A. Karagiannidis

Climatological aspects of extreme precipitation in Europe, related to mid-latitude cyclonic systems

Climatic aspects of extreme European precipitation are studied. Daily pluviometric data from 280 stations across Europe, covering the period from 1958 to 2000, are used. First, the criteria for extreme precipitation cases and episodes are communicated using threshold and spatial definitions. The cases and episodes meeting these criteria are grouped according to their area of appearance. Most of them are located in three major areas: Greece, the Alps, and the Iberian Peninsula. The existence of trends in the annual and seasonal time series of these extreme events is examined. Decreasing trends are found in most of the cases, for Greece, the Iberian Peninsula, and Europe, as a whole. The Alps present a different behavior, with no trend at all in the southern part, and a possible increasing trend in the northern part. Finally, the positive impact of altitude in the frequency of occurrence of extreme precipitation episodes in Europe is discussed.

Modeling and mapping temperature and precipitation climate data in Greece using topographical and geographical parameters

This study presents a methodology for modeling and mapping the seasonal and annual air temperature and precipitation climate normals over Greece using several topographical and geographical parameters. Data series of air temperature and precipitation from 84 weather stations distributed evenly over Greece are used along with a set of topographical and geographical parameters extracted with Geographic Information System methods from a digital elevation model (DEM). Normalized difference vegetation index (NDVI) obtained from MODIS Aqua satellite data is also used as a geographical parameter. First, the relation of the two climate elements to the topographical and geographical parameters was investigated based on the Pearson’s correlation coefficient to identify the parameters that mostly affect the spatial variability of air temperature and precipitation over Greece. Then a backward stepwise multiple regression was applied to add topographical and geographical parameters as independent variables into a regression equation and develop linear estimation models for both climate parameters. These models are subjected to residual correction using different local interpolation methods, in an attempt to refine the estimated values. The validity of these models is checked through cross-validation error statistics against an independent test subset of station data. The topographical and geographical parameters used as independent variables in the multiple regression models are mostly those found to be strongly correlated with both climatic variables. Models perform best for annual and spring temperatures and effectively for winter and autumn temperatures. Summer temperature spatial variability is rather poorly simulated by the multiple regression model. On the contrary, best performance is obtained for summer and autumn precipitation while the multiple regression model is not able to simulate effectively the spatial distribution of spring precipitation. Results revealed also a relatively weaker model performance for precipitation than that for air temperature probably due to the highly variable nature of precipitation compared to the relatively low spatial variability of air temperature field. The correction of the developed regression models using residuals improved though not significantly the interpolation accuracy.

The Air Quality of a Mediterranean Urban Environment Area and Its Relation to Major Meteorological Parameters

The paper presents a comprehensive analysis of the most basic features of the air quality of a Mediterranean urban environment area. The impact of meteorology on the air quality is also examined. Observational surface concentrations of the most important air pollutants, recorded at two measuring stations in Patras, Greece, are used. The Weather Research and Forecasting (WRF) meteorological model was employed to produce a series of surface and upper air data and local circulation and ventilation indices. These modeled data along with selected surface meteorological observational data comprise a substantial data set that was used to assess the effect of meteorology on the air quality. Mostly during the summer period, a significant proportion of the particulate matter is transported from sources away from the measuring sites. The synoptic setting of winter and summer seasons represented primarily by the local ventilation and recirculation, the wind, the boundary layer height, and the precipitation has a very strong impact in the overall formation of the air quality status.

Maritime Sector Emissions Contribution to the Particulate Matter Pollution in a Mediterranean City-Port: A Modeling Approach

The main aim of this work is the investigation of the contribution of different emission sources to the concentrations of the fine Particulate Matter (PM2.5) in the city-port of Patras in Greece using a meteorological and a photochemical model. Emphasis is given on the contribution of the maritime transport and the activities within the Patras harbor area for which the existing environmental information is very limited.

Relating Climatic Variables to Geographic Features in Greece

This study aims at investigating the relationship of climatic variables with geographic features over Greece. Seasonal and annual climate normals of temperature, rainfall and relative humidity covering the period from 1975 to 2004, from 85 meteorological stations of the Hellenic National Meteorological Service network are included in the analysis. Several geographical and environmental parameters such as altitude, location, slope, aspect, distance to coast, sea/land ratio and vegetation index obtained from a coastline dataset, a digital elevation model and a land cover database were examined for their dependencies with climatic elements. The relationship of a climate element with each geographical variable was investigated by means of graphical (e.g. scatter plots) and statistical scores. The results were used to assess the ability of each geographical parameter to explain part of the spatial variability of a climate variable. Backward stepwise linear regression was used to obtain a surface that gives the best fit to the measured climatic data. The adjusted determination coefficient (R 2 adj ) was computed to evaluate the efficiency of each model. Elevation, latitude and NDVI were found to be the most important predictors, whereas other geographical parameters contribute less to the model predictability.