On the Relationships Between Circulation Types and Changes in Rainfall Variability in Greece

INTERNATIONAL JOURNAL OF CLIMATOLOGY Int. J. Climatol. 24: 1695–1712 (2004) Published online in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/joc.1088

ON THE RELATIONSHIPS BETWEEN CIRCULATION TYPES AND CHANGES IN RAINFALL VARIABILITY IN GREECE

PANAGIOTIS MAHERAS,a,* KONSTANTIA TOLIKA,a CHRISTINA ANAGNOSTOPOULOU,a MARGARITIS VAFIADISb IOANNIS PATRIKASc and HELENA FLOCASd a Department of Meteorology and Climatology, University of Thessaloniki, 54124 Thessaloniki, Greece b Division of Hydraulics, Faculty of Technology, University of Thessaloniki, Thessaloniki Greece c Division of Hydraulics, Faculty of Technology, University of Thessaloniki, Thessaloniki, Greece d Laboratory of Meteorology, Department of Applied Physics, University of Athens, Athens, Greece Received 17 December 2003 Revised 28 June 2004 Accepted 30 June 2004

ABSTRACT An attempt is made to examine rainfall variability over the Greek area in relation to 500 hPa atmospheric circulation. Daily precipitation series from 22 evenly distributed Greek stations have been used for the period 1958–2000, along with the classification scheme of daily circulation types at 500 hPa for the same period. The seasonal frequency and the trends of circulation types have been calculated. It was found that there is a general positive trend of anticyclonic circulation types and a negative one for cyclonic types. The seasonal trends of rainy days and the precipitation totals have also been calculated and analysed. A general decreasing tendency of winter rainfall is observed; the decreasing trend during autumn and spring is less significant. Concerning the frequency and intensity of rainfall per circulation type, a decreasing tendency becomes evident for the majority of the stations during winter, whereas there is an increasing tendency during autumn. A multiple regression–cross-validation model was developed using the seasonal frequency of circulation types as predictors and the seasonal rainfall totals as predictants. Only the winter modelled precipitation shows a good agreement with the observed precipitation, whereas for the other seasons the agreement is relatively poor. This could be caused by the influence of different factors that are not captured by the classification scheme used. The proposed model could serve as a circulation-based downscaling method that could be further applied to geopotential data available from general circulation models in order to study regional climatological consequences of future climate scenarios. Copyright  2004 Royal Meteorological Society.

KEY WORDS: Greece; circulation types; trend analysis; multiple regression–cross-validation analysis; daily rainfall; seasonal rainfall, downscaling method

1. INTRODUCTION

The precipitation regime in Greece presents highly irregular behaviour, both on spatial and temporal scales, namely in rainfall amount and rainfall distribution. In fact, the precipitation pattern over Greece shows a strong gradient between the western part (where precipitation is two or three times higher) and the other regions (Xoplaki et al., 2000; Maheras and Anagnostopoulou, 2003). Furthermore, the highest precipitation totals of western Greece were found to be related to the atmospheric circulation in association with Mediterranean sea- surface temperature distribution and the complex topography of the region, as imposed by the orography of the Pindus Mountains in northwestern and central Greece and the mountains of Olympus and Crete (Metaxas, 1978; Xoplaki et al., 2000; Maheras and Anagnostopoulou, 2003). It has been demonstrated that local or regional changes of meteorological parameters in mid-latitudes, including rainfall, are mainly controlled by the atmospheric circulation (Parker et al., 1994; Steinberger and

* Correspondence to: Panagiotis Maheras, Department of Meteorology and Climatology, School of Geology, Aristotle University of Thessaloniki, 54006 Greece; e-mail: [email protected]

