Forecasting wind power production from a wind farm using the RAMS model

The importance of wind power forecast is commonly recognized because it represents a useful tool for grid integration and facilitates the energy trading. This work considers an example of power forecast for a wind farm in the Apennines in Central Italy. The orography around the site is complex and the horizontal resolution of the wind forecast has an important role. To explore this point we compared the performance of two 48 h wind power forecasts using the winds predicted by the Regional Atmospheric Modeling System (RAMS) for the year 2011. The two forecasts differ only for the horizontal resolution of the RAMS model, which is 3 km (R3) and 12 km (R12), respectively. Both forecasts use the 12 UTC analysis/forecast cycle issued by the European Centre for Medium range Weather Forecast (ECMWF) as initial and boundary conditions. As an additional comparison, the results of R3 and R12 are compared with those of the ECMWF Integrated Forecasting System (IFS), whose horizontal resolution over Central Italy is about 25 km at the time considered in this paper. Because wind observations were not available for the site, the power curve for the whole wind farm was derived from the ECMWF wind operational analyses available at 00:00, 06:00, 12:00 and 18:00 UTC for the years 2010 and 2011. Also, for R3 and R12, the RAMS model was used to refine the horizontal resolution of the ECMWF analyses by a two-years hindcast at 3 and 12 km horizontal resolution, respectively. The R3 reduces the RMSE of the predicted wind power of the whole 2011 by 5% compared to R12, showing an impact of the meteorological model horizontal resolution in forecasting the wind power for the specific site

The impact of global navigation satellite system (GNSS) zenith total delay data assimilation on the short-term precipitable water vapor and precipitation forecast over Italy using the Weather Research and Forecasting (WRF) model

The impact of assimilating GNSS-ZTD (global navigation satellite system–zenith total delay) on the precipitable water vapor and precipitation forecast over Italy is studied for the month of October 2019, which was characterized by several moderate to intense precipitation events, especially over northwestern Italy. The WRF (Weather Research and Forecasting) model, version 4.1.3, is used with its 3D-Var data assimilation system to assimilate ZTD observations from 388 GNSS receivers distributed over the country. The dataset was built collecting data from all the major national and regional GNSS permanent networks, achieving dense coverage over the whole area. The water vapor forecast is verified for the forecast hours of 1–6 h after the last data assimilation time. Results show that WRF underestimates the atmospheric water vapor content for the period, and GNSS-ZTD data assimilation improves this underestimation. The precipitation forecast is verified in the phases of 0–3 and 3–6 h after the last data assimilation time using more than 3000 rain gauges spread over Italy. The application of GNSS-ZTD data assimilation to a case study improved the precipitation forecast by increasing the rainfall maximum and by better focusing the precipitation pattern over northeastern Italy, with the main drawback being the prediction of false alarms. Considering the study over the whole period, GNSS-ZTD data assimilation had a positive impact on rainfall forecast, with an improvement in the performance up to 6 h and with statistically significant results for moderate to intense rainfall thresholds (25–30 mm (3 h)−1).</p

Improvement of Solar and Wind forecasting in southern Italy through a multi-model approach: preliminary results

The improvement of the Solar and Wind short-term forecasting represents a critical goal for the weather prediction community and is of great importance for a better estimation of power production from solar and wind farms. <br><br> In this work we analyze the performance of two deterministic models operational at ISAC-CNR for the prediction of short-wave irradiance and wind speed, at two experimental sites in southern Italy. <br><br> A post-processing technique, i.e the multi-model, is adopted to improve the performance of the two mesoscale models. <br><br> The results show that the multi-model approach produces a significant error reduction with respect to the forecast of each model. The error is reduced up to 20  % of the model errors, depending on the parameter and forecasting time

Three-model ensemble wind prediction in southern Italy

Quality of wind prediction is of great importance since a good wind forecast allows the prediction of available wind power, improving the penetration of renewable energies into the energy market. Here, a 1-year (1 December 2012 to 30 November 2013) three-model ensemble (TME) experiment for wind prediction is considered. The models employed, run operationally at National Research Council &ndash; Institute of Atmospheric Sciences and Climate (CNR-ISAC), are RAMS (Regional Atmospheric Modelling System), BOLAM (BOlogna Limited Area Model), and MOLOCH (MOdello LOCale in <i>H</i> coordinates). The area considered for the study is southern Italy and the measurements used for the forecast verification are those of the GTS (Global Telecommunication System). Comparison with observations is made every 3 h up to 48 h of forecast lead time. <br><br> Results show that the three-model ensemble outperforms the forecast of each individual model. The RMSE improvement compared to the best model is between 22 and 30 %, depending on the season. It is also shown that the three-model ensemble outperforms the IFS (Integrated Forecasting System) of the ECMWF (European Centre for Medium-Range Weather Forecast) for the surface wind forecasts. Notably, the three-model ensemble forecast performs better than each unbiased model, showing the added value of the ensemble technique. Finally, the sensitivity of the three-model ensemble RMSE to the length of the training period is analysed

Multi-instrumental Analysis of the Extreme Meteorological Event Occurred in Matera (Italy) on November 2019

