Phenomenological features of precipitation series in agricultural regions

Transcription

1 Extreme Hydroloeical Events: Precipitation, Floods and Droughts (Proceedings of the Yokohama Symposium, July 1993). IAHS Publ. no. 213, Phenomenological features of precipitation series in agricultural regions N. R. DALEZIOS Laboratory of Agrometeorology, Faculty of Crop and Animal Production, University of Thessalia, Pedion Areos, Volos, Greece A. BARTZOKAS Laboratory of Meteorology, Department of Physics, University of Ioannina, Ioannina, Greece Abstract In this paper phenomenological features of daily rainfall series are investigated in homogeneous agricultural regions. A region in central Macedonia of northern Greece is used for the analysis, where the availability of water is mandatory for the agricultural activities of the region. Seven stations are employed with a 10-year record of daily rainfall depths. At first, composite correlation diagrams are used, which justify the regional and spatial homogeneity of the data sets. Temporal characteristics of the rainfall data have shown that the majority of days throughout the year are without rain for all the stations using either mean annual or monthly rain occurrences. Similarly, the small rainfall amounts constitute the majority of the rainy cases. Moreover, harmonic analysis of the annual variation of rain occurrences is attempted using 5-day values of rainfall depths. The five strongest harmonics are presented along with phases, amplitudes, temporal cycles and total variance explained. INTRODUCTION There is a gradual trend towards growing water requirements in several regions around the world due to a number of developmental activities mainly in agriculture (Rees et al., 1990). Specifically, the region of central Macedonia in northern Greece (Fig. 1) is one of such cases with a semi-arid continental climate in which the prudent use of water is mandatory (Balafoutis, 1977; Dalezios et al., 1991; Dalezios & Christodoulou, 1989). Thus an understanding of the patterns of precipitation and its variability in agricultural regions is important for improved water management and optimization of various water needs and uses. Rainfall is non-continuous in time and space with very high variability. The spatial and temporal variability of precipitation has long generated considerable interest among scientists (Ishihara & Ikebuchi, 1973; Woolhiser et al., 1973; Winkler et al., 1988). However, the temporal variations of daily precipitation have not been well documented (Kawas & Delleur, 1975; Katsoulis & Kanbetzidis, 1989). Moreover, the spatial and regional variability of daily precipitation is not covered by previous research or if it is considered, it is not fully documented (Riley et al., 1987). The purpose of this paper is to present several phenomenological features to describe the spatial and temporal precipitation variability as well as the precipitation regimes in agricultural regions. Another objective consists of exploring a number of temporal and spatial characteristics of the precipitation series in order to identify needs

2 52 N. R. Dalezios & A Bartzokas for further analysis and research that would assist in improving the agriculture of these regions. In addition, harmonic analysis is used to describe the annual and seasonal cycles of daily precipitation depths and occurrences. In this study the emphasis is placed on identifying important harmonics to represent annual and seasonal variation of precipitation. BACKGROUND In this study daily precipitation records for seven stations in the region (Fig. 1) constitute a computerized data base for the decade dating from 1967 to There is an extended area north of Giannitsa station (Fig. 1) with rainfed agriculture, whereas the area south of this station is characterized by irrigated agriculture. Very little information is available on the spatial distribution of precipitation, the amount of precipitation per occurrence, the variations between periods of dry, wet or normal weather, as well as the impact of the above to agriculture and other areas. Initial investigations in the region under study have been performed on precipitation frequencies and average amounts of precipitation per rainy day (Dalezios, 1989). The data base is divided into two periods, one representing the cool season (October-March) and the other representing the warm season (April-September). The composite correlation fields (Berndtsson, 1988) of the cool season within the 0.7 correlation isoline cover an area less than about 2500 km 2, whereas the corresponding area for the warm Yugoslavia I EYZONOI 1 POLYKASTRO 3 «ILKIS 4 GOUMENISSA 2 GIANNITSA 5 Fig. 1 Map of study area and key map.

3 Phenomenological features of precipitation series 53 season fields is less than about 1500 km 2. These findings justify the assumption for regional homogeneity of the precipitation data sets. The temporal and spatial variability of precipitation is investigated by analysing the daily rainfall series of the seven stations in the region under study and by employing harmonic analysis. Specifically, the annual and seasonal rainfall occurrences for various classes of precipitation depths are presented and analyzed to show the fluctuation and frequency differences between light and heavy rainfall depths, as well as non-rainy days. Similarly, harmonic analysis is used to explore the significant harmonics and other stochastic features of the data sets that would assist in identifying periodicities of light and heavy rainfall depths and occurrences. PHENOMENOLOGICAL FEATURES OF RAINFALL SERIES The annual variation of rainfall depths for all seven stations using mean 5-day precipitation totals over ten years ( ) is shown in Fig. 2. The variation exhibits several maxima and minima. The main common feature of these plots is a maximum from about the 8th until the 19th 5-day interval, namely during February and March. Another period of the year where high precipitation is recorded starts at about the 54th 5-day interval, i.e. the end of September and lasts until late December. There are also peaks in summer, but the main feature of the warm period of the year is a minimum, which starts at about the 40th 5-day interval (middle of July) and lasts for about two and a half months. In general, all stations exhibit similar characteristics except for the two coastal stations, which receive the least amount of rainfall. MEAN OF ALL STATIONS DAY INTERVALS Fig. 2 Mean 5-day precipitation totals for all stations over 10 years ( ). The mean annual variation of daily rain occurrences in 5-day intervals for three different depths for Polykastro station over ten years is shown in Fig. 3. Three thresholds of daily rainfall depths are employed, namely 0.1 mm representing all rain occurrences, 2 mm indicating light rainfall and 10 mm above which rainfall is considered as heavy. It is obvious that for all rainfall occurrences (rain > 0.1 mm) the maxima are recorded in the cool season of the year where in some 5-day intervals rain falls in more than two days. As the lower limit of the precipitation class increases, the differences between winter and summer decrease. In the curve corresponding to heavy ( > 20 mm)

