Quaderno Tecnico ARPA-SMR

n° 02/2001

Characteristics of the climate variability of Summer and Winter

precipitation regimes inEmilia-Romagna

Carlo CacciamaniRodica Tomozeiu

Nota Interna ARPA-SMR -Gennaio 2001 - Autore: C. Cacciamani, R. Tomozeiu CHARACTERISTICS OF THE CLIMATE VARIABILITY OF SUMMER AND WINTER PRECIPITATION REGIMES IN EMILIA ROMAGNA. 1. INTRODUCTION Scientific studies show that human health, ecological systems and socio-economic sectors, all of which are vital to sustainable development, are sensitive to changes in climate (IPCC Special Report, 1997). In most area of the world temperature and precipitation are perceived as the key elements of climate. Precipitation is particularly important, because changes in rainfall patterns may lead to floods or droughts in different areas, these having an important influence especially in agriculture, affecting crop yields and productivity. Therefore, information about trends and spatial variability of precipitation time series has become indispensable for both the scientific and the practical point of view. Precipitation studies were performed for different periods of time and at different scales: global (Diaz et al.,1989), hemispheric (Bradley et al.,1987), regional (Schönwiese et al. 1994) or local (Baeriswyl et al.1997).

A general view of seasonal and annual precipitation trends using historical records from Italy was made by Buffoni et al. (1999), spatial analysis for different areas and time scale being performed by Galliani and Filippini (1985), Cacciamani et al. (1994), Quadrelli et al. (1999), Cacciamani et al. (1999), Brunetti et al.(2000).

This report presents an analysis for Summer and Winter precipitation over Emilia-

Romagna, a region situated in Northern Italy, in the valley of the river Po, bounded by Apennine mountains to the south and the Adriatic Sea to the east. The climatic conditions of the region are related to the climatic general conditions of the Po Valley (surrounded by the Alps and the Apennine) and are mostly influenced by the mountains and the sea this leading to a high spatial variability of the precipitation fields. The main objectives of this study are: 1) to study the temporal variability of precipitation for summer and winter season, this

including:

1.1) trend analysis of the precipitation time series and detection of the month which mostly influence the behaviour of the summer / winter precipitation; 1.2) detection of the changes in Summer/Winter precipitation

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In order to emphasise the dependence of the results on the length of the time series as well as the density of the stations, the analysis was repeated for summer precipitation using two periods of time: 1922-1995 (long period) and 1948-1995 (short period). For the long time period records from 17 stations were used, while for the short time period other 23 stations were added obtaining a total number of 40 stations (see Fig. 1). 2) to perform a spatial variability analysis of the summer precipitation, a similar

analysis will be made for winter quantity of precipitation. Various methods are known to analyse the precipitation variability. They range from the univariate methods such as trend and change point analysis (Sneyers, 1975; Pettitt, 1979; to multivariate ones such as cluster analysis (Galliani and Filippini, 1985; Cacciamani et al., 1994), empirical orthogonal function (EOF) analysis( Baeriswyl et al.1997) and canonical correlation analysis. The combination between these methods leads to an optimum information about the spatial and temporal variability of the analysed data set. The techniques used in this study in order to analyse the internal structure of the time series, which represent the first objective, are non-parametric tests: Mann-Kendall (Sneyers, 1975) for trend analysis and Pettitt (Pettitt, (1979) for detecting the changes in the precipitation. The Standard Normal Homogeneity Test (SNHT) developed by Alexandersson (Alexandersson, H. and Moberg, A., 1997) was used to detect the inhomogeneity in the summer data set.

The trend and change point analysis were made on monthly data for: June, July, August respectively December, January and February and for the total amount of precipitation during summer (JJA) respectively, winter (DJF) season.

The spatial variability of the precipitation field for both seasons, which represent the second point of the analysis, was performed in this study by means of the multivariate statistical analysis techniques of Empirical Orthogonal Functions –EOF- ( Wilks, S.D., 1995)

The data used are monthly records from 40 climatic stations, of the National Hydrographic Service , covering the years 1922-1995.

The report is organised as follows: • section 1 -introduction; • section 2 - presents the data set used in this study • the results of temporal and spatial variability of the summer precipitation are

presented in section 3; • section 4 – describes some characteristics of winter precipitation field; • the conclusions are presented in section 5.

