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SEVEN YEARS (2004-2010) PRECIPITATION DISTRIBUTION IN TRANSYLVANIA (ROMANIA) FROM DAILY DATA

OTTILIA RUSZ1

Abstract:- Seven years (2004-2010) precipitation distribution in Transylvania (Romania) from daily data. Daily precipitation amount data from 21 meteorological stations were studied. These stations are located in the following counties: Alba, Brasov, Cluj, Covasna, Harghita, Mures and Sibiu. Factor analysis was applied in order to delimit areas with same precipitation distribution patterns in Transylvania in the period 2004-2010. It was found 3 dominant factors which can explain 67.19 % of variance. All factors are related to local conditions, namely to geographic position, but they are independent from topography. Using factor loadings, 3 maps are presented, which reveals the spatial influence of these 3 factors. For each meteorological station was made a precipitation distribution figure. These figures and the 3 maps were made with Arcmap software using spline with barriers interpolation method. Distribution figures of stations defined by the same factor pattern are similar. The first factor, responsible for less precipitation affects especially the south eastern part of area. The third factor provides the highest amount of rainfall and influence mainly the northern part of region. The south western part of Transylvania is dominated by the second factor which insures the most balanced precipitation pattern. Key-words: precipitation, factor analysis, spline with barriers interpolation, Transylvania

1 Introduction In Romania, variability and discontinuity is

the main characteristic of rainfall patterns and precipitation spatial-temporal distribution. The most important precipitation amounts are registered in periods with persistent cyclonic activity. A major factor in rainfall diversification is the Carpathian Mountains, which force the change in air masses directions. Monthly precipitation amounts variability were detected using Angot pluviometric index, which reveals 5 types of zonal distribution of atmospheric precipitation over Romania. Type II is characteristic also for Transylvania, and it consist of greater amplitude of precipitation amount variation (Sandu et al, 2008). Rainfall is the main source of water for growth and development of plants, there absence or deficiency leads appearance, intensify and extend of drought. Frequency of deficient years (rainfall in may-august) for agricultural crops is 45,8% in Transylvania-Maramures (Sandu et al, 2010).

2 Study area

Daily precipitation amount data were studied from the followed Transylvanian weather stations (altitudes are shown in parentheses): Alba Iulia (246 m), Bâlea Lake (2055 m), Baraolt (508 m), Boiţa (518 m), Braşov (534 m), Bucin (1282 m), Dumbrăveni (318 m), Făgăraş(428 m), Cluj-Napoca (413 m), Joseni (750 m), Lăcăuţi (1776 m), Miercurea Ciuc (661), Roşia Montană (1196 m), Sărmaşu (399 m), Sebeş(254 m), Sfântu Gheorghe (523 m), Sibiu (443), Târgu-Mureş(308 m), Târgu Secuiesc (568 m), Târnăveni (523 m), Topliţa (687 m). 3 Data and methods

Daily precipitation data were collected from meteorological tables (TM1) of these weather stations (National Meteorological Administration), except Cluj station which data were obtained from site: http://eca.knmi.nl.

1 Târgu Mureş Weather Station, National Meteorological Administration, Libertăţii street, no. 111, Târgu Mureş, ruszotti@freemail.hu

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Factor analysis has become an important statistical method of investigation in environmental studies. Factor analysis is a data reduction method, with which can reveal the common essence of linearly related variables (Kaplunovsky, 2005). These analyses were made using PSPP software (http://www.gnu.org/software/pspp). In order to reduce number of factors, Kaiser (1958) criterion was applied (according to this method, contributions of factors are significant if eigenvalues >1). After this, Varimax method was used, the most common orthogonal rotation method. Using factor loadings, 3 maps are presented, which reveals the spatial influence of these 3 factors (fig. 1-3). There are some interpolation techniques used in climatology (Hartkamp et al., 1999, Vicente-Serrano et al. 2003), Splining is a spatial deterministic interpolation technique, which fits a mathematical

function across irregularly spaced data (Chapman and Thornes, 2003). These 3 maps were made with Arcmap software (http://www.esri.com) using spline with barriers interpolation method. At same, distribution figures of stations were made using Arcmap software (spline with barriers interpolation method). As a matter of fact, these figures are time-series figures (realized after seven years daily precipitation amounts same values as in case of factor analysis). A time-series figures from monthly precipitation data were presented by Gimesi (2011). 4 Results and discussion

The results of factorial analysis (factor loadings) are shown in table 1. It was found 3 dominant factors which can explain 67.19 % of the variance.