4 54 N. R. Dalezios & A Bartzokas DAY INTERVALS Fig. 3 Mean occurrences of precipitation in 5-day intervals for Polykastro station over 10 years ( ). rain, which is situated nearest to the x-axis, there are even fewer occurrences of rain during the winter 5-day intervals are even fewer than the summer ones. In Table 1 a summary is presented of the mean annual number of days with and without rain over ten years ( ) for all the stations. Three classes of rainfall depths are used, namely non-rainy days, days with up to 9.9 mm of rain and days with rain > 10 mm. It is shown in Table 1 that on the average about 270 days per year are rainless, whereas the number of days with light to moderate rain has an average value of 76 days and there are only 18 days per year of heavy rainfall. In Table 2 the mean monthly number of days with and without rain for the station of Giannitsa over ten years is shown. The results are similar to Table 1 indicating that on the average 75% of days per year are rainless. In Table 2 several classes of daily rainfall depths are used allowing a detailed monthly distribution. Specifically, in Giannitsa station the greatest number of rainless days occurs in August (26.7) and the smallest in February (18.5). As expected, light rain (up to 1.9 mm) occurs mainly during winter months, whereas very heavy rain (> 20 mm) occurs mainly during late spring and summer and rarely in winter months. HARMONIC ANALYSIS Since the annual variations of rainfall depths and occurrences are periodic phenomena, Table 1 Mean annual number of days with/without rain over 10 years ( ). STATIONS 0 Rainfall Classes in mm ^ 10.0 EYZONOI 60UMENISSA POLYKASTRO KILKIS GIANNITSA THESSALONIKI MIKRA MEAN

5 Phenomenological features of precipitation series 55 Table 2 Mean monthly number of days with/without rain for Giannitsa station over 10 years ( ). MONTHS Rainfall Classes in mm i JANUARY FEBRUARY MARCH APRIL MAY JUNE JULY AUGUST SEPTEMBER OCTOBER NOVEMBER DECEMBER MEAN each of them can be delineated by a sum of sinusoidal waves - the harmonics - using Fourier or harmonic analysis. The following formula is used: N F(t) = F+ C n sm(2tvnt/k + $ n ) (D where F is the mean annual value of the analyzed function F(t), C n represents the amplitude of the n-th harmonic component, $ n is the phase angle and k is the fundamental period. In this case k equals 73, since each function is analyzed by using 73 values. Hence, the number of harmonics N should not exceed (73-l)/2 = 36 (Conrad & Pollak, 1950). In this analysis it has been found that the contribution of the harmonics to the total variance does not decrease regularly as their order increases, which justifies the analysis with all the possible 36 harmonics. The reproduction of the original curve can be achieved using equation (1). For t=1 equation (1) gives the value for the first 5-day interval (1-5 January), for t=2 the value for the second 5-day interval (6-10 January) and so on. For a better assessment of results of the harmonic analysis, the time to maximum T n is frequently used, instead of the phase angle. The T n can be estimated by setting 27rnt/k+4? n = T/2 and solving equation (1) in terms of it. In this case the resulted value is multiplied by five and then the value of 2.5 is subtracted in order to present the result as a precise date of the year (e.g. the value of T n = 3.5 indicates 15 January). In Table 3 the harmonic analysis of the annual variation of rainfall occurrences greater than 0.1 mm and 10 mm, respectively, is presented for Kilkis station using 5-day values. In particular, the periodicity, the amplitude, the time to maximum and the percentage of the total variance explained by each of these harmonics are tabulated for the five most significant harmonics for each analysis. It should be mentioned that the analysis has been performed for all the stations and Table 3 is an illustration of the results for one of them (Kilkis station).

