1. INTRODUCTION. Copyright 2004 Royal Meteorological Society

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1 INTERNATIONAL JOURNAL OF CLIMATOLOGY Int. J. Climatol. 24: (2004) Published online in Wiley InterScience ( DOI: /joc.1000 THE INFLUENCE OF THE TROPICAL AND SUBTROPICAL ATLANTIC AND PACIFIC OCEANS ON PRECIPITATION VARIABILITY OVER SOUTHERN CENTRAL SOUTH AMERICA ON SEASONAL TIME SCALES GUILLERMO J. BERRI 1, *andgermán I. BERTOSSA Department of Atmospheric and Oceanic Sciences, University of Buenos Aires, 1428 Buenos Aires, Argentina Received 10 January 2003 Revised 18 November 2003 Accepted 20 November 2003 ABSTRACT This paper studiesthe temporal and spatial patterns of precipitation anomalies over southern central South America (SCSA; S and W), and their relationship with the sea-surface temperature (SST) variability over the surrounding tropical and subtropical Atlantic and Pacific Oceans. The data include monthly precipitation from 68 weather stations in central northern Argentina and neighbouring Brazil, Paraguay and Uruguay, and monthly SSTs from the NOAA dataset with a 2 resolution for the period We use the method of canonical correlation analysis (CCA) to study the simultaneous relationship between bi-monthly precipitation and SST variability. Before applying the CCA procedure, standardized anomalies are calculated and a prefiltering is applied by means of an empirical orthogonal function (EOF) analysis. Thus, the CCA input consists of 10 EOF modes of SST and between 9 and 11 modes for precipitation and their corresponding principal components, which are the minimum number of modes necessary to explain at least 80% of the variance of the corresponding field. The results show that November December presents the most robust association between the SST and SCSA precipitation variability, especially in northeastern Argentina and southern Brazil, followed by March April and May June. The period January February, in contrast, displays a weak relationship with the oceans and represents a temporal minimum of oceanic influence during the summer semester. Based on the CCA maps, we identify the different oceanic and SCSA regions, the regional averages of SST and precipitation are calculated, and linear correlation analysis are conducted. The periods with greater association between the oceans and SCSA precipitation are November December and May June. During November December, every selected region over SCSA reflects the influence of several oceanic regions, whereas during May June only a few regions show a direct association with the oceans. The Pacific Ocean regions have a greater influence and are more widespread over SCSA; the Atlantic Ocean regions have an influence only over the northwestern and the southeastern parts of SCSA. In general, the relationship with the equatorial and tropical Atlantic and Pacific Oceans is of the type warm wet/cold dry, whereas the subtropical regions of both oceans show the opposite relationship, i.e. warm dry/cold wet. Copyright 2004 Royal Meteorological Society. KEY WORDS: precipitation; southern South America; canonical correlation analysis; sea-surface temperature 1. INTRODUCTION The most dynamical feedback among the different components of the climate system takes place between the oceans and the atmosphere. The diurnal variation of the physical properties of the ocean surface are negligible compared with that observed over the continents. This characteristic allows the oceans to play the role of source of seasonal to interannual climate variability. The tropical oceans are the main source of energy and moisture for the atmosphere, and the variability of the sea-surface temperatures (SSTs) has an important effect on climate variability over the continents on regional scales. * Correspondence to: Guillermo J. Berri, Department of Atmospheric and Oceanic Sciences, University of Buenos Aires, Pabellón 2, Ciudad Universitaria, 1428 Buenos Aires, Argentina; berri@at.fcen.uba.ar 1 Member of the National Research Council of Argentina (CONICET). Copyright 2004 Royal Meteorological Society

