A climatic analysis of dry sequences in Argentina

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1 INTERNATIONAL JOURNAL OF CLIMATOLOGY Int. J. Climatol. 31: (2011) Published online 26 January 2010 in Wiley Online Library (wileyonlinelibrary.com) DOI: /joc.2092 A climatic analysis of dry sequences in Argentina María P. Llano* and Olga C. Penalba Departamento de Ciencias de la Atmósfera y los Océanos, Facultad de Ciencias Exactas y Naturales - Universidad de Buenos Aires, Argentina ABSTRACT: The study of the temporal-spatial variability of dry sequences and the probability of their occurrence are particularly important in understanding the impact of climate change on droughts. This paper analyses the different properties of dry sequences, focussing on extreme condition, analysing their degree of spatial coherence, and their temporal variability. For the study, daily precipitation data are used for the period throughout Argentina. The region north of 40 S is divided in two from the meridian of 63 W with highly differentiated dry properties. The eastern region is more homogeneous where mean dry sequences last less than six days and long sequences of about 60 days. The Andean region shows a marked east west gradient in any of the above properties, with extreme values of over 10 days (mean sequences) and 150 days (the longest sequences). At the seasonal level the above properties reflect a differential pattern according to the time of year under study. In the case of summer, when the dry sequences can be more harmful to crops, the maximum duration in the Pampa region can extend to about 25 days. Owing to the problems that dry sequences of over 30 days can produce in the different ecosystems and based on the above findings, the temporal-spatial variability is analysed, and a variability over the years, together with a progressive decrease in the occurrence of such events, is found. The study of extreme dry events provides useful tools that can be applied to different hydrological and agricultural needs. Furthermore, our climatological findings help validate climate models. Copyright 2010 Royal Meteorological Society KEY WORDS dry sequences; extreme events; regionalization; temporal variability Received 28 January 2009; Revised 17 December 2009; Accepted 18 December Introduction The climate of a region is by definition a probability distribution of meteorological variables, which are analysed over a long period of time. However, to understand a region s climate, it is necessary to observe how often extreme events occur. Society and the environment have adapted to the mean weather conditions; nevertheless, they have proven to be more vulnerable to extreme events. The magnitude of successive extreme events lies in their amplified cumulative impact. A single event may be easy to withstand but a progression of these events can be far more devastating. Changes in climate variability, weather s extreme events, as well as climatic extreme events in the last decades, are the subject of increasing attention. Understanding changes in climate variability and extreme events is not an easy task, given the interaction between the mean and its variability (IPCC, 2007). This interaction changes from one variable to another because it depends on, among other factors, its statistical probability distribution (Meehl et al., 2000). This analysis becomes * Correspondence to: María P. Llano, Departamento de Ciencias de la Atmósfera y los Océanos, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Argentina. mpllano@at.fcen.uba.ar even more complex when the variables do not come close to a normal distribution, as it is the case of precipitation. Annual and seasonal rainfall series are of deep concern to hydrologists, climatologists and farmers due to their effect on water resources planning, water use, and their role in the evolution of climate. Droughts, one end of the rainfall distribution, are a frequent cause of negative social impacts. Drought is a progressive phenomenon and it is difficult to distinguish its onset and end. The impact of drought is felt not only in agriculture and hydrology but also in urban water supplies, industrial production, pollution control, navigation and energy among others. Unfortunately, there is no generally accepted classification scheme (Wilhite and Glantz, 1985). It is possible to define drought in terms of meteorological, hydrological, agricultural and socio-economic conditions. This has resulted in a large number of drought indices, as seen in the literature (Heim, 2002; Keyantash and Dracup, 2002). Among the authors who characterize the intensity and duration of drought periods and excess water through the use of any of the indices in different regions of Southeast South America are Scian and Donnari (1997), Seiler et al. (2002), Carbone et al. (2004) and Nuñez et al. (2005). Some studies have analysed the way in which drought impact has affected productive activities and society as a whole. Vargas (1979) developed an atlas of the humid and semi-arid region of Argentina, analysing the most striking Copyright 2010 Royal Meteorological Society

