2024. március 28. csütörtök
IDŐJÁRÁS - angol nyelvű folyóirat

Vol. 118, No. 4 * Pages 293–378 * October - December 2014


Quarterly journal of the Hungarian Meteorological Service

Special Issue: Application of information and communication technologies in environmental sciences:
towards a sustainable future

Guest editor: Kálmán Kovács

Progress towards emission targets through the development of climate change policies and measures in Hungary
Márk Molnár, Sándor Molnár, and Anita Csábrági
idojaras.2014.4.1 (p. 293–)
 PDF (246 KB)   |   Abstract

Parties included in Annex I to the UNFCCC are requested to regularly submit National Communications to the Secretariat. This report presents an overview of the results of the 6th National Communication (NC6) of Hungary with respect to the relevant provisions of the Convention and Article 8 of the Kyoto Protocol.


Estimation of future precipitation conditions for Hungary with special focus on dry periods
Rita Pongrácz, Judit Bartholy, and Anna Kis
idojaras.2014.4.2 (p. 305–)
 PDF (628 KB)   |   Abstract

In this paper, estimated trends of precipitation- and drought-related climate indices and the return period of the daily precipitation amount are analyzed. For this purpose 11 regional climate model (RCM) simulations from the ENSEMBLES project with 25 km horizontal resolution for the emission scenario A1B are used after applying a bias-correction procedure. According to the results, the summer 10- and 20-year return periods will increase by a factor of 1.2–2 by the late 21st century relative to the 1961–1990 reference period. The projected changes are considerably smaller for the other three seasons compared to future summer changes. Furthermore, drought-related climate indices in summer are projected to increase significantly in Hungary as well as in Central/Eastern Europe by the end of the 21st century. Additionally, precipitation-related indices are projected to decrease in summer by 2071–2100 compared to 1961–1990.


Trend analysis of a new MODIS drought severity index with emphasis on the Carpathian Basin
Péter I. Orvos, Viktória Homonnai, Anita Várai, Zoltán Bozóki, and Imre M. Jánosi
idojaras.2014.4.3 (p. 323–)
 PDF (1202 KB)   |   Abstract

Recently, Mu et al. (2013) have compiled an open access data base of a remotely sensed global drought severity index (DSI) based on MODIS satellite measurements. Observations cover a continuous period of 12 years between January 1, 2000 and December 31, 2011 with a temporal resolution of 8 days. The highest spatial resolution is around 5 km in the geographic band between 60°S and 80°N latitudes (more than 4.9 million locations over land). Here we extend the global trend analysis by Orvos et al. (2014) of these satellite based DSI time series in order to locate geographic areas where either positive or negative trends are statistically significant. Significance is established by a standard perturbation test, where each individual record is cut into annual pieces, and the statistics of 1000 randomly shuffled and glued time series is compared with the original record. We exhibit three regions of significant wetting and/or drying trends over extended geographic ranges and try to correlate them with recent reports of local climate shifts. We are fully aware of the fact that 12 years are too short for linking the findings to global climate change. Most probably, the identified significant trends can be considered as a component of natural climate variability on decadal time scales, however, a full explanation will require to identify a couple of explanatory variables.
We demonstrate that drying and wetting trends are weakly significant in the Carpathian Basin. Nevertheless, the observations can serve as benchmark for regional climate simulations, projections can be accepted when the test period is properly reproduced considering also high resolution DSI data.


Some aspects of the impact of meteorological forecast uncertainties on environmental dispersion prediction
Tímea Haszpra and András Horányi
idojaras.2014.4.4 (p. 335–)
 PDF (908 KB)   |   Abstract

There are several types of uncertainties related to the simulation of the dispersion of pollutants in the atmosphere. For a dispersion forecast, one of the most important error sources is the meteorological data produced by a numerical weather prediction model and utilized by the dispersion model. In this paper, we will present the results of an ensemble dispersion forecast created by using an ensemble meteorological forecast and the high-resolution forecast for 2.5 days. The dispersion simulations are carried out by the RePLaT Lagrangian dispersion model for particles of different radii. Significant deviations appear both in the extension and location of the ensemble of pollutant clouds consisting of particles of the same size. Differences appear also between the dispersion scenarios which use the unperturbed meteorological forecasts with different resolutions. The difference among the ensemble members increases for small particles. The area where at least one ensemble member predicts pollutant is much larger than the area covered by the pollutant cloud of the high-resolution forecast.


Statistical analysis of relationships between road accidents involving personal injury and meteorological variables in Hungary
Pál Vécsei and Kálmán Kovács
idojaras.2014.4.5 (p. 349–)
 PDF (542 KB)   |   Abstract

Public opinion and certain human meteorological communications assume close relationship between meteorological variations and human conditions, especially the development of traffic accidents. This paper presents a detailed statistical analysis between domestic road accidents involving personal injury and relevant meteorological conditions for the period of 1990–2010 in Hungary. Approximately 431 thousand accidents were analyzed based on official statistical data. In general, a significant but weak interrelation was found between the absolute change – calculated from the previous day – of road traffic accidents involving personal injury and meteorological conditions. The results of multivariate linear regression analysis show that meteorological variations affected only nearly four percent of the variation of accidents relative to traffic. We demonstrated, however, that together with the significant variation of certain meteorological parameters, the number of accidents also significantly varies. Days with extreme meteorological variations explain the development of accidents in 9.8 percent, while in the case of days with non-extreme variations, this value was only 2.6 percent.




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