Vol. 118, No. 3 * Pages 193–291 * July - September 2014

Spatial distribution of several indices characterizing wine production in Hungary are analyzed in this paper using the bias-corrected outputs of three different regional climate models: RegCM, ALADIN, and PRECIS. For this purpose, the daily minimum, maximum, and mean temperature, and daily precipitation time series were used. The indices include the active degree days, Huglin’s heliothermal index, length of vegetation period according to thermal conditions, hydrothermal coefficient, and frequencies of extreme temperature events. In the study, first, the past changes of these indices are evaluated, and then, the main focus is on the projected changes until the end of the 21st century. Our results suggest that white wine grapes are very likely to lose their dominance over red wine grapes in Hungary in the next few decades. Furthermore, the ripening of late-ripening and very-late-ripening grape varieties will become more likely. Extreme high summer temperatures will become more frequent, while the risk of frost damage in the reproductive cycle is projected to decrease.

Dry aerosol mass concentrations (PM₁₀, PM_2.5) are determined after conditioning of the filter at t =20 ± 1 °C and RH=50 ± 5% for 48 hours according to the standard protocol EN 12341. The main result of this work is that applying the standard pre-conditioning step, complete removal of adsorbed water cannot be attained. In our experiment, aerosol samples collected in Budapest between November 2008 and March 2010 using a CEN (European Committee for Standardization) gravimetric sampler (Digitel, DHA-80) were studied. Following PM₁₀ mass concentration measurements according to the EN 12341 protocol, we repeated the gravimetric aerosol mass measurements in the laboratory using a glove box after in-situ pre-conditioning for 48 h at t =20 ± 1 °C and RH < 30%. We assumed that at this low relative humidity all the adsorbed residual water was removed, and the absolute dry mass concentrations of PM₁₀ could be determined (referred in the following as dry PM₁₀ concentration). The mass concentration of adsorbed residual water, defined as the difference between the results of the standard and dry PM₁₀ measurements, varied greatly in the range of 0.05–16.9 µgm⁻³. Expressed relative to the absolute dry PM₁₀ mass concentrations, the residual water content in the standard measurement procedure amounted to 4.2 ± 1.5% and 7.9 ± 0.8% in summer and winter, respectively. In winter, relative contributions of adsorbed water as high as 33.2 m/m% was found. The significant seasonal differences as well as the large variations between individual samples may depend on various factors such as the chemical composition of the samples, particle load, and the RH history of the particles before and after sample collection. This last factor is expected to exert rather significant influence on the amount of adsorbed residual water, yet it is impossible to reconstruct. These findings have severe implications on reported dry PM₁₀ mass concentrations using the EN 12341 protocol, especially in the winter period when most limit exceedances occur.

The evolution of the weather can be described by deterministic numerical weather forecasting models. Multiple runs of these models with different initial conditions and/or model physics result in forecast ensembles which are used for estimating the distribution of future atmospheric states. However, these ensembles are usually under-dispersive and uncalibrated, so post-processing is required. In the present work we compare different versions of Bayesian model averaging (BMA) and ensemble model output statistics (EMOS) post-processing methods in order to calibrate 2m temperature and 10m wind speed forecasts of the operational ALADIN limited area model ensemble prediction system of the Hungarian Meteorological Service. We show that compared to the raw ensemble, both post-processing methods improve the calibration of probabilistic and accuracy of point forecasts. In case of temperature, the BMA method with linear bias correction slightly outperforms the corresponding EMOS technique, while the EMOS model shows the best performance for calibrating ensemble forecasts of wind speed.

Pyranometers are fundamental instruments widely used for measuring global irradiance. When operating weather stations without continuous manning, pyranometer may tilt from horizontal position. Error caused by inclination of a few degrees was calculated for the annual, daily, and instantaneous global radiations. Global irradiance incident on both horizontal and tilted surfaces were calculated from the direct beam, diffuse and ground-reflected irradiances. These components were measured by accurately leveled and regularly supervised instruments. The second purpose of this paper was to determine the minimum tilt angle that is detectable by calculating certain quantities. To detect the east-west inclination, the sum of the global radiation before and after the solar noon was compared. To detect the north-south inclination, it was tested whether the global irradiance measured at a fixed solar elevation with a horizontal and a tilt pyranometer is stochastically equal. Our findings show that tilt angle of 1° in east-west direction is already detectable. Tilting to the direction at an angle of 15° from the north-south is the most difficult to detect. Here 3° is the smallest detectable tilt angle.

Information about the relationship between the spatial and temporal patterns of different climatic parameters and the vegetation is especially important from a nature conservation perspective. We studied the influence of microclimatic parameters (air temperature and air humidity) on certain natural habitat islands (karst sinkhole and sand dune slack) and on their plant species composition and vegetation pattern in Hungary. Vegetation data together with topographic variables were collected along transects to reveal the vegetation patterns on the slopes. Microclimatic parameters were measured with wireless sensor motes equipped with air temperature and humidity sensors. Interactions were examined using distance-based redundancy analysis. We found that the species composition of natural habitat islands varied markedly within short distances, depending on the prevailing microclimatic conditions. Elements of microclimate (daily, daytime, and nighttime averages) have different effects on vegetation pattern and species composition. The observed patterns can be interpreted based on our knowledge on the structure of plant communities and on the role of geomorphology. Future temperature increase, droughts, and forestry activities are the main threats to the habitat diversity and hence to the species diversity of habitat islands in Hungary.

There are many phenomena which confirm the fact of climate change. Two kinds of responses are mentioned often to this fact: 1. Actions by which this process can be interrupted or slowed down. 2. Accepting the fact of changes and finding adaptive strategies.
Authors present a research which aimed to increase the responsiveness of supply chains for the climate change – especially extreme weather. Secondary and primary investigation were carried out, and the nominal group technique was used to discover, group and assess the potential threats.
Results so far pointed out that both physical and control processes are involved in extreme whether consequences. Findings give good bases for a substantial risk analysis for any disaster coming from the climate change or other reasons.
The research is supported by the Government of Hungary.