2 416 G. J. BERRI AND G. I. BERTOSSA The southern cone of South America is positioned as a wedge between two immense oceans, i.e. the Atlantic and the Pacific Oceans, and their influence on the local climate is important. A good example of such an influence is the phenomenon known as El Niño southern oscillation (ENSO). Several studies have looked at the influence of ENSO on the seasonal climate variability in southeastern South America (e.g. Ropelewski and Halpert, 1987, 1989; Grimm et al., 1998, 2000). Although ENSO has been demonstrated to influence the precipitation patterns over the region in a significant manner, it is a phenomenon with its origin in only one of the tropical oceans (i.e. the Pacific Ocean), and it is present for only some of the time. Montecinos et al. (2000), studying the simultaneous SST rainfall relationship between the tropical Pacific and subtropical South America, found a more significant relationship during the second semester of the year, when ENSOrelated SST anomalies in the tropical Pacific reach their full strength and, accordingly, their influence on the global climate is greatest. According to Montecinos et al. (2000), the influence during the austral spring is of the type warm wet/cold dry (WW/CD) in southeastern South America, including southern Brazil, southern Paraguay, Uruguay and eastern Argentina. Other studies include: the modulation of local precipitation variability by convection in the tropical Pacific Ocean (Mo and Higgins, 1998); the influence of the western Pacific atmospheric wave train activity (Karoly, 1989); precipitation variability over the subtropical plains of South America in connection with SST anomalies (Nogués-Paegle and Mo, 2002) and the South Atlantic convergence zone (SACZ) (Nogués-Paegle and Mo, 1997); precipitation variability over southern Brazil (Carvalho et al., 2002); over southeastern South America (SESA; Barros et al., 2000); and river flows in SESA (Robertson and Mechoso, 2000), all in connection with the SACZ. Some studies focused on southern Brazil and Uruguay (Díaz et al., 1998), and southern Brazil (Liebmann et al., 1999). We found a lack of a comprehensive study of the influence of the surrounding oceans on the precipitation variability in the central part of southern South America covering different periods of the year. Therefore, the purpose of this research is to study the temporal and spatial patterns of precipitation anomalies over southern central South America (SCSA) in relation to SST over the tropical and subtropical Atlantic and Pacific Oceans. The unique contribution of this research is a thorough diagnostic analysis of the relationship between SCSA precipitation anomalies and SST anomalies over the tropical and subtropical surrounding oceans through six bimesters of the year. Section 2 describes the data employed, and Section 3 presents a brief description of the precipitation climatology of the region. The methodology employed, canonical correlation analysis (CCA) between SST and precipitation over SCSA, is described in Section 4, and the results are presented in Section 5. Section 6 discusses the relationship between SST and precipitation during the summer semester November through to April. In order to reduce the number of degrees of freedom, and based on the results of CCA, in Section 7 we delineate several oceanic and SCSA regions and we calculate regional averages of SST and precipitation. Then, a linear regression analysis is performed between these regional averages for the periods that show more robust relationships, i.e. November December (described in Section 8) and May June (described in Section 9). Finally, in Section 10 we present the conclusions. 2. DATA EMPLOYED The precipitation data used in the study correspond to monthly precipitation records from 68 weather stations of the National Meteorological Services of Argentina, Brazil, Paraguay and Uruguay, for the period , all located to the east of the Andes Mountains. The box in Figure 1 displays the region of the study, a rectangle between 22 S and 40 S and 54 W and 66 W, which we term SCSA. The SST data are from the NOAA data sets, and have a grid resolution of 2 in latitude and longitude. The selected region includes the Atlantic Ocean (west from 10 E) and the Pacific Ocean (east from 130 E), with a northern boundary at 30 N anda southern boundary at 44 S (as depicted in Figure 1). The analysis is carried out using the 2 month averages of January February, March April through to November December for both precipitation and SST.

3 OCEAN AND SOUTH AMERICAN PRECIPITATION VARIABILITY N 25N 20N 15N 10N 5N EQ 5S 10S 15S 25S 35S 164E 147W 98W 49W 0 Figure 1. Oceanic domain and SCSA region, indicated by the box, over South America 63W 56W Figure 2. Total annual precipitation (mm) over SCSA in the period PRECIPITATION CLIMATOLOGY OF SCSA Annual precipitation totals in SCSA (shown in Figure 2) are highest over the northeastern part, with values of up to 1800 mm, and decrease towards the southwestern corner, with values up to around 400 mm. In order to describe the annual precipitation cycle and make the values comparable across the region, monthly mean precipitation at every station is expressed as a percentage of the annual mean precipitation (period ). Then, an empirical orthogonal function (EOF) analysis is performed; only the first mode is shown, because this accounts for almost 93% of the total variance. Figure 3(a) shows the first eigenvector, with a

4 418 G. J. BERRI AND G. I. BERTOSSA (a) 63W 56W (b) Month Figure 3. (a) First eigenvector of the monthly mean precipitation over SCSA, period Superimposed are the histograms showing the annual variation of monthly mean precipitation of two stations. (b) First PC (mode 1, 92.85%) of the monthly mean precipitation over SCSA, period maximum in the northwest and decreasing values towards the southeast. The first principal component (PC), Figure 3(b), clearly shows that the maximum is in summer (November to March) and the minimum is in winter (May to August). The combination of both figures indicates that the entire region presents the same annual behaviour: maximum precipitation in summer and minimum precipitation in winter. The magnitude of the eigenvectors in the spatial pattern (Figure 3(a)) also tells us that, in the west and northwest (closer to the Andes Mountains), the annual cycle is more marked and the rainy season is sharper. As we move to the southeast, the amplitude of the annual cycle reduces and precipitation tends to be distributed more throughout the year. The different amplitude of the annual cycle of precipitation in the northwest and the southeast of the region can be appreciated in the two histograms of Figure 3(a), which show the annual variation of the monthly mean precipitation. 4. METHODOLOGY We use the CCA method to study the simultaneous relationship between precipitation variability in SCSA and SST variability in the surrounding oceans. CCA is a generalization of multiple regression analysis that

