CLIMATOLOGY OF THE SEA SURFACE TEMPERATURE FIELD FOR THE
SOUTHWESTERN ATLANTIC OCEAN.
PEREIRA, CLÁUDIO SOLANO 1
ESPIRITO SANTO, CLOVIS MONTEIRO DO 1
GIAROLLA, EMANUEL 1
ABSTRACT: This paper presents a new climatology of the sea surface temperature (SST) field for
the Southwestern Atlantic oceanic basin (10o S - 30o S, and 30o W - 60o W) corresponding to
Marsden's squares 339, 375, 376, 411, 412, and 413. To build this climatology, ships data stored in
the
National
Bank
of
Oceanographic
Data
(NBOD)
of
the
Brazilian
Navy
(http://www.dhn.mar.mil.br/) for the period from January 1960 to 1996 were used. The data
treatment and analysis procedure used for the calculation of monthly and seasonal means, and the
respective anomalies is presented. For the considered period, spatial distribution maps of number of
observations, monthly, seasonal, and annual means are shown. The low density offshore
observations is evident, emphasizing the necessity to search for another sources of data, as those
supplied by satellites images, in order to complement in site measurements. The SST climatological
mean fields show details of the strong gradients at the South Atlantic Oceanic Confluence Zone
(SAOCZ), which are not usually found in other climatologies as da Silva et al., 1994 from the
Comprehensive Ocean-Atmosphere Data Set (COADS). The SAOCZ seasonal migration is
perfectly identified in the monthly and seasonal maps, as well as the influence during winter of the
shelf waters coming from the Plata Estuary.
RESUMO: Este artigo apresenta uma nova climatologia do campo de temperatura da superfície do
mar (TSM) para a bacia oceânica do Atlântico Sudoeste (10o S – 30o S, e 30o W – 60o W) referentes
aos quadrados de Marsden 339, 375, 376, 411, 412, e 413. Para formar esta climatologia foram
utilizados dados de navios armazenados no Banco Nacional de Dados Oceanográficos da Diretoria
(1) INSTITUTO NACIONAL DE PESQUISAS ESPACIAIS – INPE
CENTRO DE PREVISÃO DO TEMPO E ESTUDOS CLIMÁTICOS - CPTEC
1758, Av. dos Astronautas
C.P. 515
12227-010 S. José dos Campos, SP, BRASIL
Tel. (55)(12) 3945-6657
FAX. (55)(12) 3945-6666
solano@cptec.inpe.br ; clovis@cptec.inpe.br ; emanuel@cptec.inpe.br
2
de Hidrografia e Navegação (BNDO/DHN) (http://www.dhn.mar.mil.br/) no período de 1960 a
1996. São apresentados todos os procedimentos de tratamento e análise de dados para o cálculo das
médias mensais, sazonais, e as respectivas anomalias. Para o período considerado são mostrados os
mapas mensais da distribuição espacial do número de observações, e os mapas das médias mensais,
sazonais e anuais da TSM. Nos mapas de distribuição espacial do número de observações fica
evidente a baixa densidade de observações em regiões fora da costa, enfatizando a necessidade da
recorrência de outras fontes de dados como a fornecida por imagens de satélites. Os campos médios
climatológicos de TSM trazem detalhes dos fortes gradientes na Zona de Confluência Oceânica do
Atlântico Sul (ZCOAS), e que normalmente não são encontrados em outras climatologias como a
de Da Silva et al. (1994) a partir do Comprehensive Ocean-Atmosphere Data Set (COADS). A
migração sazonal da ZCOAS é perfeitamente identificada nos mapas mensais e sazonais, assim
como a influência no inverno das águas de plataforma vindas do Estuário do Prata.
