Time filter

Source Type

Vujovic D.,University of Belgrade | Milic-Petrovic B.,Hydrometeorological Service of Serbia
Journal of Atmospheric Chemistry | Year: 2015

Bulk precipitation samples collected daily through bulk collectors at eight meteorological stations in Serbia were analyzed for their chemical composition. The data covers time series, from 20 to 28 years, in the period between 1982 and 2010. The most abundant ion in the samples was sulfate. Only 0.17 % of all samples were from strong acid rains (pH < 3.5). The relatively high average pH values (5.94–6.26) of the collected precipitation indicate the neutral or alkaline nature of local rainwater. Trends in both the annual amount and the composition of precipitation were tested by the nonparametric Mann–Kendall test and Sen’s slope estimator. Significant increasing trend of precipitation was identified for almost all stations. Rebuilding activities after the bombing of Serbia in 1999 were identified as a possible anthropogenic cause of the sharp increase of some ions (Ca2+) in the first year following the bombing. The origin of air masses arriving at one particular station was examined using two-dimensional backward trajectories. Western sectors (W, SW and NW) accounted for almost half (44.3 %) of all rainy days, while eastern sectors (SE, E and NE) brought only 10.4 % of all rainy days. The distribution, per sector, of volume-weighted concentrations of sulfate, nitrate, ammonium, calcium, potassium, magnesium, chloride and sodium ions, as well as the amount of precipitation and its pH values for one station, was also analyzed. Rainwater from the SE and S sectors was the most polluted. © 2015 Springer Science+Business Media Dordrecht Source

Paskota M.,University of Belgrade | Vujovic D.,University of Belgrade | Todorovic N.,Hydrometeorological Service of Serbia
Theoretical and Applied Climatology | Year: 2013

Starting from the standpoint that there are seasonal differences of climate variations on both global and local level, the authors of this paper had focused on analyzing climatologic parameters in winter months. The trends of several important parameters were detected, with temperature and precipitation having increasing, but number of ice days and snow cover having decreasing trends. Spectral analysis showed repetitive nature of climatologic parameters, some of them having the same or similar periods of about 6 to 7 years, 10 to 12 or 17.5 years, and 22 to 24 years. The precipitation has periodicity of 8 and 14 years. Further analysis of the underlying structure of the data by principal component analysis detected three easily explained dimensions: Temperature-Snow, Precipitation-Cyclone and Spring-in-Winter dimension. The spectral analysis of three virtual variables obtained by principal component analysis confirmed good agreement of original variables with the virtual dimensions. © 2012 Springer-Verlag Wien. Source

Paskota M.,University of Belgrade | Todorovic N.,Hydrometeorological Service of Serbia | Vujovic D.,University of Belgrade
International Journal of Climatology | Year: 2013

Climatology is one of the areas that rely on collecting huge quantities of data. The longer a time period is observed, the better; the more parameters are included, the better. But the human mind cannot easily extract useful information from the abundance of data; thus, many valuable facts may be overlooked. Having that in mind, the authors of this paper have focused on the data condensation with the goal of gathering more information about the underlying trends of the main climatologic parameters change to show climatic variability. The data from the Belgrade Meteorological Observatory are analysed using a number of different methods of multivariate statistical analysis. Separation of the years and time periods with similar weather pattern characteristics was successful and indicates that there is a trend of temperature increase, as well as a trend of the temperature range decrease. © 2012 Royal Meteorological Society. Source

Todorovic N.,Hydrometeorological Service of Serbia | Vujovic D.,University of Belgrade
Advances in Space Research | Year: 2014

In this paper we research the relationship between solar activity and the weather on Earth. This research is based on the assumption that every ejection of magnetic field energy and particles from the Sun (also known as Solar wind) has direct effects on the Earth's weather. The impact of coronal holes and active regions on cold air advection (cold fronts, precipitation, and temperature decrease on the surface and higher layers) in the Belgrade region (Serbia) was analyzed. Some active regions and coronal holes appear to be in a geo-effective position nearly every 27 days, which is the duration of a solar rotation. A similar period of repetitiveness (27-29 days) of the passage of the cold front, and maximum and minimum temperatures measured at surface and at levels of 850 and 500 hPa were detected. We found that 10-12 days after Solar wind velocity starts significantly increasing, we could expect the passage of a cold front. After eight days, the maximum temperatures in the Belgrade region are measured, and it was found that their minimum values appear after 12-16 days. The maximum amount of precipitation occurs 14 days after Solar wind is observed. A recurring period of nearly 27 days of different phases of development for hurricanes Katrina, Rita and Wilma was found. This analysis confirmed that the intervals of time between two occurrences of some particular meteorological parameter correlate well with Solar wind and A index. © 2014 COSPAR. Published by Elsevier Ltd. All rights reserved. Source

Vujovic D.,University of Belgrade | Paskota M.,University of Belgrade | Todorovic N.,Hydrometeorological Service of Serbia | Vuckovic V.,University of Belgrade
Atmospheric Research | Year: 2015

The pre-convective atmosphere over Serbia during the ten-year period (2001-2010) was investigated using the radiosonde data from one meteorological station and the thunderstorm observations from thirteen SYNOP meteorological stations. In order to verify their ability to forecast a thunderstorm, several stability indices were examined. Rank sum scores (RSSs) were used to segregate indices and parameters which can differentiate between a thunderstorm and no-thunderstorm event. The following indices had the best RSS values: Lifted index (LI), K index (KI), Showalter index (SI), Boyden index (BI), Total totals (TT), dew-point temperature and mixing ratio. The threshold value test was used in order to determine the appropriate threshold values for these variables. The threshold with the best skill scores was chosen as the optimal. The thresholds were validated in two ways: through the control data set, and comparing the calculated indices thresholds with the values of indices for a randomly chosen day with an observed thunderstorm. The index with the highest skill for thunderstorm forecasting was LI, and then SI, KI and TT. The BI had the poorest skill scores. © 2015 Elsevier B.V. Source

Discover hidden collaborations