INTERNATIONAL JOURNAL OF CLIMATOLOGYInt. J. Climatol. (2011)Published online in Wiley Online Library(wileyonlinelibrary.com) DOI: 10.1002/joc.2345

Seasonal anomalous rainfall in the central and easternAmazon and associated anomalous oceanic

and atmospheric patterns

Rita Valeria Andreoli,a Rodrigo Augusto Ferreira de Souza,a Mary Toshie Kayanob*and Luiz Antonio Candidoc

a Universidade do Estado do Amazonas, Escola Superior de Tecnologia Av. Darcy Vargas, 1200, Parque 10 69065-020, Manaus, AM, Brazilb Instituto Nacional de Pesquisas Espaciais Av. dos Astronautas, 1758 12227-010 Sao Jose dos Campos, SP, Brazil

c Instituto Nacional de Pesquisas da Amazonia Av. Andre Araujo, 2936, Campus II, Aleixo, 69060-001, Manaus, AM, Brazil

ABSTRACT: Previous papers have shown that the rainfall anomalies over the Amazon region result from the independentor combined effects of the eastern tropical Pacific and Atlantic Basins. Here, the monthly rainfall data of Itaituba, Manaus,Parintins, and Santarem for the 1931–1996 period has been used to classify its dry and rainy seasons into dry, very dry,wet, and very wet categories. The sea surface temperature (SST) and sea level pressure (SLP) patterns associated withthese climate conditions in the central and eastern Amazon are discussed in terms of the relative influence of the tropicalAtlantic and Pacific sectors, as well as their seasonal differences. These seasonal differences are, in part, determined bythe seasonal phase locking of the El Nino-Southern Oscillation (ENSO) and Atlantic equatorial modes. The rainy seasoncases are mostly driven by the ENSO and the inter-hemispheric SST gradient mode in the tropical Atlantic, and the dryseason cases, by the Atlantic equatorial mode (AEM). A new result here is the role of the inter-Pacific-Atlantic anomalousSST gradient mode on the rainfall anomalies. This mode acts concordantly with the Atlantic modes on the rainfall overthe central and eastern Amazon, and is responsible for precipitation extreme cases during the dry season and for the verywet rainy season case. In other words, the intense inter-Pacific-Atlantic mode for these cases is the differential factor inrelation to the moderate cases. The results here, especially in relation to the role of the inter-Pacific-Atlantic gradient inthe central and eastern Amazon precipitation, have not been discussed before and should be taken into considerationin the diagnostic activities. Copyright 2011 Royal Meteorological Society

KEY WORDS climatology; El Nino-Southern Oscillation; tropical oceans; climate variability

Received 17 August 2010; Revised 22 March 2011; Accepted 26 March 2011

1. Introduction

The Amazon encompasses one of the major continen-tal regions with intense convective activity in the globe.Thus, it constitutes an important heat source for theatmosphere and contributes to the atmospheric generalcirculation. The seasonal cycle dominates the Amazonconvective rainfall variations, with a maximum australsummer and a minimum winter (Rao and Hada, 1990).The rainfall seasonal cycle in this region is driven bythe South American monsoon system (SAMS) (Zhou andLau, 1998; Vera et al., 2006; Garcia and Kayano, 2009,2010a). On the other hand, the Amazon rainfall exhibitsmarked interannual variability, part of which has beenattributed to the sea surface temperature (SST) varia-tions in the tropical Pacific manifested as an El Nino-Southern Oscillation (ENSO) mode (Kousky et al., 1984;Kayano and Moura, 1986; Aceituno, 1988; Ropelewski

* Correspondence to: Mary Toshie Kayano, Instituto Nacional dePesquisas Espaciais, Centro de Previsao de Tempo e Estudos Climat-icos, Avenida dos Astronautas, 1758, 12227-010 Sao Jose dos Campos,SP, Brazil. E-mail: mary.kayano@cptec.inpe.br

and Halpert, 1987, 1989; Kousky and Ropelewski, 1989;Marengo and Hastenrath, 1993; among others). Thereduced (enhanced) rainfall over the Amazon, in partic-ular in its northern and central sectors, noted in someyears, is associated with El Nino (La Nina) occurrences.However, a large percentage of the interannual varianceis not explained by the ENSO (Rao et al., 1996; Marengoet al., 2001).