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2. Data

The data used in this study are the monthly precipitation amount from 40 rainfall stations located in Emilia-Romagna (fig.1), covering a period from 1922 to 1995. The stations are approximately uniform distributed over the region and their time series could be considered long enough to identify the climate signal concerning the main features of temporal and spatial variability of precipitation.

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Fig. 1 Map of Emilia- Romagna

Figure 1 shows the orographic map of Emilia Romagna subdivided in provinces, and the analysed stations. The stations with long records (1922-1995) are marked by squares while the stars evidence the 40 analysed stations with short period (1948-1995). The total amount of summer/winter precipitation was computed using the monthly quantity of precipitation from June, July and August (JJA) and, respectively December, January and February (DJF). All the data belong to the same source, the Bologna and Parma offices of the “National Hydrographic Service of Italy”. The influence of the time series length and the station density on the trend was tested for summer precipitation by performing the analysis as follows: - 1922-1995 , using the records form 17 stations (Fig.1) - 1948-1995, using an increased number of stations (up to 40 stations see Fig.1). 3. Temporal variability of the summer precipitation filed 3.1 Trends in the summer precipitation field in Emilia-Romagna region A trend analysis for time series with different length was performed using the Mann-Kendall test, for the total amount of summer precipitation (JJA).

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The distribution of Mann-Kendall statistic, computed using summer data records from 17 stations (1922-1995) is presented in figure 2a.

Considering a confidence level of 95%, from figure 2a, it can be seen that there is a positive trend in the whole region, but this is significant especially in the NW, central and NE part of the region coinciding with the Po plain.

Fig 2a. The distribution of the Mann Kendall's statistics for summer precipitation at 17 stations as derived from 1922-1995. Area where the significance level is at least 5% is shaded. The influence of the time series length on the trend was tested by performing the trend analysis for the same stations (17 stations) but for another period 1948-1995. Fig.2b Same as in figure 2a but for 1948-1995 The results displayed in Figure 2b show that the area with significant positive trend has became smaller than in the first case when the interval 1922-1995 was analysed. For studying the influence of the density of stations over the trend, it was increased the number of stations up to 40 (Fig.3) and the analysis was repeated for 1948-1995 period. The results obtained in this case were compared with those obtained for 17 stations (1948-1995, Fig 2b). In both cases it can be observed a positive trend in whole the region but a high spatial density of stations is necessary in order to have information for small areas (see Fig. 2b and Fig.3)

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Fig.3 Same as Figure 2b but for 40 stations and period 1948-1995 The same conclusion, regarding the dependence of trend by the density of stations was obtained when the analysis was repeated for groups of stations and 1948-1995 period. The results are presented in table 1. The stations was selected such that to be representative for each type of relief. Three major types of relief exist in this region: plain, hill and mountains. Taking into account this criteria and the correlation coefficient between the stations it was set up 3 groups (Table 1).For each group and each year, it was computed the spatial mean of the summer precipitation, these new series being analysed with Mann-Kendall test. The results of trend analysis for these groups (Table 1) evidence again a positive trend for each type of relief (see the Mann-Kendall statistics column), more significant in the hill and mountains area. After this step it might be conclude that in mountains and hill areas there is a significant increasing trend. Comparing these results (Table 1) with those obtained for each station (Fig.3) can be observed that the trend from Fig.3 is significant only for a small part of mountains and hill area, and not for whole the area of mountains and hill. Table 1 Trend results for group of station ( 1948-1995)

M-K statistics

(summer season)

The results of Pettitt test

(summer season)

Group

(height)

Stations (code)

Period

Significance level (α)

Trend (mm/year)

Shift point α

Plain (3m-200m)

Alfonsine(2338) Forli(2358) Reggio-Emilia(1885) Pianoro(2301)

1948-1995 1.60 (α = 0.1)

1.09 1962 0.08

Hill (200-600m)

Bagno Di Romagna(2377) Vedriano(1856) Fontanelice(2325)

1948-1995 2.8 (α = 0.005)

2.00 1962 0.01

Mountains (600-1020m)

Ligonchio C-le(1921) Monteombraro(2276) Sestola(1973)

1948-1995 2.0 (α = 0.05)

1.6 1963 0.06

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- Therefore, it can be concluded that the trend analysis performed at station data provide more exactly information than the groups analysis.