Figure 1. Geographical distribution of the stations over the Greek area

Gazit-Yaari, 1996; Turke¸¨ s, 1998), although observed changes in rainfall cannot always be explained by changes in circulation (Frei et al., 1998; Goodess and Jones, 2002). Krichak et al. (2000) and Kutiel et al. (2001) studied synoptic patterns associated with dry and wet conditions in the eastern Mediterranean and Turkey respectively. They found that dry conditions in the eastern Mediterranean are associated with a large- scale positive 500 hPa anomaly over eastern Europe, whereas a negative anomaly normally prevails over southwestern and western Europe. Brunetti et al. (2002), who have investigated the atmospheric circulation and precipitation in Italy for the last 50 years, demonstrated that two indices (western European circulation index (WERCI) and Mediterranean circulation index (MCI)) are mainly correlated with precipitation totals. Furthermore, both indices show evidence of a signal connected to a strong increase in winter air pressure in the Mediterranean area starting around 1980 (Brunetti et al., 2002). Goodess and Jones (2002) found a general decreasing tendency of the mean seasonal rainfall over the Iberian Peninsula for the period 1958–97. Comparison of the trends in rainfall and circulation-type frequency suggests possible links. Turke¸¨ s et al. (2002) showed a statistically significant negative relationship between precipitation anomalies and 500 hPa geopotential height anomalies in winter and autumn for almost all of Turkey. These types of study are highly relevant to the construction of empirical downscaling procedures that permit large-scale information to be related to regional or local parameters. According to Goodess and Jones (2002), ‘inherent to all empirical downscaling approaches are the two assumptions that firstly, these relationships will be in time invariant (i.e. unchanged in a future warmer climate regime) and secondly, that rainfall changes are driven largely by changes in circulation’. Maheras et al. (1999), who investigated wet and dry monthly anomalies across the Mediterranean basin and their relationship with circulation over the last 130 years, found that the diminution of winter precipitation in Greece could be attributed to the increased frequency of northwesterly or northeasterly dry and cold continental airflows over Greece. Xoplaki et al. (2000) studied the connection between the large-scale 500 hPa geopotential height fields and precipitation over Greece during wintertime with the aid of a canonical correlation analysis. They found that there were more wintertime blocking situations over the last 30 years and, thus, a reduced frequency of depression activity over Mediterranean areas was the main reason for dry winters over Greece. Additionally, Maheras and co-workers (Maheras, 2002; Maheras et al., 2002a; Maheras and

Copyright  2004 Royal Meteorological Society Int. J. Climatol. 24: 1695–1712 (2004) CIRCULATION TYPES AND RAINFALL VARIABILITY CHANGE 1697

Figure 2. The location of the centre of (a) anticyclonic and (b) cyclonic types

Anagnostopoulou, 2003), following a circulation-type approach based on statistical downscaling, developed a multiple regression model in order to simulate the annual cycle of rainy days and the corresponding rainfall amount, as well as selected extreme precipitation events for Greek stations. However, the relationship between circulation types and rainfall, including rainfall patterns and trends, focusing not only on mean changes but on more detailed characteristics (such as wet-day probability and intensity) has not been extensively studied yet. Such a study would help greatly in constructing a robust downscaling procedure for the development of future precipitation scenarios in Greece. Therefore, the objectives of this study are:

• To explore the spatial and temporal variations in the circulation–rainfall relationship over Greece, in order to consider whether the trend of rainfall in the Greek area that has been identiﬁed in previous studies (Anagnostopoulou, 2003; Maheras and Anagnostopoulou, 2003) can be explained, in whole or in part, by circulation changes. • To identify the best potential circulation based on predictor variables for Greek rainfall.

Table I. Description of the 14 circulation types, six anticyclonic and eight cyclonic circulation types

Anw The anticyclonic centre is located in the west or northwest of the Greek area, over central, western or northern Europe. The wind over Greece prevails from the northerly sector, with higher intensity in the cold period Ane The anticyclonic centre is located in the northeast of the Greek area, over eastern Europe. The winds are principally from the northerly sector, similar to Anw, but with lower speed A The anticyclonic centre is located over the Greek area, producing weak variable winds or calms in the warm period and relatively strong winds or calms in the cold period Asw The anticyclonic centre is located in the west or southwest of the Greek area, usually over the central or southwestern Mediterranean basin or northern African coast. This type is characterized mainly by westerly or northwesterly flow Ase The anticyclonic centre is located in the southeast of Greece, in the area of Cyprus or the Middle East. The wind prevails from the southerly sector Ae The anticyclonic centre is located in the east of Greece, over Turkey, resulting mainly in easterly flow at the surface but giving westerly flow at the 500 hPa level. C The cyclonic centre is located over the Greek area. The wind over Greece prevails mainly from the northerly sector Cs The cyclonic centre is found in the south or southeast of Greece, over the eastern Mediterranean basin. The wind blows from the northerly sector Csw The cyclonic centre is located in the southwest of the Greek area, over the central Mediterranean or northern Africa, producing intense westerly/southwesterly flow over Greece Cnw The cyclonic centre is located in the northwest of Greece, usually over the Adriatic Sea, Italy and central Europe. The prevailing wind has a westerly/southwesterly component Cne The cyclonic centre is located in the northeast of Greece, more preferably over the northern part of Turkey and the Black Sea. The wind blows mainly from the northerly or northwesterly sector Cse The cyclonic centre is located in the southeast of the Greek area, in the east of Cyprus. The wind has a pronounced northwesterly component Cn The cyclonic centre is located far north from Greece, at latitudes greater than 50 °N, usually over the Baltic Sea or Russia. The prevailing wind over Greece is westerly Cw The cyclonic centre is located far west of Greece, west of longitude 10 °E, over the western Mediterranean or west Europe, generally resulting in southwesterly winds over Greece

• To construct a downscaling procedure based on the circulation-type approach with a multiple regression and cross-validation analysis in order to develop further a plausible daily and seasonal rainfall scenario for Greece.

