Abstract

A comprehensive view is given of the precipitation and circulation anomalies associated with the various stages of El Niño (EN) and La Niña (LN) events all over southern South America (SSA). This view comprises the delineation of coherent regions with respect to precipitation anomalies, the identification of the seasons of maximum anomalies, the indication of their magnitude, and the assessment of their consistency during those events. In addition, the spatial and temporal variability of these anomalies is detailed by calculating the expected precipitation percentiles and the consistency of wet and dry anomalies for each station and each three-month running season during EN and LN events. Composites of circulation anomalies and an assessment of their consistency are also presented and their connection with the precipitation anomalies is discussed.

Southern Brazil presents the strongest average signal in EN events. The general behavior toward opposite signals in the precipitation and circulation anomalies over SSA during almost the same periods of the EN and LN events indicates a large degree of linearity in the response to these events. The timing of the anomalies changes throughout SSA, leading to the identification of eight different coherent regions in the EN case and six in the LN case. This regionalization is mostly caused by different processes leading to precipitation anomalies in SSA during those events. All these regions show a significant response in some part of each event. The magnitude and consistency of this response show a large spatial variability and some areas present very strong and consistent anomalies sometimes not disclosed when large coherent regions are analyzed. In spite of the differences in timing, some features of the precipitation anomalies are rather uniform throughout the region during EN and LN events. In EN episode, there is a tendency to lower than median precipitation in the year before the event, which continues until March of the year of the event. In a vast region, east of the Andes, the strongest positive precipitation anomalies occur in spring of this year, when the circulation anomalies concur to enhance rainfall over several regions. During the summer of the mature stage the positive precipitation anomalies almost disappear and then reappear in some regions in late summer–early autumn and in winter of the year following the starting year of the event. This description holds partially for the LN event, but with opposite signs, although there is a larger spatial variability in the LN-related anomalies in the following year and some shifts in timing. As for precipitation, the symmetry of the geopotential height anomaly fields with opposite signs between LN and EN cases is also remarkable, especially during the year (0).

1. Introduction

Southern South America (SSA; which comprises southern Brazil, Argentina, Chile, Uruguay, and Paraguay) is one of the extratropical regions most affected by El Niño (EN) and La Niña (LN) events. In fact, several areas in SSA have been reported as presenting strong interannual precipitation variability associated with these events. The areas most frequently referred to are southern Brazil, northeastern Argentina, Uruguay, and Chile (e.g., Ropelewski and Halpert 1987, 1989, hereafter RH87 and RH89; Kiladis and Diaz 1989; Aceituno 1988; Rutllant and Fuenzalida 1991; Pisciottano et al. 1994; Grimm et al. 1998). The relationship between sea surface temperature (SST) anomalies in the Pacific region affected by EN and LN events and precipitation anomalies in SSA has been demonstrated in some studies (e.g., Grimm 1996a; Diaz et al. 1998).

Previous studies on EN–LN-related rainfall anomalies in SSA have given valuable insights into several aspects of the impact of these events on SSA, as well as detailed descriptions of this impact on certain regions. Some of their conclusions will be reviewed in the next section. However, shortage of data or data gaps in certain regions, differences in methodology, and the regional focus of some studies hamper the formation of a more general panel of the EN–LN impact on SSA. In this study we propose, on the basis of an ample dataset, to give an overall view of precipitation anomalies associated with the various stages of EN and LN events all over SSA, and to associate them with circulation anomalies produced in these events. The intention is to complement those previous studies by extending the data coverage, the resolution in time, and the period of analysis within the cycle of these events.

It is worth mentioning that, in spite of the differences between various EN (LN) episodes, the similarities between them make possible the occurrence of consistent anomalies that are worth exploring for climate prediction purposes. This study is focused on these significant common features.

The first part of the study comprises the identification of the coherent regions with respect to precipitation anomalies and, in these regions, the indication of their magnitude and the assessment of their consistency. In the second part, the spatial and temporal variability of these anomalies is detailed, and a characterization of the anomalous circulation fields (and corresponding atmospheric processes) associated with those precipitation anomalies is presented. This characterization is an important step toward the understanding of the dynamical mechanisms that lead to those precipitation anomalies.

In order to give an overview of the existing studies and allow comparisons later on, we start, in section 2, with a summary of the results that are more relevant to this study. Section 3 describes the data and some features of the climate of SSA. Section 4 outlines the methodology. The results from the analysis of coherent regions with respect to the precipitation anomalies are presented and discussed in section 5a, and in section 5b the results of the detailed analysis of the precipitation anomalies are presented and related to the circulation anomalies. In section 6 the coherent regions are explained in terms of the atmospheric processes associated with the circulation anomalies. A summary and concluding remarks are presented in section 7.

2. Results of some previous studies

Studies devoted to a global view of climatic anomalies associated with the Southern Oscillation (SO) have always included areas in SSA as having consistent relationship between precipitation anomalies and the extreme phases of the SO. RH87 identified an area in this region, comprising northeastern Argentina, Uruguay, and part of southern Brazil, in which precipitation anomalies are consistently positive from November of the warm event year (EN) through February of the following year. RH89 concluded that in this same area there are consistent negative anomalies from July through December of cold event years (LN). RH87 found a relatively low coherence for this SSA region, which indicates that in this region there are different timings for the precipitation anomalies associated with an EN cycle. The EOF analysis of annual precipitation by Lau and Sheu (1988) indicated that warm event years are associated with wet conditions in SSA. According to Kiladis and Diaz (1989), the difference between rainfall in warm and cold events is significant in several areas of SSA during some seasons of the extreme events years, mainly July through August in the southernmost part and September through November in the northernmost part.

