Weather Type Classification Research Articles

Statistical–dynamical downscaling of present day and future precipitation regimes in the Aksu river catchment in Central Asia

A statistical–dynamical downscaling (SDD) approach is applied to determine present day and future high-resolution rainfall distributions in the catchment of the river Aksu at the southern slopes of the Tienshan Mountains, Central Asia. First, a circulation weather type (CWT) classification is employed to define typical lower atmospheric flow regimes from ERA-40 reanalysis data. Selected representatives of each CWT are dynamically downscaled with the regional climate model COSMO-CLM 4.8 at a horizontal grid resolution of 0.0625°, using the ERA-40 reanalysis data as boundary conditions. Finally, the simulated representatives are recombined to obtain a high-resolution rainfall climatology for present day climate. The methodology is also applied to ensemble simulations of three different scenarios of the global climate model ECHAM5/MPI-OM1 to derive projections of rainfall changes until 2100.Comparisons of downscaled seasonal and annual rainfall with observational data suggest that the statistical–dynamical approach is appropriate to capture the observed present-day precipitation climatology over the low lands and the first elevations of the Tienshan Mountains. On the other hand, a strong bias is found at higher altitudes, where precipitation is clearly underestimated by SDD.The application of SDD to the ECHAM5/MPI-OM1 ensemble reveals that precipitation changes by the end of the 21st century depend on the season. While for autumn an increase of seasonal precipitation is found for all simulations, a decrease in precipitation is obtained during winter for most parts of the Aksu catchment. The spread between different ECHAM5/MPI-OM1 ensemble members is strongest in spring, where trends of opposite sign are found. The largest changes in rainfall are simulated for the summer season, which also shows the most pronounced spatial heterogeneity. Most ECHAM5/MPI-OM1 realizations indicate a decrease of annual precipitation over large parts of the Tienshan, and an increase restricted to the southeast of the study area. These results provide a good basis for downscaling present-day and future rainfall distributions for hydrological purposes.

The SSC: a decade of climate–health research and future directions

This year marks the tenth anniversary of the development of the revised Spatial Synoptic Classification, the "SSC", by Scott Sheridan. This daily weather-type classification scheme has become one of the key analytical tools implemented in a diverse range of climatological investigations, including analysis of air quality variability, human health, vegetation growth, precipitation and snowfall trends, and broader analyses of historical and future climatic variability and trends. The continued and expanding use of the SSC motivates a review and comparison of the system's research and geographic foci to date, with the goal of identifying promising areas for future efforts, particularly within the context of human health and climate change. This review also assesses how the SSC has complemented and compares with other current environmental epidemiological studies in weather and health.

Classification of synoptic weather types using the self-organising map and its application to climate and air quality data visualisation

Classification of synoptic weather types using the self-organising map and its application to climate and air quality data visualisation

Statistical assessment and modeling of the effects of weather conditions on H2S plume dispersal from Icelandic geothermal power plants

Episodes of high atmospheric load of hydrogen sulfide (H2S), where the concentration is over 50μgm−3 hourly average value, occur about 80 times a year in Reykjavik (data from 2007 to 2009). H2S originates mainly from two geothermal power plants 25–30km (south-)east of Reykjavik, at Hellisheidi and Nesjavellir. Certain weather-dependent dispersion conditions, such as wind, cloud cover and air temperature, allow the transport of emissions towards Reykjavik and the neighboring cities, causing local air pollution. High concentrations of H2S occur within a narrow range of weather conditions, namely slow (mean value 2±1ms−1) easterly (114°±23°) winds, together with cold air temperatures (median value −3°C) and preferably no, or little, cloud cover. A classification of weather types shows the preferred occurrence of high H2S concentrations in connection with low atmospheric exchange and autochthonous weather. Stable atmospheric stratification and inversions enable the transport of H2S emissions to Reykjavik. The measured concentrations, the short lived peaks in concentration and different values at nearby measurement stations, indicate a very narrow plume, which fits well with a Gaussian plume distribution model.