KEYWORDS: COASTAL BOUNDARY LAYER, SST CLIMATOLOGY; SOUTHWESTERN
ATLANTIC; BRAZIL SOUTH AND SOUTHEAST COAST
INTRODUCTION
The Southwestern part of the Atlantic Ocean basin is important for two main aspects: i) it is a
cyclogenetic area (Gan and Rao, 1991), which is sensitive to sea surface temperature (SST)
variations (Diaz et al., 1998); ii) the oceanic circulation between 38 o S and 42o S is dominated by
the confluence of the Brazil and the Malvinas currents. This area is called “South Atlantic Oceanic
Confluence Zone (SAOCZ)” (Martos and Piccolo, 1988; Garzoli and Garraffo, 1989; Gordon,
1989; Matano et al. 1993). The boundary of these two currents is usually associated to high SST
horizontal gradients reaching values as high as 1o C/100m (Gordon and Greengrove, 1986; Olson et
al., 1988). The SAOCZ migration to the North and to the South along the continental shelf ,
extending up to 500 km (38o S – 42o S), occurs from the seasonal to the interanual time scales
(Provost et al., 1992; Matano et al., 1993). In general, this migration causes impacts in the
atmosphere, with effects on the cyclogenesis and the regional distribution of precipitation (Olson et
al., 1988; Garzoli and Garraffo, 1989; Venegas et al., 1997 a,b ; Diaz et al., 1998).
Garzoli (1999) studied the relationships between the SST patterns in the area of SAOCZ and
the precipitation records in Uruguay, using the principal components analysis, and concluded that
these fields are highly coherent (correlations larger than 0,8), with 90o phase lags. It was also seen
that an anomalous heating in December 1989 preceded a period of intense precipitation extending
3
until the end of April 1990. At the end of this rainy period, Southwestern Atlantic SST was
abnormally colder (SSTA exceeded -6o C).
Many researchers, as Diaz et al., 1998; Grimm et al, 1998; Silva, 2001, stands out the
importance of studying the influence of the spatial and temporal SST variability in South Atlantic,
especially in the Southwestern part of the basin, on the precipitation regime in the whole southsoutheast coastal area of Brazil, that affects the climate and, consequently, the life conditions on the
most densely inhabited region of South America (SACC Document, 1996). However, in spite of
this importance, there are few works presenting a climatology of this oceanic area for several
meteorological and oceanographic variables.
To produce a monthly climatology for the 12-yr period, from January 1982 through December
1993, Reynolds and Smith (1995) blended in situ (ship and buoy) SST data, from the
Comprehensive Ocean-Atmosphere Data Set (COADS) for the period 1950-1979, which was
supplemented by four years of satellite retrieval (1982-1985), and 10 years of sea ice data, and
make a higher-resolution optimum interpolation on a 1o grid.
Specifically for SST, using ship observations over the area between 17 o S to 30o S and 30o W
to 49o W for the period 1957 to 1995, Melo and Oda (1998) presented the SST distribution of the
Southwestern Atlantic, and compared to the Levitus (1987), and to the Reynolds and Smith (1995 )
climatologies . In spite of the lack of information, mainly in areas farther from coast, they verified
that these climatologies agree well.
In order to provide this oceanic area with a detailed SST climatology and its associated
anomalies, the present work intends to make a climatology using exclusively in situ data,
objectively verified and corrected, of dense gridding (1o x 1o), and inside the area between latitudes
10o S to 40o S, and the longitudes 30o W to 60o W. All the procedures developed for the data
treatment are presented. The monthly, seasonal and annual means SST fields, and the respective
SSTA of the Southwestern Atlantic are characterized for the period from 1960 to 1996. The
monthly distributions of the surface observations are presented in such a way that allows a
comparison with other climatologies.
DATA , PROCEDURE AND DEFINITIONS
Data
The ship SST dataset used in this work was supplied by the National Bank of Oceanographic
Data (NBOD) of the Brazilian Navy. The information about position of the ship, year, month, day,
hour, and the measured value of the variable registered, are divided into geographical areas of 10o
of latitude by 10o of longitude, denominated “Marsden´s Squares (MQ)”. In this work, SST data for
4
the 339, 375, 376, 411, 412 and 413 MQ, encompassing the oceanic area of 10o S–40o S, and 30o
W–60o W, for the period 1960 to 1996, were used.
Procedure
The procedure used for data treatment is enumerated bellow in order to clarify the sequence of
calculations done:
1) basic automatic preprocessing seeks mistakes on annotation of the records with respect to the
format, the position (lat. and long.), and duplicated records. If an error on data is identified and
its cause is easily recognized, the record may be corrected; otherwise it is rejected completely.
2) each MQ is divided into 1o X 1o sub-squares numbered from 00 to 99, and depending on the
latitude and longitude, a sub-square number is associated to each record. The test of the
acceptable physical limits is accomplished for each variable, which in the case of SST a value of
3o C is established for the minimum, and 33o C for the maximum. Values outside of this range
are completely rejected.
3) the number of SST observations on each sub-square for each month during the whole period are
evaluated in order to generate maps of density observations.
