János Mika

Long term climate deviations: An alternative approach and application on the Palmer drought severity index in Hungary

A new statistical test (Makra-test), applicable for long time series, is introduced to identify extended sub-periods, namely, ‘‘breaks’’, average of which is significantly higher or lower than the mean of the entire time series. In order to apply this test, normal distribution of the time series being examined is a sufficient condition. In another case, if the number of elements increases in the time series, its distribution is near normal and the test can be applied, as well (according to the Central Limit Theorem). The method is demonstrated on monthly Palmer drought severity index (PDSI) data sets, computed for five stations of East Hungary in 1901– 1999. Due to strongly recursive (auto-correlative) nature of PDSI every second month of the warm season (April, June, August and October) is analysed and treated as independent samples. Normality of the time series, which is a sufficient condition of the Makratest, is validated by Kolmogorov–Smirnov test and v 2 -test. Analysis of the PDSI time series indicates that separate treatment of the months is important not only to ensure the normality, but also to consider the existing slight seasonal differences in standard deviation and skewness of the index in the East-Hungarian region. The Makra-test delimits one or more (maximum 4) significant subperiods of the PDSI in every station and month (not considering the sub-intervals within the significant breaks, although most of them are also significant). Since the PDSI is based on monthly temperature and precipitation data that exhibit considerable inhomogeneities (Szentimry, 1999), the test is applied both for the original and the homogeneous time series. Effect of the inhomogeneity on long term variations of PDSI is strong: about the half of the significant breaks in the original time series disappear or become totally different from the time series based on homogenised data. All negative (dry) breaks of each month and station, however, occurred in more recent decades of the 20th century, according to both homogeneous and original series. � 2002 Elsevier Science Ltd. All rights reserved.

Impact of documented land use changes on the surface albedo and evapotranspiration in a plain watershed

Abstract Agricultural land use series are investigated in a plain catchment area of the Tisza River, almost identically represented by six administrative counties. Each county, commonly covering 34,000 km 2 , is characterised by high percentage (70–80 %) of managed vegetation. Effects of area coverage variations between the different plants are computed for the period 1951–1993 by applying results of a literature-based syntheses, specified for Hungary. The latter studies estimate surface-albedo values and proportion between real and potential evapotranspiration for the great majority of the plants grown in the region. Potential evapotranspiration and relative soil moisture content are estimated from the monthly meteorological series of temperature, precipitation and atmospheric water vapour pressure. Product of these plant-specific characteristics and the relative area coverage yield in monthly series of surface albedo and real evapotranspiration. Furthermore, these values are related to the energy balance of the surface-atmosphere system by using a radiative-convective model adjusted for the given location. Two questions are investigated: i) Are there monotonous trends in the given terms of the energy and water budget? ii) Are these changes comparable to the effects caused by other external forcings? Our computations give positive answer to both questions.

Comparison of objective air-mass types and the Péczely weather types and their ability to classify levels of air pollutants in Szeged, Hungary

This paper compares the efficiency of a system of objective air-mass types and the Peczelys weather types in classifying pollution levels over the Carpathian Basin for the winter and summer months. Based on the ECMWF data set, daily sea-level pressure fields analysed at 00 UTC were related to the levels of air pollutants for both the objective air-mass types and the Peczely-types in Szeged. The data base comprises daily values of 12 meteorological and eight pollutant parameters for the period 1997-2001. Mean sea-level pressure fields of the Peczely-types show higher independence from each other than those of the objective clusters in both seasons. In the winter months, anticyclonic types are mostly favourable, while cyclonic ones are mostly negligible in classification of pollutant levels both for the objective and the Peczely-types. In the summer months, neither the objective nor the Peczely classifications are effective in categorisation of pollutant concentrations.

Changes in weather and climate extremes: phenomenology and empirical approaches

The terms “weather extremes” and “climate extremes” are widely used in meteorology, often in relation to climate change. This paper reviews the empirical investigations into parallel changes in extreme events and climate change published in recent years and looks at their relevance for the global energy system. Empirical investigation into the correlation of extremes with global warming covers five groups: changes in temperature, precipitation, wind (storm) extremes, tropical and extra-tropical circulation phenomena. For temperature extremes, extensive analyses demonstrate that extreme hot days and nights will likely become more frequent, and extreme cold days and nights less frequent. Intense precipitation events will likely become more frequent in most continental regions. Scientific confidence in the trends of the frequency, duration, and intensity of tropical cyclones, is still low. A poleward shift is observed for extratropical cyclones, whereas no convincing tendencies of many smaller-scale phenomena, for example, tornados, or hail, can yet be detected. All these extremes have serious implications for the energy sector.

Relationship between the Péczely's large‐scale weather types and airborne pollen grain concentrations for Szeged, Hungary

This paper discusses a subjectively defined system of air mass types, the 13 Péczelys large‐scale weather situations over the Carpathian Basin in relation to the detected airborne pollen grain concentrations. Based on the ECMWF (European Centre for Medium‐Range Weather Forecasts) sea‐level pressure data set, daily sea‐level pressure fields analyzed at 00:00 UTC were prepared for each Péczelys weather types in order to relate the sea‐level pressure patterns with the average pollen levels in Szeged. The data basis for this study comprises daily values of 12 meteorological parameters and daily average pollen concentrations for 24 species in a 5‐year period (1997–2001). It was found that Péczelys anticyclonic ridge types 2 and 11 as well as cyclonic types 4 and 7 are favourable for pollen production and dispersal unlike the cyclonic types 3 and 13. Hence, the Péczelys large‐scale weather situations cannot alone be considered as an overall system in predicting pollen concentrations.

Applications of the MVWG Multivariable Stochastic Weather Generator

Weather generators (WG) became significant modules of crop models and decision support systems in the past decade. Using a large meteorological database from North America; two basic problems, related to the applicability of WGs in case of short or lacking data series, were investigated in the framework of the Multivariable weather generator (MVWG). First, the minimum data series length, required for adequate parameterization of the WG, was determined. Our results suggest that 15 years of observed data are enough for adequate parameterization of the MVWG. We then investigated a possibility of spatial interpolation of WG parameters using the outputs of the WG for sites with no meteorological observations. Coupled with the presented interpolation technique, MVWG was able to generate realistic weather data for sites with no measurements situated in climatically and geographically homogeneous regions.