally aimed at investigating the Ka-band for DS mission focusing the attention on the advantages of using a coupled WFM- RPM approach with respect to climatological statistics in a link budget optimization procedure. In this work we extended the study to the W- and K- band. The signal degradation, due to atmospheric effects in DS links in terms of received DV, is investigated and a comparison among K-, Ka-, W- and the more commonly used X-band is carried out. The quality of the DS downlink will be given in terms of received DV and the results at different frequencies compared showing the respective advantages and drawbacks

Investigating Ka-band science data transfer for BepiColombo mission by using radiometeorological numerical models

Deep space (DS) exploration is aimed at acquiring information about the solar system and its composition, a purpose that can be achieved only if a significant communication capacity can be provided to spacecrafts at very large distances [1]. The Ka-band (at 32-34 GHz) and higher frequency band channels can provide this capacity if compared to the current X-band (around 8.4 GHz) [2]-[4]. Ka-band can offer a striking performance advantage over X-band because of the square-frequency law increase of directivity of the downlink beam for the same physical antenna size. This opens up a possible and useful trade space for Ka-band missions with the same antenna size (and spacecraft constraints) and radio frequency power, since a Ka-band mission can return four times more data than a comparable X–band mission. For the European Space Agency (ESA), the next step in this direction will be the utilisation of Ka-band downlinks both to generate radiometric observables (in combination with X-band uplink) as well as to increase science data transfer [5]. The first satellite mission adopting such frequency operationally will be BepiColombo (BC), the ESA cornerstone mission to Mercury (expected launch in 2015) including the Mercury Orbiter Radio Experiment (MORE) at X-Ka band [6]. The optimal allocation of channel resources above Ku band is limited by the significant impact of radio- meteorological factors which can irremediably degrade the quality of service for fairly high percentage of time [7]. At Ka band, for instance, attenuation due to cloudy and rainy troposphere can be even one order of magnitude larger than at X-band. The major cause of outages at Ka band and above is due to rainfall, as well as non-precipitating clouds. For small carrier-to-noise ratio (CNR), the impact of atmospheric noise temperature can become non-negligible [4]. In order to achieve the optimum data return at Ka-band, a different approach with respect to the link budget computation at lower frequencies (e.g., S or X band) is necessary [2]. Such link analysis is based on the maximization of the expected data return in a probabilistic framework rather than on a specified link statistical availability. Recent methods uses monthly statistics collected at the receiving site with the aim of defining average values of expected received data volume [5] and the exploitation of numerical weather forecasting is also foreseen [3]. This paper introduces the preliminary concept of the RadioMetOP (RadioMeteorological Operations Planner) technique and describes its main modelling components and objectives, limiting the analysis to rainfall effects. Numerical results in terms of received frame data for unconstrained and constrained system scenarios are also described together with a discussion about the possible impact of RadioMetOP methods on BC operations

The EU Center of Excellence for Exascale in Solid Earth (ChEESE): Implementation, results, and roadmap for the second phase

The EU Center of Excellence for Exascale in Solid Earth (ChEESE) develops exascale transition capabilities in the domain of Solid Earth, an area of geophysics rich in computational challenges embracing different approaches to exascale (capability, capacity, and urgent computing). The first implementation phase of the project (ChEESE-1P; 2018¿2022) addressed scientific and technical computational challenges in seismology, tsunami science, volcanology, and magnetohydrodynamics, in order to understand the phenomena, anticipate the impact of natural disasters, and contribute to risk management. The project initiated the optimisation of 10 community flagship codes for the upcoming exascale systems and implemented 12 Pilot Demonstrators that combine the flagship codes with dedicated workflows in order to address the underlying capability and capacity computational challenges. Pilot Demonstrators reaching more mature Technology Readiness Levels (TRLs) were further enabled in operational service environments on critical aspects of geohazards such as long-term and short-term probabilistic hazard assessment, urgent computing, and early warning and probabilistic forecasting. Partnership and service co-design with members of the project Industry and User Board (IUB) leveraged the uptake of results across multiple research institutions, academia, industry, and public governance bodies (e.g. civil protection agencies). This article summarises the implementation strategy and the results from ChEESE-1P, outlining also the underpinning concepts and the roadmap for the on-going second project implementation phase (ChEESE-2P; 2023¿2026).This work has been funded by the European Union Horizon 2020 research and innovation program under the ChEESE project, Grant Agreemen

The EU Center of Excellence for Exascale in Solid Earth (ChEESE): Implementation, results, and roadmap for the second phase

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HJPACK

The software HJPACK consists of a library plus an environment to run numerical experiments on Hamilton-Jacobi equations. The present version deals with 1D and 2D model problems mainly with convex Hamiltonians. The approximation schemes are written for structured grids. Further developments for non convex Hamiltonians and unstructured grids will follow. Its main components are: • a collection of Fortran90 and C numerical routines which compute the viscosity solution for several classes of Hamilton-Jacobi equations in one and two dimensions. • a Tcl/Tk graphical interface to help the user in all the steps of the simulation, setting the input parameters, processing the data and visualizing the solution and some relevant data. • a Matlab and an Octave script for the graphic output. • OpenMP directives for the two dimensional parallelization on shared memory architectures. The package uses a graphical interface which helps the user to plug-in his own data for the experiment choosing among a list of predefined equations, boundary conditions, methods and discretization parameters. It is worth noting that the set of applications includes control theory, image processing, front propagation, grid generation, Hamiltonian systems and many others. You can choose between several numerical methods on structured rectangular grid, and you can develop your own algorithm exploiting already defined structures. All the components of the package are platform independent and have been tested on Unix (IBM, HP, Sun) and Linux (Intel) platforms