The data sets used and methodology are described in Section 2. In section 3, the relationships between Greek daily rainfall and regional circulation classiﬁcation types, as derived from an automated scheme, are analysed. Trends of rainfall in the interior of each circulation type and possible links between these trends are discussed in Section 4. The development of a method of downscaling rainfall is analysed in Section 5. Finally, the conclusions are presented in Section 6.

2. DATA AND METHODOLOGY

2.1. Rainfall data Observations of daily rainfall totals for 22 stations evenly distributed throughout Greece for the period 1958–2000 were used (Figure 1). These data series are complete, i.e. have no missing values. The homogeneity of the data was tested using the Alexandersson (1986) test. More speciﬁcally, the test was applied for each month and each station with reference time series, which have been selected because they accomplish all necessarily criteria (i.e. no changes of instruments and observing practices) (Peterson et al.,

Copyright  2004 Royal Meteorological Society Int. J. Climatol. 24: 1695–1712 (2004) CIRCULATION TYPES AND RAINFALL VARIABILITY CHANGE 1699

1998). According to the results of the Alexandersson test, the null hypothesis, demanding inhomogeneity of the series, has been rejected for all stations; thus, all data series can be considered as homogeneous. Since summer rainfall is insigniﬁcant or zero, seasonal analyses are presented only for winter (December–February), spring (March–May) and autumn (September–November).

2.2. Circulation-type catalogue A daily catalogue of 14 circulation types was constructed for the period 1958–2000. The automated classiﬁcation scheme is based on standardized 500 hPa daily geopotential height data from the National Centers for Environmental Prediction–National Center for Atmosphere Research reanalysis data archive (Kalnay et al., 1996) with a spatial resolution of 2.5° × 2.5° within the European region of 20–65 °N and 20 °W–50°E. According to this grid-point scheme, eight grid points represent the Greek area. Six anticyclonic types (Anw (A1), Ane (A2), A (A3), Asw (A4), Ase (A5) and Ae (A6)) and eight cyclonic types (C, Cs, Csw, Cnw, Cne, Cse, Cn and Cw) are deﬁned (Figure 2). The characterization of anticyclonic or cyclonic

(a)

Figure 3. Winter mean 500 hPa anomalies (hPa × 100) (1) and the corresponding geopotential height (2) for (a) the anticyclonic types and (b) the cyclonic types

(b)

Figure 3. (Continued)

Table II. Seasonal frequencies and trends of the circulation types at 500 hPa (1958–2000). The trends in bold are statistically signiﬁcant at the 0.05 level

Type Winter Spring Autumn Year Mean Trend Mean Trend Mean Trend Mean Trend

Anw 3.9 + 7.3 + 8.9 − 8.5 + Ane 5.1 + 4.8 + 7.3 + 6.7 + A 4.5 + 6.3 + 10.9 + 8.2 + Asw 11.7 + 8.8 + 14.7 + 12.0 + Ase 6.2 + 8.1 + 8.2 + 8.7 + Ae 2.9 + 3.8 + 3.5 + 3.8 + C 9.9 − 11.7 + 13.2 − 11.8 − Cs 8.9 − 9.4 + 4.7 − 6.7 − Csw 19.2 − 14.2 − 11.3 − 12.8 − Cnw 4.0 − 6.0 − 4.1 − 4.4 − Cne 13.9 − 11.1 − 8.9 + 10.3 − Cse 2.2 − 2.8 − 0.8 − 1.6 − Cn 0.7 − 1.2 − 0.3 + 0.6 − Cw 7.0 − 4.4 − 3.2 − 3.9 −

Copyright  2004 Royal Meteorological Society Int. J. Climatol. 24: 1695–1712 (2004) CIRCULATION TYPES AND RAINFALL VARIABILITY CHANGE 1701 circulation types refers to the locations of the positive or negative anomaly centre (zi = (xi − x)/σ, where zi is the standardized daily value for each grid, xi is the daily value of geopotential height for each grid i, x is the mean monthly value for each grid for the period 1958–2000, and σ is the corresponding standard deviation (SD)) in relation to the Greek area (Table I, Figure 3(a) and (b)). For example, the positive anomaly centre of the anticyclonic type A locates over Greece, whereas the location of the negative anomaly centre of Csw (cyclonic type) is in the southwest of the Greek area. More details on the classiﬁcation method are provided by Maheras and co-workers (Maheras et al., 2000; Maheras and Anagnostopoulou, 2003; Helmis et al., 2003).

