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Influences of strong and moderate ENSO events on the Maranhão precipitation from the western equatorial Atlantic SST anomalies

Abstract

This study analyzed the influence of strong and moderate El Niño-Southern Oscillation (ENSO) events on the seasonal and interannual variabilities of the sea surface temperature (SST) in the Western Equatorial Atlantic (WEA) Ocean and how the precipitation over the state of Maranhão, in Brazil, responds to the zonal teleconnection. To evaluate the ENSO magnitude and phase in the four Niño regions (1+2, 3, 3.4, and 4), the SODA 3.3.1 oceanic reanalysis database for the period from 1980 to 2015 was used. Our results showed that the La Niña phase with moderate magnitude was the most predominant among the 70 events analyzed, with Niño 3.4 presenting the highest number (20) of ENSO events (both positive and negative phases). At lag = 0, we found that significant negative correlations prevailed between the WEA SST anomalies and ENSO index, with the region of Niño 3.4 showing the most significant correlations (r = −0.25). The whole events of El Niño and La Niña were, respectively, accompanied by a cooling and a heating of up to −0.6°C or +0.8°C in the WEA Ocean. The WEA SST anomalies during El Niño and La Niña events have, respectively, reduced and increased the precipitation in Maranhão around ± 100 mm in a quarter. Strong El Niño events influence a greater precipitation deficit in Maranhão than moderate El Niño events. Moderate La Niña events have more pronounced influence on the precipitation over Maranhão than strong La Niña events do, especially on the negative anomalies. Our results showed that the central, northern, and eastern tip sectors of the state are the most affected by this zonal teleconnection. We concluded that ENSO’s significant influences on the WEA SST seasonal variability, added to the performance of the Atlantic Meridional Mode (Soares, 2019Soares, L. A. M. 2019. Influência de teleconexão Pacífico–Atlântico e de modos locais na variabilidade da temperatura da superfície do mar do Atlântico Equatorial Ocidental e impactos sobre a precipitação no estado do Maranhão (mathesis). Universidade Federal do Maranhão, São Luís.), determine the quality of the rainy season (March–April–May) in the state of Maranhão.

Keywords:
El Niño; Interannual Variability; Zonal Teleconnection; Maranhão Climate; Precipitation Variability

INTRODUCTION

The El Niño-Southern Oscillation (ENSO) is the main variability mode of the global coupled climate system (Cai et al., 2020Cai, W., McPhaden, M. J., Grimm, A. M., Rodrigues, R. R., Taschetto, A. S., Garreaud, R. D., Dewitte, B., Poveda, G., Ham, Y.-G., Santoso, A., Ng, B., Anderson, W., Wang, G., Geng, T., Jo, H.-S., Marengo, J. A., Alves, L. M., Osman, M., Li, S., Wu, L., Karamperidou, C., Takahashi, K. & Vera, C. 2020. Climate impacts of the El Niño–Southern Oscillation on South America. Nature Reviews Earth &\mathsemicolon Environment, 1(4), 215–231. DOI: https://doi.org/10.1038/s43017-020-0040-3
https://doi.org/10.1038/s43017-020-0040-...
), being configured by sea surface temperature (SST) anomalous patterns in the central-east Equatorial Pacific Ocean, with El Niño and La Niña characterizing, respectively, the warm and cold phases, with warming and cooling over this region. The oceanic component of ENSO is associated with anomalous sea level pressure (SLP) patterns in the Indo-Pacific region (Trenberth, 1984Trenberth, K. E. 1984. Signal versus noise in the Southern Oscillation. Monthly Weather Review, 112(2), 326–332.) that lead to precipitation extremes in several regions of the globe, such as South America (Carton et al., 1996Carton, J. A., Cao, X., Giese, B. S. & Silva, A. M. D. 1996. Decadal and Interannual SST Variability in the Tropical Atlantic Ocean. Journal of Physical Oceanography, 26(7), 1165–1175.; Stone et al., 1996Stone, R. C., Hammer, G. L. & Marcussen, T. 1996. Prediction of global rainfall probabilities using phases of the Southern Oscillation Index. Nature, 384(6606), 252–255. DOI: https://doi.org/10.1038/384252a0
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; Fontana and Berlato, 1997Fontana, D. C. & Berlato, M. A. 1997. Influência do El Niño Oscilação Sul sobre a Precipitação do Estado do Rio Grande do Sul. Revista Brasileira de Agrometeorologia, 5(1), 127–132.; Andreoli et al., 2016Andreoli, R. V., Oliveira, S. S. de, Kayano, M. T., Viegas, J., Souza, R. A. F. de & Candido, L. A. 2016. The influence of different El Niño types on the South American rainfall. International Journal of Climatology, 37(3), 1374–1390. DOI: https://doi.org/10.1002/joc.4783
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). Some studies have shown that ENSO influences significantly the interannual variability of the Tropical Atlantic (TA) Ocean (Saravanan and Chang, 2000Saravanan, R. & Chang, P. 2000. Interaction between tropical Atlantic variability and El Niño–Southern Oscillation. Journal of Climate, 13(13), 2177–2194.; Münnich and Neelin, 2005Münnich, M. & Neelin, J. D. 2005. Seasonal influence of ENSO on the Atlantic ITCZ and equatorial South America. Geophysical Research Letters, 32(21). DOI: https://doi.org/10.1029/2005gl023900
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; Rodrigues et al., 2011Rodrigues, R. R., Haarsma, R. J., Campos, E. J. D. & Ambrizzi, T. 2011. The Impacts of Inter–El Niño Variability on the Tropical Atlantic and Northeast Brazil Climate. Journal of Climate, 24(13), 3402–3422. DOI: https://doi.org/10.1175/2011jcli3983.1
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; Rodríguez-Fonseca et al., 2016Rodríguez-Fonseca, B., Suárez-Moreno, R., Ayarzagüena, B., López-Parages, J., Gómara, I., Villamayor, J., Mohino, E., Losada, T. & Castaño-Tierno, A. 2016. A Review of ENSO Influence on the North Atlantic. A Non-Stationary Signal. Atmosphere, 7(7), 87. DOI: https://doi.org/10.3390/atmos7070087
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; Lübbecke et al., 2018Lübbecke, J. F., Rodríguez-Fonseca, B., Richter, I., Martín-Rey, M., Losada, T., Polo, I. & Keenlyside, N. S. 2018. Equatorial Atlantic variability—Modes, mechanisms, and global teleconnections. WIREs Climate Change, 9(4). DOI: https://doi.org/10.1002/wcc.527
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). The three main regions influenced by the ENSO are the North Tropical Atlantic (NTA), the Equatorial Atlantic, and the South Tropical Atlantic (STA) (Enfield and Mayer, 1997Enfield, D. B. & Mayer, D. A. 1997. Tropical Atlantic sea surface temperature variability and its relation to El Niño-Southern Oscillation. Journal of Geophysical Research: Oceans, 102(C1), 929–945. DOI: https://doi.org/10.1029/96jc03296
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; Huang et al., 2004Huang, B., Schopf, P. S. & Shukla, J. 2004. Intrinsic Ocean–Atmosphere Variability of the Tropical Atlantic Ocean. Journal of Climate, 17(11), 2058–2077.).