2 ANALYSIS OF DRY SEQUENCES 505 features of the monthly water deficit, as well as storage and evapotranspiration, among others. This atlas gave rise to the subsequent assessment by Vargas and Nuñez (1989) in which they explored how the governmental systems respond to extreme rainy conditions, in turn assessing the economic losses in each of the events analysed. Extreme precipitation can be addressed by studying the distribution of dry sequences. Vargas and Alessandro (1983, 1985) examined the monthly precipitation in Argentina s northeast and Pampa regions to build probability models. Vargas (1981) adjusted the dry sequence by means of a geometric distribution. Ruiz (2005, 2006) analysed the daily dry conditions during 5 7 days in the winter period (May October) for various stations in the province of Buenos Aires, Argentina. Knowledge about the temporal-spatial variability of dry sequences, as well as the probability of their occurrence, is especially important if the government domain is considered. This information will be useful to take measures to alleviate the impact of these events, providing possible solutions to the problems they produce. The importance of this paper is reflected in the recent Workshop in Nebraska, whose main objectives were, among others, to facilitate progress and to make an assessment of the impact of global change on drought processes (Gutzler and Schubert, 2007). Argentine producers are particularly concerned with the water profile of the soil for future seasons (Boulanger and Penalba, 2009). Therefore, the knowledge of the different properties of the dry sequences is of great relevance in non-irrigated agriculture and, especially, in marginal regions. The purpose of this study is to determine the spatial patterns and temporal variability of dry sequences in Argentina with a focus on extreme events. The guiding questions are: (a) What is the direction and strength of dry conditions? (b) What is the degree of regional homogeneity in this variability? and (c) How do the spatial patterns change when considering different time periods? 2. Data and methodology 2.1. Definition of indices The term dry sequence of length n days is defined as a succession of n consecutive days without rain preceded and followed by days with rain. A day without rain is considered as one in which the record registers 0 mm. In this paper, an extreme event is considered when a succession of 30 or more consecutive days without rain occurs Consistency of information This study uses daily precipitation data from stations in Argentina that were provided by the National Weather Service and the National Institute for Agricultural Technology. The available database initially had more than 100 stations, covering different periods of time. While previous studies are related to the consistency of daily weather reports in Argentina, most of them analyse the event of rain per day (Boulanger et al., 2007; Penalba and Robledo, 2009). In order to obtain statistically consistent findings when analysing dry sequences throughout Argentina, it is necessary to make additional consistency analyses, which are detailed below Length of series Some stations showed shorter periods of information, which were insufficient for a climate study (less than 30 years, according to WMO, 2004). At others, the total period of analysis was relatively long, including many continuous years without data or missing data randomly distributed within the period. Finally, although the length of the series at some stations surpassed 30 years, its onset or end was dissimilar and, hence, the number of years in common did not suffice Amount of missing data All stations with 10% or more daily missing data were eliminated from the study. Since this work analyses consecutive days without rain, the following analysis was conducted with regard to the rest of the stations. If the missing data fell within a dry sequence, or at its onset and/or end, the dry sequence was eliminated from the study Erroneous long sequences Some stations presented 0 precipitation data instead of missing data. To detect erroneous dry sequences, the duration of the successive days without rain for each station was analysed. This procedure revealed erroneous sequences for three locations, where records showed that days without rainfall exceeded one year. Therefore, these stations were eliminated. This quality control was passed by 34 stations. The geographical locations of the stations are presented in Figure 1. All of the stations shared a 40-year-long period corresponding to Special coverage of the stations was satisfactory in most regions. However, the number of stations south of 40 S (Patagonia) and in mountain areas (centre-west region) is limited. Despite this limitation, their inclusion allows to characterize the country s different climatic regions Methodology For each station, the empirical probability distribution of dry sequences of length n is calculated. All the dry sequences are mutually excluded. In order to determinate the possible existence of statistically trends, a nonparametric Kendall-tau test is used for the period The significant level assumed is 95% (Sneyers, 1990). This test is a rankbased procedure suitable for detecting nonlinear trends in variables that do not have a Gaussian distribution.

