Recent Precipitation Trends in Hungary in the Context of Larger Scale Climatic Changes

The time series of monthly precipitation totals from 14 Hungarian observing stations (1901–1998) were analysed to reveal the long term changes in precipitation characteristics occurred in the 20th century. A particular attention was given to the changes in the recent decades and their links with the larger scale climatic and circulation changes over Europe and the Atlantic.The statistical significancesof systematic changes are controlled by linear trend analysis and the Mann–Kendall test. The long term fluctuations are illustrated applying a 15-point Gaussian filter on the time series. The Standardised Precipitation Index is used to evaluate the changes in the drought event frequency. The relationships with larger scale changes are mostly discussed relying on contemporary papers, and the Grosswetterlagen Catalogue is used as well.The annual precipitation total decreased by 15–20% in Hungary during the 20th century. The decline is substantial in both halves of the century, but the precipitation sums in the transition seasons declined in the first 50 years, and the winter precipitation decreased in the latest decades. The precipitation total of the period November–February declined significantly in the last 50 years. In the same time the mean winter value of the North Atlantic Oscillation Index (NAOI) increased, the positions of the main pressure patterns over the Atlantic are shifted northeastward, and lot of other coherent changes detected in the winter climate of the European–Atlantic region. The mean summer precipitation total has hardly changed, but the frequency of summer drought events increased. There are some signs of a shift of the Hungarian summer climate towards a Mediterranean like climate.     

Temporal accumulations of extreme daily meantemperature anomalies

Summary  Statistical characteristics of accumulated extreme low and high daily mean temperatures have been investigated for Hungary. Temperature extremes over periods of a few weeks were studied using 96-year temperature records. Temperature is defined as extreme in the lowest or highest five percent of the empirical distribution of anomalies. Recurrence frequencies of extreme anomalies were computed at 1, 2,…, 75 days after the initial anomalies, and compared with the respective characteristics of an appropriate 2^nd order autoregressive model. In accordance with the high 1-day lagged autocorrelation in Hungarian temperature time series, model-frequencies are large for low lags, and approach the value for independence (0.05) for periods longer than 10–15 days. Considerable similarity of recurrence frequency between observed and simulated series is found but with some important exceptions. After only 1 extreme cold winter-day or an extreme warm summer-day, the probability of the next extreme occurring with the same sign remains significantly high for longer than 1 month. Empirical frequencies are very sensitive to the calendar date of the initial extreme value occurrence. Discrepancies between real and model characteristics were tested for statistical significance by Monte Carlo simulation technique. Recurrence frequencies for the last 30 years have also been computed, and intersting similarities and differences were found relative to the earlier part of the 20^th century. To identify possible relationships between droughts and hot spells, extreme high daily temperatures and dry subperiods during summers were selected. Recurrence frequencies of extreme positive anomalies in dry periods, more than 15–20 days after an initial occurrence, are surprisingly high during the second half of the summer. Received February 15, 2000 Revised September 11, 2000     

Statistical characteristics of detectable inhomogeneities in observed meteorological time series

Statistical characteristics of detectable inhomogeneities [IHs] in more than 600 observed meteorological time series have been investigated using 16 objective homogenisation methods. Forty and 100 year long series of monthly or annual characteristics of surface air temperature, precipitation total and relative air humidity from the Czech Republic and Hungary were examined. The area of the part of the Czech observing network used here is smaller, and the density of sites is larger, than in the Hungarian network, resulting in higher spatial correlations among data in the Czech dataset relative to the Hungarian dataset. Time series with low number of gaps were supplied with interpolated data. Before homogenisation relative time series were created, using weighted averages of time series from the same geographical region as reference series. For ease of comparison, the magnitudes of the detected IHs are normalised with the standard deviation of the noise in the relative time series. Results show that observed meteorological time series usually contain large number of small IHs, and that the magnitude distribution of IHs from different data segments are surprisingly similar. Effects of different spatial coherences on the results are discussed.     