- These results show also that the trend analysis (for precipitation) is very sensitive to

period, time series length and the station density.

For detecting the month influencing most the behaviour of the summer precipitation it was performed a trend analysis for each summer month: June, July August, at 17 stations , 1922-1995 interval. A positive trend was detected in August, more significant than in July whereas no significant trend was visible in June. The Mann-Kendall’s statistics for August is presented in figure 4. Comparing these results (figure4) with those obtained for summer season (figure 2a) for the same period a similar pattern, but more extended to south- east, can be observed. Therefore it can be concluded that the upward trend in the summer precipitation amount is due to an upward trend of the precipitation amount in August month.

Fig.4 The distribution of Mann-Kendall statistics for August month 1922-1995 (17 stations) The linear regression coefficient computed using the least squares method for August and Summer precipitation (for some stations) during 1922-1995 period, are displayed in table 2. Table 2 Results of the regression coefficient

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No. Station Trend–August (mm/year)

Trend–Summer (mm/year)

1 Vedriano 0.68 1.65 2 Reggio-Emilia 0.63 1.02 3 Sestola 0.66 1.0 4 Modena Burana 0.71 1.12 5 Codigoro 0.44 0.92 6 Monteombraro 0.33 0.93 7 Rocca S.Casciano 0.45 0.74 8 Alfonsine 0.40 1.01 9 Monzuno 0.35 0.64

3.2 Changes in the summer precipitation regime Change point represents an abrupt change in the mean or in the local trend of the time series. Pettitt’s test was used in order to detect the shift points in the time series. After the detection of one significant shift point (significance level ≤ 0.05) each time series was divided into two sub-series, each sub-series being again tested, in order to identify other changes in the evolution of the precipitation regime. Pettitt’s procedure was applied for the station data from June, July, August and for total amount of precipitation in summer. Both period of time was analysed: 1922-1995 (17 stations) respectively 1948-1995 (40 stations). The analysis performed for monthly precipitation at each station, for both periods of time, shows only in August, a significant “upward shift” in the mean of the precipitation around 1962 ± 2. The same change point was detected when summer quantity of precipitation for station data was analysed. Figure 5 presents one example of change point for both analysed periods (1922-1995, 1948-1995) at stations situated in the plain (Reggio Emilia, 51 m a.s.l.), in the hills (Fontanelice, 221 m) and in the mountains (S. Maria del Taro, 744 m) for August (a, c, e) and summer precipitation (b ,d, f) respectively. Fig.5

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The problem is to find out if the shift point detected around 1962 is due to an inhomogeneity in data or is a signal of change in the natural variability of the precipitation regime. The inhomogeneities in time series usually occur as a gradual trend, as in the case of urban warming, or as an abrupt discontinuity (jump) in the time series. Such kinds of discontinuities occur for a number of reasons: station moves, instrument changes, changes in methods for calculating time averaged values (Easterling and Peterson, 1992 and Alexandersson and Moberg,1997).

The information about the analysed stations does not reveal any instrumental or methodological changes around 1962 (Elenco delle Stazioni Termopluviometriche del Servizio Idrografico Italiano,1970). Also, a statistical analysis performed using the “Standard Normal Homogeneity Test “ at the stations with long records (17 stations ) confirm again that this year is not a inhomogeneity year, such that it could be conclude that the shift point which appear around 1962 in summer is a change in the natural variability of precipitation.

Using the results of Pettitt’s test as criteria for dividing the series, we analysed the behaviour of the precipitation during summer for 1963-1995 interval. Thus, the Mann-Kendall test applied for 1963-1995 period evidence a non-significant trend in the summer precipitation.

3.2 Spatial and temporal variability of the summer precipitation provided by the EOF analysis In order to obtain a general information about the space and temporal variability of the precipitation during summer season an Empirical Orthogonal Function (EOF) analysis was performed. The patterns provided by this methods show the main spatial features of the analysed variable and their coefficient time series describe the dominant variability in the data set. The analysis was made using the anomaly of precipitation during summer (JJA) season (1922-1995 ). The percentage of variance explained by the first five EOF are presented in table 3.