3 506 M.P. LLANO AND O.C. PENALBA This analysis is also performed at seasonal levels, showing a similar behaviour to that seen on an annual basis. In order to characterize these climatically empirical distributions, various properties of these probabilities are evaluated. Figure 1. Location of the stations. 3. Characteristics of dry sequence The empirical probability of dry sequences decreases as the number of days involved increases. A detailed analysis reveals significant regional differences, demonstrating the existing variability in rainfall in Argentina. The distribution of empirical annual probability of selected stations is presented in Figure 2. These stations characterize the dry sequences across the country and complement the pattern of rainfalls. Sauce Viejo, indicated in Figure 1 as -15 -, represents the region with more annual and seasonal rainfall (Penalba and Vargas, 2008). Rivadavia -1 -, La Rioja -11- and Mendoza -18- are stations located in regions with lower rainfall and more pronounced seasonal regime (summer rain). Sauce Viejo shows a slight decrease in the empirical probability of dry sequences, which do not exceed the maximum dry month. However, note that the dry sequences between 7 and 20 days always show a greater probability than at Rivadavia. The Andean region (represented by La Rioja and Mendoza) shows sequences extending over 40 days. A comparison of these two stations shows that La Rioja presents a greater probability of short dry sequences of less than 9 days. The south of 40 S is an arid zone, with different regimes of precipitation between the east and west. However, the distribution of empirical probability of dry sequences does not present differences (see Figure 2, Esquel -32- andtrelew-33-) Average length of dry sequences Annual The average length of the dry sequences calculated in annual terms is presented in Figure 3. This result shows that Argentina has distinct characteristics: the stations located east of 63 W present dry sequences with an average value less than 6 days with little spatial variability. To the west there is a marked spatial east west gradient reaching an average length of more than 10 days, and the maximum value in the mountain range is located in Mendoza station recording 12.8 days, while the Patagonia area, south of 40 S, the mountain station, presents an average value of 6 days without precipitation and the costal stations show values of 7.4 (Esquel) and 5.1 days (Rio Gallegos-34-). To summarize, north of parallel 40 S, the isoline of 6 days without precipitation divides Argentina in two: (a) to the east wetter conditions with shorter dry sequences on average are found, and (b) to the west lies the more arid zone characterized by longer periods without rain (the winter period). At south of this parallel, the Patagonia presents a different precipitation regime with values nearing 6 days Seasonal The annual pattern of the average length of dry sequences is reflected in the autumn and spring seasons (Figure 4). From these results Argentina can be divided into two regions: north of 40 S and the Patagonia region. In the north region, despite the small differences observed between these two seasons, they generate a different rainfall behaviour. At the regional level, differences in the extreme northwestern Argentina can be seen, where the average length of dry sequences varies between 6 days in autumn and 5 days in spring. In the extreme northeast, autumn (spring) sequences average close to 5 days (4 days). In the centre region, an east west gradient can be seen, which during the spring presents a slight decrease in the average length of the dry sequences east of the 63 W and increases in the Andean mountain range. During the winter, the east west gradient north of 40 S deepens, reaching values of over 20 days in the mountain range. The longest mean dry sequence is recorded at La Rioja (21 days), while the shortest ones are concentrated in the provinces of Misiones and Corrientes and in the coastal area (Mar del Plata -29-). Regional differences between the western and eastern stations in the Patagonia have started to be observed. During the summer, the regional pattern of mean dry sequences changes and it becomes the season with the least spatial variability north of 40 S. The values are

