Analysis of Catania Flash Flood Case Study by Using Combined Microwave and Infrared Technique

Abstract In this paper, the analysis of an extreme convective event atypical for the winter season, which occurred on 21 February 2013 on the east coast of Sicily and caused a flash flood over Catania, is presented. In just 1 h, more than 50 mm of precipitation was recorded, but it was not forecast by numerical weather prediction (NWP) models and, consequently, no severe weather warnings were sent to the population. The case study proposed is first examined with respect to the synoptic situation and then analyzed by means of two algorithms based on satellite observations: the Cloud Mask Coupling of Statistical and Physical Methods (MACSP) and the Precipitation Evolving Technique (PET), developed at the National Research Council of Italy. Both of the algorithms show their ability in the near-real-time monitoring of convective cell formation and their rapid evolution. As quantitative precipitation forecasts by NWP could fail, especially for atypical convective events like in Catania, tools like MACSP and PET shall be adopted by civil protection centers to monitor the real-time evolution of deep convection events in aid to the severe weather warning service

Aerodynamics of bridge hangers in smooth and turbulent flow and implications on aeroelastic stability

The risk of large amplitude vibrations of bridge hangers due to galloping instabilities has posed a challenge to the engineering and research community. Galloping vibrations can lead to serviceability problems and reduce fatigue life. A number of aeroelastic models have been developed to predict the unstable behavior and to design counteracting measures, i.e. shape modifications and increase of structural damping. In particular, the majority of such models is based on the application of the quasi-steady theory to a 2-D model of the cable vibrating in 1 DoF, in-plane, out-of-plane and torsional. Three key issues are relevant to the sectional galloping stability assessment of dry bridge hangers: (i) the complex aerodynamics depending, on the flow conditions (smooth or turbulent), (ii) the deviation of the cable geometry with respect to that of a perfect circular cylinder, and (iii) the choice of a proper stability criterion. In this paper, aerodynamic force coefficients of a real HDPE plain cable cover were measured in the wind tunnel in smooth and turbulent conditions are presented. Cable irregularities (surface roughness, section distortion and axis curvature) are characterized and correlated to the measured aerodynamics. Then, the aerodynamic coefficients are used to investigate aerodynamic stability using different models from the literature. A comparison of the results has highlighted that the use of MDoF models is not justified, as 1-DoF models are sufficient to predict instability; furthermore, it was found that cable irregularities and flow conditions can have a strong influence on the prediction of aerodynamic stability

Combined IASI-NG and MWS observations for the retrieval of cloud liquid and ice water path: a deep learning artificial intelligence approach

A neural network (NN) approach is proposed to combine future infrared (IASI-NG) and microwave (MWS) observations to retrieve cloud liquid and ice water path. The methodology is applied to simulated IASI-NG and MWS observations in the period January–October 2019. IASI-NG and MWS observations are simulated globally at synoptic hours (00:00, 06:00, 12:00, 18:00 UTC) and on a regular spatial grid (0.125° × 0.125°) from ECMWF 5-generation reanalysis (ERA5). The state-of-the-art σ-IASI and RTTOV radiative transfer codes are used to simulate IASI-NG and MWS observations, respectively, from the earth's state vector given by ERA5. A principal component analysis of the simulated IASI-NG observations is performed. Accordingly, a NN is developed to retrieve cloud liquid and ice water path from a combination of 24 MWS channels and 30 IASI-NG PCs. Validation indicates that this combination results in liquid and ice water path retrievals with overall accuracy of 1.85 10 −2 kg/m 2 and 1.18 10 −2 kg/m 2 , respectively, and 0.97 correlation with respect to reference values. The root-mean-square error (RMSE) for CLWP results in about 30% of the mean value (5.91 10 −2 kg/m 2 ) and 22% of the variability (1-sigma). Similarly, the RMSE for CIWP results in about 41% of the mean value (2.91 10 −2 kg/m 2 ) and 22% of the variability. Two more NN are developed, retrieving cloud liquid and ice water path from microwave observations only (24 MWS channels) and infrared observations only (30 IASI-NG PCs), demonstrating quantitatively the advantage of using the combination of infrared and microwave observations with respect to either one alone

Systematic variation of the stellar Initial Mass Function with velocity dispersion in early-type galaxies

An essential component of galaxy formation theory is the stellar initial mass function (IMF), that describes the parent distribution of stellar mass in star forming regions. We present observational evidence in a sample of early-type galaxies (ETGs) of a tight correlation between central velocity dispersion and the strength of several absorption features sensitive to the presence of low-mass stars. Our sample comprises ~40,000 ETGs from the SPIDER survey (z<0.1). The data, extracted from the Sloan Digital Sky Survey, are combined, rejecting both noisy data, and spectra with contamination from telluric lines, resulting in a set of 18 stacked spectra at high signal-to-noise ratio (S/N> 400 per A). A combined analysis of IMF-sensitive line strengths and spectral fitting is performed with the latest state-of the art population synthesis models (an extended version of the MILES models). A significant trend is found between IMF slope and velocity dispersion, towards an excess of low-mass stars in the most massive galaxies. Although we emphasize that accurate values of the IMF slope will require a detailed analysis of chemical composition (such as [a/Fe] or even individual element abundance ratios), the observed trends suggest that low-mass ETGs are better fit by a Kroupa-like IMF, whereas massive galaxies require bottom-heavy IMFs, exceeding the Salpeter slope at velocity dispersions above 200km/s.Comment: 5 pages, 4 figures, accepted for publication in MNRAS Letter

A high-resolution, integrated system for rice yield forecasting at district level