Indications that the SST variability in the tropicalAtlantic also plays an important role in modulating theAmazon rainfall variability have been shown by manypapers. Among them, some use the mechanistic relation-ship between the tropical Atlantic SST variability and thenorth–south migration of the inter-tropical convergencezone (ITCZ) in this oceanic sector to explain the rainfallvariability in this region. In fact, some papers have shownthat the influence of the ITCZ in the South American rain-fall is not limited to northeastern Brazil but extends overthe Amazon (Uvo et al., 2000; Ronchail et al., 2002).Garcia and Kayano (2010a), using the outgoing longwave radiation data for the 1979–2006 period, providedobservational evidence on the relationship between the

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Atlantic ITCZ related convection and the South Amer-ican monsoon in the central Amazon. This relationshipwas further confirmed by Garcia and Kayano (2010b),who analysed the moisture and heat budgets associatedwith the South American monsoon and the ITCZ.

On the other hand, Yoon and Zeng (2010) found com-parable strengths of the tropical North Atlantic (TNA)SST and ENSO-related Pacific SST influences on theAmazon rainfall, and weaker influence of the tropi-cal South Atlantic (TSA) SST variability. For season-ally stratified analyses, they found the strongest TSA(TNA) SST variability influence over the southern Ama-zon during the wet-to-dry transition (dry) season, and thestrongest ENSO influence over the entire basin (with amaximum in the eastern Amazon) during the wet season.They proposed that the mechanistic relations between theAmazon rainfall variability and the SST variations inthe equatorial Pacific, TNA and TSA involve variations inthe Walker circulation, meridional movement of theITCZ, and Hadley circulation, respectively.

The combined effects of the tropical Pacific andAtlantic Oceans on the Amazon rainfall have also beeninvestigated. In fact, Souza et al. (2000) showed that theEl Nino and warm dipole (warmer than normal TNAand colder than normal TSA) in the tropical Atlantichave a stronger combined effect in reducing precipitationover the central-northern and western Amazon, andin increasing precipitation over the eastern Amazonduring summer than each mode acting individually.Consistently, Ronchail et al. (2002) found very strongnegative anomalies over the northern Amazon when ElNino and cold waters in TSA prevail.

From another point of view, evidence of the connec-tions between the equatorial Atlantic and the easterntropical Pacific through the SST variability associatedwith the Atlantic equatorial mode (AEM) and the ENSOhas been found in recent studies (Wang, 2006; Kucharskiet al., 2007, 2008). The AEM, similarly to the ENSO inthe Pacific, features an anomalous SST pattern roughlysymmetric to the equator in the eastern side of theAtlantic Basin, and varies in a 2–5-year timescale(Zebiak, 1993; Wagner and da Silva, 1994). The posi-tive (negative) AEM is referred to as Atlantic El Nino(Atlantic La Nina) (Zebiak, 1993). When the AEM andthe ENSO create an inter-basin east-west SST gradient,the Atlantic Walker circulation induces an anomalouseast-west flow of air across northern South America andan atmospheric direct circulation between the two oceans.Kayano et al. (2010) examining the ENSO-related pre-cipitation patterns over South America found substantialdifferences in these patterns when the ENSO extremesare associated with the AEM occurrences and AEMindependent.

From the above review, it is clear that the SST variabil-ity in both the tropical Pacific and Atlantic Oceans playsan important role in the interannual rainfall variationsover the Amazon (Aceituno, 1988; Marengo, 1992; Nobreand Shukla, 1996; Ronchail et al., 2002; among others).Furthermore, the seasonal differences on the effects of

these two Oceanic Basins strongly suggest that a sea-sonal stratified analysis should be preferred rather than awhole year analysis. Here, a precipitation index derivedfrom four raingauge stations over the central and easternAmazon is used to classify the extreme climate condi-tions in this region on a seasonal basis. The causal rela-tions between these extreme climate conditions and thelarge-scale SST and sea level pressure (SLP) anomalouspatterns are examined from composite analyses. Data andmethodology are described in Section 2, and bi-monthlycomposites of SST and SLP are described in Section 3.Conclusions are given in Section 4.