4 ANALYSIS OF DRY SEQUENCES 507 Figure 2. Distribution of empirical annual probability of dry sequences. (a) La Rioja station, (b) Mendoza station, (c) Esquel station, (d) Rivadavia station, (e) Sauce Viejo station, (f) Trelew station. central (Laboulaye -23- with 3.6 days). The maximum values are located in the Andean area but they are now displaced further south where Neuquén (-30-) shows a greater mean length of 10 days. The southern stations (Esquel, Trelew and Rio Gallegos) present a low variation between theirs along the seasons; during the winter the variation is larger, where a change in spatial behaviour can be seen, with a southeast northwest gradient (Rio Gallegos presents a value of 3.8 and Esquel 8.5 days). Figure 3. Mean length of dry sequences on an annual basis. lower across the country, reaching a minimum (less than 4 days) in the northwest (Salta -3- with 2.4 days) and 3.2. Maximum length of dry sequences The maximum length of dry sequences is an extreme and instability property. However, their analysis reveals interesting results. This index (called CDD: consecutive dry days) was analysed by other researchers. For example, Haylock et al. (2006) calculated it over the period and examined its temporal changes and its relationship with the oceans. Rusticucci et al. (2010) and Marengo et al. (2010) focus their analysis on the consensus in the geographical and temporal variability of temperature and rainfall extreme indices between observations and eight IPCC AR4 global coupled climate models Annual The study of the annual maximum length of dry sequences (figure not shown) has a strong east west

5 508 M.P. LLANO AND O.C. PENALBA Figure 4. Mean length of dry sequences on a seasonal basis. gradient. The minimum length is found in the northeastern region of the country with values registering close to 40 days. In the Pampa region, the values register a maximum of around days. The strong spatial variability in the centre-west of the country can be seen: the maximum length is around 63 days at Sauce Viejo (centre region), whereas the maximum length in the Andean region registers 192 days at La Rioja. In the agricultural region, the maximum length of dry sequences reaches no more than 2 months. These periods can be quite harmful to crops because they can only be broken by scarce or brief rainfall, cutting the dry sequence but leaving the land without an adequate supply of water or moisture Seasonal From a seasonal perspective, it is interesting to see how the patterns reflect a similar behaviour to the above case of mean sequences, although minor differences are shown.

6 ANALYSIS OF DRY SEQUENCES 509 Figure 5. Maximum length of dry sequences on a seasonal basis. Autumn presents a smaller spatial variability. The lowest values, less than one month, can be found in the east. Meanwhile, values around days are observed in northwestern Argentina and the Pampa region. Towards the west, the length of the dry sequences increases, reaching a peak (62 days) in the area of Cuyo (Mendoza, Figure 5). During the winter, an increase in the length of the dry sequence for all regions of the country has been recorded, as well as an intensification of the east west gradient. In the eastern region of the country, values range from 1 month to 40 days, increasing their length in the core region of the Pampa region. A zone with values longer than 60 days is observed in the northwestern and Cuyo, where the dry season is more evident. During the spring, the east west gradient is perceived, resuming the annual pattern. The minimum values close to 20 days are registered in Argentina s far northeast, and durations climb slightly towards the Pampa region.

7 510 M.P. LLANO AND O.C. PENALBA At this time of year, this region presents a smaller spatial variability. These values rise rapidly towards the west with values exceeding 80 days and last throughout spring. During the summer, the spatial pattern tends to reverse. Values in the central-northern area of the country register less than a month, with a lower maximum recorded at local stations in the north and the northeast corner (Rivadavia, 36 days, Santiago del Estero -10-, 33 days). Furthermore, local minima can be observed with values between 10 and 20 days (Tucumán, 19 days; Salta, 13 days). Rosario reports the longest dry sequence, 70 days without precipitation in the summer of (this season is characterized by an intense drought). This indicates how strong the variability in the Pampa region can be, as other stations in the area have recorded less than the monthly maximum duration on average. The Patagonia region presents durations ranging between 30 and 40 days. 4. The longest dry sequences 4.1. Spatial coherence The maximum length of the dry sequences per year is a property highly interesting, due to the impact on agriculture. For each station, the five years with the longest dry sequence are marked, and their spatial and temporal behaviours are analysed. This study is focussed to analyse whether they tend to occur during some particular time of the year and/or in some particular region. The first year analysed is 1962, when 12 stations register the longest sequence in their records. The sequence covers the entire Argentine territory. Values range from 31 days at Paso de los Libres (-12-) up to 110 days without precipitation at Mendoza. The months in which these extreme sequences occur varied from the beginning of the year for stations in the south of the country to the end of the year for those stations located in the centre and north. A particularity of this