4) the data are sorted by sub-square number followed by time, both in ascending order. Once the
file is ordered in position and time it is verified for each sub-square the occurrence of more than
one observation in the same day. If so the arithmetic mean of the observations is considered and
the observation time is set to 12:00h.
5) the monthly and seasonal means are calculated for each sub-square, assuming that these means
are representative of the central point of these sub-squares. The monthly and seasonal means are
weighted using the number of observations done in each month. The austral seasons relate the
following months, respectively:
Summer: January, February, March
Autumn: April, May, June
Winter: July, August, September
Spring: October, November, December
6) monthly and seasonal climatological means for the period 1960 to 1996, for each sub-square,
with at least one measurement are calculated.
7) the climatological mean and the respective standard deviation () for each register are calculated.
Those registers with deviations greater than 3* are automatically discarded.
8) the procedures (5) and (6) are then repeated with the new debugged data file.
5
To make the SST monthly and seasonal fields, the triangulation with linear interpolation was
used. This algorithm presented in Guibas and Stolfi (1985) is implemented in the SURFER
software. To perform the SST analysis along the transects, the Kriging interpolation method was
used (de Marsily, 1989). On these generated maps a visual inspection is made to verify the
consistence of the fields, and if corrections are needed. This visual technique allows corrections to
avoid unreal physical gradients. It is worth to point out that no smoothing techniques were applied
to the SST fields, in order to preserve the strong spatial and temporal gradients, which is a common
characteristic of this oceanic area.
RESULTS
Climatological Means
Figure 1 shows the Brazilian S-SE sea coast extending from 12o S to 33o S, including the
States of Espírito Santo (ES), Rio de Janeiro (RJ), São Paulo (SP), Paraná (PR), Santa Catarina (SC)
e Rio Grande do Sul (RS). At the Southeast of Rio Grande do Sul, the Brazilian most important
lakes region are located. It is composed of two extense coastal lagoons and a sort of smaller ones:
the “Lagoa dos Patos” (the more extense with 50 Km of mean width and 250 Km in length) and the
“Lagoa Mirim” (located in the border of Brazil and Uruguay). One see part of the Southeast of the
South America with Uruguay , Argentine , and Paraguay which are neighbors to some of the
South Brazilian States, the Plata Estuary, and the Marsden’s Squares (MQ) considered for analysis,
with their assigned numbers. Each 10o x 10o MQ is divided for analysis, into one hundred of 1o x 1o
blocks size. This figure also shows three transect lines (TR1, TR2, TR3) which are chosen parallel
to the coast and about 4o from each other. They range from 20o S to 40o S, because this latitude
interval characterizes the coastal S-SE region of Brazil.
-10
MQ339
-15
ES
BRAZIL
-25
Y
A
U
G
RA
PA
Latitude (S)
-20
RJ
SP
PR
MQ375
MQ376
SC
RS
-35
ARGENTINE
-30
-40
-60
URUGUAY
Pla
ta E
stu
ary
-55
MQ412
MQ411
MQ411
-50
-45
-40
-35
-30
Longitude (W)
Figure1. Map showing the six Mardsden's squares (MQ) in the Southern Atlantic, the S-SE Brazilian states,
Paraguay, Uruguay, North of Argentine litoral region, and the Plata Estuary, as mentioned in the text.
Rio Grande do Sul (RS), Santa Catarina (SC), Paraná (PR), São Paulo (SP), Rio de Janeiro (RJ)
and Espírito Santo (ES) are the six coastal S-SE Brazilian states. Also shown are the three transects
and the dashed isoline corresponding to the oceanic depth of 200 meters.
6
Figure 2 shows the spatial distribution of the number of available observations in each subsquare, for each month in the whole period (1960-1996).