Associated with the seasonal cold tongue development, the Atlantic Equatorial Mode, also known as Atlantic Niño due to its similarity with ENSO, is a dominant mode of interannual variability in the TA region (Servain et al., 1982Servain, J., Joël Picaut & Merle, J. 1982. Evidence of Remote Forcing in the Equatorial Atlantic Ocean. Journal of Physical Oceanography, 12(5), 457–463., 1999Servain, J., Wainer, I., McCreary, J. P. & Dessier, A. 1999. Relationship between the equatorial and meridional modes of climatic variability in the tropical Atlantic. Geophysical Research Letters, 26(4), 485–488. DOI: https://doi.org/10.1029/1999gl900014
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; Zebiak, 1993Zebiak, S. E. 1993. Air–Sea Interaction in the Equatorial Atlantic Region. Journal of Climate, 6(8), 1567–1586.; Chang et al., 2006Chang, P., Fang, Y., Saravanan, R., Ji, L. & Seidel, H. 2006. The cause of the fragile relationship between the Pacific El Niño and the Atlantic Niño. Nature, 443(7109), 324–328. DOI: https://doi.org/10.1038/nature05053
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; Lübbecke and McPhaden, 2012Lübbecke, J. F. & McPhaden, M. J. 2012. On the Inconsistent Relationship between Pacific and Atlantic Niños. Journal of Climate, 25(12), 4294–4303. DOI: https://doi.org/10.1175/jcli-d-11-00553.1
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). The Atlantic Equatorial Mode has been recognized since the 1980’s (Merle et al., 1980Merle, J., Fieux, M. & Hisard, P. 1980. Annual signal and interannual anomalies of sea surface temperature in the eastern equatorial Atlantic Ocean. In: Oceanography and Surface Layer Meteorology in the B/C Scale (pp. 77–101). Amsterdam: Elsevier. DOI: https://doi.org/10.1016/b978-1-4832-8366-1.50023-6
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; Servain et al., 1982Servain, J., Joël Picaut & Merle, J. 1982. Evidence of Remote Forcing in the Equatorial Atlantic Ocean. Journal of Physical Oceanography, 12(5), 457–463.; Hirst and Hastenrath, 1983Hirst, A. C. & Hastenrath, S. 1983. Atmosphere-Ocean Mechanisms of Climate Anomalies in the Angola-Tropical Atlantic Sector. Journal of Physical Oceanography, 13(7), 1146–1157.; Philander, 1986Philander, S. G. H. 1986. Unusual conditions in the tropical Atlantic Ocean in 1984. Nature, 322(6076), 236–238. DOI: https://doi.org/10.1038/322236a0
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). According to Hounsou‑Gbo et al. (2020Hounsou-Gbo, A., Servain, J., Junior, F. das C. V., Martins, E. S. P. R. & Araújo, M. 2020. Summer and winter Atlantic Niño: connections with ENSO and implications. Climate Dynamics, 55(11–12), 2939–2956. DOI: https://doi.org/10.1007/s00382-020-05424-x
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), there are two types of Atlantic Niño, which are significantly anti-correlated with ENSO and quite relevant for its predictability from 6 months to 1 year.

One of the mechanisms for climate signal transfer from the Pacific to the Atlantic basin occurs in the tropics through zonal SLP and wind anomalies associated with the Walker and Hadley cells (Kidson, 1975Kidson, J. W. 1975. Tropical Eigenvector Analysis and the Southern Oscillation. Monthly Weather Review, 103(3), 187–196.; Zhou and Lau, 2001Zhou, J. & Lau, K.-M. 2001. Principal modes of interannual and decadal variability of summer rainfall over South America. International Journal of Climatology, 21(13), 1623–1644. DOI: https://doi.org/10.1002/joc.700
https://doi.org/10.1002/joc.700...
; Nogues-Paegle et al., 2002Nogues-Paegle, J., Mechoso, C. R., Fu, R., Berbery, E. H., Chao, W. C., Chen, T.-C., Cook, K., Diaz, A. F., Enfield, D., Ferreira, R., Grimm, A. M., Kousky, V., Liebmann, B., Marengo, J. A., Mo, K., Neelin, J. D., Paegle, J., Robertson, A. W., Seth, A., Vera, C. S. & Zhou, J. 2002. Progress in Pan American CLIVAR Research: Understanding the South American Monsoon. Meteorologica, 27, 3–32.). The zonal teleconnection is modified, via Walker circulation, during the El Niño condition, then the tropical convection in its ascending branch shifts to the east, towards the central–eastern Pacific. Its descending branch also migrates eastwards, eventually inhibiting the convection over the Equatorial Atlantic and the Northeast region of Brazil (NEB), establishing drought conditions during its rainy season (March–April–May) (Hastenrath and Heller, 1977Hastenrath, S. & Heller, L. 1977. Dynamics of climatic hazards in northeast Brazil. Quarterly Journal of the Royal Meteorological Society, 103(435), 77–92. DOI: https://doi.org/10.1002/qj.49710343505
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; Grimm and Ambrizzi, 2009Grimm, A. M. & Ambrizzi, T. 2009. Teleconnections into South America from the Tropics and Extratropics on Interannual and Intraseasonal Timescales. In: Past Climate Variability in South America and Surrounding Regions (Amsterdam, pp. 159–191). Springer Netherlands. DOI: https://doi.org/10.1007/978-90-481-2672-9_7
https://doi.org/10.1007/978-90-481-2672-...
; Grimm, 2011Grimm, A. M. 2011. Interannual climate variability in South America: impacts on seasonal precipitation, extreme events, and possible effects of climate change. Stochastic Environmental Research and Risk Assessment, 25(4), 537–554. DOI: https://doi.org/10.1007/s00477-010-0420-1
https://doi.org/10.1007/s00477-010-0420-...
; Rodrigues et al., 2011Rodrigues, R. R., Haarsma, R. J., Campos, E. J. D. & Ambrizzi, T. 2011. The Impacts of Inter–El Niño Variability on the Tropical Atlantic and Northeast Brazil Climate. Journal of Climate, 24(13), 3402–3422. DOI: https://doi.org/10.1175/2011jcli3983.1
https://doi.org/10.1175/2011jcli3983.1...
; Cai et al., 2020Cai, W., McPhaden, M. J., Grimm, A. M., Rodrigues, R. R., Taschetto, A. S., Garreaud, R. D., Dewitte, B., Poveda, G., Ham, Y.-G., Santoso, A., Ng, B., Anderson, W., Wang, G., Geng, T., Jo, H.-S., Marengo, J. A., Alves, L. M., Osman, M., Li, S., Wu, L., Karamperidou, C., Takahashi, K. & Vera, C. 2020. Climate impacts of the El Niño–Southern Oscillation on South America. Nature Reviews Earth &\mathsemicolon Environment, 1(4), 215–231. DOI: https://doi.org/10.1038/s43017-020-0040-3
https://doi.org/10.1038/s43017-020-0040-...
; Hounsou-Gbo et al., 2020Hounsou-Gbo, A., Servain, J., Junior, F. das C. V., Martins, E. S. P. R. & Araújo, M. 2020. Summer and winter Atlantic Niño: connections with ENSO and implications. Climate Dynamics, 55(11–12), 2939–2956. DOI: https://doi.org/10.1007/s00382-020-05424-x
https://doi.org/10.1007/s00382-020-05424...
). Conversely, during the La Niña phase, the SST of the STA is heated more (Covey and Hastenrath, 1978Covey, D. L. & Hastenrath, S. 1978. The Pacific El Niño Phenomenon and the Atlantic Circulation. Monthly Weather Review, 106(9), 1280–1287.; Hastenrath et al., 1987Hastenrath, S., Castro, L. C. & Aceituno, P. 1987. The Southern Oscillation in the tropical Atlantic sector. Contributions to Atmospheric Physics, 60, 447--463.), resulting in the southward shift of the Intertropical Convergence Zone (ITCZ), enhancing the rainy season in the NEB (Hastenrath and Heller, 1977Hastenrath, S. & Heller, L. 1977. Dynamics of climatic hazards in northeast Brazil. Quarterly Journal of the Royal Meteorological Society, 103(435), 77–92. DOI: https://doi.org/10.1002/qj.49710343505
https://doi.org/10.1002/qj.49710343505...
; Grimm, 2011Grimm, A. M. 2011. Interannual climate variability in South America: impacts on seasonal precipitation, extreme events, and possible effects of climate change. Stochastic Environmental Research and Risk Assessment, 25(4), 537–554. DOI: https://doi.org/10.1007/s00477-010-0420-1
https://doi.org/10.1007/s00477-010-0420-...
; Cai et al., 2020Cai, W., McPhaden, M. J., Grimm, A. M., Rodrigues, R. R., Taschetto, A. S., Garreaud, R. D., Dewitte, B., Poveda, G., Ham, Y.-G., Santoso, A., Ng, B., Anderson, W., Wang, G., Geng, T., Jo, H.-S., Marengo, J. A., Alves, L. M., Osman, M., Li, S., Wu, L., Karamperidou, C., Takahashi, K. & Vera, C. 2020. Climate impacts of the El Niño–Southern Oscillation on South America. Nature Reviews Earth &\mathsemicolon Environment, 1(4), 215–231. DOI: https://doi.org/10.1038/s43017-020-0040-3
https://doi.org/10.1038/s43017-020-0040-...
). Thus, changes in the magnitude and position of ITCZ during ENSO events significantly modulate the precipitation distribution in the NEB and North region, with distinct characteristics between its phases (Münnich and Neelin, 2005Münnich, M. & Neelin, J. D. 2005. Seasonal influence of ENSO on the Atlantic ITCZ and equatorial South America. Geophysical Research Letters, 32(21). DOI: https://doi.org/10.1029/2005gl023900
https://doi.org/10.1029/2005gl023900...
; Grimm and Tedeschi, 2009Grimm, A. M. & Tedeschi, R. G. 2009. ENSO and Extreme Rainfall Events in South America. Journal of Climate, 22(7), 1589–1609. DOI: https://doi.org/10.1175/2008jcli2429.1
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; Kayano et al., 2016Kayano, M. T., Capistrano, V. B., Andreoli, R. V. & Souza, R. A. F. de. 2016. A further analysis of the tropical Atlantic SST modes and their relations to north-eastern Brazil rainfall during different phases of Atlantic Multidecadal Oscillation. International Journal of Climatology, 36(12), 4006–4018. DOI: https://doi.org/10.1002/joc.4610
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; Tedeschi et al., 2016Tedeschi, R. G., Grimm, A. M. & Cavalcanti, I. F. A. 2016. Influence of Central and East ENSO on extreme events of precipitation in South America during austral spring and summer. International Journal of Climatology, 35(8), 2045–2064. DOI: https://doi.org/10.1002/joc.4106
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).