Table 3 Percentages of variance explained by the first five EOFs

EOF1 (%) EOF2 (%) EOF3 (%) EOF4 (%) EOF5 (%) 52.6 8.2 5.6 4.5 3.5

The first EOF pattern (figure 6a) which explains 52.6% of the total variance has the same sign over the entire region. This fact suggests that there is a common physical process dominating the summer precipitation variability and this could be

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the large-scale circulation. The highest variability is observed especially in the mountain area this underlying the influence of the topography over precipitation regime. The second pattern explains 8.2% (figure 6b) of the total variance and has a dipolar structure with negative anomalies in the south-eastern part of the Emilia - Romagna and positive anomalies in the north-western part of the region.

The time coefficients associated to the first EOF (fig. 7) shows a significant upward trend the significance level being α=0.005(trend= 0.01mm/year) The Pettitt test reveals the same shift around 1962 (α=0.009) as presented for the individual stations.

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This result concludes that the EOFsignal in the data set. Schönwiese (1990) analysing the presults for summer precipitation franalysis performed for 1951-1996 bthe summer precipitation from Italy.physical phenomenon responsible could be the large-scale atmospheric

Fig.6a The configuration of the first pattern (EOF 1)

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recipitationom north y Brunetti This fact for the su circulation

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Fig.6b The configuration of EOF2

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Fig.7 Coefficient time series of the first EOF (PC1) of the totalsummer precipitation in Emilia-Romagna The mean over thetwo sub-intervals determined by the shift point (1962) are

arkem d

is a powerful tool to detect the climate

trends in Europe, has revealed similar of Italy but for 1851-1980 period. An et al.(2000) evidence a positive trend in confirms again that there is a large-scale mmer precipitation variability and this .

4. Temporal evolution of the winter precipitation in Emilia Romagna

A trend analysis was performed for winter quantity of precipitation (December, January and February) using records from 40 stations, 1960-1995 period. The results of Mann-Kendall statistics are presented in figure 8. A significant negative trend could be observed in the whole region (fig.8), more pronounced in the hill and plain areas (the significance level >95 %). The result is in agreement with those obtained by Cacciamani et al.(1999) over the Alpine area for the winter precipitation during 1971-1992 interval. Fig.8 The distribution of Mann-Kendall statistics for winter precipitation (DJF), 1960-1995

The linear regression coefficient computed using the least squares method for Winter precipitation, (table 3) reveals a negative trend more pronounced during the period 1960-1995. Table 3 Results of the regression coefficient

Trend Winter (mm/year)

No. Station

1922-1995

1960-1995

1 Vedriano -0.13 -3.97 2 Reggio-Emilia -0.50 -3.40 3 Sestola -0.20 -2.72 4 Modena Burana -0.34 -4.25 5 Codigoro -0.22 -1.27 6 Monteombraro -1.20 -4.86 7 Rocca S.Casciano -1.70 -4.63 8 Alfonsine -0.92 -2.96 9 Monzuno -1.10 -4.95

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Trend analysis performed for each winter month (December, January and February) put in evidence a significant decreasing trend in the precipitation especially in January, more significant than in December and February. The change point analysis performed at some stations, for the winter time series (DJF) by applying the Pettitt test, evidence a significant “downward “shift in the mean of winter precipitation around 1980. One example of trend for January precipitation and change point detected in the winter precipitation at Reggio-Emilia station is presented in figure 9a/ 9b.

Time evolution of the winter precipitation Reggio Emilia station

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The results for shift point analysis at Reggio-Emilia station performed for 2 different periods of time (table 3) evidence also, a decreasing more significant in the mean winter precipitation (see the significance level of shift point) during 1960-1995 period. Table 3 Shift point and significance level in the winter precipitation

Station Period Shift year Significance level Reggio Emilia 1922-1994

1960-1994 1980 1980

0.1 0.009

The analysis will be extended for the other stations in order to obtain a complete conclusion concerning the variability of the winter precipitation field from Emilia-Romagna.