Table 1. Factor loadings resulted for daily precipitation data

factor 1 factor 2 factor 3

Alba Iulia 0.21 0.77 0.28

Bâlea Lake 0.51 0.55 0.08

Baraolt 0.77 0.28 0.24

Boiţa 0.46 0.74 0.02

Braşov 0.81 0.38 0.07

Bucin 0.42 0.19 0.66

Dumbrăveni 0.43 0.64 0.27

Fagaraş 0.62 0.64 0.01

Joseni 0.55 0.27 0.60

Lăcăuţi 0.78 0.16 0.15

Miercurea Ciuc 0.7 0.22 0.49

Roşia Montană 0.05 0.63 0.51

Sărmaşu -0.03 0.07 0.31

Sebeş 0.26 0.78 0.25

Sfântu Gheorghe 0.83 0.21 0.20

Sibiu 0.36 0.80 0.10

Târgu-Muresâş 0.36 0.54 0.49

Târgu-Secuiesc 0.82 0.16 0.19

Târnăveni 0.31 0.69 0.36

Topliţa 0.43 0.22 0.67

Cluj 0.09 0.57 0.45

The factor-maps are presented in figures 1-3. The first factor affects the south eastern

part of area [fig. 1.]. These correspond to the southern part of the Eastern Carpathians, including some intermountain depressions (Brasov, Trei Scaune). In this area precipitation amount generally are less that in the other places of studied area (thus, the less mean amount of precipitation is registered in Targu

Secuiesc) [fig. 4.]. The southwestern part of Transylvania is dominated by the second factor which insures the most balanced precipitation pattern [fig. 2.]. This includes the central-northern part of the Southern Carpathians, and a major part of Transylvanian Plateau. The third factor provides the highest amount of rainfall and influence mainly the northern part of region, which includes the central part of the

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Eastern Carpathians, including Giurgeu intermountain depression and the north eastern part of Transylvanian Plateau [fig. 3.]. That is why, for instance, average precipitation in

Lacauti is less than in Bucin, in spite of that Lacauti (1776 m) is 500 m highest than Bucin (1282 m) [fig. 4.]

Fig. 1 The area of influence of the first factor. Colors represent the values of factor loadings.

Fig. 2 The area of influence of the second factor. Colors represent the values of factor loadings.

Fig. 3. The area of influence of the third factor. Colors represent the values of factor loadings

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Fig. 4. Seven year mean precipitation amounts. The meteorological stations are grouped after the results of

factor analysis [table 1.]

In addition, distribution figures of stations defined by the same factor pattern are similar. Such as, figure 5 present the similarity between precipitation time-series figures of Miercurea-Ciuc and Sfântu Gheorghe (factor 1), and figure 6 between time-series figures of Sibiu and Sebeş (factor 2). Miercurea Ciuc 2010

2009

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2004 1.jan.............................................................................................................................31.dec

Sf Gheorghe 2010

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Fig. 5. Similarity between precipitation time-series figures of Miercurea-Ciuc and Sfântu Gheorghe. (factor 1) Colours represent different amounts of precipitation.

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Sibiu 2010

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2004 1.jan................................................................................................................................31.dec

Sebes 2010

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2004 1.jan.............................................................................................................................31.dec

Fig. 5. Similarity between precipitation time-series figures of Sibiu and Sebeţ. Colours represent different amounts of precipitation. (factor 2)

Moreover, differences between the temporally distribution of precipitation appertained to three mountain stations(Lacauti,Balea Lake and Bucin, affected by the three different factors) are evidenced by figure 6. In Bucin, high daily amounts of precipitation are not limited only to summer months. Lăcăuţi 2010

2009

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2004 1.jan.................................................................................................................................31.dec

Bâlea Lake 2010

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2004 1.jan.................................................................................................................................31.dec

Bucin 2010

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Fig. 6. Differencies between precipitation time-series figures of mountain stations. Colours represent different amounts of precipitation.

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5 Conclusions

Factor analysis may reveal hidden features (relationships) of precipitation distribution. In this case we are dealing with a relatively smaller area (Transylvania, s.s.), and usually this region is presented in term of precipitation like a single entity, with differences due to elevation. This paper highlighted, that there can be made a regionalization, and the three sub-regions resulted after factor analyses of daily data are presented in maps. Time-series figures support this division. Distribution figures of stations defined by the same factor pattern are similar

References

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[2] GIMESI, L., (2011), Adatbányászati és térinformatikai módszerek biológiai és meteorológiai alaklmazásokkal. Teză de doctorat. Budapest, Óbudai Egyetem, 133 pag.

[3] HARTKAMP, A.D.,DE BEURS, K., . STEIN, A., WHITE, J.W., (1999), Interpolation Techniques for Climate Variables. NRG-GIS Series 99-01. Mexico, D.F.: CIMMYT

[4] KAISER, H.F., (1958), The varimax criteria for analytical rotation in factor analysis. Psychometrika, 23, 187-200.

[5] KAPLUNOVSKI, A.S., (2005), Factor analysis in environmental studies. HAIT Journal of Science and Engineering B, vol 2, Issues 1-2, pp. 54-94

[6] SANDU, I, PESCARU, V.I., POIANĂ, I., GEICU, A., CÂNDEA, I., ţÂŞTEA, D., (2008), Clima României, Editura Academiei Române, 366 pag.

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[8] VICENTE-SERRANO, S.M., SAZ-SANCHEZ, M.A., CUADRAT, J.M., (2003), Comparative anaysis of interpolation methods in the middle Ebro Valley (Spain): application to annual precipitation and temperature. Climate Research, vol. 24, pp. 161-180.