5 OCEAN AND SOUTH AMERICAN PRECIPITATION VARIABILITY 419 maximizes the interrelationships between two data sets. The method analyses the cross-covariance structure between two fields, looking for the patterns of variability that occur simultaneously and also for the degree of connection between the two. The strengths of CCA are its ability to operate on full fields of information and to define the most highly related patterns of variability objectively. We refer the reader to the publications by Barnett and Preisendorfer (1987) and Preisendorfer (1988) for details of the technique. In order to facilitate the analysis of the relative incidence of each ocean on SCSA, both the Atlantic and Pacific Oceans are included together in the CCA. Before conducting the CCA, the monthly time series of both fields are transformed into six time series of 2-month averages, i.e. January February, March April through to November December. Then, we calculate the anomalies by subtracting from each value the mean value and dividing by the standard deviation of the same period. Finally, a prefiltering is applied by means of an EOF analysis. Thus, in our study, the inputs consist of EOF modes of SST and precipitation anomalies and their corresponding principal components (PCs). The EOF prefiltering has the advantage of reducing the spatial dimension of the input to CCA and enables one to filter out small-scale noise. There are different ways of choosing the number of retained EOF modes. In this study we retain the minimum number of EOF modes that explain at least 80% of the variance of the corresponding field. The number of retained modes of SST is p = 10, and for precipitation it is q = 9 to 11, depending on the period of the year. The CCA method produces p and q linear combinations of the standardized time series of the PCs for precipitation u i (t) and SST v i (t) respectively. These linear combinations u i (t) and v i (t) constitute the canonical component vectors and their correlation coefficients µ i constitute the canonical correlation coefficients if they satisfy the following requirements: µ i is maximum and u i and v i are uncorrelated with u j and v j respectively if i j. The absolute values of µ i are arranged in a decreasing way with increasing i, although they do not necessarily explain, in the same order, a decreasing amount of variance. The standardized anomalies of precipitation and SST can then be represented as linear combinations of the canonical maps, g i (x, y) and h i (x, y) respectively, in the following way: p u j (t)g j (x, y), 1 q v j (t)h j (x, y) 1 The canonical maps g i (x, y) and h i (x, y) show the correlations at specific locations between the canonical vectors u i and v i and the time series for the precipitation and SST anomalies fields respectively, reconstructed from the EOF analysis. 5. RESULTS OF THE CCA BETWEEN SST AND SCSA PRECIPITATION The canonical maps of the six 2 month periods from January February to November December are shown in Figures 4(a) to 9(a) (h i (x, y) for SST) and Figures 4(b) to 9(b) (g i (x, y) for precipitation) respectively. The shaded areas represent the regions where the correlation coefficients are statistically significant at the 95% level according to the Student s t-test. During all periods studied, the canonical vectors u i (t) and v i (t) are positively correlated, i.e. they are in phase. Therefore, the relationship between oceanic regions and SCSA regions is of the type WW/CD (warm dry/cold wet (WD/CW)) whenever the canonical maps show patterns with the same (opposite) sign January February Figure 4(a) shows the absence of important patterns of variability over the Pacific Ocean, whereas in the tropical and subtropical Atlantic Ocean there are some significant regions observed. Robertson and Mechoso (2000) found a similar pattern in SST anomalies over the western subtropical South Atlantic Ocean during summertime in relation to the 200 hpa winds over the same region. They also found no significant correlations with either El Niño SST anomalies or with North Atlantic SST. In SCSA, the regions of significant variability (Figure 4(b))are located in the northern and southern parts. The relationship is of the type WD/CW (correlation coefficient 0.88) with the tropical Atlantic Ocean, and of type WW/CD with the subtropical Atlantic Ocean.

6 420 G. J. BERRI AND G. I. BERTOSSA (a) 30N 25N 20N 15N 10N 5N EQ 5S 10S 15S 25S 35S 140E 160E W 140W 120W 100W 80W 60W 40W 20W 0 (b) 63W 63W Figure 4. (a) First canonical map (CCA mode 1) of January February SST anomalies of the oceans, period Shaded areas represent regions with statistically significant correlation coefficients at the 95% level; (b) as for (a), but for precipitation anomalies over SCSA. The period of analysis is Barros et al. (2000) studied the influence of the tropical South Atlantic Ocean on the precipitation over the entire continental region of South America, between 20 S and 40 S, which is a region more extended than SCSA, using a CCA analysis for the period December February. Despite the difference in the significance levels, Barros et al. (2000) found a WW/CD (WD/CW) relationship between the tropical Atlantic and the central and eastern (northwestern and southern) part of SCSA. The opposite relation between the northern region of SCSA and the tropical Atlantic Ocean may be related to the results found by Garreaud and Aceituno (2001) over the Altiplano (bordering to the northwest of our SCSA), who found that the interannual convective anomalies over the Altiplano tend to be out of phase with convective anomalies over the SACZ and the eastern side of the continent March April Large regions with significant variability can be observed over the eastern half of the tropical South Pacific Ocean and the tropical South Atlantic Ocean, including the subtropical sectors of both oceans near the continent (Figure 5(a)). The two regions have a WW/CD type of relationship (correlation coefficient 0.92) with the precipitation variability over the northeastern and southern parts of SCSA (Figure 5(b)). The same

7 OCEAN AND SOUTH AMERICAN PRECIPITATION VARIABILITY 421 relationship was found by Montecinos et al. (2000), for southern SCSA, by means of a PC analysis between tropical Pacific Ocean SST and precipitation over SESA. Another significant region is located over the tropical North Pacific Ocean (Figure 5(a)), which has a relationship with SCSA precipitation that is opposite, i.e. WD/CW, to that of the southern oceans May June The tropical Pacific Ocean (Figure 6(a)) shows a pattern of variability similar to that of March April, but more extended toward the west and also covering the tropical North Pacific. A dipole is clearly seen across the South Pacific convergence zone (SPCZ) between the eastern tropical Pacific and the subtropical central and western South Pacific. The tropical North Pacific Ocean shows a similar dipole, but over its western half. In the Atlantic Ocean, the significant region is the tropical South Atlantic and, to a minor degree, the tropical North Atlantic, whereas the equatorial Atlantic shows a weaker relationship. The influence of the tropical Pacific and Atlantic Oceans on the precipitation variability of northeastern SCSA is of the type WW/CD (correlation coefficient 0.94), as in the previous months (see Figure 6(b)). A similar relationship was found by Montecinos et al. (2000) between the tropical Pacific Ocean and the northeast and central-south of (a) 30N 25N 20N 15N 10N 5N EQ 5S 10S 15S 25S 35S 140E 160E w 140W 120W 100W 80W 60W 40W 20W 0 (b) 63W 56W Figure 5. As for Figure 4, but for March April