Besides these global studies, regional studies of the climatic effects of the SO have focused on South America and particularly on SSA. Aceituno (1988) studied the effects on surface climate and found significant negative correlation between the SO index (SOI) and rainfall over most of SSA during November–December and over Chile mainly during July–August and September–October.

For Uruguay, using long records of data from a dense network of stations, Pisciottano et al. (1994) found a significant impact of SO on rainfall. There is significant tendency to above-average precipitation from November of the warm event year through the next January, particularly in the northern and western parts, and from March through July of the following year in the northern part. They also found a significant tendency for below-average precipitation all over Uruguay from October through December of cold events and from March through July of the year following a cold event.

Rao and Hada (1990) calculated correlation coefficients between the SOI and monthly rainfall amounts of stations all over Brazil (33 in southern Brazil), containing from 15 to 21 years of data (1958–78). In southern Brazil, they found significant values only in the southernmost part and only for the austral spring. In order to verify whether other parts of southern Brazil also show rainfall anomalies associated with warm and cold episodes and if there is also impact in another period, Grimm et al. (1998) investigated this impact using a denser network of stations. This study disclosed not only strong and consistent positive anomalies in the spring of EN years all over southern Brazil, but also in the winter of the following year over some areas. Even stronger and more consistent negative anomalies were disclosed in the spring of LN years.

The integrated analysis of precipitation and circulation EN (LN)-related anomalies over SSA has not been frequent, since most of the research has been focused on precipitation anomalies. Although some studies seek for the dynamical links between EN-related circulation anomalies that affect SSA and EN-related heat sources in the Pacific (e.g., Grimm and Silva Dias 1995; Grimm 1996b), they do not detail those circulation anomalies. Notwithstanding, there has been some previous work on circulation anomalies (e.g., Karoly 1989; Aceituno 1989; Barros and Scasso 1994), and relating rainfall and circulation anomalies in specific regions of SSA (e.g., Rutllant and Fuenzalida 1991; Grimm et al. 1998).

Aceituno (1989) concluded that during the austral winter semester (April–October) in the negative SO phase (EN) relatively cold surface conditions and negative surface, 850-, 500-, and 200-hPa height anomalies develop in the southernmost part of SSA. On the other hand, there are warm conditions and a weak tendency for positive height departures at 500 and 200 hPa over the tropical Americas. There are negative departures in the surface pressure and 850 hPa, reflecting the weakened Pacific subtropical high. The meridional height gradient is enhanced, and so are the upper-air westerlies over the Southern Hemisphere subtropics. Yet during the austral summer semester (November–April) negative correlations prevail over SSA, suggesting weak SO-related anomalies in the meridional height gradient.

Rutllant and Fuenzalida (1991) disclosed synoptic aspects associated with major winter storms in central Chile during warm events. They found a dipole-like barotropic anomaly structure with anticyclonic anomalies southwest of the southern edge of South America and cyclonic ones to the southeast. The cyclonic anomaly extends northwestward over SSA up to an anomalous low in the subtropical eastern Pacific, off the coast of Chile. There is a well-developed Atlantic subtropical anticyclone to the northeast.

According to Barros and Scasso (1994), surface pressure is significantly lower and temperature higher over subtropical Argentina during the negative phase of the SO, with the exception of the summer months. The strongest signal in pressure is in the west and center of Argentina, enhancing the semipermanent low there, especially in winter.

Grimm et al. (1998) connected the wet anomalies during the spring of EN years in southern Brazil to the intensification of mesoscale convective complexes in this region, due to the strengthening of the subtropical jet over the region during EN events. Furthermore, these wet anomalies are also associated with an anomalous cyclonic circulation west of SSA and an anticyclonic anomaly to the east, in the subtropics. These features favor baroclinic developments and are conducive to anomalous rainfall over southern Brazil. An approximately reversed situation is revealed in LN events.

3. Data and climatic aspects

a. Data

The precipitation data used in this study are monthly amounts of 134 selected stations from Argentina, Brazil, Chile, Uruguay, and Paraguay, for the period 1956–92. The database for the circulation analysis is the National Centers for Environmental Prediction–National Center for Atmospheric Research reanalysis for the period 1963–92, because many of the raob series in the region started after 1963.

The years of EN and LN episodes included in this study were chosen following the same criteria as in Grimm et al. (1998) and indicate the beginning of the episodes (Table 1). In the case of two consecutive LN years, only the first year is used in the composites as a starting year of the episode (i.e., 1970).

Table 1.

List of El Niño and La Niña episodes included in this study.

List of El Niño and La Niña episodes included in this study.
List of El Niño and La Niña episodes included in this study.

b. Climatic aspects

North of 40°S, the near-surface circulation over SSA is dominated by the quasi-stationary highs of the South Pacific (west of the Andes) and the South Atlantic (east of the Andes). Most of the time, there is a low pressure center in the central–western part of Argentina and southern part of Bolivia, known as west low (WL), originated by the interaction of the Andes, upper-level westerlies, and surface heating (Lichtenstein 1982). This WL deepens before the passage of cold fronts and disappears one or two days afterward. It is a warm system, less intense in winter, affecting only the lower troposphere (up to 700 hPa) and frequently accompanied by subsidence. South of 40°S the intense and persistent westerly low-level flow is perturbed by midlatitude systems that occasionally bring easterly flow into the continent. Polar front eruptions are less frequent in summer, when the fronts remain more to the south.

The annual cycle of precipitation in central Chile, in the Andes region, and immediately to the east of the higher mountains in northern Patagonia is conditioned by the seasonal south–north displacement of the South Pacific high, with a maximum in winter and a minimum in summer (Fig. 1).

Fig. 1.

Precipitation regimes of southern South America.

Fig. 1.

Precipitation regimes of southern South America.