Conditioning model output statistics of regional climate model precipitation on circulation patterns

Abstract. Dynamical downscaling of Global Climate Models (GCMs) through regional climate models (RCMs) potentially improves the usability of the output for hydrological impact studies. However, a further downscaling or interpolation of precipitation from RCMs is often needed to match the precipitation characteristics at the local scale. This study analysed three Model Output Statistics (MOS) techniques to adjust RCM precipitation; (1) a simple direct method (DM), (2) quantile-quantile mapping (QM) and (3) a distribution-based scaling (DBS) approach. The modelled precipitation was daily means from 16 RCMs driven by ERA40 reanalysis data over the 1961–2000 provided by the ENSEMBLES (ENSEMBLE-based Predictions of Climate Changes and their Impacts) project over a small catchment located in the Midlands, UK. All methods were conditioned on the entire time series, separate months and using an objective classification of Lamb's weather types. The performance of the MOS techniques were assessed regarding temporal and spatial characteristics of the precipitation fields, as well as modelled runoff using the HBV rainfall-runoff model. The results indicate that the DBS conditioned on classification patterns performed better than the other methods, however an ensemble approach in terms of both climate models and downscaling methods is recommended to account for uncertainties in the MOS methods.

Changes in atmospheric circulation and temperature trends in major vineyard regions of New Zealand

ABSTRACTThis paper contributes to knowledge of the impact of global warming on viticulture, using major vineyard regions of New Zealand as a case study to illustrate regional disparities in climate change impacts resulting from downscale effects of larger scale atmospheric circulation. Recent trends in air temperature in New Zealand vineyard areas are investigated. Trends since 1941 in Marlborough show an increase in temperature range, with both rising maximum temperatures and declining minimum temperatures, but no change in the annual mean. More hot days and frosts are of concern to viticulturalists, and this trend not only differs from other major vineyard areas, but also occurs at other sites in eastern parts of the country. The relationship between changes in atmospheric circulation over New Zealand and observed trends in temperature and frost occurrence at Blenheim is investigated using the Kidson weather type classification for the period 1958–2010 and the Trenberth M1 index. The increased temperature range is expected to be associated with more frequent clear skies along the east coast of the country, resulting from changes in weather patterns (more frequent anticyclones, fewer low‐pressure systems, increased zonal and southerly flow). These changes in weather patterns are shown to be closely linked to larger scale changes in atmospheric circulation via the Southern Annular Mode (SAM) and Southern Oscillation. The results show that significant regional variations in the impact of global warming can occur over areas of complex terrain such as New Zealand. Observed differences in local temperature and frost trends can be caused by the interaction of changing weather systems with mountainous terrain. These changing weather systems themselves are seen to be the result of major shifts in the larger scale atmospheric circulation. These results are important for assessing possible impacts on viticulture and in developing adaptation strategies for agriculture in response to predicted future climates.

Large-scale weather types, forest fire danger, and wildfire occurrence in the Alps

In the Alps forest fires have burnt around 14,500ha per year in the past decade. In this paper we studied large-scale (synoptic) weather patterns and the corresponding occurrence of forest fires in this complex topography. The database for our analysis comprised three main parts: a daily classification of weather types in the period 1951–2010, daily calculated forest fire danger indices at five selected stations in the Alps (1951–2010) and ten years of observed forest fires (2001–2010). Firstly we analyzed the frequency of the 11 different weather types and show that the Alps are a region where cyclonic flows in general, and westerly cyclonic in particular, are the dominating large-scale weather pattern due to their location in the westerlies of the global circulation system. Comparing the weather types with three calculated sub-indices of the Canadian Forest Fire Danger Rating System (FFMC, DC, DMC) at five selected sites (representative of the different climate regions in the Alps) revealed a strong dependence of meteorological forest fire danger on flow direction and cyclonality. Cyclonic weather types were characterized by a high relative humidity and in consequence a low fire danger, while the calculated fire danger in anticyclonic weather situations was significantly higher. Furthermore, strong regional differences occurred in dependence on the flow direction. Northerly winds resulted in low fire danger north of the Alps, due to orographic enhanced precipitation, and high forest fire danger south of the Alps, because of dry katabatic foehn winds. In general, the stations in the Northern Alps showed significantly lower fire index values than the stations in the south and additionally a stronger seasonal variation with considerably higher index values in summer. Regional differences were highest for the FFMC, followed by the DMC and the DC, and could be attributed to the time lag of different forest soil layers. DMC and DC relate to a rather thick soil layer which reacts very slowly and since weather types in the Alps usually change every 7th day, drying of this deep layer is too slow to reveal significant differences between the regions. The Alpine forest fire database was analyzed on a national basis to identify correlations between observed fires and large-scale weather types. 95% of the observed fires in the EU-defined Alpine Space in the past decade occurred in the two southern countries Italy and France. This was likely due to both favorable climatic conditions and better database quality in these two countries. Unfortunately, the datasets of some regions north of the Alps (e.g. in Switzerland, Germany, Austria) were very patchy. A strong human influence on the Alpine fire regime resulted in a generally low correlation between weather types and observed forest fires. Surprisingly, many forest fires occurred in conjunction with cyclonic weather types. This could be explained by the start date of the fire which was mostly at the end of a drought period when the large-scale synoptical conditions had already turned to cyclonic. Nevertheless, most and biggest fires occurred during high pressure systems and other anticyclonic situations when the fuels were completely dry.