8 422 G. J. BERRI AND G. I. BERTOSSA (a) 30N 25N 20N 15N 10N 5N EQ 5S 10S 15S 25S 35S 140E 160E W 140W 120W 100W 80W 60W 40W 20W 0 (b) 63W 56W Figure 6. As for Figure 4, but for May June SCSA. The regions located on the east of SCSA now form a dipole with those in the northeastern and the central-southern part July August The regions with maximum variability that were found in previous months over the tropical Pacific Ocean are, during this period, displaced toward the Southern Hemisphere. Also, there is an intense dipole between the western and eastern halves of the tropical South Pacific (Figure 7(a)). The dipole over the tropical and subtropical North Pacific is now weak. The significant area over the tropical South Atlantic is displaced toward the east, and other regions with the same type of variability emerge over the subtropical North Atlantic Ocean. Over SCSA (Figure 7(b)), the regions that are significantly linked to the oceans are located along the western part, with a relationship of the type WW/CD (except with the western South Pacific, where the relationship is of the type WD/CW) (correlation coefficient = 0.87) September October The extended significant regions that were present over the tropical and equatorial Pacific during the previous periods have now disappeared (Figure 8(a)), with only some small regions remaining over the subtropical

9 OCEAN AND SOUTH AMERICAN PRECIPITATION VARIABILITY 423 (a) 30N 25N 20N 15N 10N 5N EQ 5S 10S 15S 25S 35S 140E 160E W 140W 120W 100W 80W 60W 40W 20W 0 (b) 63W 56W Figure 7. As for Figure 4, but for July August South Pacific Ocean. In the Atlantic Ocean, the eastern part of the equatorial region remains significant. The North Atlantic region diminishes in importance with respect to the previous period, and a dipole-like pattern emerges between the equatorial region and both the subtropical North and South Atlantic Ocean. Two regions with variability of opposite sign can be seen over SCSA (Figure 8(b)). Northwestern SCSA presents a WW/CD type of relationship (correlation coefficient = 0.95) with the South Pacific Ocean and the subtropical North and South Atlantic Ocean, and the opposite relationship (WD/CW) with the northwestern Pacific and the tropical Atlantic Oceans. The eastern part of SCSA shows a dipole with the northwestern part, and it is in phase with the equatorial Atlantic Ocean November December The last period of the year presents the most robust relationship between the SSTs and precipitation over a large portion of SCSA. Figure 9(a) clearly shows the presence of an extended dipole between the tropical and subtropical regions of the Pacific Ocean: a horseshoe pattern. The relationship is of the type WW/CD (WD/CW) (correlation coefficient = 0.93) between the tropical (subtropical) Pacific Ocean and SCSA (Figure 9(b)). This pattern was also found by Barros and Silvestri (2002) in their second mode of CCA during the period October December, and by Nogués-Paegle and Mo (2002) in the correlation between

10 424 G. J. BERRI AND G. I. BERTOSSA (a) 30N 25N 20N 15N 10N 5N EQ 5S 10S 15S 25S 35S 140E 160E W 140W 120W 100W 80W 60W 40W 20W 0 (b) 63W 56W Figure 8. As for Figure 4, but for September October their first rotated PC of precipitation and global SST anomalies during the period December February. The study of Montecinos et al. (2000), which was conducted over a larger portion of SESA, reveals that, for SCSA, this period of the year is the one with the strongest influence from the tropical Pacific Ocean. Over the Atlantic Ocean, the entire southern tropics and sectors of the northern tropics show a relationship of the type WW/CD with precipitation over SCSA, whereas the subtropical South Atlantic Ocean presents a dipole with the tropical region. The pattern of precipitation variability over almost the entire SCSA region is homogeneous, because the canonical map of Figure 9(b) shows the same sign over every significant region. 6. INFLUENCE OF THE TROPICAL PACIFIC OCEAN DURING THE SUMMER SEMESTER January February is a period of relative minimum influence of the tropical Pacific Ocean on precipitation over SCSA, whereas November December shows the strongest influence and March April also shows a significant influence. The tropical Atlantic Ocean also shows a rather weaker signal during January February, compared with the previous and following periods. This particular feature has been detected during situations of strong SST anomalies in the equatorial Pacific Ocean, when looking at precipitation anomalies and river flow anomalies over the region during ENSO events.

11 OCEAN AND SOUTH AMERICAN PRECIPITATION VARIABILITY 425 (a) 30N 25N 20N 15N 10N 5N EQ 5S 10S 15S 25S 35S 140E 160E W 140W 120W 100W 80W 60W 40W 20W 0 (b) 63W 56W Figure 9. As for Figure 4, but for November December Pisciottano et al. (1994) studied the relationship between ENSO and rainfall over Uruguay (over the east of SCSA), and found that there are no significant rainfall anomalies during February after the year of onset of El Niño. Berri et al. (2002a) present composites of monthly precipitation anomalies over the southeastern part of SCSA (57 63 W, S; see box in Figure 10), during La Niña (Figure 11(a)) and El Niño (Figure 11(b)) events of the period During the period October April of El Niño (La Niña), the percentage of precipitation observations in the upper tercile is larger (smaller) than that in the lower tercile. This situation reveals a relationship of the type WW/CD. In the case of La Niña events (Figure 11(a)), the WW/CDtype relationship is more marked than that during El Niño events (Figure 11(b)). In particular, the La Niña composite clearly shows the January and February relative minimum, between the strong November and December and the rather weaker March and April signal. As mentioned above, a similar behaviour is displayed by the Paraná River flows, which is the main tributary of the La Plata River. Figure 10 shows the Paraná River basin, which extends upstream of the city of Posadas (27 23 S, W), over the northeast of the SCSA box. The monthly river flows measured at Posadas are used to create anomaly composites during the ENSO events of the past 100 years (Berri et al., 2002b), which are shown in Figure 12. From October until April the river flows are above average during El Niño events