2.3. Methodology In order to examine the relationship between rainfall and circulation type, three parameters have been calculated. The first parameter is the ratio Propct/Proptot (Goodess and Palutikof, 1998; Goodess and Jones, 2002), where Propct is the proportion of days of a specific circulation type that are wet and Proptot is the proportion of all days that are wet. The second is the ratio Precct/Prectot, where Precct is the mean daily amount of rainfall of the wet days of the circulation type and Prectot is mean daily amount of rainfall for the total of wet days. The third parameter indicates the seasonal contribution of each circulation type to the seasonal rainfall total for each station and is expressed as a percentage. For the first two parameters, if the ratio is greater (less) than 1.0 then the probability of rain or amount of rainfall per rain day is greater (less) than the corresponding seasonal mean of the station (Goodess and Palutikof, 1998; Goodess and Jones, 2002).

Figure 4. Winter standardized ratios Propct/Proptot for the 14 circulation types and the 22 rainfall stations for the period 1958–2000

Figure 4. (Continued)

Linear regression was chosen to study the trends of rainy days and seasonal precipitation totals, as well as the rainfall probability and wet-day amount by circulation type for each station and each season. In addition, the Spearman’s rank correlation test (Sneyers, 1990) was chosen to detect significant trends at the 95% confidence level. The method of kriging (Delfiner and Delhomme, 1975) was used in order to produce contours of the spatial distribution maps. As a next step, multiple linear regression models were constructed for each station using a number of selected predictor variables. Assuming that the probability of rainfall and mean daily amounts of rainfall per predictor variable (the circulation types) must be the same both for the calibration and the validation periods, a cross-validation approach was used in order to calculate the seasonal predicted values of rainfall. According to Wilks (1995), in the cross-validation the available data are repeated, and divided into developmental and verification data subsets. Cross-validation is very often carried out using developmental data sets of size n − 1 and verification data sets containing the remaining single observation of the predictant. In this case, the regression model is recalculated for each group of years. In this study, one year was removed sequentially for the period 1958–2000 and the remaining values used to calibrate the regression model for the rainfall for the omitted year. Two measures are calculated in order to quantify and describe the skill of the multiple regression–cross- validation model. These are the root-mean-square error (RMSE) and the coefficient of determination R2. The differences between the observed and simulated values were also calculated, as well as the corresponding SD

Copyright  2004 Royal Meteorological Society Int. J. Climatol. 24: 1695–1712 (2004) CIRCULATION TYPES AND RAINFALL VARIABILITY CHANGE 1703 of the two data sets. The student’s t test was chosen to detect the signiﬁcant differences between observed and simulated values. The mean seasonal frequencies of the circulation types and the direction of their trend over the period 1958–2000 are shown in Table II.

3. RELATIONSHIP BETWEEN RAINFALL AND CIRCULATION TYPE

Winter values of the three above-mentioned parameters for the 22 Greek stations are shown in Figures 4–6 for the period 1958–2000. Spring, autumn and annual values have similar relationships to the winter ones (not shown). The anticyclonic types are associated with lower than average probability of rain at all stations. The exception is type Ase, which has a high probability of rain at the stations of Ioannina and Kerkyra (Figure 4). The prevalence of Ase over Greece is accompanied by strong southwesterly cyclonic conditions in the western and central Mediterranean (Figure 3(a–e1)). These cyclonic conditions have a greater inﬂuence on the stations of Kerkyra and Ioannina, located in northwestern Greece (Fig. 3(a–e1)). However, the relationships of the anticyclonic types show regional variations, as might be expected. Thus, the ratios of stations in Crete and the Ionian Sea are higher than those at other stations. In contrast, the probability for most of the cyclonic types is higher than the average probability of rainfall, with strong regional variations, however, for all types, except for C and Cse types. More speciﬁcally, the C type shows very high values of probability, whereas the Cse has low values. Types Csw and Cnw have high values of probability, except for Crete for the latter type. On the contrary, the Cs type shows a high value of intensity only for the stations of Crete. Finally, types Cne, Cn and Cw are characterized by higher than average probability in the Ionian and northern and eastern Aegean stations.