East of the Andes, there are only two possible sources of water vapor in SSA: the Atlantic Ocean and the South American tropical forest (Wang and Paegle 1996). This has an important effect on the annual cycle of precipitation. In winter, there is little chance of water vapor supply from the Atlantic, since the westerly flow reaches lower latitudes. On the other hand, relatively dry conditions prevail in the tropical forest. Thus, except on the Atlantic coastal region, the winter is dry. In the western part of the subtropical region a pronounced annual cycle with a maximum in summer prevails, when both the surface heating and the northerly water vapor advection favor the convection. In the east, the water vapor is available throughout the year, but the stronger baroclinic conditions of winter and spring favor a relative maximum in this season. Actually, all over the eastern part of the region, precipitation occurs all through the year and in fact the interannual variance is greater than that associated with the annual cycle (Gonzalez and Barros 1997).

Southern Brazil is a region of transition between two adjacent regimes: summer monsoon and midlatitude winter conditions, which are responsible for the peak rainy seasons in January (in the northern part) and July (in the southeastern part), respectively. There is also a region, in west southern Brazil, where the bimodal variation prevails, with wet seasons occurring in March–April and September–October. These features are also noticed in Paraguay and eastern Argentina and may be due to the seasonal change of the upper-tropospheric subtropical jet, which may intensify the mesoscale convective complexes in this region (Velasco and Fritsch 1987).

4. Methodology

In order to allow a subsequent comparison of the results with those of RH87, RH89, Pisciottano et al. (1994), and Grimm et al. (1998), the methodology of the first part of the analysis is based on RH87 and is summarized below. The first three steps analyze the spatial structure of the rainfall anomalies associated with EN and LN events, besides giving a first estimation of their magnitudes. Some questions related to this methodology are discussed in Grimm et al. (1998).

  1. At each station, the monthly precipitation data are represented as percentile ranks. The EN and LN composites of the percentile ranked precipitation are formed for the 24-month period from July of the year before [July (−)] to June of the year after an episode [June (+)].

  2. The first Fourier harmonic of each composite is represented as a vector. The phase of the vector refers to the maximum (minimum) of the first harmonic for EN (LN) episodes.

  3. Regions of spatially coherent EN (LN)-related rainfall anomalies are selected through the maximization of an index of coherence, given by the ratio between the magnitude of the vector sum and the sum of the magnitudes of the vectors for all stations in a region.

The timing and consistency of the anomalies in each of the coherent regions are examined through the following steps.

 4. Monthly rainfall amounts for each station are transformed into precipitation percentiles based on gamma distributions fitted to the data of each month. As the time series for some stations contain several zeros (for instance, in northern Chile), a correction is introduced in the gamma distribution. In this case, a mixed distribution function of zeros and continuous precipitation amounts is employed, as suggested by Thom (1966). This is given by

 
H(x) = q + pG(x),

where q is the probability of a zero and p = 1 − q. Thus, when x = 0, H(0) = q. If m is the number of zeros in a climatological series of n terms, q may be estimated by

 
formula

 5. The EN (LN) composites are formed from the precipitation percentiles for each station for the 36-month period from January (−) to December (+) and averaged to form an EN (LN) “aggregate” composite for each coherent region. If q > 0.50 but the composite rainfall is zero, then the percentile 50 will be used, to avoid the zeros pulling up the values of the percentiles, giving the false impression that there are wet anomalies. The aggregate composite is used to identify the seasons with the largest anomalies. The period was extended in order to allow the detection of anomalies out of the biennia July (−) to June (+). Possible implications of using a 36-month period are discussed in Grimm et al. (1998).

 6. The statistical significance of the relationship between EN and LN events and rainfall anomalies is assessed for running seasons of three months. The hypothesis is tested that these periods are especially wet (rainfall above the median) or especially dry (rainfall below the median) during these episodes, by using the hypergeometric distribution. It gives the probability of obtaining d dry (wet) episodes in t trials from a population of n1 dry and n2 wet samples. This test is very robust to skewness, as is desirable for a parameter such as monthly rainfall. To test the consistency of the relationship EN–wet (dry) conditions of a population that contains t EN episodes and d (w) of them are dry (wet), the probability of obtaining more than d (w) dry (wet) cases in a sample of t episodes taken at random from this population is computed [i.e., the cumulative probability of obtaining d + 1, d + 2, . . . , (w + 1, w + 2, . . . ), up to t dry (wet) cases]. This will give the significance level of this relationship.

Although the previous methodology allows an overall view of the magnitude and timing of the EN and LN influence on the precipitation over SSA, it does not give a detailed spatial and temporal description of the precipitation anomalies in each stage of these events. The coherent regions have common characteristics with respect to the timing and sign of the anomalies, but may show a large spatial variability with respect to their magnitude and consistency. In order to detail better the spatial and temporal variability for the second part of the analysis, the EN- and LN-related median precipitation is calculated for each station and each running trimester, from May (0) through August (+), and expressed as a percentile value of the entire period gamma distribution. This percentile can be interpreted as the precipitation percentile expected in EN and LN episodes. Besides, an assessment of the consistency of the anomalies is made for each station, following the same procedure described in item 6 above. This additional analysis facilitates the identification of the centers of maximum anomalies and the joint analysis of precipitation and circulation anomalies.

The analysis of the circulation anomalies and associated processes that lead to the precipitation anomalies is carried out with composites of geopotential height anomalies at 850 and 200 hPa associated with EN and LN events. The consistency of the anomalies (above or below the mean) is also tested by using the hypergeometric distribution.

It is worth pointing out that it is not the significance of the difference between EN and LN conditions (which are almost opposite) that is calculated in this study. To achieve a better view of the impact of each type of episode, the consistency of the associated anomalies is calculated separately, with respect to the whole series of data, which is a more demanding test. Furthermore, in the second part of the analysis, the consistency of the EN (LN)-related anomalies is calculated for each station, which is much more demanding than if it is calculated for coherent regions, as in the first part of the analysis, and thus lower significance would be expected.