Periods of severe droughts related to ENSO events were recorded in states of NEB, such as Ceará, Pernambuco, and Paraíba, where the precipitation anomalies showed a better correlation with the SST anomalies that occurred in STA than in NTA (Cerqueira, 2010Cerqueira, H. D. Velasco. 2010. Modulação da temperatura da superficie do mar do Pacífico e Atlântico Tropical na precipitação no Estado da Paraíba (mathesis). Centro de Tecnologia e Recursos Naturais, Universidade Federal de Campina Grande, Campina Grande. Retrieved from http://dspace.sti.ufcg.edu.br:8080/jspui/handle/riufcg/4784
http://dspace.sti.ufcg.edu.br:8080/jspui...
; Rodrigues et al., 2011Rodrigues, R. R., Haarsma, R. J., Campos, E. J. D. & Ambrizzi, T. 2011. The Impacts of Inter–El Niño Variability on the Tropical Atlantic and Northeast Brazil Climate. Journal of Climate, 24(13), 3402–3422. DOI: https://doi.org/10.1175/2011jcli3983.1
https://doi.org/10.1175/2011jcli3983.1...
; Braga et al., 2014Braga, C. C., Amanajás, J. C., Cerqueira, H. D. V. & Vitorino, M. I. 2014. The Role of the Tropical Atlantic and Pacific Oceans SST in Modulating the Rainfall of Paraíba State, Brazil. Revista Brasileira de Geofísica, 32(1), 97–107. DOI: https://doi.org/10.22564/rbgf.v32i1.399
https://doi.org/10.22564/rbgf.v32i1.399...
). By considering an index derived from an empirical relationship that incorporates the effects of drought-induced senescence, Cunha et al. (2018Cunha, A. P. M. A., Tomasella, J., Ribeiro-Neto, G. G., Brown, M., Garcia, S. R., Brito, S. B. & Carvalho, M. A. 2018. Changes in the spatial-temporal patterns of droughts in the Brazilian Northeast. Atmospheric Science Letters, 19(10), e855. DOI: https://doi.org/10.1002/asl.855
https://doi.org/10.1002/asl.855...
) showed that strong El Niño-related droughts were spatially limited to the northern sector, covering only around 30% of the NEB. Thus, severe drought events are not only associated with the occurrence of ENSO, but also with certain oceanic and atmospheric configurations in the TA Ocean, such as warmer SST anomalies in the NTA and colder SST anomalies in the STA (Alves et al., 2009Alves, J. B., Servain, J. & Campos, J. N. B. 2009. Relationship between ocean climatic variability and rain-fed agriculture in northeast Brazil. Climate Research, 38, 225–236. DOI: https://doi.org/10.3354/cr00786
https://doi.org/10.3354/cr00786...
; Hounsou-Gbo et al., 2016Hounsou-Gbo, G. A., Servain, J., Araujo, M., Martins, E. S., Bourlès, B. & Caniaux, G. 2016. Oceanic Indices for Forecasting Seasonal Rainfall over the Northern Part of Brazilian Northeast. American Journal of Climate Change, 5(2), 261–274. DOI: https://doi.org/10.4236/ajcc.2016.52022
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), that shift the ITCZ northwards (Rodrigues and McPhaden, 2014Rodrigues, R. R. & McPhaden, M. J. 2014. Why did the 2011-2012 La Niña cause a severe drought in the Brazilian Northeast? Geophysical Research Letters, 41(3), 1012–1018. DOI: https://doi.org/10.1002/2013gl058703
https://doi.org/10.1002/2013gl058703...
). Extreme precipitation events majorly impact human activities, affecting important sectors of society such as agriculture and energy generation. In view of the accelerating regional and local climate changes in response to the global warming trend, this article aims to analyze the influence of strong and moderate ENSO events on the seasonal and interannual SST variability of the Western Equatorial Atlantic (WEA) Ocean, focusing on the potential impacts over the precipitation regime in the state of Maranhão.