2. Data and methodology

The dataset used in this paper consists of reconstructedmonthly SST series at 2° × 2° latitude-longitude resolu-tion grids obtained by Smith and Reynolds (2004). Thisdataset consists of the version 2 of the monthly grid-ded SST. The SST time series are obtained in the globaldomain between 30°N and 30 °S and for the 1931–1996period. Monthly SST anomalies are obtained as depar-tures from the 1931–1996 means. Monthly anomaly timeseries of SST at each grid point are normalized by thecorresponding monthly standard deviation. In addition,the HADSLP2 archive containing monthly SLP data at5° × 5° latitude-longitude resolution obtained from theMet Office Hadley Centre is also used (Allan and Ansell,2006). The SLP time series in the global band between60°N and 60 °S for the same period as those of the SSTare subjected to the calculations described for the SST.The choice of the 1931–1996 period for the presentanalysis is based on the period with precipitation dataavailability.

Monthly precipitation time series of Manaus, Parintins,Itaituba, and Santarem provided by the Instituto Nacionalde Meteorologia (INMET) are also used. Their geograph-ical locations and periods with available precipitation dataare listed in Table I. These four raingauge stations areclose to each other and located in the central and east-ern Amazon. Considering all four stations, their dry andrainy seasons present a slight lag towards east. The rainyseason for Santarem (the station located more to the east)lags by one month the rainy season spanning from Jan-uary to April (JFMA) for the other three stations. The dryseason for Parintins and Santarem lags by two monthsthe dry period from June to September (JJAS) for theother two stations (Table I). So, considering the periodsJJAS and JFMA the dry and rainy seasons, respectively,two time series representing the precipitation in the cen-tral and eastern Amazon for these seasons have beenconstructed based on these four raingauge stations. Foreach station, the seasonal rainfall value is obtained byaveraging the corresponding monthly values. For eachseason, seasonal time series is obtained by averaging theseasonal values in space. In order to avoid unbalancedcontributions of the raingauge stations, only the commonperiod among them with available data, which spans from

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Table I. Raingauge stations in the central and eastern Amazon: geographical location, period with available data, and the monthscorresponding to their dry and rainy seasons.

Station Lat. Long. Period Rainy season Dry season

Itaituba - PA 04°27′S 55°29′W 1931–2004 JFMA JJASManaus - AM 03°07′S 59°57′W 1925–2007 JFMA JJASParintins - AM 02°38′S 56°44′W 1923–2001 JFMA ASONSantarem - PA 02°25′S 54°42′W 1915–1996 FMAM ASON

1931 to 1996 is considered in the analyses. For the samereason, the years with missing data in one or more rain-gauge stations are not considered in the analyses. Theseyears are 1937, 1938, 1939, 1943, 1959, 1960, 1977, and1995. These seasonal time series represent the rainy anddry seasons in the central and eastern Amazon. Here-inafter, the references to dry and rainy seasons are forthis region.

These seasonal time series are then used to identifyvery dry, dry, wet, and very wet conditions in the centraland eastern Amazon during its dry and rainy seasons.Considering one seasonal value per year, the time seriesfor the period from 1931 to 1996 without the 8 mentionedmissing years totalizes 58 values. So, the seasonaltime series are ranked from 1 for the smallest valueto 58 for the largest value. The ranked amounts aredivided by 58. The resulting percentile ranks (R) varyingfrom approximately zero to 1 are then used to classifythe seasonal rainfall. Considering the ranked seasonalprecipitation time series, with one seasonal value peryear, a year is classified as very dry, dry, wet, and verywet if R ≤ 0.15, 0.15 < R ≤ 0.35, 0.65 ≤ R < 0.85,and R ≥ 0.85, respectively. The years when the dryand rainy seasons are classified as very dry, dry, verywet, and wet categories are listed in Tables II and III,respectively.