-10
-15
1 to 40
40 to 80
80 to 200
200 to 400
400 to 800
800 to 1600
(64
( 9
( 7
( 7
( 7
( 6
%)
%)
%)
%)
%)
%)
(57
(18
( 6
( 6
( 9
( 4
%)
%)
%)
%)
%)
%)
(56
(17
( 8
( 4
(10
( 5
%)
%)
%)
%)
%)
%)
1 to 40
40 to 80
80 to 200
200 to 400
400 to 800
800 to 1600
JAN
(59
(13
(11
( 9
( 4
( 4
%)
%)
%)
%)
%)
%)
(54
(14
(12
( 7
( 9
( 4
%)
%)
%)
%)
%)
%)
(62
(10
(10
( 6
( 7
( 5
%)
%)
%)
%)
%)
%)
FEB
-20
-25
-30
-35
-40
-60
-10
-15
-55
1 to 40
40 to 80
80 to 200
200 to 400
400 to 800
800 to 1600
-50
-45
-40
-35
-30
-55
1 to 40
40 to 80
80 to 200
200 to 400
400 to 800
800 to 1600
MAR
-50
-45
-40
-35
-30
-40
-35
-30
-40
-35
-30
APR
-20
-25
-30
-35
-40
-60
-10
-15
-55
1 to 40
40 to 80
80 to 200
200 to 400
400 to 800
800 to 1600
-50
-45
-40
-35
-30
-55
1 to 40
40 to 80
80 to 200
200 to 400
400 to 800
800 to 1600
MAY
-50
-45
JUN
-20
-25
-30
-35
-40
-60
-55
-50
-45
-40
-35
-30
-55
-50
-45
7
-10
-15
1 to 40
40 to 80
80 to 200
200 to 400
400 to 800
800 to 1600
(64
(10
( 7
( 8
( 6
( 5
%)
%)
%)
%)
%)
%)
(53
(19
( 9
( 5
( 8
( 6
%)
%)
%)
%)
%)
%)
(60
(14
( 4
( 9
( 6
( 7
%)
%)
%)
%)
%)
%)
1 to 40
40 to 80
80 to 200
200 to 400
400 to 800
800 to 1600
JUL
(60
(10
(10
( 7
( 7
( 6
%)
%)
%)
%)
%)
%)
(58
(13
( 8
( 7
( 9
( 5
%)
%)
%)
%)
%)
%)
(60
(11
(10
( 6
( 8
( 5
%)
%)
%)
%)
%)
%)
AUG
-20
-25
-30
-35
-40
-60
-10
-15
-55
-50
1 to 40
40 to 80
80 to 200
200 to 400
400 to 800
800 to 1600
-45
-40
-35
-30
-55
1 to 40
40 to 80
80 to 200
200 to 400
400 to 800
800 to 1600
SEP
-50
-45
-40
-35
-30
-40
-35
-30
-40
-35
-30
OCT
-20
-25
-30
-35
-40
-60
-10
-15
-55
-50
1 to 40
40 to 80
80 to 200
200 to 400
400 to 800
800 to 1600
-45
-40
-35
-30
-55
1 to 40
40 to 80
80 to 200
200 to 400
400 to 800
800 to 1600
NOV
-50
-45
DEC
-20
-25
-30
-35
-40
-60
-55
-50
-45
-40
-35
-30
-55
-50
-45
Figure 2. Spatial distribution of the number of observations on each month at each Marsden´s subsquare. The NBOD data set is for the period 1960-1996.
For the whole South-Southeast coast of Brazil, the region near the shore presents larger
density of observations, with sub-squares presenting more than 80 observations in the period 196096 on each month, decreasing as one goes towards open sea. During the analyzed period, the
squares 376 (20o–30o S; 40o–50o W) and 339 (10o–20o S; 30o–40o W) present larger density of
observations, and along the littoral zone of the states Rio de Janeiro and Espirito Santo (18o S to 23o
S, approximately) the density is greater than 400 observations by month. Out the total of 600 sub-
8
squares only 13 (~ 2%) usually present more than 400 observations on every months, with
prevalence in summer months. The density of observations gets even lower below 30o S, among the
meridians 30o W and 45o W, corresponding to MQ 411 and 412.
Figure 3 shows the time series of the number of trimonthly observations during the period
1960-1996 along TR1, TR2, TR3 transects. It is evident in this figure the scarcity of data on the SW
Atlantic region, mainly farther from the coast (TR3 transect). Along the TR1 transect, closer to the
coast, mainly in the littoral of ES, RJ, and SP States, there is a reasonable number of SST
observations, which can be used confidently as the base of a data bank. One surprising aspect is the
total absence of data during the 1970 decade, along all the observed transect lines. An inventory to
the NBOD data set should be made to realize the reason to this lack of data during this extensive
period of time.