5. Results

a. Harmonic analysis and coherent regions

Figures 2 and 3 show the vectors representing the first harmonic fitted to the composite percentile precipitation at each station. In Fig. 2 the vectors represent the maximum of this harmonic for EN events, whereas in Fig. 3 they represent its minimum for LN events. Coherent regions are characterized by the similarity of the phase angle of the vectors. Thus, some parts of a region may present smaller magnitude of the vectors than other ones, and the mean vector of the region may be diminished, in spite of the large signal in some areas.

Fig. 2.

Amplitudes and phases of the first harmonic fitted to composites of monthly percentile ranks of precipitation for El Niño events, in the biennia from the Jul before to the Jun after the events. The phases and magnitudes of the vectors are indicated by the“vector clocks.” The phases refer to the maximum of the first harmonic. Spatially coherent regions are numbered.

Fig. 2.

Amplitudes and phases of the first harmonic fitted to composites of monthly percentile ranks of precipitation for El Niño events, in the biennia from the Jul before to the Jun after the events. The phases and magnitudes of the vectors are indicated by the“vector clocks.” The phases refer to the maximum of the first harmonic. Spatially coherent regions are numbered.

Fig. 3.

Amplitudes and phases of the first harmonic fitted to composites of monthly percentile ranks of precipitation for La Niña events, in the biennia from the Jul before to the Jun after the events. The phases and magnitudes of the vectors are indicated by the vector clock. The phases of the vectors refer to the minimum of the first harmonic. Spatially coherent regions are numbered.

Fig. 3.

Amplitudes and phases of the first harmonic fitted to composites of monthly percentile ranks of precipitation for La Niña events, in the biennia from the Jul before to the Jun after the events. The phases and magnitudes of the vectors are indicated by the vector clock. The phases of the vectors refer to the minimum of the first harmonic. Spatially coherent regions are numbered.

Figure 2 suggests the existence of eight regions of coherent behavior as regards precipitation anomalies during EN events. Their description is summarized in Table 2. The vectors present a very ample range of directions, reflecting the shift of the maximum of the first harmonic from the winter of year (0) to the winter of year (+), with most frequent occurrence during the spring–summer of the year (0). That is why RH87 found a low coherence for the region they determined in SSA. It is worth pointing out that the maximum of the first harmonic does not always indicate the actual time of the maximum anomaly. This is seen in the aggregate composites for each region.

Table 2.

Characteristics of the homogeneous regions for El Niño–related precipitation.

Characteristics of the homogeneous regions for El Niño–related precipitation.
Characteristics of the homogeneous regions for El Niño–related precipitation.

The vectors map confirms the conclusion of Grimm et al. (1998) that in SSA the area of largest impact of EN events on precipitation is southern Brazil. The amplitude of the vectorial mean is even larger in the present study, probably due to the fact that the data series are shorter (1956–92). This is consistent with the fact that the impact of EN was smaller before this period in that region, as can be seen in Fig. 9 of Grimm et al. (1998).

Fig. 9.

Composite of geopotential height anomalies at 200 hPa (left) and 850 hPa (right) for the indicated season of the La Niña cycle. Shadowed areas indicate anomalies consistent to a level of significance better than 90%. The contour interval is 5.0 m on the left and 2.5 m on the right.

Fig. 9.

Composite of geopotential height anomalies at 200 hPa (left) and 850 hPa (right) for the indicated season of the La Niña cycle. Shadowed areas indicate anomalies consistent to a level of significance better than 90%. The contour interval is 5.0 m on the left and 2.5 m on the right.

It should be stressed that the results for regions 4 and 7 should be viewed with caution, because the composites for these regions comprise less than five EN for some months in the period July (−) to June (+), due to missing data in the series. Region 8, comprising the extreme northwest of Southern Brazil and east of Paraguay, embraces few stations that may not be very representative of this region and therefore has a small index of coherence and a relatively small magnitude of the mean vector.

The vectors representing the minimum of the first harmonic fitted to the LN composites (Fig. 3) present a much more coherent behavior than the EN vectors. Therefore, the characteristics of the regions (Table 3) are more alike than for EN, at least as they refer to the phases. This coherence is not reproduced all over southern Brazil, but only in its southernmost part, although there are strong anomalies during the spring of LN years all over southern Brazil, as shown by Grimm et al. (1998). The minimum of the first harmonic occurs only in the range August (0) to December (0), with the exception of region 6. This region actually presents a maximum associated with LN events, and so the minimum on September (−) actually corresponds to a maximum of the first harmonic on March (+).

Table 3.

Characteristics of the homogeneous regions for La Niña–related precipitation.

Characteristics of the homogeneous regions for La Niña–related precipitation.
Characteristics of the homogeneous regions for La Niña–related precipitation.

The EN and LN regions are approximately similar, especially region 5 (Figs. 2 and 3). The timing of the precipitation responses in these regions is roughly in opposite phase during the EN and LN events. As can be seen in Tables 2 and 3, the maximum of the first harmonic in the EN case differs by at most one month from the LN minimum. This means that in those regions, the precipitation anomalies generally have opposite signals along the EN and LN cycles, indicating a large degree of linearity in the response to these events.

The EN “aggregate” composites (average gamma percentiles) for each coherent region in Fig. 2 are shown in Fig. 4. In spite of the differences in the magnitude and timing of the anomalies between regions, it is possible to summarize a general behavior. In the year before EN there is a tendency to less than normal precipitation from April (−) to March (0) [with a discontinuity in September (−)], with the exception of region 6, where it rains more than normal during July (−) to November (−). There are positive rainfall anomalies during the spring of the warm event year [August (0) to November (0)] over all regions, except regions 6 and 7. There is a weakening (and even a sign reversal in some regions) of the anomalies in January (+), which begins in December over the coastal regions of southern Brazil. The behavior is not so coherent from April (0) to July (0) and during the year (+). While it rains more than normal in southern Brazil during the winter of the year (+), there are dry or not consistent wet anomalies in other regions.