It is worthwhile mentioning that if one raingauge timeseries is excluded from the areal averaged seasonal pre-cipitation time series, the classification of the result-ing dry and rainy seasons is not altered. However, in

Table II. Years when the dry season is classified as very dry,dry, very wet, and wet categories.

Manaus, Parintins, Itaituba, Santarem – Dry season (JJAS)

Very dry years Dry years Wet years Very wet years

1935 1931 1933 19661936 1932 1934 19701957 1942 1956 19731958 1945 1968 19741961 1946 1971 19751963 1947 1972 19841967 1950 1978 19881976 1954 1981 19891982 1955 1985 1994

1965 19871992 1991

Table III. Years when the rainy season is classified as very dry,dry, very wet, and wet categories.

Manaus, Parintins, Itaituba, Santarem – Rainy season (JFMA)

Very dry years Dry years Wet years Very wet years

1936 1931 1934 19451966 1932 1935 19501973 1940 1944 19621980 1941 1948 19751981 1951 1952 19821983 1954 1955 19841986 1957 1958 19891990 1969 1961 19941992 1974 1964 1996

1978 19711987 1991

order to have a seasonal time series that represents bet-ter regional rainfall, we adopt the areal averaged sea-sonal precipitation time series for all four raingaugestations.

Two-month running mean composites of SST anoma-lies in the tropical sector and of SLP in the global bandbetween 60°N and 60 °S are obtained for the dry, verydry, wet, and very wet categories. The rainy season com-posites span from October/November to March/April,and the dry season composites, from March/April toAugust/September. In order to assess the statistical sig-nificance of the composites, the number of degrees offreedom is the number of years. It is assumed that a vari-able X with n values and S standard deviation shows aStudent-t distribution. So, only composites with absolutevalues exceeding tα(n−1)S/

√(n − 1) are statistically sig-

nificant (Panofsky and Brier, 1968). The confidence level90% is used for both variables.

3. Results

In order to facilitate the discussion, a positive (negative)inter-Pacific-Atlantic anomalous SST gradient refers toan anomalous pattern with a La Nina (El Nino) and anAtlantic El Nino (La Nina). On the other hand, in thetropical Atlantic a positive (negative) inter-hemisphericanomalous SST gradient or warm (cold) dipole refersto an anomalous pattern with positive (negative) SSTanomalies in the TNA and opposite sign anomalies inthe TSA.

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Figure 1. Bi-monthly composites from October/November to March/April for the very dry rainy season case of normalized anomalies of a) SST,and b) SLP. Contour interval is 0.2 standard deviations for both variables with the first contour being of 0.1 for SST and of 0.2 for SLP. Thezero line has been omitted. Negative (positive) contours are dashed (continuous). Dark (light) shaded areas encompass positive (negative) values

which are significant at the 90% confidence level for SST and SLP.

3.1. Rainy season

The very dry rainy season seems to be more stronglymodulated by the tropical Pacific than by the tropi-cal Atlantic. For this case, a strong El Nino patternfor the SST and SLP remains well defined from Octo-ber/November to March/April (Figure 1a) and b)). Dur-ing these months, the largest significant positive SSTanomalies move from the eastern equatorial Pacific to anequatorial band centered at 140 °W, where they weakenslightly in March–April. For this bi-month in particu-lar, non-significant negative SST anomalies are notedin the western equatorial Atlantic. So, a negative inter-Pacific-Atlantic SST gradient mode is established. The

anomalous SST pattern is accompanied by an anoma-lous SLP pattern with significant negative anomaliescentered in the eastern tropical Pacific and the posi-tive ones almost everywhere else in the tropics featuringtwo centers, one over the western Pacific and anotherover the Atlantic-African sector. The significant posi-tive SLP anomalies in the equatorial Atlantic contributeto weaken the Atlantic ITCZ or to maintain it to thenorth of its climatological position. Thus, the dryingeffect of the El Nino is strengthened over the Ama-zon. Therefore, in this case, the El Nino is the mostimportant phenomenon modulating the rainfall over thecentral and eastern Amazon during its rainy season.