analysis is that the dry sequence spreads across the entire territory, as also discussed by Malaka and Nuñez (1980). Another year in which dry sequences coincided in 11 locations is The longest sequences are observed in La Rioja (128 days) and at Santiago del Estero (103 days), during winter season. This severe drought was analysed by Alessandro and Lichtenstein (1996), which affected the centre of Argentine Temporal variability The most recent Intergovernmental Panel on Climate Change report (IPCC, 2007) examines the overall increase in dry areas from To analyse the behaviour of extreme dry sequences in recent decades and to study the presence of preference regions as well, the following analysis is made. The evolution in time of the longest dry sequence per year, as well as the mean and standard deviation for each of the stations in Argentina (for a better display graphics, the scales are different), are shown in Figure 6. While this property of the sequences shows a great deal of dry temporal variability, it is higher in the Andean mountain regions (Mendoza and La Rioja) and northwestern Argentina (Rivadavia). The stations located in other areas register a lower variability, as in the case of Esquel, where the number of days that make up the longest sequence maintains the average value of 27 days, with the exception of isolated cases at the beginning of period. All stations tend to show a decrease in the duration of the longest dry sequences, except for La Rioja. This behaviour is mainly due to the longest dry sequence in Mendoza is the only station with significant negative trend. However, if the cases of sequences, whose duration is above the average plus one standard deviation, are analysed, there would appear to be more cases in the first half of the record than in the second one. The same situation is reflected at the other stations, where a lesser chance that these sequences are registered with a greater number of days can be found, as in Rivadavia. 5. Extreme events As was mentioned above, the longest dry sequences are of most interest. So, from the point of view of climate and its impact in particular, it is useful to analyse the tails (extremes) of the distributions of the sequences of dry days according to their duration. In line with the results presented in the previous section and taking into consideration that the length ofthe dry sequencesdepends on the region under review, the spatial and temporal behaviour of dry sequences whose duration exceeded 30 days are examined (hereafter extreme event) Spatial variability The number of extreme events is shown in the map of Figure 7. The spatial pattern of extreme events (east west gradient) observed in the other properties shows no change. The largest number of cases occurs in the mountain range from the centre of the country, where the sequences last over 1 month in 100 cases. In the rest of the country, while the spatial behaviour tends to be random, small homogeneous areas can be identified: (a) the Pampa region with a range of 10 and 25 events, and (b) stations in the east presenting fewer sequences, with an absolute minimum of 1 at Mar del Plata. The study of this southern region shows that Trelew on the east coast records 42, the largest number of cases, while lower Rio Gallegos shows 13. The number of times that these extreme events occur in different seasons reveals that Argentina has different behaviours, depending on the season. The southern stations and Neuquén record almost 10 events occurring during the warmer months (spring and summer). In the rest of the country, the occurrence of extreme events is low and isolated. In this region, the spatial

8 ANALYSIS OF DRY SEQUENCES 511 Figure 6. Most extreme sequence per year (by its duration). The straight line represents the mean value of the longest sequence throughout the register and the dotted line represents a sigma of deviation. (a) La Rioja station, (b) Mendoza station, (c) Esquel station, (d) Rivadavia station, (e) Sauce Viejo station, (f) Trelew station. Figure 7. (Map) Number of events. (Time series) Number of days each event lasted for each year. (a) La Rioja station, (b) Mendoza station, (c) Esquel station, (d) Rivadavia station, (e) Sauce Viejo station, (f) Trelew station. pattern observed in Figure 7 is similar to the cold seasons. During these seasons the highest number of cases occurs during the winter months followed by autumn (results not shown) Temporal variability To complement the previous analysis, the existence of an increase or decrease in the number of times that these