DATA, METHODS, AND ANALYZES

SST and precipitation data

The SST monthly averages from the Simple Ocean Data Assimilation (SODA, version 3.3.1) oceanic reanalysis database were used (Carton and Giese, 2008Carton, J. A. & Giese, B. S. 2008. A Reanalysis of Ocean Climate Using Simple Ocean Data Assimilation (SODA). Monthly Weather Review, 136(8), 2999–3017. DOI: https://doi.org/10.1175/2007mwr1978.1
https://doi.org/10.1175/2007mwr1978.1...
), with horizontal resolution of 0.25° x 0.25° (28 km at the Equator) and 50 vertical levels, for the period from January 1980 to December 2015. This reanalysis used the ocean component of the Geophysical Fluid Dynamics Laboratory’s coupled climate model (GFDL/CM2.5), which includes an active sea ice component.

The SST monthly averages were obtained for Niño 4 (5°N–5°S; 160°E–150°W), Niño 3.4 (5°N–5°S; 170°W–120°W), Niño 3 (5°N–5°S; 150°W–90°W), Niño 1+2 (0°–10°S; 90°W–80°W), and WEA (10°N–10°S; 60°W–20°W) regions, as was also proposed by Soares (2019Soares, L. A. M. 2019. Influência de teleconexão Pacífico–Atlântico e de modos locais na variabilidade da temperatura da superfície do mar do Atlântico Equatorial Ocidental e impactos sobre a precipitação no estado do Maranhão (mathesis). Universidade Federal do Maranhão, São Luís.) (Figure 1). Based on these data, quarterly SST average anomalies (SSTA) were calculated to generate climate indices for each Niño region and then to build the climate composites for the WEA region.

Figure 1.
Spatial domain of the Western Equatorial Atlantic (WEA) Ocean and Niño regions, location of the state of Maranhão and the meteorological stations.

Observational monthly precipitation data of Maranhão were obtained from the Meteorological Database for Teaching and Research (BDMEP) elaborated by the National Institute of Meteorology (INMET), comprising the years from 1980 to 2015, available at www.inmet.gov.br/portal/index.php?r=bdmep/bdmep. The data were obtained for the 12 automatic meteorological stations located in the state: Alto Parnaíba, Bacabal, Balsas, Barra do Corda, Carolina, Caxias, Chapadinha, Colinas, Imperatriz, São Luís, Turiaçu, and Zé Doca (Table 1, Figure 1).

Table 1.
Location and altitude of the INMET meteorological stations in the state of Maranhão used in this study.

Oceanic Niño Index calculation and its correlations with the WEA SSTA

The Oceanic Niño Index (ONI) in the Equatorial Pacific Ocean was computed from the quarterly SST average anomalies (SSTA, in °C) (quarterly average with 1-month moving window, i.e., DJF, JFM, FMA, …) for each Niño region (1+2, 3, 3.4, and 4), separately. For obtaining the SSTA, we calculated the quarterly averages for each year separately, and the total quarterly averages considering the entire period analyzed (1980–2015). From the quarterly average for each year (e.g., DJF of 1985) the total average of this quarter was subtracted (e.g., DJF), thus leading to the quarterly average anomaly for DJF. The SSTA were normalized and divided by their standard deviations to compare different Niño regions. An event was classified as El Niño or La Niña when the SSTA reached the threshold of ± 0.5°C (positive for El Niño and negative for La Niña) and persisted for a minimum of five consecutive seasons. The ONI was used to classify ENSO events according to their phases and intensities (see Table 2) as moderate El Niño (1.0 ≤ SSTA < 1.5°C) and strong El Niño (SSTA ≥ 1.5°C), moderate La Niña (−1.0 ≥ SSTA > −1.5°C) and strong La Niña (SSTA ≤ −1.5°C), based on thresholds predicted by the Climate Prediction Center of the National Oceanic and Atmospheric Administration (NOAA, 2019aNOAA. 2019a. Cold & Warm Episodes by Season. Accessed: https://origin.cpc.ncep.noaa.gov/products/analysis_monitoring/ensostuff/ONI_v5.php
https://origin.cpc.ncep.noaa.gov/product...
, 2019bNOAA. 2019b. El niño regions. Accessed: https://www.cpc.ncep.noaa.gov/products/analysis_monitoring/ensostuff/nino_regions.shtml
https://www.cpc.ncep.noaa.gov/products/a...
). Events considered weak were not analyzed in this study.

Pearson’s linear correlation coefficient (Press et al., 1992Press, W. H., Teukolsky, S. A., Vetterling, W. T. & Flannery, B. P. 1992. Numerical Recipes in C: the art of scientific computing (2nd ed.). Cambridge: Cambridge University Press.) was calculated based on the time series of climate indices between the different Niño (1+2, 3, 3.4, and 4) and the WEA region, separately, considering the lag = 0. These were computed spatially with the view to determine the sectors with the highest correlations. As proposed by Sasaki (2014Sasaki, D. K. 2014. Mudanças dos Modos de Variabilidade do Atlântico Tropical no Século XX (mathesis). Universidade de Sao Paulo, Instituto Oceanográfico, São Paulo. https://doi.org/10.11606/d.21.2014.tde-10032015-151036
https://doi.org/10.11606/d.21.2014.tde-1...
), the Pearson’s correlation is here classified as strong (r > 0.7), from moderate to strong (0.5 < r < 0.7), moderate (0.3 < r < 0.5), and weak (r < 0.3).

Climate composites for WEA SST and Maranhão precipitation anomalies

To set up a teleconnection pattern between the central–eastern Equatorial Pacific and the WEA Ocean, total SSTA composites (spatial patterns) were constructed for the WEA region representative of the different phases (El Niño vs La Niña) and intensities (strong vs moderate). The total climate composites (considering all Niño regions in the analysis) were elaborated since at least one ENSO event has occurred in at least one of the Niño regions.

We created a numerical mesh to spatialize the INMET’s meteorological stations precipitation data for the Maranhão state domain. Their boundary conditions were derived from the cartographic base of political limits of Brazilian states for the year 2006, provided by the Brazilian Institute of Geography and Statistics (IBGE). The coordinates were edited to obtain a single closed polygon, to carry out the steps of data extrapolation and interpolation for the Maranhão mesh grid (Furtado, 2019Furtado, T. M. S. 2019. Variabilidade Climática e Tendência da Precipitação Pluviométrica no Estado do Maranhão e sua Relação com a Temperatura da Superfície do Mar no Atlântico Tropical Equatorial. (candthesis). Universidade Federal do Maranhão, São Luís.).