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Figure 2. Bi-monthly composites from October/November to March/April for the dry rainy season case, of normalized anomalies of a) SST, andb) SLP. Display is the same as in Figure 1.

This modulation is processed through the El Nino-relateddescending motion over this region, which reduces therainfall over there, as previously shown in many papers(Ropelewski and Halpert, 1987; Aceituno, 1988; Kayanoet al., 1988).

The dry rainy season shows the most significant SSTanomalies in the equatorial Atlantic and TSA sectorswith signs of an Atlantic La Nina (or negative AEM)pattern and significant positive SST anomalies in thewestern TSA during October–November (Figure 2a)).While the significant positive SST anomalies weaken,the Atlantic La Nina pattern becomes better establishedfrom November/December to December/January. Severalauthors have shown that an Atlantic La Nina induces theestablishment of a Pacific El Nino through an east-west

anomalous circulation (Wang, 2006; Kucharski et al.,2007, 2008; Kayano et al., 2010) during the subsequentmonths. This is the case here, as a negative inter-Pacific-Atlantic anomalous SST gradient is established fromJanuary/February to March/April (Figure 2a)). Moreover,signs of significant positive SST anomalies are also notedin the TNA during these bi-months. Although weak,a positive inter-hemispheric SST gradient in the tropi-cal Atlantic is also established from January/February toMarch/April (Figure 2a)). Signs of an east-west anoma-lous SLP gradient between the equatorial Atlantic andcentral eastern Pacific, and a north-south SLP gra-dient between the equatorial Atlantic and TNA areapparent in the SLP composites, in particular duringFebruary–March and March–April months (Figure 2b)).

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Figure 3. Bi-monthly composites from October/November to March/April for the very wet rainy season case, of normalized anomalies of a)SST, and (b) SLP. Display is the same as in Figure 1.

Indeed, weak positive SLP anomalies prevail over theequatorial Atlantic and eastern South America, and sig-nificant negative SLP anomalies are noted over the east-ern tropical Pacific, the western Amazon and part of theTNA, in particular during February–March. So, both thenegative inter-Pacific-Atlantic anomalous SST gradientand the positive inter-hemispheric anomalous SST gradi-ent in the tropical Atlantic contribute to the dry conditionin the central and eastern Amazon, through anomalouseast-west and north-south direct circulations. Consistentwith this result, Kayano et al. (2010) found reduced rain-fall over the central Amazon due to the action of a neg-ative inter-Pacific-Atlantic anomalous SST gradient; andSouza et al. (2000) noted dry conditions over the cen-tral and northern Amazon due to the combined effect of

El Nino and positive inter-hemispheric anomalous SSTgradient.

The very wet rainy season case is also strongly mod-ulated by the anomalous SST conditions in both thetropical Pacific and Atlantic Oceans (Figure 3a) and b)).In this case, a positive inter-Pacific-Atlantic anomalousSST gradient is established from October/November toMarch/April. The main SST anomalous centers with sig-nificant negative anomalies in the eastern Pacific andthe positive ones in the equatorial Atlantic are locatedalong the equatorial band from October/November toJanuary/February. During the following two bi-months,although the main negative center of the equatorial Pacificis located in the central part of this Ocean, significant neg-ative SST anomalies become more intense in the eastern

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Figure 4. Bi-monthly composites from October/November to March/April for the wet rainy season case, of normalized anomalies of a) SST, andb) SLP. Display is the same as in Figure 1.

equatorial Pacific due to the action of a persistent warmAEM mode. This anomalous SST pattern features a posi-tive inter-Pacific-Atlantic anomalous SST gradient whichis associated with an anomalous Atlantic Walker circula-tion, as shown by many authors (Wang, 2006; Kusharskiet al., 2007, 2008, 2009; Losada et al., 2009; Wang et al.,2009). During February–March and March–April, a neg-ative inter-hemispheric anomalous SST gradient is alsoconspicuous (Figure 3a)). The associated SLP anomalouspattern features a La Nina pattern with significant pos-itive anomalies in the eastern tropical Pacific and thenegative ones in the western tropical Pacific in mostbi-months; and an inter-hemispheric anomalous SLP gra-dient with significant positive anomalies in the TNA andthe negative ones in the TSA from December/January to

March/April (Figure 3b)). Thus, the very wet conditionin the central and eastern Amazon is driven by the directeast-west and north-south circulations associated with theSST anomalous patterns in the eastern equatorial Pacificand tropical Atlantic sectors.

