Extension of the Discrete-Ordinates Transport Solver IDT to Regular Two-Dimensional Triangular Meshes

In this work, the Integro-Differential Transport solver (IDT), which is one of the transport solvers available in the APOLLO3(R) lattice code, has been extended to handle 2D unstructured meshes. In particular, the previously implemented method of short characteristics (MoSC) used to solve for the spatial variable in the framework of an SN approach has been extended to triangular cells which represent the natural discretization for calculating the hexagonal lattices present in fast reactors. The coefficients of the collision-probability matrices have been evaluated by means of a split-cell algorithm, specialized for dealing with different orientations of the triangle with respect to each discrete ordinate of the SN sweeping. A new sweeping routine for unstructured meshes has been added to IDT. The correct implementation of the method and its robustness with respect to the skewness and the optical thickness of the triangle has been verified. The method of manufactured solutions has been employed to obtain a numerical estimate of the spatial convergence order of the method. The same version of the MoSC has then been implemented in MINARET, another solver available in APOLLO3(R). Finally, the modified IDT applied to an unstructured mesh for the C5G7 benchmark has been successfully benchmarked against MC calculations, and the modified MINARET has been applied to a neutron transport calculation for the RJH research reactor

Plasma protein's glycation is decreased in Sprague Dawley rats under caloric restriction.

Different dietary regimens were applied to three cohorts of rats. The first was fed ad libitum every day (AL), the second was fed ad libitum every other day (EOD) and the third was fed a diet equivalent to 60% of the caloric intake (60% CI) of the AL cohort. Levels of stable early glycation products in plasma proteins were then measured according to two different methods, Glycation of plasma proteins progressively increased in AL animals belonging to the 2-12 month age interval, while it showed a less pronounced age-dependent increase in EOD and 60% CI animals. The lowest degree of glycation was detected 2-3 months after the beginning of caloric restriction, After 12 months of age a lower level of glycation was detected in 60% CI rats than in EOD animals, Body weight was lower in restricted animals than in AL animals and was lowest in 60% CI rats. During the life span, glycemia was lower in fasting 60% CI than in EOD or AL rats

Finsler geodesics in the presence of a convex function and their applications

We obtain a result about the existence of only a finite number of geodesics between two fixed non-conjugate points in a Finsler manifold endowed with a convex function. We apply it to Randers and Zermelo metrics. As a by-product, we also get a result about the finiteness of the number of lightlike and timelike geodesics connecting an event to a line in a standard stationary spacetime.Comment: 16 pages, AMSLaTex. v2 is a minor revision: title changed, references updated, typos fixed; it matches the published version. This preprint and arXiv:math/0702323v3 [math.DG] substitute arXiv:math/0702323v2 [math.DG

UV Raman lidar measurements of relative humidity for the characterization of cirrus cloud microphysical properties

Abstract. Raman lidar measurements performed in Potenza by the Raman lidar system BASIL in the presence of cirrus clouds are discussed. Measurements were performed on 6 September 2004 in the frame of the Italian phase of the EAQUATE Experiment. The major feature of BASIL is represented by its capability to perform high-resolution and accurate measurements of atmospheric temperature and water vapour, and consequently relative humidity, both in daytime and night-time, based on the application of the rotational and vibrational Raman lidar techniques in the UV. BASIL is also capable to provide measurements of the particle backscatter and extinction coefficient, and consequently lidar ratio (at the time of these measurements, only at one wavelength), which are fundamental to infer geometrical and microphysical properties of clouds. A case study is discussed in order to assess the capability of Raman lidars to measure humidity in presence of cirrus clouds, both below and inside the cloud. While air inside the cloud layers is observed to be always under-saturated with respect to water, both ice super-saturation and under-saturation conditions are found inside these clouds. Upper tropospheric moistening is observed below the lower cloud layer. The synergic use of the data derived from the ground based Raman Lidar and of spectral radiances measured by the NAST-I Airborne Spectrometer allows the determination of the temporal evolution of the atmospheric cooling/heating rates due to the presence of the cirrus cloud. Lidar measurements beneath the cirrus cloud layer have been interpreted using a 1-D cirrus cloud model with explicit microphysics. The 1-D simulations indicate that sedimentation-moistening has contributed significantly to the moist anomaly, but other mechanisms are also contributing. This result supports the hypothesis that the observed mid-tropospheric humidification is a real feature which is strongly influenced by the sublimation of precipitating ice crystals. Results illustrated in this study demonstrate that Raman lidars, like the one used in this study, can resolve the spatial and temporal scales required for the study of cirrus cloud microphysical processes and appear sensitive enough to reveal and quantify upper tropospheric humidification associated with cirrus cloud sublimation