A 150-year record of coastline dynamics within a sediment cell: Eastern England

Coastal sediment cells reflect processes operating at a range of scales, but it is the medium spatial and temporal scales (decades to centuries) that are of greatest interest for coastal management. This paper focuses on coastline position change within a single sediment cell over 150years where the geomorphology includes cliffs, beaches and saltmarshes. The focus is the east coast of England from Flamborough Head to Gibraltar Point. Although the updrift sector of this sediment cell has been studied for well over a century, the downdrift sector has attracted significantly less attention. Using topographic profiles, bathymetric profiles, aerial photographs and historical maps we mapped coastline erosion and accretion using the Digital Shoreline Analysis System (DSAS) and calculated volumetric changes for different morphometric units. Rapid erosion of the updrift Holderness cliffs has been counterbalanced with accretion on beaches along the downdrift Lincolnshire coast. The amount of accretion in Lincolnshire corresponds to around 29% of the volume of sediment eroded from Holderness. Much of the eroded cliff material is likely to be deposited temporarily into nearshore and offshore sand banks before being redistributed by cross-shore currents. An exploration of storm surge impact on long-term erosion and accretion rates showed no clear relationship between storm surge frequency and change in coastline position, however this may be in part due to the relative timing of storm occurrence and data acquisition. The Jenkinson daily weather type classification was found to be a reasonable proxy for the occurrence of strong onshore winds which may offer scope for further investigation of the role of forcing factors over time periods beyond the length of the meteorological and tidal station records. Winter North Atlantic Oscillation phase was not a good indicator of storminess on the east coast of England but may be a useful proxy for quiescence.

Long‐term trends of hail‐related weather types in an ensemble of regional climate models using a Bayesian approach

This paper investigates the long‐term variability of specific weather types that are associated with damaging hailstorms in Germany for past (1971–2000) and future (2011–2050) time periods. Forty large‐scale weather types are determined by the objective weather type classification scheme of German Weather Service. This scheme is applied to both reanalyses (ERA‐40) and eight different regional climate model (RCM) simulations. It is shown that the RCMs are able to approximately reproduce the distribution of weather type occurrences obtained from the reference of ERA‐40. Using additional insurance loss data, the weather types are further identified as hail‐related or hail‐unrelated. Hailstorms are neither captured comprehensively by existing observation systems nor can they be modeled reliably and the large‐scale weather types are here considered as proxies for hail occurrence. Four weather types that are most likely associated with damaging hailstorms show a slight increase both during the past and future period according to the RCM simulations. A novel statistical model is developed for the probabilistic prediction of the fraction of hail damage days conditional on the weather types. The model is Bayesian and uses a Markov Chain Monte Carlo approach. For the ERA‐40 reanalysis the model prediction agrees well with fraction of hail damage days observed in the insurance data. For most of the RCM projections, the statistical model predicts a slight increase in the number of hail days in the future (2031–2045), with relative changes between 7 and 15% compared to the period 1971–2000.

A new atmospheric circulation tree-ring index (ACTI) derived from climate proxies: Procedure, results and applications

This paper introduces a new procedure to investigate the influence of weather types on spatio-temporal tree-ring growth patterns. Within the framework of the procedure a new proxy-based climate index termed as the atmospheric circulation tree-ring index (ACTI) is calculated that combines weather-type classification data with climate proxies. The new approach is tested using a Central European multi-species tree-ring width network consisting of 115 sites. The procedure used to calculate the ACTI time series includes: 1. Monte Carlo simulations, 2. multiple testing correction, and 3. selection and grouping algorithms. The tree-ring width series are grouped according to their weather-type responses, and the ACTI time series were computed for each group.The new procedure explains the climate signal preserved in tree-ring chronologies more comprehensively because the complex interaction between the different climate elements is taken into account by using weather-type classification data. Strong correlations between the ACTI and tree-ring width series (r=0.69) and between the ACTI time series and climate gridded datasets (r>0.6) were observed. Further a correlation between ACTI and northern hemisphere mean temperatures (r=0.5) were found. These results indicate that the ACTI enables the investigation of weather-type growth relationships.