The wet rainy season seems to be related to a weakeast-west inter-Pacific-Atlantic anomalous SST gradient(Figure 4a)). Indeed, weak negative SST anomalies per-sist in the eastern tropical Pacific from October/Novemberto March/April. On the other hand, a positive AEM isflanked by significant negative SST anomalies in theTNA and TSA from November/December to Decem-ber/January. Gradually the negative anomalies weakenin the TNA, and a small center with significant positiveSST anomalies locates in the western equatorial Atlantic,

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Figure 5. Bi-monthly composites from March/April to August/September for the very dry dry season case, of normalized anomalies of a) SST,and b) SLP. Display is the same as in Figure 1.

in particular during February–March and March–April.Thus, a weak positive inter-Pacific-Atlantic anomalousSST gradient is established. The associated SLP com-posites show significant positive anomalies in the east-ern central Pacific and over most of the tropical SouthAmerica from October/November to December/January(Figure 4b)). Gradually the significant positive SLPanomalies weaken over South America, in response tothe weakening of the negative SST anomalies in theeastern tropical Pacific. On the other hand, significantnegative SLP anomalies are established over the equa-torial Atlantic and part of tropical South America inMarch–April, in response to the significant positive SSTanomalies located in the western equatorial Atlantic, par-ticularly during February–March and March–April. This

SLP pattern is consistent with a weak positive inter-Pacific-Atlantic anomalous SST gradient during the rainyseason. So, the results here indicate that the intensity ofa positive inter-Pacific-Atlantic anomalous SST gradientis the factor distinguishing between a very wet rainyseason and a wet rainy season. Thus, a weak positiveinter-Pacific-Atlantic anomalous SST gradient is the mainfactor leading to the wet conditions in the central andeastern Amazon during its rainy season.

3.2. Dry season

The very dry dry season case shows a well-definednegative inter-Pacific-Atlantic anomalous SST gradientin most bi-months, in particular from May/June toAugust/September (Figure 5a)). Signs of non-significant

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Figure 6. Bi-monthly composites from March/April to August/September for the dry dry season case, of normalized anomalies of a) SST, andb) SLP. Display is the same as in Figure 1.

positive SST anomalies noted in the TNA from June/Julyto August/September are indicative of a weak posi-tive inter-hemispheric anomalous SST gradient. The SLPanomalous maps also feature a well-defined El Ninopattern, with significant negative anomalies in the east-ern tropical Pacific and the positive ones in the tropicalAtlantic and western tropical Pacific from May/June toAugust/September bi-months (Figure 5b)). The signifi-cant positive SLP anomalies extend over the eastern equa-torial South America in August–September. Thus, theassociated east-west anomalous Atlantic Walker circula-tion, with ascending motion over the eastern equatorialPacific and descending motion extending over the westernequatorial Atlantic and the surrounding central and east-ern Amazon, is the main factor contributing to diminish

the rainfall over this continental area. This result confirmsprevious findings by Kayano et al. (2010) on the relation-ship between the inter-Pacific-Atlantic anomalous SSTgradient and the South American rainfall. It is worthwhilerecalling that the weak positive inter-hemispheric anoma-lous SST gradient in the tropical Atlantic also contributesto dry conditions in the central and eastern Amazon dur-ing its dry season.

