Search results for "Meteorological data"

showing 6 items of 6 documents

A new preprocessing tool of ECMWF data for CALMET forecasting simulations

2019

Today, strategies for emergency preparedness, in presence of accidental scenarios in high-risk plants with releases into the atmosphere, have become a priority. To achieve this goal, it is important to have forecast meteorological data in local areas to use in dispersion and transport models and so to respond in advance emergency situations. The paper reports results of research performed to develop a new tool, called FORCALM that is capable to elaborate European Centre for Medium-Range Forecasts (ECMWF) forecast data to use for simulations by CALMET/CALPUFF modeling system. A case study, relevant to an accident occurred in Mediterranean Refinery at Milazzo (Italy), has been examined to val…

Air pollution forecast meteorological data ECMWF CALMET CALPUFF.
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Mapping snow density through thermal inertia observations

2023

Snow, as a fundamental reservoir of freshwater, is a crucial natural resource. Specifically, knowledge of snow density spatial and temporal variability could improve modelling of snow water equivalent, which is relevant for managing freshwater resources in context of ongoing climate change. The possibility of estimating snow density from remote sensing has great potential, considering the availability of satellite data and their ability to generate efficient monitoring systems from space. In this study, we present an innovative method that combines meteorological parameters, satellite data and field snow measurements to estimate thermal inertia of snow and snow density at a catchment scale.…

FIS/06 - FISICA PER IL SISTEMA TERRA E PER IL MEZZO CIRCUMTERRESTREGEO/04 - GEOGRAFIA FISICA E GEOMORFOLOGIAGEO/12 - OCEANOGRAFIA E FISICA DELL'ATMOSFERASoil ScienceGeologyThermal inertia Snow density Landsat images Meteorological data Mountainous areasComputers in Earth SciencesMeteorological dataLandsat imageMountainous areaSnow densitySettore ICAR/06 - Topografia E CartografiaThermal inertia
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www.climateofburundi.org

2010

Daily rainfall and air temperature data were collected by IGEBU. For a given station, the number of missing daily rainfall data, MRDm (days), was determined for each month of the recording period. The monthly rainfall depth, Pm (mm), and the monthly number of rainy days, NRDm (days),were determined for each month with a complete record of daily rainfall data. For a given month, Pm was obtained by summing the daily rainfall depth values and NRDm was obtained by counting the number of days of the month characterized by a daily rainfall depth greater than zero. The number of missing daily temperature data, MTDm (days), was also determined for each month of the recording period. The mean of the…

Meteorological Data of Burundi Igebu Ruyigi Bujumbura Gitega Karuzi Gisozi Nyamuswaga Ruvyironza Rwegura Kirundo Ngozi Muyinga Cankuzo Kinyinya Muriza Musasa MuyagaSettore AGR/08 - Idraulica Agraria E Sistemazioni Idraulico-Forestali
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Association between climate and new daily diagnoses of COVID-19

2020

AbstractBackgroundAlthough evidence is accumulating that climate conditions may positively or negatively influence the scale of coronavirus disease 2019 (COVID-19) outbreaks, uncertainty remains concerning the real impact of climate factors on viral transmission. Methods. The number of new daily cases of COVID-19 diagnosed in Verona (Italy) was retrieved from the official website of Veneto Region, while information on daily weather parameters in the same area was downloaded from IlMeteo website, a renowned Italian technological company specialized in weather forecasts. The search period ranged between March 1 to November 11, 2020. The number of new daily COVID-19 cases and meteorological da…