Efficiency evaluation for detecting inhomogeneities by objective homogenisation methods

Evaluation and comparison of efficiencies of widely used objective homogenisation methods (OHOMs) are presented relying on some test-datasets and efficiency measures. Problems related to the choice of efficiency measure, creation of appropriate test-datasets and use of OHOM parameterisation are discussed. The detection parts of the OHOMs are examined only. Power of detection, false alarm rate, detection skill and skill of linear trend estimation are calculated and compared for eight OHOMs and six test-datasets. Each test-dataset comprises 10,000 100 year-long artificially simulated time series. In the simplest test dataset, each time series contains one inhomogeneity (IH), while a structure of inhomogeneities that is similar to that of real central European temperature time series is included in the most complex simulated dataset. Distinct attention is given to OHOMs that contain (1) cutting algorithm, (2) semihierarchic algorithm, (3) direct detection of multiple IHs, (4) detection of change-point and trend-line shaped IHs. Results show that Caussinus?CMestre method and Multiple Analysis of Series for Homogenization are the most powerful tools in detecting and correcting IHs in climatic time series.     

Long-term changes in observed temperature and precipitation series 1901–1998 from Hungary and their relations to larger scale changes

Summary ¶Trends and low frequency fluctuations relying on 14 observed temperature and precipitation series 1901–1998 from Hungarian sites are presented. The statistical significances of systematic changes are calculated by the t-test for the linear trends and the Mann-Kendall test. Characteristics of long-term fluctuations are investigated by spectrum analysis (Fisher-test), fitting optimum-ranked polynomials as well as illustrated by smoothed curves of 15-point Gauss-filter application.While the increase of mean temperature in Hungary during the 20^th century is not significant, the annual precipitation totals have substantially decreased. In the first half of the century mainly the precipitation totals in the transitional seasons decreased. By the second half of the century the seasonal structure of the precipitation trends has altered significantly: there was practically no systematic change in the transitional seasons, but winter precipitation decreased dramatically. The paper makes some comparisons with the same type climatic characteristics of the surrounding geographical regions, the temperature changes of the Northern Hemisphere, as well as discusses the relationship between winter precipitation in Hungary and the North Atlantic oscillation.A significant 50-year oscillation was found in the summer mean temperatures and the annual sums of extreme positive daily temperature anomalies in Hungary. This oscillation seems to be in tune with other processes over the Euro-Atlantic region. A cycle of 3.6 years in the annual precipitation totals was found to be significant at the 0.10 level.Received May 27, 2002; revised October 7, 2002; accepted November 4, 2002 Published online June 4, 2003     

Statistical Characteristics of Extreme Temperature Anomaly Groups in Hungary

Summary Investigation of diurnal temperature data series in Hungary indicates that extreme anomalies often occur in groups. Periods which include at least 3–6 extreme anomalous days with 3–5 times higher frequency relative to the climatological average are referred to as periods of extremity (PE). Although PEs cover only 5–12% of the whole time-series (1901–1993), they include 40–90% of all days with extreme temperatures. This refers both to the positive and negative anomalies. This paper shows a method for delimitation technique of PEs which is more suitable for the revelation of time-sequence structure of extreme temperature value occurrences, than traditional investigations of daily or monthly values. As it was checked by Monte-Carlo simulations, a one step autoregressive model, exhibiting nearly normal distribution gives a fairly good approach of extreme temperature occurrences. However, significant differences between the statistical characteristics of real and simulated PEs are also experienced. Statistical connections between PEs and macrocirculation are also investigated. Received November 12, 1996 Revised July 6, 1997     

Correlation of ice load with large-scale and local meteorological conditions in Hungary

Conditional probability of icing in correlation with local weather elements, as well as with different macrocirculation types are investigated on the basis of 23 years of daily observations for two stations situated in the Pannonian Plain (Debrecen) and in mountainous region (Kékestetö, 1000 m above sea-level). Empirical histograms are calculated and a theoretical model of the distribution is elaborated. Ice is generally twice as frequent at night as during the day. Icing is 5–6 times as frequent on the top of the hill as on the plain, especially considering larger water-contents. Macrosynoptic conditions favourable for icing are essentially different in the two circumstances. At the higher altitude icing is more frequent in cyclonic situations. Considerable load is often accompanied with southwesterly, southerly currents. On the plain station however the anticyclonic situations are somewhat more frequently accompanied with ice formation. Wind speed is practically indifferent at the top of the hill, but on the plain ice formation prefers low wind speeds. These differences are in coincidence with the a priori information of the different nature of ice load. Namely, at the top of hill in-cloud icing is the predominant form, while on the plain fine rime and frozen precipitation represent the overwhelming majority of ice load events. No clear differences in probabilities of icing in any of the above relations appear, however, between the two perpendicular directions of measuring devices. From among the possible applications of the results, a local scenario on ice load changes assuming a 0.5 K global warming is presented.