Detecting extreme rainfall events using the WRF-ERDS workflow: the 15 July 2020 Palermo case study

In this work, we describe the integration of Weather and Research Forecasting (WRF) forecasts produced by CIMA Research Foundation within ITHACA Extreme Rainfall Detection System (ERDS) to increase the forecasting skills of the overall early warning system. The entire workflow is applied to the heavy rainfall event that affected the city of Palermo on 15 July 2020, causing urban flooding due to an exceptional rainfall amount of more than 130 mm recorded in about 2.5 h. This rainfall event was not properly forecasted by meteorological models operational at the time of the event, thus not allowing to issue an adequate alert over that area. The results highlight that the improvement in the quantitative precipitation scenario forecast skills, supported by the adoption of the H2020 LEXIS computing facilities and by the assimilation of in situ observations, allowed the ERDS system to improve the prediction of the peak rainfall depths, thus paving the way to the potential issuing of an alert over the Palermo area

Heavy Rainfall Identification within the Framework of the LEXIS Project: The Italian Case Study

LEXIS (Large-scale EXecution for Industry and Society) H2020 project is currently developing an advanced system for Big Data analysis that takes advantage of interacting large-scale geographically-distributed HPC infrastructure and cloud services. More specifically, LEXIS Weather and Climate Large-Scale Pilot workflows ingest data coming from different sources, like global/regional weather models, conventional and unconventional meteorological observations, application models and socio-economic impact models, in order to provide enhanced meteorological information at the European scale. In the framework of LEXIS Weather and Climate Large-scale Pilot, CIMA Research Foundation is running a 7.5 km resolution WRF (Weather Research and Forecasting) model with European coverage, radar assimilation over the Italian area, and daily updates with 48 hours forecast. WRF data is then processed by ITHACA ERDS (Extreme Rainfall Detection System - http://erds.ithacaweb.org), an early warning system for the monitoring and forecasting of heavy rainfall events. The WRF model provides more detailed information compared to GFS (Global Forecast Systems) data, the most widely used source of rainfall forecasts, implemented in ERDS also. The entire WRF - ERDS workflow was applied to two of the most severe heavy rainfall events that affected Italy in 2020. The first case study is related to an intense rainfall event that affected Toscana during the afternoon and the evening of 4th June 2020. In this case, the Italian Civil Protection issued an orange alert for thunderstorms, on a scale from yellow (low) to orange (medium) to red (high). In several locations of the northern part of the Region more than 100 mm of rainfall were recorded in 3 hours, corresponding to an estimated return period equal to or greater than 200 years. As far as the 24-hours time interval concerns, instead, the estimated return period decreases to 10-50 years. Despite the slight underestimation, WRF model was able to properly forecast the spatial distribution of the rainfall pattern. In addition, thanks to WRF data, precise information about the locations that would be affected by the event were available in the early morning, several hours before the event affected these areas. The second case study is instead related to the heavy rainfall event that affected Palermo (Southern Italy) during the afternoon of 15th July 2020. According to SIAS (Servizio Informativo Agrometeorologico Siciliano) more than 130 mm of rain fell in about 2.5 hours, producing widespread damages due to urban flooding phenomena. The event was not properly forecasted by meteorological models operational at the time of the event, and the Italian Civil Protection did not issue an alert on that area (including Palermo). During that day, in fact, only a yellow alert for thunderstorms was issued on northern-central and western Sicily. Within LEXIS, no alert was issued using GFS data due to the severe underestimation of the amount of forecasted rainfall. Conversely, a WRF modelling experiment (three nested domain with 22.5, 7.5 and 2.5 km grid spacing, innermost over Italy) was executed, by assimilating the National radar reflectivity mosaic and in situ weather stations from the Italian Civil Protection Department, and it resulted in the prediction of a peak rainfall depth of about 35 mm in 1 hour and 55 mm in 3 hours, roughly 30 km far apart the actual affected area, thus values supportive at least a yellow alert over the Palermo area. Obtained results highlight how improved rainfall forecast, made available thanks to the use of HPC resources, significantly increases the capabilities of an operational early warning system in the extreme rainfall detection. Global-scale low-resolution rainfall forecasts like GFS one are in fact widely known as good sources of information for the identification of large-scale precipitation patterns but lack precision for local-scale applications