Multivariate analysisCoronavirus disease 2019 (COVID-19)Leadership and ManagementStrategy and Management2020. The number of new daily COVID-19 cases and meteorological data in Verona were correlated using both univariate and multivariate analysis. Results: The number of daily COVID-19 diagnoses in Verona was positively associated with the number of days in lockdown and humidity1% decrease in humidityWind speedmin and max temperatureand influence the likelihood or course of local COVID-19 outbreaks. Preventive measuresHealth Information Managementa renowned Italian technological company specialized in weather forecasts. The search period ranged between March 1 and November 11mean air temperature1.2% and 5.4% reduction in new COVID-19 daily diagnoses. A significant difference was observed in values of all-weather parameters recorded in Verona between days with &ltHealth Policy1 km/h increase in wind speed and day with rainfall were independently associated with 1.0%Significant differencehumidityUnivariateOutbreakHumidityand inversely correlated with meanmean wind speed and number of days with rainfall. Days of lockdownwhile information on daily weather parameters in the same area was downloaded from IlMeteo websitetesting policies and hospital preparedness should be reinforced during periods of higher meteorological risk and in local environments with adverse climate conditions.Background: Although evidence is accumulating that climate conditions may positively or negatively influence the scale of coronavirus disease 2019 (COVID-19) outbreaks0.3%uncertainty remains concerning the real impact of climate factors on viral transmission. Methods: The number of new daily cases of COVID-19 diagnosed in Verona (Italy) was retrieved from the official website of Veneto RegionGeography100 or ≥100 new daily COVID-19 diagnoses. Conclusions: Climate conditions may play an essential role in conditions of viral transmissionAir temperaturemean wind speed and number of days with rainfall remained significantly associated in multivariate analysis. The four weather parameters contributed to explaining 61% of variance in new daily COVID-19 diagnoses. Each 1% increase in air temperatureBackground: Although evidence is accumulating that climate conditions may positively or negatively influence the scale of coronavirus disease 2019 (COVID-19) outbreaks uncertainty remains concerning the real impact of climate factors on viral transmission. Methods: The number of new daily cases of COVID-19 diagnosed in Verona (Italy) was retrieved from the official website of Veneto Region while information on daily weather parameters in the same area was downloaded from IlMeteo website a renowned Italian technological company specialized in weather forecasts. The search period ranged between March 1 and November 11 2020. The number of new daily COVID-19 cases and meteorological data in Verona were correlated using both univariate and multivariate analysis. Results: The number of daily COVID-19 diagnoses in Verona was positively associated with the number of days in lockdown and humidity and inversely correlated with mean min and max temperature mean wind speed and number of days with rainfall. Days of lockdown mean air temperature humidity mean wind speed and number of days with rainfall remained significantly associated in multivariate analysis. The four weather parameters contributed to explaining 61% of variance in new daily COVID-19 diagnoses. Each 1% increase in air temperature 1% decrease in humidity 1 km/h increase in wind speed and day with rainfall were independently associated with 1.0% 0.3% 1.2% and 5.4% reduction in new COVID-19 daily diagnoses. A significant difference was observed in values of all-weather parameters recorded in Verona between days with <100 or ≥100 new daily COVID-19 diagnoses. Conclusions: Climate conditions may play an essential role in conditions of viral transmission and influence the likelihood or course of local COVID-19 outbreaks. Preventive measures testing policies and hospital preparedness should be reinforced during periods of higher meteorological risk and in local environments with adverse climate conditions.DemographyJournal of Hospital Management and Health Policy
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Aircraft type-specific errors in AMDAR weather reports from commercial aircraft

2008

AMDAR (Aircraft Meteorological DAta Relay) automated weather reports from commercial aircraft provide an increasing amount of input data for numerical weather prediction models. Previous studies have investigated the quality of AMDAR data. Few of these studies, however, have revealed indications of systematic errors dependent upon the aircraft type. Since different airlines use different algorithms to generate AMDAR reports, it has remained unclear whether a dependency on the aircraft type is caused by physical properties of the aircraft or by different data processing algorithms. In the present study, a special AMDAR dataset was used to investigate the physical type-dependent errors of AMD…

Systematic errorAtmospheric ScienceData processingMeteorologybusiness.industryAircraft meteorological data relayType specificNumerical weather prediction modelsContrast (statistics)Temperature biasTemperature measurementSoftwareAircraft Meteorological Data RelayEnvironmental sciencebusinessAircraft measurementsUpper air data
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A new tool to process forecast meteorological data for atmospheric pollution dispersion simulations of accident scenarios: A Sicily-based case study

2021

Emergency response plans to mitigate the severity of the accidental release of hazardous compounds in the air have become a primary concern in view of the many adverse events occurred over the years in high-risk plants. To do this, an accurate estimate of forecast meteorological data to be used in dispersion models can be very useful to respond in advance to emergency situations. In this field, FORCALM is a new tool developed to elaborate European Centre for Medium-Range Weather Forecasts data on a 3D computational domain with a high-resolution grid. FORCALM data can be used to perform predictive simulations of impacts on local and regional levels by using CALPUFF modelling system. A case s…

TechnologySettore ING-IND/11 - Fisica Tecnica AmbientaleAir pollution; Forecast meteorological data; Dispersion model; Risk analysis; High-risk plantMeteorologyRenewable Energy Sustainability and the EnvironmentProcess (engineering)risk analysisTair pollutionAir pollutionEnergy Engineering and Power TechnologyAtmospheric pollutionEconomic growth development planningEnvironmental Science (miscellaneous)medicine.disease_causehigh-risk plants.Based case studydispersion modelmedicineHD72-88Environmental scienceStatistical dispersionAir pollution Forecast meteorological data Dispersion model Risk analysis High-risk plants.forecast meteorological dataWater Science and TechnologyJournal of Sustainable Development of Energy, Water and Environment Systems
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