RESULTS AND DISCUSSION

Influences of ENSO phases and intensities on the WEA SSTA

Figure 2 shows the ONI calculated for the four Niño regions, separately. The most intense events of the positive phase of ENSO (El Niño condition) occurred in 1982–1983, 1997–1998, and 2015 in the Niño 1+2, Niño 3, and Niño 3.4 regions, with Niño 4 showing only the event of 2015. The Niño 3.4 had the highest number of most intense events, that is, 6 strong El Niño and 5 strong La Niña events (Figure 2 b), followed by Niño 3, which had 4 strong El Niño and 4 strong La Niña events (Figure 2 c). The Niño 1+2 region presented the largest positive SST anomalies for the two strongest El Niño events (1982–1983 and 1997–1998) that occurred during the period analyzed (1980–2015). Besides that, the highest number of moderate events occurred in this region, with 5 moderate El Niño and 8 moderate La Niña events (Figure 2 d). Niño 4 had fewer events, which were classified as moderate and weak (Figure 2 a). For the negative phase of ENSO (La Niña condition), the events that occurred in 2007 and 1988 were the most intense. In the La Niña event of 1988, the strongest negative SST anomalies have appeared in the Niño 3.4 region (Figure 2 b), followed by the Niño 3 (Figure 2 c). In the event of 2007, the most evident negative SST anomalies occurred in Niño 1+2 (Figure 2 d), followed by the Niño 3 (Figure 2 c). Compared with the other Niño regions, we found the Niño 3.4 and Niño 3 indices were the suitable reference of ENSO acting on the SSTA of the Pacific Equatorial region. According to Li et al. (2010), the Niño 4 index is not effective on tracking El Niño events since it can represent a joint performance of the El Niño classic and El Niño Modoki signals. This may explain the little information on ENSO events in the Niño 4 region (Figure 2 a).

Figure 2.
Oceanic Niño Index (ONI), from 1980 to 2015, based on quarterly SSTA of the SODA reanalysis (version 3.3.1) for the regions of: a) Niño 4; b) Niño 3.4; c) Niño 3; d) Niño 1+2. The dotted lines represent the thresholds for moderate events (± 1.0), whereas the dashed lines represent the thresholds for strong events (± 1.5).

The results show that the 36 years (from 1980 to 2015) analyzed had 13 strong events, with 6 El Niño and 7 La Niña events; and 27 moderate events, with 10 El Niño and 17 La Niña events (Table 2). To determine the Niño region with the greatest influence on the WEA SSTA variability associated with the zonal (Pacific–Atlantic) teleconnection, each ENSO phase was also classified according to its phase and intensity. The results showed that the Niño 3.4 region had the highest number of events (20 events), and the Niño 1+2 and Niño 3 regions had the same number of events (19 events in each region), although they have different phases and intensities. The Niño 4 region was the region with the lowest number of events (12 events) for the analyzed period (Table 2).

Table 2.
Years of ENSO events from 1980 to 2015 classified according to its phase (El Niño vs La Niña) and intensity (strong vs moderate) in each Niño region (4, 3.4, 3, and 1+2).

The linear correlation computed between the ONI and the WEA SSTA has shown that this ocean exhibited spatially negative correlations (r = −0.25) with all Niño regions, mainly over the equatorial band and the STA basin (Figure 3). The higher and lower significant negative correlations were found between the SSTA in the WEA and Niño 3.4 and Niño 1+2, respectively. Significant negative correlations were also found near the west coast of Maranhão (Niño 3.4 and Niño 3) and near the capital of Maranhão (Niño 3.4 and Niño 4) (Figure 3). Positive weak correlations (r = +0.1) have been obtained for small areas, such as in NTA around 8°N and near the Northeast (Niño 1+2 and Niño 3) and the North (Niño 4) regions of Brazil.

Figure 3.
Correlation coefficients (lag = 0) between the SSTA in the Western Equatorial Atlantic (WEA) Ocean and in the Niño regions (4, 3.4, 3, and 1+2), separately. The yellow lines surround the statistically significant values at the 5% significance level (p ≤ 0.05).

The weak significant correlation found between ENSO and WEA SSTA in this study corroborates the results found by Zebiak (1993Zebiak, S. E. 1993. Air–Sea Interaction in the Equatorial Atlantic Region. Journal of Climate, 6(8), 1567–1586.), Enfield & Mayer (1997Enfield, D. B. & Mayer, D. A. 1997. Tropical Atlantic sea surface temperature variability and its relation to El Niño-Southern Oscillation. Journal of Geophysical Research: Oceans, 102(C1), 929–945. DOI: https://doi.org/10.1029/96jc03296
https://doi.org/10.1029/96jc03296...
), and Rodrigues et al. (2011Rodrigues, R. R., Haarsma, R. J., Campos, E. J. D. & Ambrizzi, T. 2011. The Impacts of Inter–El Niño Variability on the Tropical Atlantic and Northeast Brazil Climate. Journal of Climate, 24(13), 3402–3422. DOI: https://doi.org/10.1175/2011jcli3983.1
https://doi.org/10.1175/2011jcli3983.1...
) who found a weak correlation between Niño 3 and the TA ocean. Despite the low correlation coefficients between ENSO and WEA at lag = 0 in this study, Soares (2019Soares, L. A. M. 2019. Influência de teleconexão Pacífico–Atlântico e de modos locais na variabilidade da temperatura da superfície do mar do Atlântico Equatorial Ocidental e impactos sobre a precipitação no estado do Maranhão (mathesis). Universidade Federal do Maranhão, São Luís.) has shown that, except for Niño 4, all correlations between ENSO and NTA/STA regions were significant at a 5% significance level. In the positive phase of ENSO, a positive SSTA is expected in the NTA oceans, with the highest correlation at lag = −5 and +5, and in the negative phase, a negative SSTA is expected in the STA oceans, with the highest correlation at lag = −5. According to this author, the highest lagged correlations have occurred between the NTA and STA and Niño 4 and Niño 3.4 regions, respectively. This result is consistent with those of Servain (1991Servain, J. 1991. Simple climatic indices for the tropical Atlantic Ocean and some applications. Journal of Geophysical Research, 96(C8), 15137–15146. DOI: https://doi.org/10.1029/91jc01046
https://doi.org/10.1029/91jc01046...
), Latif & Barnett (1995Latif, M. & Barnett, T. P. 1995. Interactions of the Tropical Oceans. The Journal of Climate, 8(4), 952–964.), Uvo et al. (1998Uvo, C. B., Repelli, C. A., Zebiak, S. E. & Kushnir, Y. 1998. The relationships between Tropical Pacific and Atlantic SST and northeast Brazil monthly precipitation. Journal of Climate, 11(4), 551–562.), and Wang et al. (2004Wang, C., Xie, S.-P. & Carton, J. A. 2004. A global survey of ocean–atmosphere interaction and climate variability. In: Wang, C., Xie, S., & Carton, J. A. (eds.), Earth’s climate: the ocean–atmosphere interaction (Vol. 147, pp. 1–19). Washington, DC: American Geophysical Union.). Enfield & Mayer (1997Enfield, D. B. & Mayer, D. A. 1997. Tropical Atlantic sea surface temperature variability and its relation to El Niño-Southern Oscillation. Journal of Geophysical Research: Oceans, 102(C1), 929–945. DOI: https://doi.org/10.1029/96jc03296
https://doi.org/10.1029/96jc03296...
) found a positive correlation (r = +0.5) between the positive phase of ENSO and NTA SSTA from lag = +4 to +5. Several authors, such as Alexander et al. (2002Alexander, M. A., Bladé, I., Newman, M., Lanzante, J. R., Ngar-Cheung Lau & Scott, J. D. 2002. The Atmospheric Bridge: The Influence of ENSO Teleconnections on Air–Sea Interaction over the Global Oceans. Journal of Climate, 15(16), 2205–2231.) and He et al. (2020He, S., Yu, J.-Y., Yang, S. & Fang, S.-W. 2020. ENSO’s impacts on the tropical Indian and Atlantic Oceans via tropical atmospheric processes: observations versus CMIP5 simulations. Climate Dynamics, 54(11–12), 4627–4640. DOI: https://doi.org/10.1007/s00382-020-05247-w
https://doi.org/10.1007/s00382-020-05247...
), state that positive NTA SSTA immediately follow the mature phase of El Niño, about 3–5 months after the ENSO peaks, a result consistent with the findings of this study. Latif and Grötzner (2000Latif, M. & Grötzner, A. 2000. The equatorial Atlantic oscillation and its response to ENSO. Climate Dynamics, 16(2–3), 213–218. DOI: https://doi.org/10.1007/s003820050014
https://doi.org/10.1007/s003820050014...
) has found delayed response of the equatorial Atlantic to ENSO (Niño 3), with SST anomalies in the eastern equatorial Atlantic lagging those in the equatorial Pacific by six months. Concerning the STA SSTA, these SSTA may be related to strengthening the South Atlantic Subtropical Gyre, it means, in response to a local and not a remote forcing (Lübbecke et al., 2010Lübbecke, J. F., Böning, C. W., Keenlyside, N. S. & Xie, S.-P. 2010. On the connection between Benguela and equatorial Atlantic Niños and the role of the South Atlantic Anticyclone. Journal of Geophysical Research, 115(C9). DOI: https://doi.org/10.1029/2009jc005964
https://doi.org/10.1029/2009jc005964...
).