Figure 5. Winter standardized ratios Precct/Prectot for the 14 circulation types and the 22 rainfall stations for the period 1958–2000

Figure 5. (Continued)

According to Figure 5, the intensity of rainfall presents similar behaviour to probability. Thus, all anticyclonic types are of below-average intensity (with the exception of stations Argostoli, Kerkyra, Alexandroupoli, Ierapetra, Kythira and Samos). On the contrary, cyclonic types are associated with a higher than average intensity of rainfall at several stations (with the exception of Cne and Cse types). The probability of C and Csw types has the highest values of ratios for all stations, whereas Cs and Cnw types show high intensity for stations on Crete (Chania, Heraklio and Ierapetra) and the Ionian stations respectively. The percentage contribution of each circulation type to mean winter precipitation amount for all stations is shown in Figure 6. For all stations, two cyclonic types (C and Csw) are associated with a very high percentage rainfall, more than 60% of the total winter precipitation amount. In contrast, all anticyclonic types, as well as Cse and Cn types, are characterized by a very low percentage of rainfall. Finally, types Cs, Cnw, Cne and Cw show similar regional variability of the percentage contribution with the probability/intensity rainfall. Similar results are obtained for spring, autumn and the whole year (not shown). In summary, two circulation types, C and Csw, can be considered as high probability/high intensity/high percentage contribution rainfall types in winter for all stations, whereas types Cs, Cnw, Cne and Cw are characterized by strong regional variations of the above characteristics of rainfall.

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4. TREND ANALYSES

4.1. Rainfall trends The spatial distribution of trends for seasonal number of rainy days is summarized in Figure 7. It can be seen that significant negative trends are clearly depicted in winter, especially in the Ionian Islands, the western mountainous regions, and the northeastern part of the Aegean Sea. Insignificant negative trends are indicated in the Aegean Sea, whereas insignificant positive trends are observed in central continental Greece. For spring, negative and positive trends are not significant, while for autumn there are only insignificant negative trends in the major part of Greece. The spatial distribution of seasonal trends of precipitation totals can be found in Figure 8. The Ionian Islands, the mountainous regions in west, and the north, eastern and southeastern Aegean Sea are characterized by a significant decrease of winter precipitation. Spring reveals decreasing trends in most of the country, and autumn presents remarkable decreasing trends in the Ionian Islands and the mountainous regions in west. It is evident that the general decreasing tendency of rainfall for almost the whole Greek region is due to the decrease in the number of rainy days, especially in winter. However, this relation varies from station to station and from season to season.

4.2. Trend in the probability of rainfall and in the wet-day amount by circulation type As can be seen in Table II, the seasonal frequency of the anticyclonic types shows mostly positive trends. On the contrary, the frequency of the cyclonic types presents negative trends. The trends of the cyclonic types are consistent with the general decrease of rainy days and the negative trends of rainfall during the period 1958–2000. Some serious questions about the relationship between circulation types and rainfall totals arise. First, is this relationship stable or does it change with time? Second, is there any other mechanism that could result in this relationship? To answer these questions, the trends of wet-day amount and rainfall probability

Figure 6. Winter proportion of precipitation total for the 14 circulation types and the 22 rainfall stations for the period 1958–2000

Figure 6. (Continued) were calculated separately for each cyclonic circulation type, each station and each season. From Table III, where the results of these calculations are summarized, it can be seen that the frequency of rainfall has decreased for most of the cyclonic circulation types for all stations, with the exception of Agrinio, Ierapetra, Larissa, and Thessaloniki. Some stations present significant negative trends for a circulation type that is related to the highest probability of rainfall, e.g. Csw (Alexandroupoli Argostoli, Athens, Chania, and Rodos) and Cw (Argostoli, Rodos, Samos, Tripoli and Thessaloniki). This means that there has been a general decrease in the probability of rainfall, this being correlated to the observed changes in cyclonic circulation types frequency. For winter, most of the cyclonic types present significant negative trends for the rainfall totals (Table III), such as Csw and Cw, which are related to a high probability of rainfall. On the contrary, a few stations (Thessaloniki and Milos) present positive trends for cyclonic types C and Cs. It is noticeable that some stations present a significant negative trend both for frequency and rainfall totals. In spring, the results (not shown) resemble those deduced for the trends of frequencies. In autumn, positive trends were found for all stations and circulation types, except for Alexandroupoli, which is characterized by negative trends (not shown). The differences in the behaviour of autumn (both frequency and rainfall amounts per circulation type), compared with the other seasons, could be attributed to the much higher variability of the geopotential heights and relative vorticity for the 500 hPa level (Flocas et al., 2001; Maheras et al., 2002b). In addition, this could also be interpreted as a lower correlation between frequencies of the cyclonic circulation types and frequencies and amounts of rainfall in Greece, in autumn, compared with the other seasons (Maheras and Anagnostopoulou, 2003). The smaller decrease of precipitation in autumn compared with in winter is more likely due to the inconsistent tendencies between frequencies of types of circulation and frequencies–quantities

