Vol. 119, No. 2 * Pages 129–306 * April - June 2015

Excessive precipitation may result in different environmental and socio-economical damages. In order to mitigate or avoid the potential losses associated to these, it is essential to provide estimations of precipitation tendencies for the future, which facilitate to build appropriate adaptation strategies in time. In this paper we used bias-corrected daily precipitation outputs of 11 regional climate model (RCM) simulations to determine the projected precipitation trends for the Carpathian Basin. According to the results of the analysis of precipitation indices, frequency of extreme precipitation will generally increase in the entire Central/Eastern European domain, except in summer, when decreasing trend is very likely in Hungary as well as in the southern regions.

The increase of the temperature and frequency of extreme weather events are predicted as the most visible effects of expected climate change. The number of publications dealing with heat-related mortality has been increasing for the last 20 years. They concluded that no formal definition of a heat wave existed, so the definition of such events would be very important. A more consistent methodology for calculating excess mortality would enhance comparisons between studies.
It is a growing demand to elaborate and use indicators which can provide comparable information of the impact of heat on mortality in different geographic and climatic regions. Therefore, the World Health Organization developed a set of climate change related health indicators in the CEHAPIS (Climate, Environment and Health Action Plan Information System) project. The authors aimed to assess heat related excess mortality by using this methodology, in addition to indicators used in the Hungarian Heat Alert System, in order to provide a recommendation for a more precise detection of health effects in Budapest.
In this paper, the heat wave related daily excess mortality is analyzed for the summer periods of 2000 –2010 in Budapest. Mortality is characterized by the daily total mortality and that of the age group 65 years and over. Meteorological variables of the Pestszentlőrinc station, regarded as an urban background meteorological station, were used. Daily temperature was characterized by four indicators: mean and maximum daily temperatures, and mean and maximum daily apparent temperatures. The impact on mortality was compared in relation to the different temperature indicators and threshold values. A method was developed to define the optimal threshold range where the excess mortality could be identified effectively.
The recommended method is capable to detect the changes of temperature and to assess the impact of heat waves on daily mortality. The results are in accordance with previous studies. Concerning the indicators, the application of daily mean temperature values seems to be optimal for Budapest. Further analyses are required to answer the question to what extent the Budapest findings can be used in other cities.

This paper analyzes midlatitude cyclones identified and tracked in the Mediterranean region for the recent past, between 1981 and 2010. The Mediterranean region is especially interesting since the complex land orography favors lee cyclogenesis, and the warm sea area provides latent heat for the developing cyclones. These cyclones may result in heavy precipitation, even flood events affecting southern and central Europe, including Hungary.
Cyclones are identified using two different reanalyses, the ERA Interim reanalysis from ECMWF at 0.75° horizontal resolution and the NCEP-DOE R2 reanalysis at 2.5° horizontal resolution. For the identification, a multivariable approach is used to eliminate and assess the uncertainties rising from the choice of a specific variable, which is particularly important in the Mediterranean, where the systems are tend to be weak and shallow. Mean sea level pressure (MSLP), geopotential heights of the 1000 hPa, and the 850 hPa isobaric levels are used as main variables, and relative vorticity at 850 hPa isobaric level serves, an additional variable. The applied algorithm has uni- and bivariate modes. In the bivariate mode, relative vorticity at 850 hPa is added to the main variable.
The results suggest that time series of annual number of cyclones using the two reanalyses correlate significantly, however, using the higher resolution dataset, more cyclones can be identified. The largest and the smallest frequency of cyclones over the entire domain occur in spring and summer, respectively. The largest spread of the multi-variable ensemble is in summer, probably caused by non-frontal thermal lows. Furthermore, summer is mostly dominated by short-lived cyclones. The main cyclogenesis regions are the Gulf of Genoa and the Cyprus region, with some minor centers at the Adriatic Sea, the northern part of the Black Sea, and the Iberian Peninsula. The cyclone frequency trend is slightly increasing in most parts of the region, especially over the Adriatic Sea and near Cyprus. Hungary is affected annually by approximately 30 cyclones from the Mediterranean area, most frequently in spring.

This paper presents the results of an objective analysis on thunderstorm climatology in Hungary. The examination was based on composite PPI (plan position indicator) images made by Doppler radars of the Hungarian Meteorological Service between 2004 and 2012.In our research, thunderstorms were represented with so-called thunderstorm ellipses, and their time and spatial distribution were examined. Three types of thunderstorm ellipses and stormy days were defined with radar reflectivity set to 45, 50, or 55 dBZ. Most stormy days and ellipses happened in late spring and summer of 2007 and 2010. The daily frequency of these objects peaked in the late afternoon period. The detected ellipses had maxima in the north-eastern, north-central, and south-western parts of Hungary. Beyond information and characteristics from the past, these methods and results can be useful for forecasting severe thunderstorms.