Influence of the ENSO phases and intensities on the precipitation in Maranhão

Figures Figure 4 to 11 show the total composites for the WEA SSTA and the precipitation in Maranhão for different phases (El Niño vs La Niña) and intensities (strong vs moderate). The total composites were computed to determine how WEA Ocean responds to Equatorial Pacific SSTA, regardless of the region where they occurred (if Niño 1+2, 3, 3.4, and/or 4). The total composites of WEA SSTA for El Niño years showed cold SST over the ocean throughout the months, with negative SSTA practically dominating the region (Figure 4 and Figure 5). In strong events (Figure 4), the negative SSTA are even more intense in the equatorial region and the STA (around −0.6°C) from May to October (MJJASO), with the peak of negative SSTA occurring from May to August and even more consistently in the eastern band. Negative SSTA anomalies (around −0.4°C) are also found over the Continental Shelf of Maranhão (CS–MA), particularly from June to November (JASON). These anomalies are spreading towards the northwest from the Maranhão Gulf. The most intense negative SSTA arrive later (AMJ quarter) in the WEA during strong El Niño and are persistent over time until SON quarter (Figure 4). In moderate events (Figure 5) the largest negative SSTA (around −0.4°C) are observed in the NTA from February to June (FMAMJ), when they disperse towards the equatorial Atlantic band and then in the STA from July to October (JASO). In DJF and NDJ, the moderate El Niño signal is weak over the WEA SSTA. The SSTA in the WEA has a shorter duration (5 months) and happens earlier compared with the strong events (6 months). The impacts on the CS–MA SSTA are weak during moderate El Niño. Previous studies, including Araújo et al. (2013Araújo, R. G., Andreoli, R. V., Candido, L. A., Kayano, M. T. & Souza, R. A. F. de. 2013. A influência do evento El Niño - Oscilação Sul e Atlântico Equatorial na precipitação sobre as regiões norte e nordeste da América do Sul. Acta Amazonica, 43(4), 469–480. DOI: https://doi.org/10.1590/s0044-59672013000400009
https://doi.org/10.1590/s0044-5967201300...
), have confirmed our results, showing negative SSTA in the WEA during El Niño events, in their case, from March to May.

Figures Figure 6 and 7 show the total composites of precipitation anomalies in the state of Maranhão for strong and moderate El Niño events. Our findings show a strong relationship between El Niño and the precipitation in the Maranhão state. Composites of negative SSTA during strong El Niño events were associated with negative precipitation anomalies in Maranhão, except in DJF, when positive precipitation anomalies are spreading over the state with the largest values occurring in the central-northwest sector (Figure 6). The most significant response to these events occurred in the MAM, AMJ, MJJ, and NDJ quarterlies, which covers the months of the rainy season of Maranhão (March–April–May), with the central, northern, and eastern tip sectors of regions being more affected. However, the negative precipitation anomalies started to weaken from the JJA quarter and strengthen again in NDJ. This agrees with the results of Souza et al. (2000), who found negative precipitation anomalies over Maranhão associated with El Niño event, from March to May. For the moderate El Niño phase, in turn, positive and negative precipitation anomalies alternated, both with smaller associated intensity. Positive precipitation anomalies were observed from DJF to JJA, as well as negative precipitation anomalies from JAS to NDJ (Figure 7). In DJF, AMJ, and MJJ quarterlies. the most evident positive anomalies have appeared in Maranhão, which also include the two months (April and May) of its rainy season, with the highest anomalies over the central, northern, and eastern sectors of the state. In JJA, a weak positive precipitation anomaly is seen in a central part of the state. From JAS to OND, negative precipitation anomalies were present but relatively weaker. However, in NDJ, negative precipitation anomalies were strong in almost the entire state of Maranhão (Figure 7).

Figure 4.
Total composites of quarterly SST anomalies in the Western Equatorial Atlantic (WEA) Ocean for strong El Niño events in the Equatorial Pacific region.
Figure 5.
Total composites of quarterly SST anomalies in the Western Equatorial Atlantic (WEA) Ocean for moderate El Niño events in the Equatorial Pacific region.
Figure 6.
Total composites of quarterly precipitation anomalies in the state of Maranhão for strong El Niño events in the Equatorial Pacific region.
Figure 7.
Total composites of quarterly precipitation anomalies in the state of Maranhão for moderate El Niño events in the Equatorial Pacific region.