12 426 G. J. BERRI AND G. I. BERTOSSA 17 S Brazil Paraguay Parana River Basin Argentina Posadas Posadas South- Eastern SCSA Uruguay Ur Atlantic Ocean 43 S 73 W 39 W Figure 10. Rectangular box for the spatial average of SCSA precipitation, and Paraná River basin upstream of the city of Posadas (a) % of Area Jul Aug Sep Oct Nov Dec Upper tercile Jan Feb Mar Apr May Lower tercile Jun (b) % of Area Jul Aug Sep Oct Nov Dec Upper tercile Jan Feb Mar Apr May Jun Lower tercile Figure 11. (a) Percentage of the area over southeastern SCSA (57 63 W, S) with precipitation excess (upper tercile) and precipitation deficit (lower tercile), averaged over seven La Niña events in the period , from the mid part of the year of onset until the mid part of the following year (after Berri et al. (2002a)). (b) As for (a), but average of 11 El Niño events during (after Berri et al. (2002a)) and they are below average during La Niña events, confirming a relationship of the type WW/CD. The largest difference between El Niño and La Niña flows is during November and December of the year of onset; from February to April of the following year the difference is also present, but to a lesser degree. Clearly, the difference in the flows during January is totally suppressed. This result again confirms a minimum of the influence, in this case of the tropical Pacific Ocean, on precipitation over the region in the middle of the summer semester. 7. REGIONAL SST INFLUENCE ON SCSA PRECIPITATION CCA is an appropriate tool to explore the relationship between two sets of variables. However, the simultaneous presence of several significant oceanic regions, as revealed by the canonical maps, makes it difficult to determine which specific regions of the oceans have more influence on precipitation over particular subregions in SCSA. For example, Figure 9(a) (c) tells us that both the tropical Atlantic and the tropical Pacific Oceans have a significant influence on precipitation variability over most of SCSA during

13 OCEAN AND SOUTH AMERICAN PRECIPITATION VARIABILITY Mean monthly anomalies (m 3 /s) Jul(0) Aug(0) Sep(0) Oct(0) Nov(0) Dec(0) Jan(1) Feb(1) Mar(1) Apr(1) May(1) Jun(1) El Niño La Niña Figure 12. Composite of Paraná River flows at Posadas (27 23 S, W, on the upper right corner of the box in Figure 1) during the ENSO events of the period : El Niño years, full line; La Niña years, dashed line. The index (0) indicates the year when the event begins and (1) the year when the event ends (after Berri et al. (2002b)) November December. However, these figures cannot answer, for example, such simple questions as: Does the equatorial Pacific Ocean have more influence than the tropical South Atlantic Ocean on the precipitation anomalies over the northeastern part of SCSA? Is the precipitation variability over southeastern SCSA equally influenced by all shaded regions of the tropical oceans? The answers to these questions are important to understanding the mechanisms through which the surrounding oceans influence the precipitation variability over SCSA. In other words, given a particular subregion of SCSA, it is not possible from the maps to determine the relative importance of individual oceanic regions. All we know is that the entire spatial pattern of the SSTs is associated with the entire spatial pattern of SCSA precipitation. In this section we study the relative importance of different selected oceanic regions on the precipitation variability in different subregions of SCSA. For this purpose we identify 11 oceanic regions, displayed in Figure 13, and 10 continental regions over SCSA, displayed in Figure 14. The regions were selected by considering all shaded areas on the canonical maps corresponding to CCA mode 1 and mode 2 (not shown). However, the regions sketched with these two modes were checked with the canonical maps of higher modes, and no relevant differences were found. The criteria for delimiting the regions are: (i) the region must display statistically significant correlation coefficients; and (ii) the correlation coefficient must be homogeneous (either positive or negative) everywhere in the region. Then, the spatial average of SST and precipitation is calculated in every region. In the case of the oceans, the shape of the region was approximated to a rectangle or a combination of two rectangles in order to facilitate the data handling to calculate the spatial average. In the case of SCSA, the spatial precipitation average was calculated by simply adding all station values regardless of the distribution within the box. Finally, we calculated the linear correlations between each individual time series of precipitation and the time series of SST in every oceanic region. The calculations were carried on for the six 2 month periods, shown in Tables I to IV for November December, May June, March April, July August respectively (January February and September October show no significant results). The set of tables shows the correlation coefficients only when they are statistically significant at at least the 95% level. Only the two periods that show stronger relationships with the oceans are analysed in more detail. In order to facilitate the interpretation, the results are summarized in Figures 15 and 16, for November December and May June respectively, only for the regions with significant correlation.

