Processing reflectivity and Doppler velocity from EarthCARE's cloud-profiling radar: the C-FMR, C-CD and C-APC products

The Earth Clouds, Aerosols and Radiation (EarthCARE) satellite mission is a joint effort by the European Space Agency (ESA) and the Japanese Aerospace Exploration Agency (JAXA). The EarthCARE mission features the first spaceborne 94 GHz cloud-profiling radar (CPR) with Doppler capability. The raw CPR observations and auxiliary information are used as input to three Level-2 (L2) algorithms: (1) C-APC: Antenna Pointing Characterization; (2) C-FMR: CPR feature mask and reflectivity; (3) C-CD: Corrected CPR Doppler Measurements. These algorithms apply quality control and corrections to the CPR primary measurements and derive important geophysical variables, such as hydrometeor locations, and best estimates of particle sedimentation fall velocities. The C-APC algorithm uses natural targets to introduce any corrections needed to the CPR raw Doppler velocities due to the CPR antenna pointing. The C-FMR product provides the feature mask based on only-reflectivity CPR measurements and quality-controlled radar-reflectivity profiles corrected for gaseous attenuation at 94 GHz. In addition, C-FMR provides best estimates of the path-integrated attenuation (PIA) and flags identifying the presence of multiple scattering in the CPR observations. Finally, the C-CD product provides the quality-controlled, bias-corrected mean Doppler velocity estimates (Doppler measurements corrected for antenna mispointing, non-uniform beam filling and velocity folding). In addition, the best estimate of the particle sedimentation velocity is estimated using a novel technique.</p

Quantum Monte Carlo study of the reaction: C1 + CH3OH -->CH2OH+ HCl

A theoretical study is reported of the Cl + CH{sub 3}OH {yields} CH{sub 2}OH + HCl reaction based on the diffusion Monte Carlo (DMC) variant of the quantum Monte Carlo method. Using a DMC trial function constructed as a product of Hartree-Fock and correlation functions, we have computed the barrier height, heat of reaction, atomization energies and heats of formation of reagents and products. The DMC heat of reaction, atomization energies, and heats of formation are found to agree with experiment to within the error bounds of computation and experiment. Moller-Plesset second order perturbation theory (MP2) and density functional theory, the latter in the B3LYP generalized gradient approximation, are found to overestimate the experimental heat of reaction. Intrinsic reaction coordinate calculations at the MP2 level of theory demonstrate that the reaction is predominantly direct, i.e., proceeds without formation of intermediates, which is consistent with a recent molecular beam experiment. The reaction barrier as determined from MP2 calculations is found to be 2.24 kcal/mol and by DMC it is computed to be 2.39(49) kcal/mol

Detection and localisation of multiple in-core perturbations with neutron noise-based self-supervised domain adaptation

The use of non-intrusive techniques for monitoring nuclear reactors is becoming more vital as western fleets age. As a consequence, the necessity to detect more frequently occurring operational anomalies is of upmost interest. Here, noise diagnostics — the analysis of small stationary deviations of local neutron flux around its time-averaged value — is employed aiming to unfold from detector readings the nature and location of driving perturbations. Given that in-core instrumentation of western-type light-water reactors are scarce in number of detectors, rendering formal inversion of the reactor transfer function impossible, we propose to utilise advancements in Machine Learning and Deep Learning for the task of unfolding. This work presents an approach to such a task doing so in the presence of multiple and simultaneously occurring perturbations or anomalies. A voxel-wise semantic segmentation network is proposed to determine the nature and sourcelocation of multiple and simultaneously occurring perturbations in the frequency domain. A diffusion-based core simulation tool has been employed to provide simulated training data for two reactors. Additionally, we work towards the application of the aforementioned approach to real measurements, introducing a self-supervised domain adaptation procedure to align the representation distributions of simulated and real plant measurements

G band atmospheric radars: new frontiers in cloud physics

Clouds and associated precipitation are the largest source of uncertainty in current weather and future climate simulations. Observations of the microphysical, dynamical and radiative processes that act at cloud scales are needed to improve our understanding of clouds. The rapid expansion of ground-based super-sites and the availability of continuous profiling and scanning multi-frequency radar observations at 35 and 94 GHz have significantly improved our ability to probe the internal structure of clouds in high temporal-spatial resolution, and to retrieve quantitative cloud and precipitation properties. However, there are still gaps in our ability to probe clouds due to large uncertainties in the retrievals. The present work discusses the potential of G band (frequency between 110 and 300 GHz) Doppler radars in combination with lower frequencies to further improve the retrievals of microphysical properties. Our results show that, thanks to a larger dynamic range in dual-wavelength reflectivity, dual-wavelength attenuation and dual-wavelength Doppler velocity (with respect to a Rayleigh reference), the inclusion of frequencies in the G band can significantly improve current profiling capabilities in three key areas: boundary layer clouds, cirrus and mid-level ice clouds, and precipitating snow

G band atmospheric radars: New frontiers in cloud physics

Clouds and associated precipitation are the largest source of uncertainty in current weather and future climate simulations. Observations of the microphysical, dynamical and radiative processes that act at cloud scales are needed to improve our understanding of clouds. The rapid expansion of ground-based super-sites and the availability of continuous profiling and scanning multi-frequency radar observations at 35 and 94 GHz have significantly improved our ability to probe the internal structure of clouds in high temporal-spatial resolution, and to retrieve quantitative cloud and precipitation properties. However, there are still gaps in our ability to probe clouds due to large uncertainties in the retrievals. The present work discusses the potential of G band (frequency between 110 and 300 GHz) Doppler radars in combination with lower frequencies to further improve the retrievals of microphysical properties. Our results show that, thanks to a larger dynamic range in dual-wavelength reflectivity, dual-wavelength attenuation and dual-wavelength Doppler velocity (with respect to a Rayleigh reference), the inclusion of frequencies in the G band can significantly improve current profiling capabilities in three key areas: boundary layer clouds, cirrus and mid-level ice clouds, and precipitating snow. © 2014 Author(s)

Nanoscale processes during the interaction of aluminosilicate and carbonate mineral surfaces with acid mine drainage (AMD)

Depto. de Mineralogía y PetrologíaFac. de Ciencias GeológicasTRUEpu

Virtual reality rehabilitation system for neuropathic pain and motor dysfunction in spinal cord injury patients

Spinal cord injury (SCI) causes both lower limb motor dysfunction and associated neuropathic pain. Although these two conditions share related cortical mechanisms, different interventions are currently used to treat each condition. With intensive training using entertaining virtual reality (VR) scenarios, it may be possible to reshape cortical networks thereby reducing neuropathic pain and improving motor function. We have created the first VR training system combining action observation and execution addressing lower limb function in incomplete SCI (iSCI) patients. A particular feature of the system is the use of size-adjustable shoes with integrated motion sensors. A pilot single-case clinical study is currently being conducted on six iSCI patients. Two patients tested to date were highly motivated to perform and reported improved physical well-being. They improved in playing skill and in controlling the virtual lower limbs. There were post-intervention indications of neuropathic pain decrease, muscle strength increase, faster walking speed and improved performance on items relevant for ambulation. In addition functional MRI before and after treatment revealed a decreased activation pattern. We interpret this result as an improvement of neuronal synergies for this task. These results suggest that our VR system may be beneficial for both reducing neuropathic pain and improving motor function in iSCI patients