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5. Conclusions The main characteristics of the spatial and temporal variability of summer and winter precipitation in the Italian region of Emilia-Romagna are presented in this report. The sensitivity of these characteristics to the chosen time interval, density of stations and local topography is revealed. For this purpose it was considered the 1922-1995 time interval for 17 stations and the 1948-1995 interval for 40 stations. An increasing trend of the summer precipitation over the 1922-1995 interval (considering 17 stations) was found in the northern, central and eastern part of the region studied. This characteristic is influenced mostly by the August precipitation the climate signal was also present over a smaller area when the analysis was repeated for the 1948-1995 interval. Increasing the number of stations up to 40, a positive trend was detected in the whole region and new small areas with a significant upward trend appeared in the south-eastern area. This result shows that the climate signal related to the trend is strongly dependent on the time interval and the density of stations. A simultaneous upward shift in the summer precipitation (particularly in August) was detected around 1962. After 1980 a slow decrease in precipitation at some stations was noted.

The first EOF pattern showed the same sign of climate variability over the entire region with higher values in the mountains. The time series associated to this pattern reveals the same type characteristics of variability as presented above for the station analysis. The second EOF pattern shows an opposite sign of variability between the north-western and south-eastern parts of the region These results lead to the idea that a common large-scale physical mechanism could be responsible for the regional precipitation variability and this could be the large-scale atmospheric circulation, to be investigated in a forthcoming study. The influence of local factors such as topography were also revealed and the influence of the Adriatic Sea was noted in the eastern part of Emilia Romagna.

A similar analysis was performed for the winter precipitation. A significant decreasing trend was detected in the whole region, more significant in 1960-1995 interval, when data from each station was analysed. Trend analysis applied for each winter month evidence, that the decreasing is significant especially in January. Shift point analysis performed using data from some stations evidence a downward shift around 1980, the analysis will be extended for the rest of the stations. References .

Alexandersson, H., and Moberg, A.,1997: Homogenization of Swedish temperature data. Part I: a homogeneity test for linear trends. Int. J. Climatol., 17 , 25-34.

Baeriswyl , P. A., Rebetez, M., 1997: Regionalization of precipitation in Switzerland by means of Principal Component Analysis. Theor. Appl. Climatol. 58, 31-41.

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Bradley, R. S., Diaz, H. F., Eischeid, J. K., Jones, P. D., Kelly, P. M., Goodes, C. M., 1987: Precipitation fluctuations over Northern Hemisphere land areas since the Mid-19th

Century. Science, 237,171-175.

Buffoni, L., Maugeri, M., Nanni, T., 1999: Precipitation in Italy from 1833 to 1996. Theor. Appl. Climatol. 63, 33-40.

Brunetti, M.,Buffoni,L.,Maugeri, M.,Nanni,T.,2000: Precipitation intensity trends in northern Italy, Int. J. of Climatol., 20, 1017-1031

Cacciamani, C., Nanni, S., Tibaldi, S., 1994: Mesoclimatology of winter temperature and precipitation in the Po Valley of Northern Italy. Int. J. of Climatol., 14, 777-814.

Cacciamani,C., Lazzeri, M., Quadrelli, R., Tibaldi, S., 1999: Analisi climatologica della precipitazione nel bacino padano-adriatico e nella regione alpina. Atti del 3° Convegno nazionale sulla protezione e gestione delle acque sotterranee per il III millennio. Parma 13-15 Ottobre 1999, Quaderni di Geologia Applicata, Pitagora Editrice Bologna, 389-399.

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Diaz, H. F., Bradley, R. S., Eischeid, J. K., 1989: Precipitation fluctuation over global land areas since the late 1800s. J. Geophys. R es., 94, 1195-1240.

International Panel on Climate Change, 1997: The regional impacts of climate change: an assessment of vulnerability, IPCC Special Report

Pettitt, A. N., 1979: A non-parametric approach to the change-point problem. App. Statist.,126-135.

Quadrelli, R., Pavan, V., Molteni, F., 1999: Winter Mediterranean precipitation variability and its links with upper–air large scale circulation anomalies. Submitted to Climate Dynamics.

Schönwiese, C. D., Rapp, J., Fuchs, T., Denhard, M., 1994: Observed climate trends in Europe 1891-1990. Meteorol. Zeitschrift N. F., 3, 22-28.

Schönwiese, C. D., Stähler, U., Birrong, W., 1990: Temperature and precipitation trends in Europe and their possible link with greenhouse-induced climatic change. Theor. Appl. Climatol., 41, 173-175.

Sneyers, R., 1975: Sur l’analyse statistique des series d’observations. Note technique OMM, 143, 189 pp.

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