Fig. 4.

El Niño events “aggregate” composites (average gamma percentiles) for each coherent region in Fig. 2, for the 36-month period centered on the El Niño year.

Fig. 4.

El Niño events “aggregate” composites (average gamma percentiles) for each coherent region in Fig. 2, for the 36-month period centered on the El Niño year.

The LN aggregate composites for the six coherent regions in Fig. 3 are shown in Fig. 5. There is a common period of negative anomalies during the spring of the year (0) in regions 1 and 2. For regions 3, 4, and 5 the negative anomalies occur mostly in winter of this year. In region 6 there is a tendency to above-normal precipitation in the beginning and winter of year (+). Generally, there is above-normal precipitation during the year before LN events and below-normal precipitation during the LN year, with the exception of region 6. The behavior in the year following LN is not so clear. A remarkable feature is the reversal of the sign of the anomalies during January (+), particularly over regions 1 and 2. This behavior is symmetric to the one observed during EN events.

Fig. 5.

La Niña events aggregate composites (average gamma percentiles) for each coherent region in Fig. 3, for the 36-month period centered on the La Niña year.

Fig. 5.

La Niña events aggregate composites (average gamma percentiles) for each coherent region in Fig. 3, for the 36-month period centered on the La Niña year.

In order to verify whether the average anomalies during the EN and LN events in each region occur consistently during these events, the analysis described in step 6 of section 3 is systematically applied to three-month running seasons. The results are summarized in Tables 4 and 5. The periods with the largest average anomalies in Figs. 4 and 5 are not always those with the most consistent ones. This becomes clear by comparing the levels of significance (Table 4) and average gamma percentiles (Fig. 4) for the EN wet periods September (0) to November (0) and October (0) to December (0) for region 1. This may be explained by the influence of outliers on some average anomalies.

Table 4.

Level of significance of the hypothesis test that the indicated periods are wetter or drier than normal during El Niño events within the eight coherent regions. The periods that present the largest significance (above 90%) are set in bold.

Level of significance of the hypothesis test that the indicated periods are wetter or drier than normal during El Niño events within the eight coherent regions. The periods that present the largest significance (above 90%) are set in bold.
Level of significance of the hypothesis test that the indicated periods are wetter or drier than normal during El Niño events within the eight coherent regions. The periods that present the largest significance (above 90%) are set in bold.
Table 5.

Level of significance of the hypothesis test that the indicated periods are wetter or drier than normal during La Niña events within the six coherent regions. The periods that present the largest significance (above 90%) are set in bold.

Level of significance of the hypothesis test that the indicated periods are wetter or drier than normal during La Niña events within the six coherent regions. The periods that present the largest significance (above 90%) are set in bold.
Level of significance of the hypothesis test that the indicated periods are wetter or drier than normal during La Niña events within the six coherent regions. The periods that present the largest significance (above 90%) are set in bold.

Table 4 confirms clearly the general tendency to dryness in the year preceding EN, after April (−), except in region 6. Although half of the EN episodes of Table 1 were preceded by LN events, the significant dry anomalies in year (−) of EN and year (0) of LN do not coincide exactly. There is also a general tendency to wetness during EN year (with the exception of region 6), with higher consistency in region 1. The anomalies in the year (+) have less common aspects.

Table 5 shows a significant tendency to dryness during LN years in different regions (with the exception of region 6), with highest consistency in regions 1 and 2. In the year before LN there are significant wet anomalies, but not as spread out as the dry anomalies in the year before EN. There are few consistent anomalies in year (+).

There are other longer periods during EN and LN cycles that show a high level of significance for the consistency of the associated precipitation anomalies. For example, the period April (–) to March (0) is consistently dry in EN events in regions 1, 2, and 3, with levels of significance of 99.3, 92.6, and 95.3, respectively. The period September (0) to December (0) is consistently wet in the same regions with levels of significance of 99.8, 99.8, and 95.3.

The results obtained here are in good agreement with previous regional studies, which used a denser network of data. Southern Brazil (our region 1) presents quite similar distribution of anomalies along the EN events to that of region 1 of Grimm et al. (1998). Northwestern Uruguay, which is here included in region 1, presents strong positive anomalies during spring of the EN year and also consistent positive anomalies in the autumn–winter of the following year. Yet southeastern Uruguay, here included in region 3, has weaker positive anomalies during the spring of EN year and no consistent anomalies during autumn–winter of the following year. This general behavior agrees with the results of Pisciottano et al. (1994).

The positive significant rainfall anomalies over most of SSA during the spring of EN years and over Chile during winter and spring, shown in this study, are visible in Aceituno (1988). However, the significant positive anomalies in southern Brazil during the winter of the following year appear as a significant correlation with the SOI neither in Aceituno (1988), nor in Rao and Hada (1990), perhaps because the anomalies of this index are not consistent and strong at this phase of the EN events.

The small differences between the present results and those of RH87 and RH89 are mainly due to the fact that their coherent region in SSA comprised parts of regions 1, 2, and 3.

b. Joint seasonal analysis of precipitation and circulation

The precipitation anomalies associated with EN and LN events may be caused by changes in the water vapor availability, in the dynamics leading to vertical movements, and in the vertical stability of the air, or due to a combination of these factors. In general, the humid (dry) anomalies result from the enhancement (weakening) of already existing climatic circulation features that favor (oppose) the precipitation during a given season in specific regions. In SSA the main processes leading to EN–LN-related precipitation anomalies include

  1. changes in the subtropical jet and in vorticity advection,

  2. changes in the northerly advection of humidity,

  3. establishment of equivalent barotropic anomalies over and near Chile, and

  4. changes in the advection of humidity from the Atlantic Ocean.