Theoretically-Driven Infrastructure for Supporting Health Care Teams Training at a Military Treatment Facility

Designated a Department of Defense Team Resource Center (TRC) in 2008, Naval Medical Center Portsmouth (NMCP) currently hosts three tri-service health care teams training courses annually. Each consists of didactic learning coupled with simulation-based training exercises to provide an interactive educational experience for health care professionals. Simulated cases are developed to reinforce specific teamwork skills and behaviors, and to incorporate a variety of technologies including standardized patients, manikins, and virtual reality. The course is also the foundation of a research program designed to explore applications of modeling and simulation for enhanced team training in health care. The TRC has adopted two theoretical frameworks for evaluating training efficacy and outcomes, and has used these frameworks to guide a systematic reconfiguration of the infrastructure supporting health care teams training at NMCP

Theoretically-Driven Infrastructure for Supporting Healthcare Teams Training at a Military Treatment Facility

The Team Resource Center (TRC) at Naval Medical Center Portsmouth (NMCP) currently hosts a tri-service healthcare teams training course three times annually . The course consists of didactic learning coupled with simulation exercises to provide an interactive educational experience for healthcare professionals. The course is also the foundation of a research program designed to explore the use of simulation technologies for enhancing team training and evaluation. The TRC has adopted theoretical frameworks for evaluating training readiness and efficacy, and is using these frameworks to guide a systematic reconfiguration of the infrastructure supporting healthcare teams training and research initiatives at NMCP

Beidelita de la mina Dos Amigos, Los Menucos, prov. de Río Negro, Argentina

The presence of beidellite developed in veins from the core of the fluorite vein Dos Amigos (Prov. de Rio Negro) is cited. It was studied bv means of XRD, optical microscopy, SEM, TG, DTA, IR and Chemical analysis. The beidellite is associated to fluorite and quartz, with subordinated kaolinite. It has a good crystallinity. It is considered to have been formed in the latest stage of mineralization, from the fluids that give rise the fluorite vein

BPD and BPD-DS Concerns and Results

none5Papadia FS; Elghadban H; Weiss A; Parodi C; Pagliardi F.Papadia, FRANCESCO SAVERIO; Elghadban, H; Weiss, Andrea; Parodi, Corrado; Pagliardi, Francesc

On the parametrization of lateral dose profiles in proton radiation therapy.

Abstract Purpose The accurate evaluation of the lateral dose profile is an important issue in the field of proton radiation therapy. The beam spread, due to Multiple Coulomb Scattering (MCS), is described by the Moliere's theory. To take into account also the contribution of nuclear interactions, modern Treatment Planning Systems (TPSs) generally approximate the dose profiles by a sum of Gaussian functions. In this paper we have compared different parametrizations for the lateral dose profile of protons in water for therapeutical energies: the goal is to improve the performances of the actual treatment planning. Methods We have simulated typical dose profiles at the CNAO (Centro Nazionale di Adroterapia Oncologica) beamline with the FLUKA code and validated them with data taken at CNAO considering different energies and depths. We then performed best fits of the lateral dose profiles for different functions using ROOT and MINUIT. Results The accuracy of the best fits was analyzed by evaluating the reduced χ2, the number of free parameters of the functions and the calculation time. The best results were obtained with the triple Gaussian and double Gaussian Lorentz–Cauchy functions which have 6 parameters, but good results were also obtained with the so called Gauss–Rutherford function which has only 4 parameters. Conclusions The comparison of the studied functions with accurate and validated Monte Carlo calculations and with experimental data from CNAO lead us to propose an original parametrization, the Gauss–Rutherford function, to describe the lateral dose profiles of proton beams