14 428 G. J. BERRI AND G. I. BERTOSSA 30N 25N 20N 15N 10N 5N EQ 5S 10S 15S 25S 35S NA NWP N 3 EA N 3.4 TP S E TSA SWP P SP SA 164E 147W 98W 49W 0 Figure 13. Oceanic regions for spatial SST averages NW 2 NW 1 NE C3 C2 E1 C1 E2 S SE 70W 63W 56W 49W Figure 14. SCSA regions for spatial precipitation averages 8. THE NOVEMBER DECEMBER PERIOD For every box in SCSA, Figure 15 and Table I indicate the name of the oceanic region where the SSTs are significantly correlated with the precipitation over that box in SCSA, meaning that the signal is strongest over that box and decays as we move away. The first aspect to highlight is that there are always two or more oceanic regions influencing every SCSA region. The boxes over the tropical Pacific Ocean (Niño3 and Niño3.4) and the subtropical Pacific Ocean (SWP, SEP, and SP) are the regions that have influence over most of the SCSA regions. As was pointed out in Section 5, the results of Montecinos et al. (2000) also show that this period is the one with the most significant influence of the tropical Pacific Ocean on SCSA. The northwest Pacific box (NWP) does not show any direct influence on SCSA. The Atlantic Ocean shows less influence over SCSA than the Pacific Ocean. Curiously, the north Atlantic box (NA) affects three boxes in

15 OCEAN AND SOUTH AMERICAN PRECIPITATION VARIABILITY 429 Table I. Correlation coefficient between the spatial SST average of every oceanic region (see Figure 13 for details) and the spatial precipitation average of every SCSA box (see Figure 14 for details) during November December of the period Numbers in bold indicate that the correlation coefficient is statistically significant at the 99% level; otherwise, the level of significance is 95% Niño3 TP SP SWP NWP SA TSA EA NA SEP Niño3.4 NE E E SE S C C C NW NW Table II. As for Table I, but for May June Niño3 TP SP SWP NWP SA TSA EA NA SEP Niño3.4 NE E E2 SE S C1 C2 C NW1 NW2 Table III. As for Table I, but for March April Niño3 TP SP SWP NWP SA TSA EA NA SEP Niño3.4 NE 0.35 E E SE S C C2 C3 NW1 NW SCSA, whereas the equatorial (EA) and South Atlantic boxes (SA, TSA) affect only one. The relationship with both the Pacific and the Atlantic Oceans is of the type WW/CD for the equatorial and tropical regions, and of type WD/CW for the subtropical regions. It is interesting to note that the influence of the Atlantic regions is only over the southeastern boxes and the extreme northwestern box of SCSA.

16 430 G. J. BERRI AND G. I. BERTOSSA Table IV. As for Table I, but for July August Niño3 TP SP SWP NWP SA TSA EA NA SEP Niño3.4 NE E1 E2 SE 0.39 S C1 C2 C3 NW1 NW N 3 N 3.4 TP SEP NA SWP N 3 N 3.4 TP SEP SP SWP N 3 N 3.4 TP SEP TP SEP SP SWP SWP SP SWP N 3.4 TP SEP NA N 3.4 SWP N 3 N 3.4 TP SP N 3 N 3.4 TP SEP SWP SP SWP TP NA N 3 N 3.4 SA TSA EA SWP 70W 63W 56W 49W Figure 15. Summary of regional SST influence on regional SCSA precipitation during November December. The name of an oceanic region (see Figure 13 for details) on a particular SCSA box (see Figure 14 for details) indicates that there is a statistically significant correlation coefficient (95% level) between the spatial SST average and the spatial precipitation average. When the correlation coefficient is positive (negative) the name of the oceanic region is printed in normal font (underlined italic font). The period of analysis is The remote influence of the equatorial Pacific Ocean may be related to the subtropical jet over South America. Antico and Berri (2000) found that, during the period September November , the monthly mean speed of the subtropical jet intensifies when the SSTs in the equatorial Pacific show large positive anomalies, and its mean latitudinal position tends to be anchored at around 30 S. In this respect, Grimm et al. (1998) connected the wet anomalies during the spring of warm ENSO events in southern Brazil to the intensification of mesoscale convective complexes due to the strengthening of the subtropical jet over the region.

17 OCEAN AND SOUTH AMERICAN PRECIPITATION VARIABILITY 431 N 3 N 3 N 3.4 TP SEP SA TSA SP SWP, EA N 3 N 3.4 TP SWP 70W 63W 56W 49W Figure 16. As for Figure 15, but for May June In November December, the Atlantic Ocean has a significant influence over the southern and southeastern parts of SCSA due to the enhanced water vapour advection into eastern Argentina. Grimm et al. (2000) indicate that, during warm ENSO events, the easterly component of the near-surface flow is enhanced over central Argentina due to the southward shift of the South Atlantic high. In this sense, the canonical maps of Figure 9 show a direct association with the SST anomalies in the equatorial Pacific Ocean and the tropical Atlantic Ocean, so warmer (colder) waters in TSA and EA should yield an increase (decrease) of water vapour advection and, consequently, more (less) precipitation over the southeastern SCSA. CCA mode 2 (Figure 17(a)) for November December indicates that negative (positive) SST anomalies over the western South Atlantic, offshore South America, are related to less (more) precipitation over most of the SCSA (Figure 17(b)), except for the northeast, which shows a reversed signal. Barros et al. (2000) find that, in summertime, a cold (warm) SST over a similar Atlantic region (20 40 S, to the west of 30 W) is likely to be accompanied by the strengthening (weakening) of the SACZ. This is in agreement with the results of Nogués-Paegle and Mo (1997), who found that the strengthening of the SACZ is associated with less precipitation over the subtropical plains of South America during summer. Simultaneously, these negative SST anomalies are associated with positive precipitation anomalies over the northeastern part of SCSA (Figure 17(b)). This last result is in agreement with Carvalho et al. (2002), who found that approximately two-thirds of all extreme precipitation events over the state of São Paulo (to the northeast of our SCSA region) occur when the convective activity in the SACZ is extensive and intense. It is also in agreement with Robertson and Mechoso (2000), who found significant variations in summertime river flows, i.e. enhanced flows to the north (Paraná and Paraguay Rivers) and diminished flows to the south (Uruguay and Negro Rivers), associated with an intensified SACZ. The influence of the tropical North Atlantic (NA) region and the equatorial Atlantic (EA) region on several SCSA regions (NW2, E2 and C1; see Figure 14 for details) may be explained by different mechanisms that are part of the summer monsoon circulation discussed by Zhou and Lau (1998). One of these mechanisms is the anomalous water vapour influx into the South American continent that is strongly related to the SST anomalies in the tropical North Atlantic Ocean. Wang and Fu (2002) identified a cross-equatorial flow in the northern part of South America that, in the austral summer, allows for the water vapour transport from tropical