Circulation weather types and wildland forest fires in the western Iberian Peninsula

The use of six indices associated with geostrophic wind and vorticity has allowed a classification of circulation weather types to be determined. This classification was employed to study the impact of low-level circulations at low levels on the daily number of forest fires over the western Iberian Peninsula (Portugal and the Spanish region of Galicia). It was found that easterly circulations [east (E), northeast (NE), and hybrid anticyclonic northeast (HANE)] were associated with an increase in the number of forest fires in the domain studied. The number of forest fires per day was 549, 357, and 309 for the E, NE, and HANE, respectively, whereas the average value was 299 fires per day. It was seen that this effect is the result of the low-level heating and drying caused by easterly circulations. The possible impact of easterly circulations on the low-level wind was also analysed, although in this case the results were not clear. The indices used to classify the circulation weather types were also employed to develop a statistical model for the daily number of forest fires. Stepwise multiple regression showed that only two indices are necessary (correlation coefficient 0.5, significant at the 0.01% level): the western component of geostrophic wind and geostrophic wind intensity. Copyright © 2012 Royal Meteorological Society

Extreme climate, not extreme weather: the summer of 1816 in Geneva, Switzerland

Abstract. We analyze weather and climate during the "Year without Summer" 1816 using sub-daily data from Geneva, Switzerland, representing one of the climatically most severely affected regions. The record includes twice daily measurements and observations of air temperature, pressure, cloud cover, wind speed, and wind direction as well as daily measurements of precipitation. Comparing 1816 to a contemporary reference period (1799–1821) reveals that the coldness of the summer of 1816 was most prominent in the afternoon, with a shift of the entire distribution function of temperature anomalies by 3–4 °C. Early morning temperature anomalies show a smaller change for the mean, a significant decrease in the variability, and no changes in negative extremes. Analyzing cloudy and cloud-free conditions separately suggests that an increase in the number of cloudy days was to a significant extent responsible for these features. A daily weather type classification based on pressure, pressure tendency, and wind direction shows extremely anomalous frequencies in summer 1816, with only one day (compared to 20 in an average summer) classified as high-pressure situation but a tripling of low-pressure situations. The afternoon temperature anomalies expected from only a change in weather types was much stronger negative in summer 1816 than in any other year. For precipitation, our analysis shows that the 80% increase in summer precipitation compared to the reference period can be explained by 80% increase in the frequency of precipitation, while no change could be found neither in the average intensity of precipitation nor in the frequency distribution of extreme precipitation. In all, the analysis shows that the regional circulation and local cloud cover played a dominant role. It also shows that the summer of 1816 was an example of extreme climate, not extreme weather.

An objective circulation pattern classification for the region of svalbard

Käsmacher, O. and Schneider, C., 2011. An objective circulation pattern classification for the region of Svalbard. Geografiska Annaler: Series A, Physical Geography, 93, 259–271. DOI: 10.1111/j.1468‐0459.2011.00431.xThis study presents an automated or so‐called objective circulation pattern classification for the region of the Svalbard archipelago on the basis of gridded NCEP/NCAR‐reanalysis data in a spatial resolution of 2.5 × 2.5° for the variables sea level pressure and geopotential heights on the 500 and 700-hPa levels. Self‐organizing maps were set up and run several times, each time using a different number of clusters into which to partition the data. After evaluating the results for all clusters by means of statistical indices we decided to use nine circulation patterns for further analysis. The resulting patterns were related to surface variables for Svalbard in order to test how good the catalogue of circulation patterns performs as a tool for the analysis of synoptic forcing. Furthermore, the catalogue was compared to an alternative subjective classification of weather types which results in only partly coherence. We show that the different circulation patterns derived in this study nicely represent seasonal states of the atmosphere. Within seasons, significant deviations of surface air temperature and precipitable water content are associated with the different weather types. The latter fact points to a broad applicability of this circulation pattern classification for studies that address the impact of interannual atmospheric variability on other parts of the geo‐system such as glaciers, ice caps and vegetational patterns.