9 512 M.P. LLANO AND O.C. PENALBA extreme events occurred is also analysed, through a study of rates of change. The number of days each extreme event lasted for each year is presented in Figure 7 (see time series). Note that some years present no extreme events (for example, Sauce Viejo, ) and others present more than one (same station, 1995). An analysis of the Andean stations (La Rioja and Mendoza) shows that extreme events occur throughout the period. La Rioja shows that the duration of these extreme events is less than 75 days until 1979 (except for isolated extreme events). From 1979, the duration of these extreme events is higher. Mendoza shows an inverse temporal behaviour until the year 1984 when there is greater dispersion in their occurrence. This dispersion decreases and increases until 1993 at the end of the period under analysis. To the north of Argentina (Rivadavia) the length of extreme events tends to decrease when comparing the first with the last decade, with extreme events happening in isolated years (between 1987 and 1990) and other years with no record of occurrence (1968, 1974, 1982, 1984, 1986 and early 1990). Towards the northeast and in the Argentine Pampas, the stations show a uniform temporal behaviour throughout the entire period (see Sauce Viejo). In southern Argentina, the occurrence of extreme events depends on the region. The west (Esquel) registers fewer and shorter extreme events than on the east coast (Trelew). In studying the variability of these extreme events from a seasonal perspective, it is only possible to carry out the analysis in certain regions and seasons. During the winter the temporal distribution of these extreme events is uniform throughout the period, the main difference being the length of extreme events. At the Andean stations (La Rioja and Mendoza) around 20 extreme events, whose duration lasts under 50 days, and infrequent cases of longer-lasting dry sequences are found. The length of extreme events recorded at the stations in the north (Rivadavia) is similar, but they tend to decrease the amount of opportunity in which they arise. The duration in the Pampa region is less than 30 days. In the summer, the south shows the highest number of extreme events. Esquel and Neuquen register more than 10 cases reaching sequences of about 40 days, while Trelew shows fewer extreme events. This kind of event is infrequent in the rest of the country. 6. Conclusions This analysis will contribute to the knowledge of the direction and strength of dry conditions, the degree of regional homogeneity and the percentage of change in the last decades. Among the different properties of dry sequences, their mean longitude was analysed, which presents a marked east west gradient north of 40 S across Argentina, averaging 6 days in the Pampa region and over 12 days in the Andean region. At the seasonal level, the values change owing to the marked dry season depending on the zone under analysis. In winter the gradient becomes more intense and the stations located in the Andean region can register a mean sequence of more than 20 days. The maximum length of the dry sequences was also analysed. The isoline of 60 consecutive days without precipitation located in the 63 W divides Argentina into two zones: the east shows lower values and the west presents a strong gradient that can reach up to 192 days without precipitation in La Rioja. Throughout the different stations, the values of the maximum sequences vary, winter registering the greatest number of sequences at most of the stations that were analysed, although at the seasonal level an absolute maximum of 88 days was registered in Mendoza in spring. The maximum dry sequences per year show a strong spatial coherence, principally in the cases of the extreme droughts that Argentina experienced in 1962 and With respect to temporal variability, the stations in the Andean zone register the greatest variability; records for those in the centre-east of the country show little variability except in isolated cases. All of the stations register a negative tendency in the duration of the longest sequences per year, except for La Rioja. One of the most important findings shows a progressive decrease in these extreme events over the years. However, this temporal variability shows no regional coherence. This study is an objective analysis to estimate the magnitude and the spatial domain of extreme dry sequences that can be used for hydrological applications and the validation of climate models to test their ability and the simulation of such change. Acknowledgements We thank anonymous referees for their valuable comments and critical reading of the manuscript. Support for carrying out this work was provided by the following grants: University of Buenos Aires 01X/170, AGENCIA BID 1728/OC-AR-PICT 38273, CLARIS LPB Project. (European Commission Project). References Alessandro P, Lichtenstein E Situación sinóptica asociada a la sequía del invierno de Geofísica 45: Julio Diciembre Boulanger JP, Penalba OC Assessment of climate information needs in the Argentinean Agro-business sectors. Climatic Change Special issue, DOI: /s Boulanger JP, Martinez F, Penalba OC, Segura EC Neural network based daily precipitation generator (NNGEN-P). 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