Most of the municipalities of the Italian territory are located in areas of high hydrogeological risk, i.e. exposed to flooding and landslides. Consequently, part of the existing cultural heritage on the national territory is located in areas subject to flood risk, which compromises the accessibility, preservation and integrity of cultural heritage. As an example, we consider a single flood event that occurred in southern Italy on November 11th and 12th, 2019, which mainly affected the city of Matera and its surroundings. This episode appears to be significant for the violence of the phenomenon that led to considerable quantities of water flowing inside the city, a UNESCO World Heritage Site, causing damage to buildings, including historical ones. The event has been analysed using both meteorology and geomatic technologies, to have an overview on spatial and temporal evolution of the phenomenon. Global Navigation Satellite System Zenith Total Delay (GNSS-ZTD) data obtained by receivers located around the city of Matera, were compared with measurements from ground-based devices (i.e. weather stations), Numerical Weather Prediction (NWP) models, and ERA5 reanalysis. To assess the extent of the flood and show the flooded areas, the images provided by the Sentinel-1 Synthetic Aperture Radar (SAR) were used, isolating and analyzing the images captured before and after the event. Finally, through a digital terrain model, developed using Agisoft Metashape software from satellite images, the morphology of Matera was recreated to evidence the areas of accumulation of water. Once all the information was obtained, the data correlated showed an overall view of the event

Potential risk factors for the development of acute renal failure in preterm newborn infants: a case-control study

Aims: To determine in a case-control study possible associations between the development of acute renal failure in preterm newborns and therapeutic interventions, particularly drug treatments. Methods: The study population was 172 preterm infants of <38 weeks gestation; 71 had acute renal failure and 101 were controls closely matched for gestational age and birth weight. Maternal and neonatal information was collected for both groups through questionnaires and interviews. Routine data on renal variables were also collected. Univariate and multivariate logistic regression analyses were performed. Results: Very low birthweight infants were at high risk of acute renal failure (79% of cases were <1500 g). However, the acute renal failure was transient. Mothers of infants with acute renal failure received more drugs during pregnancy and delivery (mainly antibiotics and non-steroidal anti-inflammatory drugs). Of the possible therapeutic interventions, intubation, catheterisation, and phototherapy were mainly applied to case subjects. A low Apgar score and patent ductus arteriosus were diagnosed in a greater percentage of neonates with acute renal failure. Moreover, in the first few days of life and before diagnosis of acute renal failure, case subjects received more drugs (antibiotics, non-steroidal anti-inflammatory drugs, and diuretics) and for a longer time. In the multivariate logistic analysis, medullary hyperechogenicity (odds ratio (OR) 4.491; 95% confidence interval (CI) 1.879 to 10.731) and ceftazidime administration (OR 5.082; 95% CI 1.493 to 17.297) were associated with a greater risk of acute renal failure. Conclusions: The results suggest the need for careful monitoring of very low birthweight infants and attention to drug treatments, as it is difficult to differentiate between normality and renal failure in the first few days of life

Meteorology and aerosol studies at a Black Sea coastal site

Coastal meteorology is characterised with complex physical and chemical processes related to aerosols exchange and transport. Aerosol measurements in Bulgaria are rare in areas outside big cities which makes extremely valuable the 3-year effort of a bilateral project between BAS and CNR to perform experimental campaigns at a rural Black Sea coastal site. Not only the concentration of different fractions of PM, but also the chemical composition of aerosols was studied during three short experimental studies in 2016, 2017 and 2018

RAPPORTO DI FINE CAMPAGNA Campagna Oceanografica I-AMICA_2013_01 Progetto PON I-AMICA OR.4.4 Foce del Fiume Volturno Golfo di Gaeta, Mar Tirreno

La campagna oceanografica I-AMICA_2013_01, svoltasi dal 29 gennaio al 11 febbraio 2013, costituisce una parte integrante delle attivit\ue0 di ricerca previste dall\u2019Obiettivo Realizzativo OR4 - Attivit\ue0 4.4 (Processi interfaccia biosfera idrosfera e funzionalit\ue0 degli ecosistemi costieri) del Progetto PON03 di potenziamento strutturale I-AMICA (Infrastruttura di Alta tecnologia per il Monitoraggio Integrato Climatico-Ambientale; http://www.i-amica.it). L\u2019attivit\ue0 di ricerca di monitoraggio ambientale integrato della foce del Fiume Volturno, attraverso studi del fondo mare e della colonna d\u2019acqua, vuole chiarire quali interazioni incorrono a scala stagionale tra il suddetto fiume, che interessa un bacino idrografico di circa 6000 km2, ed un tratto della zona costiera del Golfo di Gaeta fortemente antropizzato. In particolare, alcune delle attivit\ue0 svolte nel corso della campagna oceanografica, rientrano nel monitoraggio stagionale delle variazioni dell\u2019ecosistema marino\u2010costiero alla Foce del Fiume Volturno (Golfo di Gaeta - Tirreno centrale). Le operazioni sono state effettuate utilizzando la nave oceanografica Urania del CNR (Fig. 1), ed hanno avuto una durata di 14 giorni (29 gennaio al 11 febbraio 2013) con imbarco e sbarco al porto di Napoli. Il personale presente a bordo comprende ufficiali e personale di bordo, tecnici di laboratorio e personale scientifico afferente a IAMC-CNR di Napoli, ISMAR di Bologna, ISAC di Lamezia Terme, INGV di Roma, Universit\ue0 di Palermo e Universit\ue0 Roma3. La zona di lavoro ha compreso il settore marino di piattaforma continentale del Golfo di Gaeta prospiciente la Foce del Fiume Volturno, ubicato tra l\u2019isobata dei \u201310 e \u20132 0 0 m per un totale di circa 300 Kmq. In particolare la superficie investigata \ue8 distribuita in un settore che si estende per circa 8 mn dall\u2019attuale linea di costa verso mare e per 6.5 mn da nord verso sud parallelamente alla linea di costa