Connection between NAO, weather types and precipitation in León, Spain (1948–2008)

AbstractThe variability of winter precipitation in the west of the Iberian Peninsula is strongly affected by the North Atlantic Oscillation (NAO). This study focuses on identifying the relationship that exists between precipitation registered in the city of León (in northwestern Spain), the NAO index and the associated weather type during the same period. In order to achieve this objective, the prevailing weather type has been calculated for each day in León from January 1948 to March 2009, using the objective Lamb Weather Types classification method. The most significant results appear in winter (from December to March). During these months an increase has been observed in the frequency of ‘anticyclonic’ weather type (A) (very dry), and a decrease in the ‘cyclonic’ (C), ‘south‐westerly’ (SW) and ‘westerly’ (W) types (the three rainiest weather types). The positive trend in the NAO index could be the main cause of the decrease in the frequency of the three rainiest weather types (C, SW and W) and therefore, responsible for the relevant decline in winter precipitation observed in the city of León. The high correlation coefficients between the NAO index, the frequency of the three rainiest weather types and winter precipitation suggests an interesting method to forecast rainfall. Using a binary logistic regression model, a downscaling model for daily precipitation has been obtained based on the weather types and the NAO index. The daily results obtained for the winter months are good (TSS = 0.64) bearing in mind that only sea level pressure data were used in the logistic model. Copyright © 2011 Royal Meteorological Society

Odour-impact assessment around a landfill site from weather-type classification, complaint inventory and numerical simulation

Gases released from landfill sites into the atmosphere have the potential to cause olfactory nuisances within the surrounding communities. Landfill sites are often located over complex topography for convenience mainly related to waste disposal and environmental masking. Dispersion of odours is strongly conditioned by local atmospheric dynamics. Assessment of odour impacts needs to take into account the variability of local atmospheric dynamics. In this study, we discuss a method to assess odour impacts around a landfill site located over complex terrain in order to provide information to be used subsequently to identify management strategies to reduce olfactory nuisances in the residential neighbourhoods. A weather-type classification is defined in order to identify meteorological conditions under which olfactory nuisances are to be expected. A non-steady state Gaussian model and a full-physics meteorological model are used to predict olfactory nuisances, for both the winter and summer scenarios that lead to the majority of complaints in neighbourhoods surrounding the landfill site. Simulating representative scenarios rather than full years make a high resolution simulation of local atmospheric dynamics in space and time possible. Results underline the key role of local atmospheric dynamics in driving the dispersion of odours. The odour concentration simulated by the full-physics meteorological model is combined with the density of the population in order to calculate an average population exposure for the two scenarios. Results of this study are expected to provide helpful information to develop technical solutions for an effective management of landfill operations, which would reduce odour impacts within the surrounding communities.

Online 24-h solar power forecasting based on weather type classification using artificial neural network

► The RBFN model can forecast PV power output accurately in sunny days and cloudy days. ► The RBFN model makes a direct forecast of the power output of the PV system . ► A self-organized map is applied to classify the local weather type. ► The main factors are identified to forecast the power output of the PV system. Power forecasting is an important factor for planning the operations of photovoltaic (PV) system. This paper presents an advanced statistical method for solar power forecasting based on artificial intelligence techniques. The method requires as input past power measurements and meteorological forecasts of solar irradiance, relative humidity and temperature at the site of the photovoltaic power system. A self-organized map (SOM) is trained to classify the local weather type of 24 h ahead provided by the online meteorological services. A unique feature of the method is that following a preliminary weather type classification, the neural networks can be well trained to improve the forecast accuracy. The proposed method is suitable for operational planning of transmission system operator, i.e. forecasting horizon of 24 h ahead and for PV power system operators trading in electricity markets. Application of the forecasting method on the power production of an actual PV power system shows the validity of the method.