-20
-20
Latitude
TR1
-25
-25
-30
-30
-35
-35
-40
-20
-40
60
65
70
75
80
YEAR
85
90
95
-20
Latitude
TR2
-25
-25
-30
-30
-35
-35
-40
-20
-40
60
65
70
75
80
YEAR
85
90
95
-20
Latitude
TR3
-25
-25
-30
-30
-35
-35
-40
-40
60
65
70
75
1
2
4
15
85
>
90
95
90 to 270
45 to 90
12 to 45
6 to 12
3 to 6
1 to 3
<
80
YEAR
1
-2
-4
-1
5
-3
0
( Observations / month )
30
Figure 3. Number of registered observations on each trimester during the period 1960-1996, along
the three transects (TR1, TR2 and TR3).
Figure 4 shows the mean SST and standard deviation fields for the Southwestern Atlantic, for
the whole period of analysis (1960 – 1996). A general characteristic seens at all latitudes is that
along a fixed latitude line, the water gets warmer when moving from the open sea to the border of
the continental platform. Also, starting at 30o S latitude to the South direction strong meanders
appear, which should be associated to SAOCZ. Most of the area shows a SST standard deviation
9
lower than 2.0o C. SST standard deviation in the 2o – 3o C interval and at even higher values occurs
at few blocks, probably representing regions with very scarce “in situ” measurements.
-10
-10
Annual
Climatology
-15
Annual SST
Standard Deviation ( C) o
-15
-20
-20
)S
(
ed
u -25
ti
atL
-25
-30
-30
-35
-35
-60
-55
8
-50
12
-45
Longitude (W)
16
20
-40
24
-35
28
-60
-55
0
-50
1
-45
Longitude (W)
2
3
-40
4
-35
6
Figure 4. Annual SST mean and standard deviation (oC) for the period 1960-1996.
The annual movement of the SST gradient in Southwestern Atlantic is well evidenced in
Figure 5 where maps of SST seasonal means are presented. It is difficult to realize any seasonal
variations due to the low densities of data involved, mainly in MQ 411 and 412. In most of these
sub-squares the SST values are interpolated in space, mainly during winter and spring seasons. But
it is worth-while to note the meridian oscillation of the temperature gradients, which characterizes
the well known Brazilian Current: the intrusion of cold waters coming from the South of Plata
Estuary, during winter and spring, running Northward very close to the sea coast. The seasonal
migration of SAOCZ (Tseng et al., 1977; Olson et al., 1988; SACC, 1996; Zavialov et al., 1998) is
represented in this climatology by the southern displacement of the intense SST gradients.
10
-10
SUMMER
-15
AUTUMN
Latitude (S)
-20
-25
-30
-35
-10
WINTER
-15
SPRING
Latitude (S)
-20
-25
-30
-35
-60
-55
-50
-45
Longitude (W)
-40
8
-35
12
16
-60
20
-55
24
-50
-45
Longitude (W)
-40
-35
28
o
Figure 5. Seasonal mean SST ( C) for the period 1960-1996.
Figure 6 shows the monthly mean SST fields with more details than usually found in other
climatologies, as for instance, the COADS (Da Silva et al., 1994), which also uses resolution of 1 o x
1o, or the one specifically used for the oceanic area of the Southwestern Atlantic Ocean expressed
in the works of Zavialov et al. (1998, 1999 and 2002), whose region is considered here in this work.
Maps of monthly SST and standard deviation are shown side by side to quantify the monthly SST
variability in the Southwestern Atlantic Ocean.
11
-10
Climatology
JANUARY
SST Standard Deviation
JANUARY
Climatology
FEBRUARY
SST Standard Deviation
FEBRUARY
Climatology
MARCH
SST Standard Deviation
MARCH
Climatology
APRIL
SST Standard Deviation
APRIL
March
Climatology
Climatology
MAY
SST Standard Deviation
MAY
-15
Latitude (S)
-20
-25
-30
-35
-10
-15
Laitude (S)
-20
-25
-30
-35
-10
-15
Climatology
JUNE
SST Standard Deviation
JUNE
Latitude (S)
-20
-25
-30
-35
-60
8
-55
12
-50
16
-45
Longitude (W)
20
-40
24
-60
-35
28
-55
0
-50
1
2
-45
Longitude (W)
3
-40
4
-35
6
-60
-55
8
12
-50
16
-45
Longitude (W)
20
-40
24
-35
-60
28
-55
0
-50
1
2
-45
Longitude (W)
3
-40
4
-35
6
12
-10
Climatology
JULY
SST Standard Deviation
JULY
Climatology
AUGUST
SST Standard Deviation
AUGUST
Climatology
SEPTEMBER
SST Standard Deviation
SEPTEMBER
Climatology
OCTOBER
SST Standard Deviation
OCTOBER
-15
Latitude (S)
-20
-25
-30
-35
-10
-15
Latitude (S)
-20
-25
-30
-35
-10
Climatology
DECEMBER
SST Standard Deviation
NOVEMBER
Climatology
NOVEMBER
-15
SST Standard Deviation
DECEMBER
Latitude (S)
-20
-25
-30
-35
-60
8
-55
12
-50
-45
Longitude (W)
16
20
-40
-35
24
-60
-55
-50
-45
Longitude (W)
-40
-35
-60
0
1
2
3
4
6
8
-55
12
-50
-45
Longitude (W)
16
20
-40
-35
24
-60
-55
-50
-45
Longitude (W)
0
1
2
3
-40
-35
4
6
Figure 6. Monthly mean SST and standard deviation (oC). The NBOD data set is for the period
1960-1996.