The total composites of WEA for La Niña events show a predominance of positive SSTA, with a similar spatial pattern between strong (around +0.8°C) and moderate (around +0.3°C) events, with smaller intensity for the latter composites (Figure 8 and Figure 9). For the strong events, positive SSTA are primarily configured over the STA from January to April (JFMA), moving further into the equatorial band from May to September (MJJAS) (Figure 8). The strongest positive anomalies are seen in the eastern band, intensifying in January, and reaching a peak from April to July (Figure 8). The positive anomalies start to weaken in the eastern sector during the ASO quarter and this may be due to these once strong positive anomalies moving towards the east equatorial Atlantic (EEA). In OND and NDJ, the weak positive anomalies may be the final stop of the strong positive anomalies that moved eastward from the WEA. According to the studies by Munnich and Neelin (2005Münnich, M. & Neelin, J. D. 2005. Seasonal influence of ENSO on the Atlantic ITCZ and equatorial South America. Geophysical Research Letters, 32(21). DOI: https://doi.org/10.1029/2005gl023900
https://doi.org/10.1029/2005gl023900...
), positive SST anomaly patterns were found in the WEA area associated with La Niña event in the Niño 3.4 in May, and this event induced wind stress anomalies in the WEA, which in turn, displaced warm water from the WEA towards the EEA. In moderate events, the positive SSTA are observed over the STA, especially from January to August (JFMAMJJA) (Figure 9). Positive SST anomalies in the WEA are weak during moderate La Niña events. At the DJF and NDJ, the La Niña signal in the WEA is practically nonexistent (Figure 9). These results align with those of Munnich & Neelin (2005Münnich, M. & Neelin, J. D. 2005. Seasonal influence of ENSO on the Atlantic ITCZ and equatorial South America. Geophysical Research Letters, 32(21). DOI: https://doi.org/10.1029/2005gl023900
https://doi.org/10.1029/2005gl023900...
) and Nicholson & Selato (2000Nicholson, S. E. & Selato, J. C. 2000. A influência de La Niña na precipitação africana. Jornal Internacional de Climatologia, 20(14), 1761–1776.), who found positive SSTA in the WEA during La Niña events, particularly from January to September, and tend to weaken from October to November.

Figure 8.
Total composites of quarterly SST anomalies in the Western Equatorial Atlantic (WEA) Ocean for strong La Niña events in the Equatorial Pacific region.
Figure 9.
Total composites of quarterly SST anomalies in the Western Equatorial Atlantic (WEA) Ocean for moderate La Niña events in the Equatorial Pacific region.

Figures Figure 10 and Figure 11 show the total composites of precipitation anomalies in the state of Maranhão for strong and moderate La Niña events. The WEA SSTA under the influence of strong La Niña events has been associated with either positive or negative precipitation anomalies. The DJF quarter show the strongest positive precipitation anomaly. The positive precipitation anomalies in JFM and FMA are more widespread in the central and northern sectors of Maranhão. The rainy season (MAM, AMJ, and MJJ quarter) shows positive precipitation anomalies covering almost the entire state, with the most noticeable positive anomalies concentrated in the central, northern, and eastern sectors. At the JJA, JAS, and ASO quarterlies, the positive precipitation anomalies weaken and are more confined to the northern sector of Maranhão, as weak negative precipitation anomalies appear in a part of the central and southern sectors. The La Niña signal is weak in terms of precipitation during the SON and OND quarterlies. In contrast to the positive anomalies, negative anomalies are generally weak, except in NDJ, which shows an evident negative precipitation anomaly (Figure 10). Regarding the influence of moderate La Niña events, positive precipitation anomalies were well pronounced from DJF to JJA, with a peak in DJF, MAM, AMJ, and MJJ (Figure 11). The DJF quarter shows the most intense positive precipitation anomaly in the state. From JFM to MJJ, positive precipitation anomalies spread across most of the state, with the most noticeable anomalies concentrated in the central, northern, and eastern tip sectors, and especially during the rainy season (MAM). At the JJA, JAS, and ASO quarterlies, positive precipitation anomalies are observed in the northern sector, whereas weak negative precipitation anomalies appear in a part of the central sector. The moderate La Niña signal on precipitation is absent in the SON quarter and relatively weak in OND. The negative anomalies of precipitation are generally weak, except in NDJ, which shows an evident negative precipitation anomaly (Figure 11).

Figure 10.
Total composites of quarterly precipitation anomalies in the state of Maranhão for strong La Niña events in the Equatorial Pacific region.
Figure 11.
Total composites of quarterly precipitation anomalies in the state of Maranhão for moderate La Niña events in the Equatorial Pacific region.

In short, the impacts of ENSO events on precipitation in Maranhão are stronger in the central, northern, and eastern tip sectors of the state, and less in the southern sector. The WEA SSTA during El Niño (La Niña) events are related to negative (positive) precipitation anomalies in Maranhão, with the peak in MAM, AMJ, MJJ, JJA, and NDJ (DJF and AMJ), respectively. Strong El Niño events significantly impact the reduction of precipitation over the state, whereas moderate El Niño events have mild effects. Positive precipitation anomalies occur in Maranhão in its rainy season (MAM).