Estimation of the dispersion of an accidental release of radionuclides and toxic materials based on weather type classification

We investigate the influence of the regional-scale weather types on the atmospheric dispersion processes of the air pollutants originated from point sources. Hypothetical accidents were simulated with two different dispersion models. During a year’s test period, the 6-h emission of a radionuclide from the Paks Nuclear Power Plant (Paks NPP, Hungary) was assumed every day and the transport and deposition of the radionuclide was simulated by the Eulerian TREX dispersion model over the Central European region. In addition, the ALOHA Gaussian air dispersion model was also used for the local environment of the Paks NPP to simulate hypothetical hourly releases of ammonia during a 10-year period. During both types of model simulations, the dispersion of the plume for each time was analysed and tested with consideration of 13 circulation types corresponding to daily weather patterns over the Carpathian Basin. There are significant correlations between circulation types and plume directions and structures both in local and regional scales. The daily circulation pattern can be easily obtained from weather analyses; the expected size and direction of polluted area after an accidental release can be quickly estimated even before an accident occurs. However, this fast method cannot replace or neglect dispersion model simulations. It gives a ‘first guess’ and a fast estimation on the direction of the plume and can provide sufficient information for decision-making strategies.

Weather types accompanying very high pressure in Krakow in the period 1901-2000

The paper presents a classification of weather types observed in Krakow during the 20th century on days with particularly strong highs. The classification was based on daily values of a number of weather elements recorded at Krakow's Historic Weather Station during the period 1901–2000. Days with very high pressure were defined as those with an air pressure at 12 UTC equal to or greater than the 99th percentile of all the cases analysed (≥1037.5 hPa). A slightly modified version of a classification developed by Woś (1999) was used to determine weather types on each of the days identified. Very high pressure was found to have occurred solely during the cold half of the year (October–March). It was mostly accompanied by fairly frosty (9---) or moderately frosty (8---) weather types; subtype: sunny or with little cloud amount and very sunny (-02-) and very cloudy, without sunshine or with little sunshine (-20-); and weather class: without fog (---0). No significant annual or seasonal trends were found in the occurrence of days with very high pressure or in the various weather types. Copyright © 2010 Royal Meteorological Society

Reduced space optimal interpolation of daily rain gauge precipitation in Switzerland

The coarse spacing of automatic rain gauges complicates near‐real‐time spatial analyses of precipitation. We test the possibility of improving such analyses by considering, in addition to the in situ measurements, the spatial covariance structure inferred from past observations with a denser network. To this end, a statistical reconstruction technique, reduced space optimal interpolation (RSOI), is applied over Switzerland, a region of complex topography. RSOI consists of two main parts. First, principal component analysis (PCA) is applied to obtain a reduced space representation of gridded high‐resolution precipitation fields available for a multiyear calibration period in the past. Second, sparse real‐time rain gauge observations are used to estimate the principal component scores and to reconstruct the precipitation field. In this way, climatological information at higher resolution than the near‐real‐time measurements is incorporated into the spatial analysis. PCA is found to efficiently reduce the dimensionality of the calibration fields, and RSOI is successful despite the difficulties associated with the statistical distribution of daily precipitation (skewness, dry days). Examples and a systematic evaluation show substantial added value over a simple interpolation technique that uses near‐real‐time observations only. The benefit is particularly strong for larger‐scale precipitation and prominent topographic effects. Small‐scale precipitation features are reconstructed at a skill comparable to that of the simple technique. Stratifying the reconstruction method by the types of weather type classifications yields little added skill. Apart from application in near real time, RSOI may also be valuable for enhancing instrumental precipitation analyses for the historic past when direct observations were sparse.

Analysis of long-range transport of particulate matters in connection with air circulation over Central and Eastern part of Europe

The aim of this paper is to establish a practical methodology for examining the long-range transport of particulate matters (PM), named TSP. The daily concentration values of TSP from years 2001 and 2002, for three sites, Baia Mare (RO), Vienna (AU), Aosta (IT), were analyzed. In order to connect the main air circulation types with the aerosol concentrations at the selected sites, the catalogues of Circulation and Weather type Classification (COST733) were used. Spectral analysis was made using spectrum software based on Lomb–Scargle periodograms, and multiresolution analysis (MRA) technique based on Maximal Overlap Discrete Wavelet Transform (MODWT) with Fejer-Korovkin in 22 points wavelet filter (waveslim package). Spectral analysis shows a dominant one-year periodicity for all the time series with a variance around 22% for each time series. In addition, several winters TSP pollution episodes from each city were analyzed using a back trajectory model (HYSPLIT4), in order to compare with the resulted air circulation types. Two important concluding remarks emerge: (i) the Eastern part of Europe shows a dominant easterly air circulation and central Europe is characterized by south-west air circulations, which drive the maxima of pollutant concentrations; (ii) the choice of the domain for analysis of the circulation types is very important.