18 432 G. J. BERRI AND G. I. BERTOSSA (a) 30N 25N 20N 15N 10N 5N EQ 5S 10S 15S 25S 35S 140E 160E W 140W 120W 100W 80W 60W 40W 20W 0 (b) 63W 56W Figure 17. As for Figure 4, but for CCA mode 2 for the period November December latitudes of the Northern Hemisphere into subtropical regions of the southern continent. The low-level jet to the east of the Andes mountains (discussed in detail by Paegle (1998) and Nogués-Paegle and Mo (1997)) becomes much stronger in this northerly regime, establishing moisture corridors that fuel precipitation in subtropical and midlatitudes of South America. 9. THE MAY JUNE PERIOD In May June (Figure 16 and Table II), the SCSA regions that have a significant relationship with the tropical oceans are less than for November December. It is worth mentioning that the influence of the Atlantic Ocean is only over the northeastern part of SCSA. During May June, the SST influence, in particular from the equatorial Pacific Ocean, is concentrated in the northeastern, central-eastern and southeastern parts of SCSA, with an isolated box in the central part of SCSA that is influenced by the Niño3 region. These results are in agreement with those found by Montecinos et al. (2000). Gan and Rao (1991) seem to support our results, since they found higher (lower) cyclogenesis over southern Brazil during warm (cold) ENSO events, and they mention the month of May as the one that presents the maximum frequency of cyclogenesis.

19 OCEAN AND SOUTH AMERICAN PRECIPITATION VARIABILITY 433 The dipole in the Pacific Ocean revealed by our analysis (Figure 6(a)) may be related to the Pacific South American pattern described by Mo and Higgins (1998), who analysed the evolution of the leading lowfrequency modes of variability in the Southern Hemisphere and their linkage to tropical convection in winter. They found that one mode is linked to tropical heating anomalies in the central Pacific, extending from 160 E to 150 W just south of the equator (where we find a positive correlation with SST anomalies), and suppressed convection in the western Pacific with maximum outgoing longwave radiation anomalies at 20 N (where we find a negative correlation with SST anomalies). Tropical convection in this region generates eastward and poleward-moving wave trains that are more variable during the winter of the Southern Hemisphere (Karoly, 1989). This could be one of the mechanisms responsible for the influence of the Pacific Ocean dipole over the SE box (southeastern SCSA), as shown in Figure CONCLUSIONS An analysis is conducted of the relationship between the SST variability of the tropical and subtropical Atlantic and Pacific Oceans and the precipitation variability over SCSA, during the period and on a bi-monthly averaged basis. The analysis is carried out by means of a CCA of the simultaneous standardized anomalies of SST and precipitation, after applying a prefiltering by means of an EOF analysis and retaining the minimum number of EOF modes that explain at least 80% of the variance of both variables. The result of the analysis reveals that March April, May June, July August and November December are the periods with a clearer influence of the oceans over SCSA precipitation. This conclusion is based on the extension and homogeneity of the oceanic regions whose SST variability is significantly correlated with regional precipitation variability over SCSA. November December is the period with the most robust pattern of simultaneous association between the variability of the tropical ocean SSTs and precipitation over SCSA. The relationship is of the type WW/CD everywhere in the equatorial and tropical regions of the North and South Atlantic Oceans and also of the tropical central and eastern Pacific Ocean. The SSTs in the Pacific Ocean during November December display a typical horseshoe-type ENSO pattern with a well-defined dipole across the SPCZ between the tropics and the subtropics. The SSTs in the South Atlantic Ocean during November December also show a dipole-type structure across the SACZ. During January February, the influence of the tropical Pacific Ocean vanishes and the regions with significant correlation in the Atlantic Ocean are small and dispersed, and relevant near the mean position of the SACZ. The northern and southern parts of SCSA show a relationship of the type WD/CW with the tropical Atlantic Ocean, and of type WW/CD with the subtropical Atlantic Ocean. During March April, the oceanic influence on SCSA precipitation reappears, especially from the tropical Pacific, and the SST pattern of variability is similar to that of November December, i.e. WW/CD over the northeastern and southern parts of SCSA, although it is less robust. This result suggests that precipitation variability over SCSA during the summertime peak in January February is more dependent on local instabilities than on tropical ocean influences, whereas the latter seem to be more important at the beginning (November December) and the end (March April) of the summer semester. This singularity is also clearly detected during conditions of extreme SST anomalies, as revealed by composite analyses of both the Paraná River flows during the month of January of the peak of ENSO events in the period and the averaged regional precipitation anomalies over the central-eastern part of SCSA during the ENSO events of the period The SST pattern during May June, and to a lesser degree July August, is similar to that of the previous periods, although the significant oceanic regions are less extended. In particular, the SSTs during May June clearly show the SPCZ. During these two periods, the regions over SCSA that show significant correlation with the SSTs are small and dispersed. In particular, during July August, the oceanic influence over SCSA precipitation concentrates over the western half of the region. The SST pattern during September October is similar to that of January February, i.e. a limited influence of the tropical Atlantic Ocean and no clear influence of the tropical Pacific Ocean. During March April, May June, July August and, particularly, November December, the SSTs over the tropical Atlantic and Pacific Oceans show an in-phase type of relationship with the precipitation variability