Copyright  2004 Royal Meteorological Society Int. J. Climatol. 24: 1695–1712 (2004) CIRCULATION TYPES AND RAINFALL VARIABILITY CHANGE 1707

Figure 7. Geographical distribution of linear trends (raindays per year) of seasonal rain days of rainfall. If the number of rain days increases, then the rainfall amount of a particular type also increases. It follows that the observed mean amount of rainfall in the autumn is the greatest.

5. REGRESSION ANALYSIS

According to Goodess and Jones (2002), the main purposes of the regression analysis ‘are to identify the best circulation based predictor variables ... to determine whether and, if so, how they vary over space and/or time, and whether or not the resulting models can explain the observed rainfall trends and/or have sufﬁcient skill for downscaling’. Previous work (Maheras and Anagnostopoulou, 2003) shows that there is a high degree of correlation between seasonal precipitation amounts and seasonal rainy days and the corresponding frequency of cyclonic circulation types at 500 hPa (period 1958–97) for Greece: 0.84 and 0.87 for winter; 0.7 and 0.74 for spring;

Figure 8. Geographical distribution of linear trends (mm/year) of seasonal precipitation totals

0.51 and 0.56 for autumn. Since the correlation between the rainfall/circulation-type frequency is stronger in winter than in other seasons, the results of the regression analysis will now be presented in detail for winter and briefly for the other seasons. In this study, the analysis was performed in two stages. In the first stage, a multiple regression method was used in order to identify the best predictor variables and to eliminate variables that are not significantly correlated with the seasonal amounts of rainfall, using a significance level of 0.05 for the correlation coefficient as a criterion to select a variable. As shown in Table IV, up to six cyclonic circulation types were selected for winter at individual stations (C, Csw, Cs, Cnw, Cne, Cw), whereas all the anticyclonic types, as well as the cyclonic types Cse and Cn, were eliminated. The predictor variables selected vary from station to station, although the types C and Csw are the most important for all stations. The types Cnw, Cne and Cw were also selected as predictors for several stations, whereas the type Cs is selected only for the southern stations, especially in Crete. The adjusted R2 values for the 22 stations vary from 0.20 to 0.80 for the period 1958–2000. The lowest value appears in Kozani (0.20) and the highest value in Kerkyra (0.80).

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Table III. Winter trends in number of rain days (Freq. = days/year) and wet-day amount (Am. = mm/year) for 22 Greek stations. The trends in bold are statistically signiﬁcant at a signiﬁcance level of 0.05

C Cs Csw Cnw Cne Cse Cn Cw Freq. Am. Freq. Am. Freq. Am. Freq. Am. Freq. Am. Freq. Am. Freq. Am. Freq. Am.

Agrinio +−+++−+−−−+−−− −+ Alexandroupoli −+−−−−+−−−++−−−+ Argostoli −−−−−−−−−−−−−−−− Athens ++−−− −−−++−−−−−− Chania − − −+− −−−−− − +−−−− Elliniko +++−−− −+−+−−−−−− Heraklio −+−−−−+−−−−+ + −−− Ierapetra +−+− + − +−−− +−−+−− Ioannina +−+−−−+−− −−+ −−−− Kalamata −+++−−−+−++− −−−+ Kerkyra −−+−−−+− + − −+−− − − Kozani ++−−++−−−−−− −−−− Kythira −−++−−−−−−−−++−− Larissa + ++−+−−+−+−−+++− Milos + + +−−−−− +−−−−−−− Mytilini +++−−− −−−− ++−−−− Naxos ++−−−+−− ++−−+ +−− Rodos −+− − −−−+−−++−−−+ Samos ++++−− − − − − ++−+−− Skyros −−−−−− −−− −−−−−−− Tripoli +−+−−−−−−−−−−−− − Thessaloniki + + +++−++−−−−−−−−