The SST composites for the dry dry season featurea positive inter-hemispheric anomalous SST gradient inthe tropical Atlantic with significant negative anomaliesin the equatorial Atlantic and in the TSA, and non-significant positive anomalies in the TNA for mostof the bi-month composites (Figure 6a)). On the otherhand, non-significant small-magnitude SST anomalies

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Figure 7. Bi-monthly composites from March/April to August/September for the very wet dry season case, of normalized anomalies of a) SST,and b) SLP. Display is the same as in Figure 1.

prevail in the tropical Pacific. An inter-hemisphericanomalous SLP gradient consistent with the positiveinter-hemispheric anomalous SST gradient is noted inJune–July composite (Figure 6b)). These anomalous SSTand SLP patterns in the tropical Atlantic have been relatedto the interannual climate variations in northeastern Brazilthrough the dynamics due to the air-sea interactions inthis oceanic sector which affect the position and intensityof the ITCZ (e.g. Moura and Shukla, 1981; Nobre andShukla, 1996). However, more recent studies have shownthat the effect of the ITCZ on the rainfall might extendover the Amazon (Uvo et al., 2000; Ronchail et al.,2002). Therefore, the dry conditions in the central andeastern Amazon during its dry season are mostly related

to the tropical Atlantic SST and SLP inter-hemisphericanomalous patterns.

The SST and SLP patterns for the very wet dryseason case (Figure 7a) and b)) are similar to those ofthe very dry dry season (Figure 5a) and b)), but withopposite signs. So, as in the analysis above, the verywet conditions in the central and eastern Amazon aredetermined by the combined contribution of a positiveinter-Pacific-Atlantic and a negative inter-hemisphericanomalous SST gradient modes. In terms of the SSTanomalies, the former is due to a La Nina and anAtlantic El Nino; and the latter, to the significant negativeSST anomalies in the TNA and the opposite sign SSTanomalies in the TSA. Contrasting with the very dry

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Figure 8. Bi-monthly composites from March/April to August/September for the wet dry season case, of normalized anomalies of a) SST, andb) SLP. Display is the same as in Figure 1.

dry season case, the very wet dry season case showswell-defined inter-hemispheric anomalous SST and SLPgradient patterns in the tropical Atlantic, in particularfrom May/June to August/September. So, both the inter-Pacific-Atlantic and inter-hemispheric anomalous SSTgradient modes contribute to very wet conditions overthe central and eastern Amazon during its dry season.

Similar to the dry dry season case, the wet dry sea-son case shows relatively weak non-significant SSTanomalies in most of the tropical Pacific, and a neg-ative inter-hemispheric anomalous SST gradient withsignificant positive anomalies in the equatorial Atlanticand the negative ones in the TNA (Figure 8a)). Thisinter-hemispheric anomalous SST gradient is particu-larly well-defined from May/June to August/September.Signs of an inter-hemispheric anomalous SLP gradient,

with non-significant negative SLP anomalies in the TSAand significant positive SLP anomalies in the TNA, areapparent in July–August (Figure 8b)). In consequence,the wet condition in the central and eastern Amazonis established by the tropical Atlantic SST and SLPanomalies.

4. Conclusions

The mechanistic relations between the dry, very dry,wet, and very wet conditions in the central and easternAmazon and the SST and SLP variability in the trop-ical Atlantic and Pacific Oceans are analysed for the1931–1996 period. In order to examine the seasonal dif-ferences the dry and wet seasons are analysed separately.

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Table IV. Summary of the results.

Inter-Pacific-Atlantic SST gradient ENSO Inter-hemispheric SST gradient

Very dry rainy season Negative intense El Nino Not observedDry rainy season Negative moderate weak El Nino Positive moderateVery wet rainy season Positive intense intense La Nina Negative intenseWet rainy season Positive weak Not observed Negative weakVery dry dry season Negative intense El Nino Positive intense negative AEMDry dry season Not observed Not observed Positive intense negative AEMVery wet dry season Positive intense La Nina Negative intense positive AEMWet dry season Not observed Not observed Negative moderate