The warm and cold oceanic currents are indicated by zones of strong SST gradients along the
continental borders, associated to Brazil (BC) and
Malvinas (MC) currents, and to the cold
platform waters coming from the Plata Estuary. One may notice that on February the waters with
SST above 24o C reach up to about 35o S, as BC representative. On May-June, with the weakness of
the winds over South Atlantic Ocean basin, there is a reduction in the intensity of the large oceanic
gyre with the consequent weakness and retraction of the BC (Stramma, 1987; Peterson and
Stramma, 1991; Matano et al., 1993). This retraction with maximum in August-September can be
observed in the displacement of cold waters (values lesser than 18o C) toward north. With the
weakness of the BC, cold waters associated to the MC and the coastal waters from the Plata Estuary
penetrate into continental platform and, in the transition boundary, intense gradients of SST appear
evidencing the SAOCZ. These SST gradients show an annual cycle associated with a smaller
horizontal contrast of temperature during the summer months.
The whole oceanic area shows an uniform distribution of SST standard deviation values,
except a small region near the Plata Estuary with standard deviation values greater than 3 o C
13
occurring mainly on December. It is also evident that during months from June to November the
sea-shore waters are well colder than the waters far from the coast.
CONCLUSIONS
The results presented in this work showed that the supplied NBOD data set bring information
on details of the SST field for the Southwestern Atlantic oceanic basin, which in general, are not
found in other climatological databases. This new group of SST climatological data, that evidences
the strong gradients in the SAOCZ area , can contribute to the improvement of climatic models
results, especially for the Brazilian South-Southeast coastal area.
The time series of SST anomalies along the transect lines, reinforce the fact that in the
Southwestern Atlantic the SST is predominantly seasonal and the SSTA is relatively weak,
comparing to other Oceans. Along the TR1 line, with more data availability, most of the SST
anomaly values are in the interval  2o C. Based on the time distribution of oceanic observations on
the SW Atlantic Ocean, any research involving measured SST, may rely only on time series after
1980, and even so, being careful when dealing with far from coastal regions like the TR3 transect
line.
Acknowledgements. The authors thank the National Bank of Oceanographic Data for the supply of
the data and to FAPESP for the financial support to the project “Synoptic Climatology of the
South-Southeast Brazilian Coastal Area” (Process 98/04332-6).
REFERENCES
Da Silva, A. M., Young, C., Levitus, S., 1994. Atlas of Surface Marine Data 1994. NOAA Atlas
NESDIS 6, U.S. Department of Commerce, NOAA, NESDIS.
De Marsily, G., 1989. Geostatistic and Stochastic Approach in Hidrogeology. In Academic Press,
Inc.(Ed.), Quantitative Hydrogeology – Groundwater Hydrology for Engineers, chap. 11, 284337.
Diaz, A.F., Studzinski, C.D., Mechoso, C.R., 1998. Relationships between precipitation anomalies
in Uruguay and Southern Brazil and sea surface temperature in the Pacific and Atlantic
Oceans. Journal of Climate, 11(2), 251-271.
Gan, M.A., Rao,V.B., 1991. Surface cyclogenesis over South America. Monthly Weather Review
119 (5), 1293-1302.
Garzoli, S. L., 1999. The relevance of the South Atlantic for climate studies. Clivar Exchanges 4(3),
35-38.