Table V summarizes the results of the cross-validation regression analyses. According to the Student’s t test there are no significant differences between observed and simulated mean winter rainfall totals (most of the stations present low values of negative differences). On the contrary, the simulated SD show significantly lower values than the observed SD at six stations, suggesting that the simulated series presents lower year- to-year variability than the observed series. The RMSE values show considerable regional variation, being lowest for the continental stations (Larissa 40.8) and the stations located along the Aegean Sea (Milos: 46.1; Naxos: 54.6) and highest in the two extreme Greek regions, in the Ionian Sea (Argostoli: 121.6) and in the eastern Aegean Sea (Samos: 142.5; Rodos: 126.8). Finally, the adjusted R2 values are also characterized by considerable regional variations. According to Table V, the highest values of R2 are observed at the stations in the western part of Greece, and the stations of Cyclades (Naxos: 0.74; Milos: 0.76). The lowest values of R2 are observed both in continental stations (Kozani: 0.41) and coastal stations of the Aegean Sea (Alexandroupoli: 0.38; Elliniko: 0.41; Chania: 0.34). According to the above analysis, it can be supported that the RMSE values are almost proportional to the winter rainfall totals per station, further supporting that this parameter cannot be used alone for an objective evaluation of the performance of the method employed. On the contrary, the R2 values seem to be more objective, because this parameter is the amount of variance explained by the model. For the other seasons, the explained variance is quite low for all stations, especially in autumn, which could be attributed to the higher variability of the geopotential height during autumn compared with winter (Maheras et al., 2002b). This further suggests that the automated circulation classification scheme used here is relatively unable to capture some important mesoscale or convective processes related to cyclonic types during autumn.

Table IV. Winter predictor variables for precipitation totals

Station TCHCPredictors: circulation types

Agrinio C, Csw, Cnw, Cne, Cw Alexandroupoli C, Csw, Cnw, Cne, Cw Argostoli C, Csw, Cnw, Cne, Cw Athens C, Cs, Csw Chania C, Cs, Csw, Cne Elliniko C, Cs, Csw Heraklio C, Cs, Csw, Cne Ierapetra C, Cs, Csw, Cne Ioannina C, Csw, Cnw, Cne, Cw Kalamata C, Csw, Cnw, Cme, Cw Kerkyra C, Csw, Cnw, Cne, Cw Kozani C, Csw, Cnw, Cw Kythira C, Cs, Cw Larissa C, Csw, Cw Milos C, Cs, Csw, Cnw Mytilini C, Csw, Cw Naxos C, Cs, Csw Rodos C, Cs, Csw, Cnw, Cne Samos C, Cs, Csw, Cne Skyros C, Cs, Csw, Cne Thessaloniki C, Csw, Cne, Cw Tripoli C, Csw, Cnw, Cne, Cw

6. CONCLUSIONS

Linear regression and Spearman’s correlation test reveal significant negative trends in winter and autumn precipitation amounts over Greece and support the findings of Xoplaki et al. (2000) and Maheras and Anagnostopoulou (2003). However, western, northern and eastern parts of Greece reveal significant trends. For wintertime and for the majority of the stations, the decreasing trends of wet-day amount and the probability of rainfall are consistent with the observed changes in cyclonic circulation-type frequency regardless of circulation type. However, during the same season for a number of stations the wet-day amount as well as the probability of rainfall for some cyclonic circulation types is uncorrelated with the observed decrease of the same circulation-type frequency. In addition, during autumn the majority of stations present a general increase in wet-day amount as well as the probability of rainfall for a large number of the cyclonic circulation types that are characterized by a decrease in frequency. This may partially compensate the general decrease in the seasonal amount of rainfall. As the number of rainy days increases along with the mean wet-day amount of a particular cyclonic type, a greater seasonal total of precipitation is observed. It seems that these characteristics may be related to changes in the temperature and humidity of the atmosphere restricted to a particular circulation type and station for winter or regardless of circulation type and station for autumn. Thus, the observed rainfall changes cannot be explained only by changes in circulation-type frequency. The winter multiple regression models of precipitation show a high and robust correspondence with the observed precipitation. For the other seasons, the simulated amounts of rainfall are less consistent with the observed values. This behaviour could mainly be caused by the influence of different air masses on the precipitation during the transition seasons, which are not captured by the classification scheme. In addition, during autumn the cyclones passing through the area, due to the high variability of the geopotential at 500 hPa (Maheras et al., 2002b), are not as closely associated with precipitation amount as in winter. The fact that