6 56 N. R. Dalezios & A Bartzokas In the case of all rain occurrences (rain > 0.1 mm) all the stations reveal a strong 1st harmonic explaining from 25.2% of the total variance for Eyzonoi station to 54.1% for Thessaloniki station with 32.6% for Kilkis station (Table 3a). The 14th (26 days) and the 8th (46 days) harmonic also appear in most of the stations as important ones with amplitudes being constant about 0.20 days and their maximum occurring in early and middle January, respectively. Finally, the 21st harmonic (17 days) should also be mentioned, since it is included among the five most important harmonics in five out of seven stations. In the second case of rain occurrences > 10 mm in Table 3b the results are more complicated. It is well known that most summer thunderstorms are caused by thermal instability of local nature. As a result important periodicities are not found in all the stations. The 3rd harmonic (122 days) appears in the five stations except in the two coastal ones with an amplitude between and days and its maximum appearing in late February. It is interesting to emphasize the absence of the 3rd harmonic from the coastal stations and that the time of maximum is identical to the behaviour of the 3rd harmonic of the annual variation of rainfall. Table 3 Harmonic analysis of annual variation of rainfall occurrences using 5-day values for Kilkis station: a) occurrences of rain > 0.1 mm (mean number of rainy days over 5-day intervals: 1.30 days). MONIC PERIODICITY (days) AMPLITUDE (days) T max (date) VARIANCE (%) 1st 14th 11th March 1 January 8 January th January th January 4.2 b) occurrences of rain > 10 mm (mean number of rainy days over 5-day intervals: 0.24 days). MONIC PERIODICITY (days) AMPLITUDE (days) T max (date) VARIANCE (%) 21st January th February th January th January 5.1 8th January 4.5 SUMMARY AND CONCLUSIONS In this paper several spatial and temporal features of daily rainfall data sets are investigated in an agricultural region of central Macedonia in northern Greece (Fig. 1).

7 Phenomenological features of precipitation series 57 The computed composite correlation fields (Berndtson, 1988) justify the regional and spatial homogeneity of the employed seven stations with a 10-year record. The results of the temporal feature analysis indicate that on the average 270 days per year are rainless using either mean annual or monthly rain occurrences. Similarly, the majority of the rainy cases consists of small rainfall amounts, whereas the occurrences of large rainfall amounts constitute a very small portion of the rainy days. The annual variation of daily rainfall in all stations also shows high values in March, April and November with low values occurring in summer and fall. These findings suggest that there are usually shortages of rainfall during the agriculturally critical periods, especially in the rainfed crops of the northern part of the region under study (Fig. 1). Furthermore, the harmonic analysis of the annual variation of daily rain occurrences has explored several stochastic features of the data sets such as phases, amplitudes, cycles and percentages of total variance explained. REFERENCES Balafoutis, C. (1977) Contribution to the study of the climate of Macedonia and west Thrace. Ph. D. Dissertation, Arist. Univ. of Thessaloniki, Greece. Berndtsson, R. (1988) Temporal variability in spatial correlation of daily rainfall. Wat. Resour. Res., 24(9), Conrad, V. & Pollak, L. W. (1950) Methods in Climatology. Harvard Univ. Press, 459pp, Cambridge Dalezios, N. R., Papazafiriou, Z. G., Papamichail, D. M. & Karacostas T. S. (1991) Drought assessment for the potential of precipitation enhancement in northern Greece. Theor. Appl. Climatol., 44, Dalezios, N. R. (1989) Pre-investigative study of precipitation enhancement potential for northern Greece. Intera Technologies Ltd., Final Rept. M for ELGA (OGA). Dalezios, N. R. & Christodoulou, M. (1989) Feasibility of rain enhancement for northern Greece. Proc. 5th WMO Scient. Conf. on Weather Modification and Applied Cloud Physics, Beijing, China, WMO, 8-12 May, Ishihara, T. & Ucebuchi, S. (1973) Stochastic structures in space and time of daily precipitation and their simulation. In: Floods and Droughts, WRP, Fort Collins, Colorado, Katsoulis, B. & Kambetzidis, H. (1989) Analysis of the long-term precipitation series at Athens, Greece. Climatic Change, 14, Kavvas, M. L. & Delleur, J. W. (1975) Analysis of trends and the persistence structure in the daily rainfall occurrences in Indiana. Proc. National Symp. on Precipitation Analysis for Hydrologie Modeling. AGU, Davis, California, June, Rees, D. I., Samiullah, A., Rehman, F., Kidd, C. H. R., Keatinge, I. D. H. & Raza, S. H. (1990) Precipitation and temperature regimes in upland Baluchistan: Their influence on rain-fed crop production. Agric. For. Meteorol., 32, Riley, G. T., Landin, M. G. & Bosart, L. T. (1987) The diurnal variability of precipitation across the central rockies and adjacent great plains. Mon. Weath. Rev., 115(6), Winkler, J. A., Skeeter B. R. & Yamamoto, P. D. (1988) Seasonal variations in the diurnal characteristics of heavy hourly precipitation across the United States. Mon. Weath. Rev., 116(9), Woolhiser, D. A., Rovey, E. & Todorovic, P. (1973) Temporal and spatial variation of parameters for the distribution of n-day precipitation. In: Floods and Droughts, WRP, Fort Collins, Colorado,

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