To meet the growing demands from public and private stakeholders for early yield estimates, a high-resolution (2 km × 2 km) rice yield forecasting system based on the integration of the WARM model and remote sensing (RS) technologies was developed. RS was used to identify rice-cropped area and to derive spatially distributed sowing dates, and for the dynamic assimilation of RS-derived leaf area index (LAI) data within the crop model. The system—tested for the main European rice production districts in Italy, Greece, and Spain—performed satisfactorily; >66% of the inter-annual yield variability was explained in six out of eight combinations of ecotype × district, with a maximum of 89% of the variability explained for the ‘Tropical Japonica’ cultivars in the Vercelli district (Italy). In seven out of eight cases, the assimilation of RS-derived LAI improved the forecasting capability, with minor differences due to the assimilation technology used (updating or recalibration). In particular, RS data reduced uncertainty by capturing factors that were not properly reproduced by the simulation model (given the uncertainty due to large-area simulations). The system, which is an extension of the one used for rice within the EC-JRC-MARS forecasting system, was used pre-operationally in 2015 and 2016 to provide early yield estimates to private companies and institutional stakeholders within the EU-FP7 ERMES project

Oxidoreductases and metal cofactors in the functioning of the earth

: Life sustains itself using energy generated by thermodynamic disequilibria, commonly existing as redox disequilibria. Metals are significant players in controlling redox reactions, as they are essential components of the engine that life uses to tap into the thermodynamic disequilibria necessary for metabolism. The number of proteins that evolved to catalyze redox reactions is extraordinary, as is the diversification level of metal cofactors and catalytic domain structures involved. Notwithstanding the importance of the topic, the relationship between metals and the redox reactions they are involved in has been poorly explored. This work reviews the structure and function of different prokaryotic organometallic-protein complexes, highlighting their pivotal role in controlling biogeochemistry. We focus on a specific subset of metal-containing oxidoreductases (EC1 or EC7.1), which are directly involved in biogeochemical cycles, i.e., at least one substrate or product is a small inorganic molecule that is or can be exchanged with the environment. Based on these inclusion criteria, we select and report 59 metalloenzymes, describing the organometallic structure of their active sites, the redox reactions in which they are involved, and their biogeochemical roles

Fog Detection Based on Meteosat Second Generation-Spinning Enhanced Visible and InfraRed Imager High Resolution Visible Channel

In this study, the Meteosat Second Generation (MSG)-Spinning Enhanced Visible and Infrared Imager (SEVIRI) High Resolution Visible channel (HRV) is used in synergy with the narrow band MSG-SEVIRI channels for daytime fog detection. A new algorithm, named MSG-SEVIRI SatFog, has been designed and implemented. MSG-SEVIRI SatFog provides the indication of the presence of fog in near real time and at the high spatial resolution of the HRV channel. The HRV resolution is useful for detecting small scale daytime fog that would be missed in the MSG-SEVIRI low spatial resolution channels. By combining textural, physical and tonal tests, a distinction between fog and low stratus is performed for pixels identified as low/middle clouds or clear by the Classification-MAsk Coupling of Statistical and Physical Methods (C-MACSP) cloud detection algorithm. Suitable thresholds have been determined using a specific dataset covering different geographical areas, seasons and time of the day. MSG-SEVIRI SatFog is evaluated against METeorological Aerodrome Reports (METAR) data observations. Evaluation results in an accuracy of 69.9%, a probability of detection of 68.7%, a false alarm ratio of 31.3% and a probability of false detection of 30.0%

Benchmark on the Aerodynamics of a Rectangular 5:1 Cylinder: An overview after the first four years of activity

In July 2008, a benchmark study on the aerodynamics of a stationary rectangular cylinder with chord-to- depth ratio equal to 5 (BARC) was launched. This paper gives an outline of the state of the art on the aerodynamics of 5:1 rectangular cylinders prior to the starting of BARC, and summarizes the results obtained by the contributors during the first four years of activity. The results of about 70 realizations of the BARC flow configuration obtained under a nominally common set-up in both wind tunnel experiments and numerical simulations are compared among themselves and with the data available in the literature prior to BARC, in terms of bulk parameters, flow and aerodynamic load statistics, pressure and force spanwise correlations. It is shown that the near wake flow, the base pressure and, hence, the drag coefficient obtained in the different flow realizations are in very good agreement. Conversely, the flow features along the cylinder lateral surfaces and, hence, the lift, are strongly sensitive to set-up and modelling, leading to a significant dispersion of both wind tunnel measurements and numerical predictions. Finally, a possible asymmetry of the time averaged flow has been recognized both in wind tunnel tests and in numerical simulation

Downstream Services for Rice Crop Monitoring in Europe: From Regional to Local Scale

The ERMES agromonitoring system for rice cultivations integrates EO data at different resolutions, crop models, and user-provided in situ data in a unified system, which drives two operational downstream services for rice monitoring. The first is aimed at providing information concerning the behavior of the current season at regional/rice district scale, while the second is dedicated to provide farmers with field-scale data useful to support more efficient and environmentally friendly crop practices. In this contribution, we describe the main characteristics of the system, in terms of overall architecture, technological solutions adopted, characteristics of the developed products, and functionalities provided to end users. Peculiarities of the system reside in its ability to cope with the needs of different stakeholders within a common platform, and in a tight integration between EO data processing and information retrieval, crop modeling, in situ data collection, and information dissemination. The ERMES system has been operationally tested in three European rice-producing countries (Italy, Spain, and Greece) during growing seasons 2015 and 2016, providing a great amount of near-real-time information concerning rice crops. Highlights of significant results are provided, with particular focus on real-world applications of ERMES products and services. Although developed with focus on European rice cultivations, solutions implemented in the ERMES system can be, and are already being, adapted to other crops and/or areas of the world, thus making it a valuable testing bed for the development of advanced, integrated agricultural monitoring systems