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This paper presents a method for grouping weather types that occur over an area, which combines meteorological parameters, reflecting air mass characteristics at the surface, with synoptic conditions prevailing over an area. Five quantitative meteorological parameters are used in the procedure: temperature, precipitation, relative humidity, wind velocity and sunshine duration. In addition, two qualitative variables related to the prevailing circulation type and whether it is cyclonic or anticyclonic are also included. The study period is 43 years (1958–2000) and is restricted to the cold and wet sub-period of the year, December–March. Weather types are defined using a relatively new method of cluster analysis, two-step cluster analysis, which allows the simultaneous use of both quantitative and qualitative variables. The aim of the present study is to distinguish primary weather patterns so that the investigation into the relationship between weather patterns and circulation types will be more effective. For Athens, six weather types are created, whereas for Thessaloniki five are produced. For both stations, only two weather types are related to anticyclonic situations. The majority of the identified weather types correspond to a distinctive and well-defined synoptic situation. Each weather type differs from the others, not only in terms of the circulation conditions referring to it, but also with reference to meteorological variables such as temperature and precipitation. The results of the evaluation of the aforementioned procedure are considered to be highly satisfactory. [ABSTRACT FROM AUTHOR]

A discriminant analysis is applied in order to determine the relationships between circulation types in the middle troposphere and prevailing weather types over two major Greek cities, Athens and Thessaloniki. In order to describe the synoptic conditions, an automatic classification scheme for the Greek region is used. For each circulation type identified (14 in total), several meteorological parameters at the 500 hPa level are calculated such as geopotential heights and their anomalies, temperature and relative vorticity. Weather group-types that reflect the conditions at the surface, were previously defined using a two-step cluster analysis. These types result from a combination of five meteorological parameters—maximum temperature, precipitation amount, relative humidity, wind velocity and sunshine duration. The study period is 43 years long (1958–2000) and is restricted to the cold and wet period of the year, from December until March. For Athens, six weather types are developed, whereas for Thessaloniki five are produced. By means of a stepwise discriminant analysis (DA) model, the most important variables from the 500 hPa level are found and are used to generate the necessary functions that can discriminate weather types over the two stations. The aim of the present study is first to discriminate weather types effectively and to identify the most important discriminating variables, and second, to connect these weather types to elements of the prevailing synoptic pattern, through mathematical functions provided by DA. The results of the evaluation of the aforementioned procedure are considered to be very satisfactory. [ABSTRACT FROM AUTHOR]

The article reports on the study regarding the changes in the climate of the Aegean regions during 1961 until 2002. In the study, the authors use information on surface temperature climate at several stations. Moreover, the author uses multiple sliding time-windows of data in analyzing the significant changes in the Aegean region climate. According to the authors, the statistical significance of the trends and the number of stations were the quantities used in producing a regional summary. Tables and charts regarding the data used in the study are included in the article.

The main objective of the present study was the examination and the quantification of the uncertainties in the precipitation time series over the Greek area, for a 42-year time period. The uncertainty index applied to the rainfall data is a combination (total) of the departures of the rainfall season length, of the median data of the accumulated percentages and of the total amounts of rainfall. Results of the study indicated that all the stations are characterized, on an average basis, by medium to high uncertainty. The stations that presented an increasing rainfall uncertainty were the ones located mainly to the continental parts of the study region. From the temporal analysis of the uncertainty index, it was demonstrated that the greatest percentage of the years, for all the stations time-series, was characterized by low to high uncertainty (intermediate categories of the index). Most of the results of the uncertainty index for the Greek region are similar to the corresponding results of various stations all over the European region. [ABSTRACT FROM AUTHOR]

Statistical downscaling techniques have been developed for the generation of maximum and minimum temperatures in Greece. This research focuses on the four conventional seasons, and three downscaling approaches, Multiple Linear Regression using a circulation type approach (MLRct), Canonical Correlation Analysis (CCA) and Artificial Neural Networks (ANNs), are employed and compared to assess their performance skills. Models were developed individually for each variable (Tmax, Tmin), station and season. The accuracy of downscaled values has been quantified in terms of a number of performance criteria, such as differences of the mean and standard deviation ratios between observed and modelled data, the correlation coefficients of the two sets, and also the RMSEs of the downscaled values relative to the observed. All methods revealed that during the cool season Tmax tends to be better reproduced, whereas Tmin is overestimated, particularly over western Greece, which is characterised by higher orography. With respect to the warm season, the simulation of Tmax reveals greater divergence, whereas Tmin is better generated. The distinction between the three techniques is somewhat blurred. None of the methods were found to be superior to the others and each has been shown to be a good estimator in some cases. This study concludes that all proposed methods comprise useful tools for simulating daily temperatures, as the high correlation coefficients, between observed and downscaled values, have demonstrated. However, the importance of local factors, which affect the natural variability of temperature, has been emphasised indicating that the geography of a region constitutes an important and rather complex factor, which should be included in models to improve their performance. [ABSTRACT FROM AUTHOR]