14
Garzoli, S. L., Garrafo, Z., 1989. Transports, frontal motions and eddies at the Brazil-Malvinas
currents confluence. Deep-Sea Research 36 (5A), 681-703.
Gordon, A.L., 1989. Brazil-Malvinas confluence – 1984. Deep Sea Research 36 (3A), 359-405.
Gordon, A.L., Grenngrove, C. L., 1986. Geostrophic circulation of the Brazil-Falkland confluence.
Deep-Sea Research 33 (5A), 573-585.
Grimm, A.M., Ferraz, S.E.T., Gomes, J., 1998. Precipitation anomalies in Southern Brazil
associated with El Niño and La Niña events. Journal of Climate, 11 (10), 2863-2880.
Guibas, L., Stolfi, J., 1985. Primitives for the manipulation of general subdivisions and the
computation of Voronoi Diagrams. ACM Transactions on Graphics 4(2), 74-123.
Levitus, S. A., 1987. A comparison of the annual cycle of two sea surface temperatures
climatologies of the world ocean. Journal of Physical Oceanography 17(2), 197-214.
Martos, P., Piccolo, M.C., 1988. Hydrography of the Argentine continental shelf between 38o S and
42o S. Continental Shelf Research 8(9), 1043-1056.
Matano, R. P., Schlax, M. G., Chelton, D. B., 1993. Seasonal variability in the Southwestern
Atlantic. Journal of Geophysical Research 98 (C10), 18027-18035.
Melo, G. V., Oda, T. O., 1998. Distribuição de temperatura da superfície do mar na região Sudeste
do Brasil. X Congresso Brasileiro de Meteorologia, Brasília (DF), Brazil, unpublished.
Olson, D.B., Podesta, G.P., Evans, R.H., Brown, O.B., 1988. Temporal variations in the separation
of Brazil and Malvinas currents. Deep-Sea Research 35 (12), 1971-1990.
Peterson, R.G., Stramma, L., 1991: Upper-level circulation in the South Atlantic Ocean. Progress in
Oceanography 26(1), 1-73.
Provost, C., Garcia, O., Garcon, V., 1992. Analysis of satellite sea surface temperature time series
in the Brazil Malvinas Currents Confluence region: Dominance of the annual and semiannual
periods. Journal of Geophysical Research 97 (C11), 17.841-17.858.
Reynolds, R. W., Smith, T. M.,1995. A high resolution global sea surface temperature climatology.
Journal of Climate, 8(6), 1571-1583..
SACC (South Atlantic Climate Change) Document, 1996. NOAA/AOML/PhOD Report. Web site:
http:/www.oce.orst.edu/po/research/matano2/index.html.
Silva, I. R., 2001. Variabilidade sazonal e interanual das precipitações na região Sul do Brasil
associadas às temperaturas dos oceanos Atlântico e Pacífico. MsC Dissertation, INPE, S. José
dos Campos, 90pp., unpublished.
Stramma, L., 1987. The Brazil current transport South 23o S. Deep-Sea Research 36(4A), 639-646.
Tseng, Y. C., Inostroza, H. M., Kumar, R., 1977. Study of the Brazil and Falkland currents using
THIR images of Nimbus V and oceanographic data in 1972 to 1973. Proceedings of Eleven
15
International Symposium in Remote Sensing of Environment, vol. II, 25-29 April, 1977, 859871.
Venegas, S. A., Mysak, L.A., Straub, D., 1997a. Evidence for interanual and interdecadal climate
variability in the South Atlantic. Geophysical Research Letters 23, 2673-2676.
Venegas, S. A., Mysak, L.A., Straub, D., 1997b. Atmosphere-Ocean coupled variability in the
South Atlantic. Journal of Climate 10(11), 2904-2920.
Zavialov, P.O., Ghisolfi, R. D., Garcia, C. A. E., 1998. An inverse model for seasonal circulation
over the Southern Brazilian shelf: Near-surface velocity from the heat budget. Journal of
Physical Oceanography 28(4), 545-562.
Zavialov, P.O., Möller, O. Jr., Campos, E., 2002. First direct measurements of currents on the
continental shelf of Southern Brazil. Continental Shelf Research 22(14), 1975-1986.
Zavialov, P.O., Wainer, I., Absy, J.M., 1999. Sea surface temperature variability off southern Brazil
and Uruguay as revealed from historical data since 1854. Journal of Geophysical Research,
104(C9), 21,021-21,032.