In this paper, an overview of the complex nowcasting system of the Hungarian Meteorological Service is presented. The system named MEANDER started to work as a linear extrapolation process to provide warnings on convective storms. The role of the numerical weather prediction (NWP) models have been increased by involving the Weather Research and Forecasting (WRF) Model into nowcasting procedures. In the current state, MEANDER system consists of 2 main segments: NWP and linear parts.
In the NWP segment, WRF model is used in two steps: in the first step, WRF (WRF-ALPHA) is run at a 2.5×2.5 km horizontal resolution grid, using non-hydrostatic dynamics and ECMWF model data as initial and boundary conditions. The second step is a higher resolution (1.2×1.2 km) WRF model run – named WRF-BETA –, that uses lateral conditions and first guess data coming from WRF-ALPHA outputs and assimilates radar reflectivity, satellite and surface observation data. The domain of WRF-BETA is included in the domain of WRF-ALPHA. The applied nowcasting-specific assimilation helps the model to develop significant precipitating weather systems on the right location in the right time. WRF-BETA outputs provides such background information for the nowcasting system that makes the forecast of the linear segment more exact.
In the linear part, the actual objective analysis is considered at the beginning and the NWP prediction at the end of the nowcasting period. In the meantime, linear interpolation is applied. Radar data has key role in the nowcasting procedures in the linear segment, too. There are several derived parameters that are used for calculating the SYNOP-type present weather parameter for all grid points in the analysis and for the entire forecast time.
The MEANDER system has a warning process that is able to create weather warnings for all districts of Hungary, helping decisions of forecasters.

The operational AROME (Applications of Research for Operations at MEsoscales) mesoscale numerical weather prediction (NWP) model has been run using interpolated analyses of the ALADIN (Aire Limitée Adaptation Dynamique Développement International) NWP model for its initialization since the end of 2010 at the Hungarian Meteorological Service (HMS). In order to improve the initial conditions, a local three-dimensional variational (3DVAR) data assimilation system was developed for the Hungarian version of AROME (AROME-Hungary). Regarding the data assimilation cycling strategy, it was shown that 3 hourly rapid update cycling (RUC), which was implemented operationally in March 2013 using conventional observations, outperforms 6 hourly cycling method. This paper describes at length the main characteristics of this local data assimilation system and its impact on the model short-range forecasts. Although the forecasts of AROME-Hungary based on a local data assimilation were already improved compared to the previous implementation (initialization via interpolated analyses of the ALADIN model), there is still a way to go to exploit the full benefit of the local 3DVAR assimilation cycle. Current development works aim at improving the system through exploitation of remote sensing observations (radar, GPS, satellite AMVs), with a special emphasis on humidity information. All tested observations showed promising performance on both the analyses and forecasts of the AROME-Hungary model, which should lead to their respective operational implementation in the near future.

At the Hungarian Meteorological Service (HMS), the AROME non-hydrostatic numerical weather prediction model has been running operationally since the end of 2010. The horizontal resolution is 2.5 km, thus it is assumed that deep convection is explicitly resolved. To achieve this, apart from increasing the horizontal and vertical resolution of the model, advanced physical parameterizations have to be applied. In this paper, some recent developments in connection with dynamics and physical parameterizations performed at the HMS are described. Model sensitivities related to horizontal diffusion, microphysics, turbulence, and shallow convection are discussed. Main features of the applied surface scheme “SURFEX” are highlighted as well as developments in connection with the prognostic treatment of vegetation. Recent work focusing on high resolution probabilistic forecasting with the AROME model is also summarized. It is shown that the AROME model is able to adequately predict severe weather events, however, as resolution increases, the importance of a probabilistic forecasting approach increases. An initial condition perturbation method and a model error representation scheme are described and their impact in an AROME-EPS test configuration is also presented.

During the history, it has been proved several times that ignoring the quickly changing meteorological circumstances and atmospheric phenomana or their insufficient assessement can result in catastrophic impacts on military operations. Weather plays a very significant role in flight operations, and it can be vital even for planning and executing operations of land forces and for any other open air activities involving armed forces (e.g., disaster relief activities, industrial and natural catastrophes, and in assessement of chemical, biological, radiological, and nuclear events). The possible course of weather and the range of the climatological factors should be taken into consideration for protecting life, property and infrastucture.
In the Hungarian Defence Forces, the focus of the meteorological support is on providing the necessary meteorological information for decision makers supporting the planning and executing certain military activities, and enhancing efficiency. This is a very complex task and that is the reason for having specialized meteorological service and capability within the Hungarian Defence Forces which can meet these requirements.
The military weather warnings and advisories (“military weather warnings”) are specialized type of forecasts. They alert the military users on the possible or expectable severe weather, which can significantly impact life and property in order to mitigate the unfavorable effects of the severe weather. For avoiding misinformation in the meteorological support in our daily routine, the military weather warnings should be in harmony with the weather warnings issued by the Hungarian Meteorological Service for civilian users, which is enabled by the strong and efficient cooperation between the two services.
This paper describes some effects of weather on military activities in general and military weather warnings within the Hungarian Defence Forces.

Deep cyclones, originating in the Mediterranean area, are frequently the cause of heavy precipitation and environments characterized by large temperature gradients and strong wind. In winter period, several types of precipitation can be observed in such situations, including freezing rain and wet snow, which can cause serious damage on the electricity power lines or other infrastructure. On March 14–15, 2013, deep snowdrifts resulted in blocking of thousands of vehicles on Hungarian highways. Similar cases motivated the research of these phenomena in Hungary, using and adapting empirical approaches to calculate wet snow loads on wires or to calculate the blowing snow index (BSI) to assess the intensity of the snowdrifts development. Forecasting of these parameters is possible by using inputs from global and limited numerical weather prediction models (ECMWF, WRF). The paper describes methods for wet- and blowing snow diagnostics and classification of their intensity. The results are demonstrated on case studies and supported by observations and available damage reports. The possibility of further refinement of the diagnostics and its operational application is also discussed.