Friday 29 March 2024
Időjárás - Quarterly Journal of the Hungarian Meteorological Service (OMSZ)

Vol. 122, No. 3 * Pages 217–361 * July - September 2018


Quarterly Journal of the Hungarian Meteorological Service

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The analysis of climatic indicators using different growing season calculation methods – an application to grapevine grown in Hungary
Ildikó Mesterházy, Róbert Mészáros, Rita Pongrácz, Péter Bodor, and Márta Ladányi
DOI:10.28974/idojaras.2018.3.1 (p. 217–)
 PDF (7486 KB)   |   Abstract

DOI:10.28974/idojaras.2018.3.1

The precise knowledge of the beginning and the end of the growing season is necessary for the calculation of climatic indicators with evident effect on grapevine production. The aim of this study is to develop suitable methods on the basis of thermal conditions that can be used for calculation of the beginning, the end, and the length of the growing season for every single year. The two most accurate methods (‘5mid’ and ‘int’) are selected using the root-mean-square error compared to the reference growing season values based on averaging the daily mean temperature for several decades. In case of the ‘5mid’ method, the beginning (or the end) is the middle day of the first (or last) 5-day period with temperature not less than 10 °C. In case of the ‘int’ method, the beginning (or the end) of the growing season is the day after March 15 (or September 15), when the smoothed series of daily temperature using the monthly average temperatures of March and April (or September and October) exceeds 10 °C (or falls below 10 °C). As a next step, several climatic indicators (e.g., Huglin index and hydrothermal coefficient) are calculated for Hungary for three time periods (1961−1990, 2021−2050, and 2071−2100) using the ‘5mid’ and ‘int’ methods. For this purpose, the bias-corrected daily mean, minimum, and maximum temperature and daily precipitation outputs of three different regional climate models (RegCM, ALADIN, and PRECIS) are used. Extreme temperature and precipitation indices are also evaluated as they determine the risk of grapevine production. The spatial distributions of the indicators are presented on maps. We compare the indicators for the past and for the future using one-way completely randomized robust ANOVA (analysis of variance).
Results suggest that changes of temperature conditions in the 21st century will favor the production of red grapevine and late-ripening cultivars. Furthermore, drought seasons will be longer and extreme high summer temperatures will become more frequent, which are clearly considered as high risk factors in grapevine production. Besides the negative effects, the risk of winter frost damage is expected to decrease, which is evidently a favorable change in terms of grapevine production.


An assessment of daily extreme temperature forecasts – stations average view
Hristo Hristov and Andrey Bogatchev
DOI:10.28974/idojaras.2018.3.2 (p. 237–)
 PDF (1861 KB)   |   Abstract

DOI:10.28974/idojaras.2018.3.2

The present article is the first one of a couple of articles, related to the assessment of the human forecasts (forecast made by weather forecasters). In this article, we have performed an integral assessment of the human-derived extreme temperature forecasts during 2009–2014. It will give us a more general picture of the forecasts, their accuracy over the years of the period in consideration, and their change through the different months of the year. We will show how the accuracy of the forecasts increases in the assessing period, and also how human forecasts underestimate extreme temperatures. The integral assessment gives us a more clear view on the movement of the various errors in time, but it has a significant shortcoming – the spatial distribution of the information is lost. The spatial distribution would give us a valuable feedback, that could be used to correct the forecasts. It will be discussed in the second article, where an assessment by stations will be made.


Spatial analysis of air temperature and its impact on the sustainable development of mountain tourism in Central and Western Serbia
Danijela Vukoičić, Saša Milosavljević, Ivana Penjišević, Nikola Bačević, Milena Nikolić, Radomir Ivanović, and Bojana Jandžiković
DOI:10.28974/idojaras.2018.3.3 (p. 259–)
 PDF (3835 KB)   |   Abstract

DOI:10.28974/idojaras.2018.3.3

Empirical studies of the late twentieth and early twenty-first century indicate the existence of a growth trend in air temperature. This trend is particularly pronounced in the region of Southern Europe, including the Republic of Serbia. Many problems occur in the socio-economic areas due to global warming, which directly influences the development of tourism. In this study, we will deal with the influence of climate change on the sustainable development of mountain tourism in the area of the western and central Serbia tourist zones, which includes Starovlaška and Kopaonik mountain chain. The data on changes in the temperature of air will be gathered at six different altitude meteorological stations, for the period from 1990 to 2014. All weather stations in the studied area were classified into three groups: lowland, middle and high mountain. In order to obtain trends, three sets of data were used: the average monthly temperature, the maximum monthly temperature, and the monthly minimum temperature, recorded in each station. The seasonal classification has been conducted based on four seasons: spring, summer, autumn, and winter. Three statistical approaches were used to analyze the temperature trends in 15 time series, for each group of stations individually. First, the trend equation was calculated for each time series, then, completely separate from the first approach, all trends were assessed using the Mann-Kendall test, and in the end, in all cases, the trend magnitude was calculated based on the trend equation. The results show that there is a significant positive trend of temperature rise on an annual basis, while the trend is significantly positive during the fall and spring seasons. In winter, the trend is slightly positive or absent, while in the summer trend is moderately positive in all three groups of stations.