For the joint analysis of precipitation and circulation anomalies, composites of low-level circulation anomalies, to identify changes of flow from moisture sources, and of upper-level anomalies, to indicate changes in the dynamic lift, are provided, with an assessment of consistency. In addition, a more detailed analysis of rainfall is presented.

The results of the detailed analysis of precipitation for each station are shown in Figs. 6 and 7. They present maps of the mean precipitation percentiles expected for every other running trimester in EN and LN events, centered on May (0) to July (+). This is a useful complement to the analysis already discussed, because it allows a greater spatial and temporal refinement. On these maps, the shadowed areas contain stations with consistently wet or dry anomalies during the indicated trimester, with a level of significance better than 90%. In regions with few stations, these shadowed areas may appear fragmented. Figures 8 and 9 show the geopotential height anomalies at 200 and 850 hPa for the same periods.

Fig. 6.

Seasonal mean precipitation percentiles expected for the indicated season of the El Niño cycle. Shadowed areas have precipitation anomalies consistent to a level of significance better than 90%.

Fig. 6.

Seasonal mean precipitation percentiles expected for the indicated season of the El Niño cycle. Shadowed areas have precipitation anomalies consistent to a level of significance better than 90%.

Fig. 7.

Seasonal mean precipitation percentiles expected for the indicated season of the La Niña cycle. Shadowed areas have precipitation anomalies consistent to a level of significance better than 90%.

Fig. 7.

Seasonal mean precipitation percentiles expected for the indicated season of the La Niña cycle. Shadowed areas have precipitation anomalies consistent to a level of significance better than 90%.

Fig. 8.

Composite of geopotential height anomalies at 200 hPa (left) and 850 hPa (right) for the indicated season of the El Niño cycle. Shadowed areas indicate anomalies consistent to a level of significance better than 90%. The contour interval is 5.0 m on the left and 2.5 m on the right.

Fig. 8.

Composite of geopotential height anomalies at 200 hPa (left) and 850 hPa (right) for the indicated season of the El Niño cycle. Shadowed areas indicate anomalies consistent to a level of significance better than 90%. The contour interval is 5.0 m on the left and 2.5 m on the right.

Figure 6 shows that during autumn of EN years [April (0) to June (0)], there is a broad region in subtropical Argentina and Paraguay, covering region 7 and most of regions 2 and 3, where precipitation is above the median. Also over Patagonia there are positive anomalies. Yet during winter [June (0) to August (0)] the subtropical areas have near-normal precipitation, while the positive anomalies are shifted southward in Argentina. Positive signals appear in central Chile. From late winter [August (0) to October (0)] to spring [October (0) to December (0)] the positive anomalies over central Chile and Patagonia strengthen, and, also, strong and consistent wet anomalies spread over southern Brazil and northeastern Argentina. In spring (0) there is higher than median precipitation over most of SSA, with the exception of northwest Argentina and northern Chile.

Figure 8 shows that from autumn to spring (0) of EN events the 200-hPa anomaly pattern comprises cyclonic anomalies over the South Pacific high, anticyclonic anomalies to the south, anticyclonic anomalies in the subtropical Atlantic, and cyclonic anomalies to the south, southeast of SSA. This pattern is nearly equivalent barotropic and dipole-like both in the Pacific and in the Atlantic, but with reversed polarity. Its action centers undergo some changes of magnitude and position during the EN cycle. It is stronger and more stable in the Pacific. This pattern strengthens the westerlies over the eastern Pacific in the subtropics and over the western Atlantic in the midlatitudes, causing its anomalous cyclonic curvature just west of SSA. In late winter (0), it moves to the north and to the east.

In autumn–winter (0), when the dipole pattern is more to the south, the westerlies are intensified over the southern part of SSA, south of 40°S, thus favoring precipitation over this region and the shifting to the south of migratory systems. This leads to the wet anomalies over Patagonia and part of Chile. Cold fronts are less frequent to the north and the WL can stay longer at each of its deeper phases, consistent with the results of Barros and Scasso (1994). In fact, the 850-hPa maps show a tendency to negative height anomaly over northwestern Argentina and a positive anomaly over the region of the subtropical high in the Atlantic. This pattern enhances the zonal height gradient to the east of the WL and thus the warm and sometimes humid northerly advection from the tropical forest. The April (0) to June (0) season of the EN event is an example of how this enhancement produces anomalous precipitation in Paraguay, subtropical Argentina, and parts of southern Brazil and Uruguay. Although the conditions at 200 hPa are not very favorable, with an anomalous ridge along this region and a decrease of baroclinicity to its north, there is significant above-median precipitation all over eastern Argentina and Paraguay (see Fig. 6). Though the WL enhancement is intense during the winter (0), the relatively dry conditions prevailing to the north of the region, in central Brazil, during July (0) to August (0), do not allow the advection of much additional water vapor to produce rainfall anomalies. Besides, in winter (0) the ridge in the troposphere over the subtropical region is enhanced and the positive rainfall anomalies are shifted to the south.

In late winter–spring (0), the dipole patterns move to the north and to the east, approaching the South American continent. Thus, there is anticyclonic circulation southwest of the southern tip of South America and cyclonic circulation north of 40°S. A trough axis extends southeast–northwest through southern Argentina and central Chile. Consistent with the weakening of the South Pacific high along the Chilean coast and the anticyclonic anomaly to the south, there is diversion of the migratory systems toward the latitudes of central Chile, as was described by Rutllant and Fuenzalida (1991) for case studies. This situation produces higher than median precipitation over central Chile and in most of region 3 in Argentina. At this time the northerly flux of moisture into eastern Argentina, Uruguay, and southern Brazil is again enhanced. In spring (0), when the dipoles are in their northernmost position, there is an enhancement of the subtropical jet over SSA, and a clear cyclonic vorticity advection over northeastern Argentina, southern Brazil, and Uruguay, producing strong rainfall impact on these regions, as was described by Grimm et al. (1998). This process acts jointly with the enhancement of northerly advection of moisture. At this time of the year, the baroclinicity still remains at low latitudes and its enhancement in this region favors the already frequent developments of mesoscale systems and cyclogenesis on eastern subtropical SSA (Necco 1982; Velasco and Fritsch 1987).