The tropical Pacific and Atlantic Oceans, through theENSO and the Atlantic SST variability modes, haveimportant roles depending on the cases and the seasons.The seasonal differences are in part determined by theseasonal phase locking of these modes. While the maturestage of the ENSO extremes from December to February(Rasmusson and Carpenter, 1982) and the period (australautumn) when the inter-hemispheric mode occurs morefrequently in the tropical Atlantic (Enfield and Mayer,1997) overlap the central and eastern Amazon rainy sea-son, the mature stage of the AEM from June to September(Zebiak, 1993) encompasses the dry season. Thus, oneexpects that the rainy season cases be mostly driven bythe ENSO and by the inter-hemispheric SST mode in thetropical Atlantic and the dry season cases, by the AEM.And truly, these correspondences are noted in most cases(Table IV). For the rainy season, the very dry case ismostly driven by an intense El Nino; the dry and verywet cases coincide, respectively, with the occurrences ofweak El Nino and intense La Nina patterns. Also, forthe dry, very wet, and wet cases of the rainy season, thepositive moderate, negative intense, and negative weakinter-hemispheric SST gradient modes are, respectively,noted (Table IV). For the dry season, the very dry and drycases are both accompanied by an intense negative AEM,and the very wet case, by an intense positive AEM. Theexception seems to be the wet dry season case which ismostly driven by a negative moderate inter-hemisphericSST gradient (Table IV).

The association of the very dry (very wet) rainy seasoncase with the El Nino- (La Nina)- related SST andSLP patterns confirms previous findings that the ENSO-related rainfall variations in the central Amazon regionare noted mostly from June (0) to March (+1), with thesymbols (0) and (+1) referring to the onset and matureENSO phases, respectively (Ropelewski and Halpert,1987, 1989). Yoon and Zeng (2010) also found that thestrongest ENSO influence over the entire Amazon Basinis observed mostly during its rainy season.

On the other hand, the relationships of the dry seasoncases with the AEM confirm previous findings that theAmazon rainfall relation to the tropical Atlantic SSTis mainly noted during the austral autumn (Ronchailet al., 2002). More specifically, Yoon and Zeng (2010)found that the southern Amazon rainfall is strongly

influenced by the TSA SST variability during the wet-to-dry transition season which spans through the australautumn months.

Another interesting result of the present analysis isthe role of the inter-Pacific-Atlantic anomalous SSTgradient mode. Except for the very dry rainy season,the other extreme cases (very wet rainy season, verydry dry season, and very wet dry season) seem to beclosely related to an intense inter-Pacific-Atlantic SSTgradient mode which acts to reinforce the effect of thetropical Atlantic SST anomalous mode (Table IV). Theintense inter-Pacific-Atlantic SST gradient mode is alsoan important factor to distinguish the moderate (wetand dry) cases from the extreme cases (very wet andvery dry). This is particularly noticeable for the dryseason.

The inter-hemispheric and inter-Pacific-Atlantic SSTgradient modes occurring simultaneously have a concor-dant (drying or wetting) effect on the central and easternAmazon region through the direct anomalous circulationin the east-west (Atlantic Walker circulation) and north-south directions. The drying (wetting) effect is due to thedescending (ascending) branch of the east-west and/ornorth-south direct anomalous circulation cells which actto impede (enhance) the tropical convection in the centraland eastern Amazon. These zonal and meridional cir-culation cells are driven by the SST anomalies in thetropical eastern Pacific and tropical Atlantic regions withascending (descending) motions in the areas with positive(negative) SST anomalies. The results here, especially inrelation to the role of the inter-Pacific-Atlantic gradientin the central and eastern Amazon precipitation, have notbeen discussed before and should be taken into accountin the diagnostic activities.

Acknowledgements

The authors thank the Conselho Nacional de Desenvolvi-mento Cientıfico e Tecnologico of Brazil for researchsupport (CNPq, 569749/2008-5 and INCT/CEAB-UEA).All authors were partially supported by the ConselhoNacional de Desenvolvimento Cientıfico e Tecnologicoof Brazil. The authors thank the two anonymous review-ers for their helpful suggestions.

Copyright 2011 Royal Meteorological Society Int. J. Climatol. (2011)

SEASONAL ANOMALOUS RAINFALL IN THE CENTRAL AND EASTERN AMAZON

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