Vol. 110, No. 1 * Pages 1–89 * January - March 2006

Winter precipitation is one of the most challenging meteorological phenomena for operational weather forecasters. A possible way of increasing forecast skill is to investigate cases occurred in the past, trying to find essential processes as well as important parameters, and to draw conclusions based on the results. Heavy snowfall events have been investigated for the period 1953–2003 in Budapest. After providing a precise definition of heavy snowfall events, SYNOP reports for the station Pestlőrinc (Budapest) as well as data from the NCEP/NCAR Reanalysis dataset with a temporal resolution of 6 hours have been collected for each event. Based on this comprehensive database, two types of investigation have been carried out. The first part of the paper contains the main characteristics of heavy snowfall events, while in Part II, results connected with the subjective classification of the cases will be presented. The length of the investigated period (50 years) makes it possible to seek potential signs of climate change as well. One of the most important results of the first part of the study is the high stability of the climate system in terms of heavy snowfall events in Budapest. In most of the characteristics, there has been only a slight change during the past 50 years. The most important change revealed by the research, however, is the considerable modification of the frequency of heavy snowfall events within the winter period itself. It can be also stated that our results could be efficiently used in operational weather forecasting.

This paper presents the sensitivity of a second-generation local-scale disper­sion model, called AERMOD, which was adapted at the Hungarian Meteorological Service (HMS) in 2003. AERMOD was designed to introduce current planetary boundary layer concepts into regulatory dispersion models. In this paper the calculation of the most important planetary boundary layer parameters for dispersion calculations are described. The character of the boundary layer is represented with some case studies. We especially wanted to examine, what kind of meteorological parameters can result in high, short time average (1-hour) concentrations in the modeling domain. Finally, we also made a sensitivity analysis study of the newly implemented dry and wet deposition algorithms.

Climate extreme indices are analyzed and compared for the Carpathian Basin for the 20th century based on the guidelines suggested by the joint WMO-CCl/CLIVAR Working Group on climate change detection. These climate extreme indices include the numbers of severe cold days, winter days, frost days, cold days, warm days, summer days, hot days, extremely hot days, cold nights, warm nights, the intra-annual extreme temperature range, the heat wave duration, the growing season length, etc. Therefore, daily maximum, minimum, and mean temperature observations are used in the present statistical analysis. Our results suggest that similarly to the global and continental trends, regional temperature of Central/Eastern Europe became warmer during the second half of the 20th century.

Agricultural land use series are investigated in a plain catchment area of the river Tisza within Hungary, almost identically represented by six administrative counties. Each county, commonly covering 34,900 km², is characterized by high percentage (72–82%) of managed vegetation. Effects of the area coverage variations between the different plant species are computed for the period 1951–2000, by applying results of literature-based syntheses specified for Hungary. The latter studies estimate surface albedo values for the great majority of the plant species grown in the region. Product of the plant-specific albedo values and the relative area coverage results in monthly series of surface albedo. Furthermore, by using a radiation transfer model, these series are also used to simulate radiation balance series for the surface-atmosphere system. Two questions are investigated and positively answered: (i) Are there monotonous trends in the radiation balance? (ii) Are these changes comparable to the effects caused by other external forcing factors?

Objective homogenization methods (OHOMs) are applied on time series of observed meteorological data mostly from Hungarian sites. The used database comprises temperature and precipitation series at 20 stations from Hungary and 4 stations from other countries in Central Europe. Different ways of data treatment multiply the number of the available series, whereas lack of data limits them. Altogether, 215 series of monthly or annual mean temperatures and 112 series of monthly or annual precipitation totals are analyzed. All of the series are 98–100 years long. The time step between the adjacent members of each series is 1 year. Statistical characteristics of the detected change points, such as mean number of change points per time series, mean magnitude of shifts, etc., are calculated. The aims of the investigation are: (i) to get a general insight into the detectable inhomogeneities in meteorological time series from Hungary, and (ii) to gather the necessary knowledge for the development of testing the efficiency of OHOMs. The study also explains the concept of OHOM, presents its main kinds, and provides some arguments about conditions, advantages, and limitations related to their practical application. Twelve OHOMs are applied in the study, their results have several common features. The OHOMs are taken from the literature with slight modifications, and they are always applied on relative time series, i.e., on the differences of candidate series and reference series. Identical process of reference series derivation, constructed from commonly used elements, is used for all included OHOMs. The main results of the study are: (i) More than half of the examined time series are inhomogeneous. (ii) Most of the detected shift magnitudes are hardly larger than the standard deviation of the noise term. (iii) Serial correlation is indicative of homogeneity quality. (iv) Homogeneity quality of winter temperatures is much better than that of summer temperatures. (v) Distribution of the detected shift magnitudes is skewed positively for each of the OHOMs and each examined meteorological variable.