Figure 6 shows that in summer [December (0) to February (+)] the wet anomalies move westward to northern Argentina and Paraguay. There are no consistent wet anomalies over central Chile. Figure 8 shows that in that season the dipole patterns also move westward and weaken, and so do the cyclonic anomalies over Chile. The rainfall anomalies weaken and tend to reverse their sign during January (+), particularly in southern Brazil, Uruguay, and eastern Argentina (regions 1 and 3) as was already reported by Grimm et al. (1998) for southern Brazil (Fig. 4). Monthly analysis (not shown) indicates that also the polarity of the dipoles tend to reverse in January (+). This reduces the northerly advection of moisture, which is important for rainfall in these regions during summer. However, during summer there is another process able to impact the rainfall over Uruguay and eastern Argentina: the enhancement (weakening) of the advection from the Atlantic Ocean. During EN events, the easterly component of the near-surface flow is enhanced over Uruguay and central Argentina due to the southward shift of the South Atlantic high. In January (+) it may have a compensating effect in relation to the decrease of the northerly advection, keeping rainfall near normal in these regions.

In late summer (+) [February (+) to April (+)] the rainfall anomalies strengthen again to the east, in parts of regions 1 and 3, and in Chile, but not to the magnitude of spring (0), as circulation anomalies undergo a brief return to conditions similar to spring (0), although displaced to the south. Also the northerly advection of moisture is enhanced into these regions.

In autumn (+) [April (+) to June (+)], normal conditions prevail over most of SSA. The anomalous northerly advection decreases, the cyclonic anomaly is centered on the southern tip of South America, and the anticyclonic anomaly southeast of SSA weakens.

In winter (+) [June (+) to August (+)] the cyclonic anomaly displaces northward and significant wet anomalies reappear over southern Brazil, due to the increased subtropical jet and advection of cyclonic vorticity into this region. Dry conditions prevail over Argentina.

Figure 7 shows the maps for the LN case. In general, during year (0) the precipitation anomalies evolve in the same way as in the EN case, but with opposite sign, although there are some shifts in space and time. For instance, the dry anomalies over Chile start earlier in winter (0) and are not so strong in spring (0). The correspondence in spring (0) is very good in southern Brazil, Uruguay, and eastern Argentina. In summer [December (0) to February (+)], also in symmetry with EN events, the negative anomalies weaken over southern Brazil and shift westward over Argentina. In January (+) there is a break with respect to the preceding months, and wet anomalies appear over part of southern Brazil and Paraguay (regions 1 and 2) (Fig. 5). As in the EN episodes, after the January break, the spring (0) anomalies tend to return in late summer (+), particularly in the southernmost part of southern Brazil, Uruguay, and east Argentina. This pattern tends to weaken and become noisier during autumn (+), with more temporal and spatial variability. In winter (+) dry conditions return to the southernmost part of southern Brazil, Uruguay, and northeastern Argentina.

As for precipitation, the symmetry of the geopotential height anomaly fields with opposite signs between LN and EN cases is also remarkable during year (0), as can be seen from the comparison of Figs. 8 and 9. Thus, from autumn (0) to spring (0) of LN events there is a decreased westerly flow over the eastern Pacific in the subtropics and over the western Atlantic in the midlatitudes. An anticyclonic anomalous curvature predominates west of SSA. From winter (0) to spring (0), the dipole patterns move to the north and to the east. The symmetry is weaker in the Atlantic sector. There are some shifts with respect to the EN opposite anomalies, with a tendency to be at lower latitudes in winter and at higher in spring and summer. Zonal shifts are generally toward the west. From February (+) on, there is less symmetry with respect to the EN cycle, perhaps due to the shorter duration of the LN events.

The composites of geopotential height anomalies at 200 hPa for June (0) to August (0) and December (0) to February (+) of EN events are in reasonable agreement with those of Karoly (1989) near SSA, because they contain the same basic features. This is an indication of the stability of these composites, for Karoly used three of the nine events used here (1972, 1976, and 1982) and included the year 1977, considered a year (+) in this study.

There are some differences between the circulation features disclosed here and in Aceituno (1989). They may be due to differences in methodology and in datasets. For example, in the present study negative height anomalies prevail over SSA in spring (0) of EN events, along with a strengthened subtropical jet. In Aceituno (1989) the negative SO phase (generally associated with EN) during spring is associated with positive height anomalies and a decrease of the subtropical westerlies, as is inferred from his Figs. 3f and 6f.

6. Circulation anomalies and regionalization of rainfall anomalies

Each of the processes described in section 5b has largest impact at a particular phase of the EN and LN cycles and on specific regions. It is therefore natural to ask, to what extent are they responsible for the regionalization described in Figs. 2 and 3, based on the phase of the first harmonic fitted to the 24-month composite of the precipitation percentiles?

The changes in the subtropical jet (process 1) affect the precipitation field mainly in region 1. This region has the maximum (minimum) of the first harmonic in the EN (LN) cycle in spring (0), when those changes cause the largest anomalies in the precipitation field.