Statistical structure of day by day alteration of daily average wind speeds
Károly Tar and István Lázár
DOI:10.28974/idojaras.2018.3.4 (p. 285–)
 PDF (1199 KB)   |   Abstract

DOI:10.28974/idojaras.2018.3.4

One of the most complex problems of wind power plant operators is to compose a so-called “timetable” that is based on estimating the amount of power produced on the next day divided into small time units. Creation of this timetable could be based on the mathematical statistical method presented in this paper. Our statistical method is based on the construction of a model based on the statistical structure of the change of measured daily average wind speed, that enables the estimation of the probability of decreasing or increasing daily average wind speed by the next day in certain time periods or at various weather conditions. The statistical structure of daily average wind speed changing day by day provides further important information on the wind climate of Hungary and may help protection against wind erosion, building planning, and estimating bioclimatic factors. The basics of the method and the estimation of the sign of changes for the next day are presented in the following. The database is composed of daily average wind speed data measured at nine Hungarian meteorological stations between 1991 and 2000. Studies were performed for the whole period and for anticyclone and cyclone conditions based on Péczely’s macrosynoptic situations and their transitional situations as well. The relative amount characterizing the change of daily average wind speed day by day was defined, and then the most important basic statics were analyzed. The distribution by sign of this amount and the relationship with the actual daily average wind speed were studied. Based on the results, the sign of wind speed change by the next day is estimated. As a conclusion, it can be stated that the presented model yields best results if the present day belongs to cyclone conditions.


Application of the crop model WOFOST in grid using meteorological input data from reanalysis and objective analysis
Hristo Chervenkov, Valentin Kazandjiev, and Veska Gorgieva
DOI:10.28974/idojaras.2018.3.5 (p. 305–)
 PDF (2958 KB)   |   Abstract

DOI:10.28974/idojaras.2018.3.5

Meteorological gridded datasets from the reanalysis ERA-Interim of the ECMWF and the objective analysis E-OBSv14.0 of the ECA&D are used to initialize the crop model WOFOST. The data is on daily basis with 0.25° horizontal resolution and the model domain entirely covers southeastern part of Europe. Hence, the general of the authors goal is to investigate the response of the crops system to the averaged weather conditions, rather than of a particular year. For this purpose, multi-year daily averages from the 30-year period of 1981–2010 are considered. This time-span is often treated as “modern climate”, and it is frequently used in many evaluation studies. A special, purpose-build software system is designed to perform the simulation, which steers the data flow and the exchange between the different modules. The produced outcome, in form of three-dimensional digital map of the crop production specific variables, shows high spatial and temporal consistency, revealing the relevant features of the geographical and chronological variation of the output parameters at the same time.


Bioclimatic and climatic tourism conditions at Zlatibor Mountain (Western Serbia)
Biljana Basarin, Tin Lukić, Dajana Bjelajac, Tanja Micić, Goran Stojićević, Igor Stamenković, Jasmina Đorđević, Tijana Đorđević, and Andreas Matzarakis
DOI:10.28974/idojaras.2018.3.6 (p. 321–)
 PDF (5004 KB)   |   Abstract

DOI:10.28974/idojaras.2018.3.6

This study presents the climatic and bioclimatic conditions at Zlatibor, as well as their modification and distribution over the year. Zlatibor Mountain is a popular tourist destination in Serbia, and it stands out as a mountain of exquisite natural and anthropogenic values. Information about climate and bioclimate is presented by using physiologically equivalent temperature (PET), and universal thermal climate index (UTCI) over 10-day periods. The Climate-Tourism/Transfer-Information-Scheme (CTIS) was also used as it displays climate and bioclimate information for tourism purposes based on thresholds of relevant parameters and the frequency of occurrence. The weather suitability index (WSI) was calculated as well, because itprovides synthetic information about suitability of weather for different forms of recreational and tourism activities. The results obtained in this study were used to develop a bioclimatological leaflet for Zlatibor, which could be very useful to the tourism industry and stakeholders in decision-making, but also it will enable tourist to choose the best time for holiday depending on personal preferences and requirements.


A dynamic data-driven forecast prediction methodology for photovoltaic power systems
Kapros Zoltán
DOI:10.28974/idojaras.2018.3.7 (p. 345–)
 PDF (738 KB)   |   Abstract

DOI:10.28974/idojaras.2018.3.7

At present, the capacity of the new photovoltaic (PV) systems are growing rapidly in Hungary. The limit to growth can be estimated, but it is influenced by several things. Even a realistic goal for the next 20–30 years can be to reach the 20–25% variable renewable energy ratio in the electricity consumption. The main barrier is the variability of these systems, thus the grid integration is a huge challenge in the near future. A new dynamic data-driven forecasting methodology is worked out and tested by examining the Budapest District Heating Co. Ltd. top installed solar systems. The tested prediction method was only for 5 minutes ahead in the expected average performance in a 15-minute period. The main elements of the tested methodology and some main results will be presented in this article.




IDŐJÁRÁS - Quarterly Journal