20 434 G. J. BERRI AND G. I. BERTOSSA over SCSA, i.e. both oceans present simultaneously extended regions with either positive or negative SST anomalies. In order to identify the influence of the different oceanic regions on the SCSA precipitation, we identify a total of 11 oceanic regions and 10 SCSA regions from the patterns of the canonical maps of CCA modes 1 and 2. Regional averages of SST and precipitation are calculated over these regions and linear correlation analyses are conducted between individual time series of precipitation and SST. The analysis of results focuses on the two periods with a greater association between the oceans and SCSA precipitation, i.e. November December and May June. During November December, every selected region over SCSA reflects the influence of several oceanic regions. The Atlantic Ocean has a lesser influence over SCSA precipitation than does the Pacific Ocean. The tropical Pacific (Niño3 and Niño3.4) and the subtropical Pacific regions (SWP, SEP, SP) are those with a greater influence over most of the SCSA regions. The North Atlantic (NA) region has an influence on the extreme northwest and southeast of SCSA, and the other two Atlantic regions influence (SA, TSA) is only over the southeast. The relationship with both the Pacific and the Atlantic Oceans is of the type WW/CD for the equatorial and tropical regions, and of type WD/CW for the subtropical regions. During May June, the oceanic influence over SCSA precipitation is considerably less extended, and only a few regions show a direct association with the oceans. These regions are over the northeast (both the Atlantic and Pacific Oceans), the southeast (only the Pacific Ocean), and an isolated region in the central part of SCSA (Niño3). The northwest Pacific (NWP) is the only oceanic region that does not show any direct influence during these two periods, and its presence is only detected during March April over the south of SCSA. ACKNOWLEDGEMENTS Thanks to Alvaro Diaz, Universidad de la República, Uruguay, for useful discussions and to the anonymous reviewers who contributed to improving this paper. Thanks also to the National Meteorological Services of Argentina, Brazil, Paraguay and Uruguay for providing the data. This research was partially supported by research grant PIP-0389/98 from Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) of Argentina, research grant PICT from Agencia Nacional de Promoción Científica y Tecnológica (ANPCyT) of Argentina, and Ubacyt 2001/2002 X126 from Universidad de Buenos Aires, Argentina. REFERENCES Antico PA, Berri GJ The subtropical jet stream over South America. In Preprints XI Brazilian Congress of Meteorology, Rio de Janeiro, Brazil. Barnett TP, Preisendorfer RW Origins and levels of monthly and seasonal forecast skill for United States surface air temperatures determined by canonical correlations analysis. Monthly Weather Review 115: Barnos V, Silvestri G The relation between sea surface temperature at the subtropical South-Central Pacific and precipitation in southeastern South America. Journal of Climate 15: Barros V, González M, Liebmann B, Camilloni I Influence of the South Atlantic convergence zone and South Atlantic sea surface temperature on interannual summer rainfall variability in southeastern South America. Theoretical and Applied Climatology 67: Berri GJ, Flamenco EA, Spescha L, Tanco RA, Hurtado R. 2002a. Some effects of La Niña on summer rainfall, water resources and crops in Argentina. In La Niña and its Societal Impacts: Facts and Speculation, Glantz MH (ed.). United Nations University Press. Berri GJ, Ghietto MA, Garcia NO. 2002b. The influence of ENSO in the flows of the Upper Paraná River of South America over the past 100 years. Journal of Hydrometeorology 3: Carvalho LM, Jones C, Liebmann B Extreme precipitation events in southeastern South America and large-scale convective patterns in the South Atlantic convergence zone. Journal of Climate 15: Díaz AF, Studzinski CD, Mechoso CR Relationships between precipitation anomalies in Uruguay and southern Brazil and sea surface temperature in the Pacific and Atlantic Oceans. Journal of Climate 11: Gan MA, Rao V Surface cyclogenesis over South America. Monthly Weather Review 119: Garreaud RD, Aceituno P Interannual rainfall variability over the South American Altiplano. Journal of Climate 14: Grimm AM, Feraz SET, Gomes J Precipitation anomalies in southern Brazil associated with El Niño and La Niña events. Journal of Climate 11: Grimm AM, Barros VR, Doyle ME Climate variability in southern South America associated with El Niño and La Niña events. Journal of Climate 13: Karoly D Southern Hemisphere circulation features associated with El Niño southern oscillation events. Journal of Climate 2:

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