Kalman filter physical retrieval of surface emissivity and temperature from geostationary infrared radiances

The high temporal resolution of data acquisition by geostationary satellites and their capability to resolve the diurnal cycle allows for the retrieval of a valuable source of information about geophysical parameters. In this paper, we implement a Kalman filter approach to applying tempo-ral constraints on the retrieval of surface emissivity and temperature from radiance measurements made from geostationary platforms. Although we consider a case study in which we apply a strictly temporal constraint alone, the methodology will be presented in its general four-dimensional, i.e., space-time, setting. The case study we consider is the retrieval of emissivity and surface temperature from SEVIRI (Spinning Enhanced Visible and Infrared Imager) observations over a target area encompassing the Iberian Peninsula and northwestern Africa. The retrievals are then compared with in situ data and other similar satellite products. Our findings show that the Kalman filter strategy can simultaneously retrieve surface emissivity and temperature with an accuracy of ± 0.005 and ±0.2 K, respectively

A Feedforward Neural Network Approach for the Detection of Optically Thin Cirrus From IASI-NG

The identification of optically thin cirrus is crucial for their accurate parameterization in climate and Earth's system models. This study exploits the characteristics of the infrared atmospheric sounding interferometer-new generation (IASI-NG) to develop an algorithm for the detection of optically thin cirrus. IASI-NG has been designed for the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) polar system second-generation program to continue the service of its predecessor IASI from 2024 onward. A thin-cirrus detection algorithm (TCDA) is presented here, as developed for IASI-NG, but also in parallel for IASI to evaluate its performance on currently available real observations. TCDA uses a feedforward neural network (NN) approach to detect thin cirrus eventually misidentified as clear sky by a previously applied cloud detection algorithm. TCDA also estimates the uncertainty of "clear-sky" or "thin-cirrus" detection. NN is trained and tested on a dataset of IASI-NG (or IASI) simulations obtained by processing ECMWF 5-generation reanalysis (ERA5) data with the s-IASI radiative transfer model. TCDA validation against an independent simulated dataset provides a quantitative statistical assessment of the improvements brought by IASI-NG with respect to IASI. In fact, IASI-NG TCDA outperforms IASI TCDA by 3% in probability of detection (POD), 1% in bias, and 2% in accuracy, and the false alarm ratio (FAR) passes from 0.02 to 0.01. Moreover, IASI TCDA validation against state-of-the-art cloud products from Cloudsat/CPR and CALIPSO/Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) real observations reveals a tendency for IASI TCDA to underestimate the presence of thin cirrus (POD = 0.47) but with a low FAR (0.07), which drops to 0.0 for very thin cirrus

Spectrum Synergy for Investigating Cloud Microphysics

Observations from spaceborne microwave (MW) and infrared (IR) passive sensors are the backbone of current satellite meteorology, essential for data assimilation into modern numerical weather prediction and for climate benchmarking. While MW and IR observations from space offer complementary features with respect to cloud properties, their synergy for cloud investigation is currently underexplored, despite the presence of both MW and IR sensors on operational meteorological satellites such as the EUMETSAT Polar System (EPS) MetOp series. As such, several key cloud microphysical properties are not part of the operational products available from EPS MetOp sensors. In addition, the EPS Second Generation (EPS-SG) series, scheduled for launch starting from 2024 onward, will carry sensors such as the Microwave Sounder (MWS) and IASI Next Generation (IASI-NG), enhancing spatial and spectral resolutions and thus capacity to retrieve cloud properties. This article presents the Combined MWS and IASI-NG Soundings for Cloud Properties (ComboCloud) project, funded by EUMETSAT with the overall objective to specify, prototype, and validate algorithms for the retrieval of cloud microphysical properties (e.g., water content and drop effective radius) from the synergy of passive MW and IR observations. The article presents the synergy rationale, the algorithm design, and the results obtained exploiting simulated observations from EPS and EPS-SG sensors, quantifying the benefits to be expected from the MW-IR synergy and the new generation sensors

Validation of statistical clustering on TES dataset using synthetic Martian spectra

In this work we present some results concerning the analysis of Thermal Emission Spectrometer (TES) data, looking at the methane Q-branch spectral signature at 1304 cm-1. Such analysis has been enabled by producing some synthetic spectral datasets, simulating the atmospheric and surface variability observed on Mars, excluding the high latitude regions. The use of synthetic spectra is aimed to provide a better comprehension of the influence that the atmospheric state vector and its composition have on the spectral behavior. This effort is important, because the TES data are characterized by a low resolution (10 cm-1) and a significant random and systematic noise which could, in principle, give results whose quality needs to be improved. We apply statistical clustering of the synthetic spectra to evaluate the effectiveness of detecting methane, and estimating its abundance