Copyright  2004 Royal Meteorological Society Int. J. Climatol. 24: 1695–1712 (2004) CIRCULATION TYPES AND RAINFALL VARIABILITY CHANGE 1711

Table V. Results of the cross-validation regression analysis models for winter rainfall, 1958–2000

Adjusted R2 Station rainfall total (mm) Station rainfall total (mm) Observed Simulated Difference Observed Simulated Difference RMSE

Agrinio 0.73 377.6 378.0 0.4 130.4 110.8 −19.6 89.4 Alexandroupoli 0.35 198.5 189.0 −9.5 89.8 77.8 −12.0 112.5 Argostoli 0.69 409.8 405.5 −4.3 166.0 140.7 −25.3 121.6 Athens 0.47 154.3 152.7 −1.6 60.6 44.4 −16.2∗ 55.2 Chania 0.34 320.0 316.9 −3.1 128.5 105.3 −23.2 134.5 Elliniko 0.41 154.4 148.0 −6.4 62.4 46.8 −15.6∗ 60.2 Heraklio 0.56 238.4 238.1 −0.3 83.1 72.2 −10.9 72.2 Ierapetra 0.64 275.4 274.2 −1.2 116.3 100.6 −15.7 91.6 Ioannina 0.81 406.9 401.1 −5.8 155.3 140.4 −14.9 91.2 Kalamata 0.54 356.6 356.0 −0.6 114.3 84.9 −29.4∗ 97.4 Kerkyra 0.81 438.2 434.7 −3.5 163.1 148.1 −15.0 95.0 Kozani 0.41 117.1 113.5 −3.6 56.7 50.6 −6.1 58.0 Kythira 0.56 275.0 272.4 −2.6 87.0 70.1 −16.9 74.2 Larissa 0.48 121.3 120.5 −0.8 44.9 33.5 −11.4∗ 40.8 Milos 0.76 216.6 215.4 −1.2 69.9 63.4 −6.5 46.1 Mytilini 0.66 353.2 349.2 −4.0 132.1 109.3 −22.8 100.8 Naxos 0.74 192.0 192.7 0.7 81.2 69.8 −11.4 54.6 Rodos 0.53 412.0 410.4 −1.6 147.3 109.7 −37.6∗ 126.8 Samos 0.60 443.7 437.7 −6.0 170.0 151.0 −19.0 142.5 Skyros 0.55 197.7 195.0 −2.7 95.5 86.2 −9.3 85.6 Thessaloniki 0.47 122.3 120.2 −2.1 58.6 82.2 23.6∗ 56.2 Tripoli 0.63 341.7 338.8 −2.9 123.1 102.0 −21.1 97.6

∗ Statistically significant at the 0.05 level of significance based on an F-test. the models underestimate the standard deviation of the simulated amounts of rainfall suggests that the model is unable to capture extreme values, resulting in low interannual variability of seasonal rainfall (Wilby et al., 1998; Goodess and Jones, 2002). It seems that other meteorological parameters may need to be taken into account. According to Goodess and Jones (2002), the two most important variables that should be incorporated in a circulation-type approach to downscaling of rainfall are temperature and atmospheric humidity. Thus, further work is required to investigate whether these additional variables would increase the performance of the models and, if so, how they can be used. A first approach is to incorporate them in the regression models or an alternative one is to use them as variables in a new classification scheme of circulation types. Despite the fact that the performance of the linear regression models is high and robust only during winter with either relatively medium or unable performance during the other seasons, it is considered that the circulation type approach offers great potential. It provides information about rainfall regime changes, and in several cases in extreme-event rainfall regime changes (Maheras and Anagnostopoulou, 2003), in a way that their interpretation is possible in terms of physical mechanisms. The method could also be applied to geopotential data available from a general circulation model in order to study regional climatological consequences of future climate scenarios. We are working in this direction and hoping to report our results at a later date.

ACKNOWLEDGEMENTS

We are grateful for the funding of this work by the European Commission under the Fifth Framework Program. The work was part of the EU research project STARDEX (under contract EVK2-CT-2001-00115). We would like to express our gratitude to the referees for their constructive comments and suggestions. Also, we would

Copyright  2004 Royal Meteorological Society Int. J. Climatol. 24: 1695–1712 (2004) 1712 P. MAHERAS ET AL. like to express our gratitude to Mr Michael O’Connor for his valuable help in improving the language of the manuscript.

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