The region where the changes in the northerly advection (process 2) are associated with precipitation anomalies coincides approximately with region 2 of EN and LN. Its first harmonic peak is in December (0) because, besides the major anomalies during spring (0), due mainly to process 1, there are also anomalies in February (+) to April (+), when the advection of humidity from the north is largely responsible for the anomalous precipitation. This second peak shifts the phase of the first harmonic peak to December (0), although there is no rainfall peak in this month.

Central Chile, located in region 5, has a maximum in the first harmonic for the EN cycle in July (0), although the real maximum is in August (0). For LN the minimum occurs in August (0). These extremes are caused by the approach of the Pacific cyclonic (anticyclonic) anomaly to the continent (process 3).

Region 3 has its maximum in the first harmonic for EN in September (0) and the minimum for LN in October (0), shortly after the extremes for region 5 and shortly before those for region 2. Actually, region 3 shares with these regions their main processes leading to precipitation anomalies. During EN, in autumn (0) and in spring (0) there is increased humidity advection from the north, which is reinforced in spring (0) by the tropospheric cyclonic anomalies and in early summer by the increased advection from the Atlantic. In winter (0), region 3 shares with region 5 the influence of the approach of the Pacific height anomalies to the continent. During LN, approximately opposite anomalies prevail.

Thus, three of the main coherent regions (1, 2, and 5) are largely determined by the timing of particular aspects of the circulation during the EN and LN cycles. In region 3, which is a transition zone, there is a concurrence of processes shared by the other three regions.

7. Summary and concluding remarks

The analysis of a large dataset of monthly precipitation records of SSA, south of 15°S, permits us to conclude that this entire region shows precipitation anomalies associated with EN and LN events. The timing of these anomalies changes throughout SSA, leading to the identification of eight different coherent regions in the EN case and six in the LN case. All these regions show a significant response at some part of each event. Southern Brazil is the region with the strongest signal in the EN event.

The main coherent regions in the EN and LN cases are basically the same, except for some minor differences. Furthermore, there is a general behavior toward opposite signals in the precipitation anomalies during almost the same seasons of the respective EN and LN cycles, especially until the mature phase. This is coherent with the symmetry of the circulation anomalies over SSA and the contiguous oceans during these seasons, although there are little shifts in time and space. The symmetry is more marked over the Pacific and indicates the large degree of linearity in the response over SSA to those events.

Some features of the precipitation anomalies during the EN event are rather alike thorough the region. There is a tendency to lower than median precipitation in the year (−), which continues until March (0), even in those cases when an LN event does not occur in the year before EN. In a vast region, east of the Andes, the strongest positive rainfall anomalies are found in the spring (0). During this period, the event is reaching its mature stage and the circulation anomalies favor processes leading to precipitation anomalies in various regions. During January (+), positive anomalies disappear or even are reversed in some regions and then reappear in February (+). Though the event is mature during the austral summer (+), it does not produce important anomalies in the circulation over SSA during this season, and the response of the precipitation field is weaker than in the spring (0). During the year (+) the response of the precipitation field is not very consistent over large areas, except southern Brazil. This description holds for LN cycle with opposite signs.

The most remarkable features in the circulation anomalies are the nearly equivalent barotropic dipole-like circulation anomalies over the Pacific and Atlantic Oceans, with reversed polarity. This pattern strengthens (weakens) the westerlies over the eastern Pacific in the subtropics and over the western Atlantic in the midlatitudes, causing an anomalous cyclonic (anticyclonic) curvature just west of SSA. The centers of the anomalies undergo some changes of magnitude and shifts in position. For instance, in the spring, this pattern moves to the north and to the east. It is strongest and more stable in the Pacific.

In general, the precipitation anomalies result from changes of already existing climatic circulation features that influence the precipitation during a given season in specific regions. This is the case, during EN (LN), of the enhancement (weakening) of the subtropical jet in spring (0) with advection of cyclonic (anticyclonic) vorticity over southern Brazil, and of the deepening (weakening) of the west low during most of the cycle, with increased (decreased) northerly advection of moisture. The weakening (strengthening) of the South Pacific high near central Chile in winter–spring (0) and the increase (decrease) of the humid advection from the Atlantic into eastern Argentina and Uruguay in summer (0+) are also examples of variation of climatic features related to precipitation.

The discussion relating seasonal mean anomaly fields of geopotential height and precipitation is a zero-order approximation, since precipitation events are related to more transient and smaller-scale modes of the atmospheric circulation. However, these transient modes are transported by the mean flow, contribute to the seasonal anomalies, and are modulated by the large-scale low-frequency circulation patterns caused by EN or LN events, favoring or suppressing precipitation. It is possible to find a qualitative explanation of the seasonal precipitation anomalies by analyzing the mean seasonal height anomalies. However, it is convenient to mention that there are intraseasonal differences in the impact of EN and LN events that recommend a monthly analysis during certain phases of their cycles. Some features that are very consistent in monthly maps may be smoothed out in the seasonal analysis. These month-to-month differences are due to the evolution of the atmospheric basic state and the heat sources associated with EN during its cycle, as well as the interaction between the low-frequency large-scale anomalies associated with EN–LN and the mechanisms associated with the local annual cycle of precipitation.

Fig. 6.

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Fig. 6.

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Fig. 7.

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Fig. 7.

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Fig. 8.

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Fig. 8.

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Fig. 9.

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Fig. 9.

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Acknowledgments

This research has been supported by CNPq (Brazil) and CONICET (Argentina). Alice Grimm also received support from the Federal University of Paraná Foundation (FUNPAR) and Vicente Barros from the University of Buenos Aires. We are grateful to Simone E. T. Ferraz, Daniel Weingaertner, and Rodrigo Siqueira, for their help in processing the data and preparing the figures.

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Footnotes

Corresponding author address: Dr. Alice M. Grimm, Department of Physics, Federal University of Panama, Caixa Postal 19081, CEP 80531-990 Curitiba, Brazil.