Data recovery and climate reconstruction are an important support for climate change research, as they provide information from periods and areas with sparse meteorological networks. Various sources are currently in use for obtaining valuable evidence of past climate, such as ship logs, diaries, books, monastery documents. This study exploits newspaper reports in order to enrich
Air pollution is one of the major problems of mankind, transport of pollutants extending far beyond the borders of the countries where they were produced, causing unpredictable, direct and indirect changes of the environment. The main tool for the study of this phenomenon consists of mathematical modeling of complex physical and chemical phenomena involved. In practice, air emissions are estimated on basis of measurements taken from selected sources being representative of the major categories and types. At national level, the Air Quality Evaluation Center (CECA) provides regular reports to the European Environment Agency (EEA) or the European Commission as requirements of Romania’s lawful duties in air quality domain. The registry of emissions TNO/ MACC (Netherlands Organisation for Applied Scientific Research/ Monitoring Atmospheric Composition and Climate) contains emissions inventories which have been homogenized and checked in advance and obtained from emissions officially reported at sectoral level for each country. In this study, for the analysis of the weather numerical dispersion and transport of pollutants, it has been used the numerical air quality model WRF-CHEM version 3.5, centered over Romania, at the spatial resolution of 10 km, using as input data the TNO emission database for 2009. By interpolating values from the regular grid of the TNO database with the WRF-CHEM model 3.5 grid, monthly average values were obtained for each day of the week, for any parameter considered. Preliminary results obtained for different pollutants (for example: PM10, O3) confirm the need to validate these results by implementing and integrating air quality forecasting model by assimilating different types of measurements (data model, gravimetric data observations, etc.).
This study presents the meteorological information spanning the last two decades of the end of 19th century (1880-1900) extracted from three Romanian newspapers (România Liberă, Gazeta de Transilvania and Foaia Poporului). It describes the characteristics of the newspaper data included in the database, it offers and overview of the meteorological network and climate picture at that time in Romania and discuss some of the climatic features that can be extracted from the database as potential information for further reconstructions.
-Analysing the homogeneity of air temperature, relative air humidity, precipitation and wind data series using 'Climatol' and meteorological metadata. Errors are inherent in all measurement activity, and meteorology is no exception. Homogenization of climatological series to eliminate disturbances often contained in them, due to changes in the conditions of observations, is a mandatory process to increase the reliability of studies of climate variability derived from their analysis. The "Climatol" R package is devoted to the problem of homogenizing climatological data series in order to remove the perturbations produced e.g. by changes in the conditions of observation or in the nearby environment, to allow the series to reflect the climatic variations. As it is known, changes in the location of meteorological observatories, changes in instrumentation (from classic equipment to automated sensors) or in shelters intended to protect sensors from solar radiation, or even changes in the environment (land uses, new constructions, etc.) are alterations that can not be attributed to changes in the climate. Such information regarding this changes are known as "metadata". In this paper the "Climatol" method was used for air temperature, relative air humidity, precipitation and wind daily data homogenization for the period since 1961 till 2015 at Cluj-Napoca, Oradea, Satu Mare and Vlădeasa 1800 meteorological stations. With the help of metadata, the results were validated and changes in statistical parameters of meteorological data string were identified, for the analysed meteorological parameters, due to the relocation of the meteorological platforms, changes of the meteorological equipment and changes of the measuring methodology.
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