The results found in this study are consistent with those found by Nascimento et al. (2017Nascimento, F. das C. A. do, Braga, C. C. & Araújo, F. R. da C. D. 2017. Análise Estatística dos Eventos Secos e Chuvosos de Precipitação do Estado do Maranhão. Revista Brasileira de Meteorologia, 32(3), 375–386. DOI: https://doi.org/10.1590/0102-77863230005
https://doi.org/10.1590/0102-77863230005...
) who showed that the northern region of Maranhão presented wet and drought events related to La Niña and El Niño, respectively. They also reported extremes of droughts in the southern region of the state. The studies from Grimm & Tedeschi (2009Grimm, A. M. & Tedeschi, R. G. 2009. ENSO and Extreme Rainfall Events in South America. Journal of Climate, 22(7), 1589–1609. DOI: https://doi.org/10.1175/2008jcli2429.1
https://doi.org/10.1175/2008jcli2429.1...
), Araújo et al. (2013Araújo, R. G., Andreoli, R. V., Candido, L. A., Kayano, M. T. & Souza, R. A. F. de. 2013. A influência do evento El Niño - Oscilação Sul e Atlântico Equatorial na precipitação sobre as regiões norte e nordeste da América do Sul. Acta Amazonica, 43(4), 469–480. DOI: https://doi.org/10.1590/s0044-59672013000400009
https://doi.org/10.1590/s0044-5967201300...
), Tedeschi et al. (2016Tedeschi, R. G., Grimm, A. M. & Cavalcanti, I. F. A. 2016. Influence of Central and East ENSO on extreme events of precipitation in South America during austral spring and summer. International Journal of Climatology, 35(8), 2045–2064. DOI: https://doi.org/10.1002/joc.4106
https://doi.org/10.1002/joc.4106...
), and Cai et al. (2020Cai, W., McPhaden, M. J., Grimm, A. M., Rodrigues, R. R., Taschetto, A. S., Garreaud, R. D., Dewitte, B., Poveda, G., Ham, Y.-G., Santoso, A., Ng, B., Anderson, W., Wang, G., Geng, T., Jo, H.-S., Marengo, J. A., Alves, L. M., Osman, M., Li, S., Wu, L., Karamperidou, C., Takahashi, K. & Vera, C. 2020. Climate impacts of the El Niño–Southern Oscillation on South America. Nature Reviews Earth &\mathsemicolon Environment, 1(4), 215–231. DOI: https://doi.org/10.1038/s43017-020-0040-3
https://doi.org/10.1038/s43017-020-0040-...
) showed that the greatest impacts of El Niño and La Niña on the NEB precipitation occur in March and April, which result in reduced and increased precipitation, respectively. In addition to the influence of ENSO on precipitation in the NEB, the TA SSTA resulting from local variability modes have also modulated the precipitation in this region during its rainy season, such as the Atlantic Meridional Mode (e.g. Rodrigues et al., 2011Rodrigues, R. R., Haarsma, R. J., Campos, E. J. D. & Ambrizzi, T. 2011. The Impacts of Inter–El Niño Variability on the Tropical Atlantic and Northeast Brazil Climate. Journal of Climate, 24(13), 3402–3422. DOI: https://doi.org/10.1175/2011jcli3983.1
https://doi.org/10.1175/2011jcli3983.1...
; Andreoli et al., 2016Andreoli, R. V., Oliveira, S. S. de, Kayano, M. T., Viegas, J., Souza, R. A. F. de & Candido, L. A. 2016. The influence of different El Niño types on the South American rainfall. International Journal of Climatology, 37(3), 1374–1390. DOI: https://doi.org/10.1002/joc.4783
https://doi.org/10.1002/joc.4783...
; Kayano et al., 2018Kayano, M. T., Andreoli, R. V., Garcia, S. R. & Souza, R. A. F. de. 2018. How the two nodes of the tropical Atlantic sea surface temperature dipole relate the climate of the surrounding regions during austral autumn. International Journal of Climatology, 38(10), 3927–3941. DOI: https://doi.org/10.1002/joc.5545
https://doi.org/10.1002/joc.5545...
; Soares, 2019Soares, L. A. M. 2019. Influência de teleconexão Pacífico–Atlântico e de modos locais na variabilidade da temperatura da superfície do mar do Atlântico Equatorial Ocidental e impactos sobre a precipitação no estado do Maranhão (mathesis). Universidade Federal do Maranhão, São Luís.) and the Atlantic Niño (Servain et al., 1982Servain, J., Joël Picaut & Merle, J. 1982. Evidence of Remote Forcing in the Equatorial Atlantic Ocean. Journal of Physical Oceanography, 12(5), 457–463.; Zebiak, 1993Zebiak, S. E. 1993. Air–Sea Interaction in the Equatorial Atlantic Region. Journal of Climate, 6(8), 1567–1586.; Wu et al., 2004Wu, L., Zhang, Q. & Liu, Z. 2004. Toward Understanding Tropical Atlantic Variability Using Coupled Modeling Surgery. In: Wang, C., Xie, S., & Carton, J. A. (eds.), Earth’s climate: the ocean–atmosphere interaction (Vol. 147, pp. 157–170). Hoboken: American Geophysical Union. DOI: https://doi.org/10.1029/147gm09
https://doi.org/10.1029/147gm09...
; Hounsou-Gbo et al., 2020Hounsou-Gbo, A., Servain, J., Junior, F. das C. V., Martins, E. S. P. R. & Araújo, M. 2020. Summer and winter Atlantic Niño: connections with ENSO and implications. Climate Dynamics, 55(11–12), 2939–2956. DOI: https://doi.org/10.1007/s00382-020-05424-x
https://doi.org/10.1007/s00382-020-05424...
). Tedeschi et al. (2016Tedeschi, R. G., Grimm, A. M. & Cavalcanti, I. F. A. 2016. Influence of Central and East ENSO on extreme events of precipitation in South America during austral spring and summer. International Journal of Climatology, 35(8), 2045–2064. DOI: https://doi.org/10.1002/joc.4106
https://doi.org/10.1002/joc.4106...
) and Soares (2019Soares, L. A. M. 2019. Influência de teleconexão Pacífico–Atlântico e de modos locais na variabilidade da temperatura da superfície do mar do Atlântico Equatorial Ocidental e impactos sobre a precipitação no estado do Maranhão (mathesis). Universidade Federal do Maranhão, São Luís.) report that the joint action of the Atlantic Meridional Mode and ENSO positive phases in the quarterly of March–April–May intensify the negative precipitation anomalies over the NEB region.

CONCLUSION

In this study, 36 years (from 1980 to 2015) of SST monthly data are used to investigate the influence of the different phases and intensities of ENSO events on the seasonal and interannual variability of the SST in the WEA Ocean. It also assesses the impacts of the WEA SSTA in ENSO events on the seasonal precipitation in the state of Maranhão.

Our results showed a weak linear correlation between the Niño regions and the WEA Ocean at lag = 0. Seasonally, the most pronounced SSTA found in the WEA region were related to strong El Niño and La Niña events. Based on the ONI, more moderate ENSO events occurred from 1980 to 2015 than strong ones. Among the events classified as both strong and moderate, La Niña events predominated, with the Niño 3.4 being the region with the largest number of events. Concerning the action of zonal (Pacific-Atlantic) teleconnections, a decrease and an increase in the WEA SST was observed in El Niño and La Niña years, respectively, with a delay of 3–5 quarterlies after the ENSO peaks.

Regarding the impact of the WEA SSTA during ENSO events on the precipitation in Maranhão, the results showed that the central, northern, and eastern sectors of the state are the most affected by this internal variability, as also appointed by Nascimento et al. (2017Nascimento, F. das C. A. do, Braga, C. C. & Araújo, F. R. da C. D. 2017. Análise Estatística dos Eventos Secos e Chuvosos de Precipitação do Estado do Maranhão. Revista Brasileira de Meteorologia, 32(3), 375–386. DOI: https://doi.org/10.1590/0102-77863230005
https://doi.org/10.1590/0102-77863230005...
). The positive precipitation anomalies in these regions, especially in the quarter of DJF and MAM, AMJ, MJJ, were associated with the WEA SSTA resulting from the La Niña events, with the negative ones happening in the MAM, AMJ, MJJ and NDJ quarterlies and resulting from El Niño. Strong El Niño events influence a greater precipitation deficit in Maranhão than the moderate events. Positive precipitation anomalies in Maranhão are more closely related to moderate than to strong La Niña events.

This study is pioneer in investigating the influence of different Niño regions, phases, and intensities of ENSO on SST variability in the WEA region, analyzing the impacts of zonal (Pacific-Atlantic) teleconnections on the seasonal variability of precipitation in Maranhão. With the findings of this study, we concluded that ENSO significantly influences the SST variability in the WEA region, and adds to the action of the Atlantic Meridional Mode (Soares, 2019Soares, L. A. M. 2019. Influência de teleconexão Pacífico–Atlântico e de modos locais na variabilidade da temperatura da superfície do mar do Atlântico Equatorial Ocidental e impactos sobre a precipitação no estado do Maranhão (mathesis). Universidade Federal do Maranhão, São Luís.) on determining the quality of the rainy season (MAM) over the state. This joint action is being analyzed to be included in future publications.

ACKNOWLEDGMENTS

The authors would like to thank the funding of the Coordenação de Aperfeiçoamento de Pessoal de nível Superior (CAPES) to the Projects “Advanced Studies in Oceanography of Medium and High Latitudes” (Process 23038.004304/2014–28) and “Use and Development of the Brazilian Earth System Model for the Study of the Ocean-Atmosphere-Cryosphere System in High and Medium Latitudes – BESM/SOAC” (Process 145668/2017–00) and the funding of CNPq to the Projects “Impactos do Aumento do Gelo Marinho da Antártica no Clima da América do Sul: Simulações por Conjunto x Reanálises” (Process 420406/2016–6). This publication was also supported by the Fundação de Amparo à Pesquisa e ao Desenvolvimento Científico e Tecnológico do Maranhão - FAPEMA (Process 00850/17). We also thank the reviewers for their careful reading of the manuscript and their constructive remarks.

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  • The authors would like to thank the funding of the Coordenação de Aperfeiçoamento de Pessoal de nível Superior (CAPES) to the Projects “Advanced Studies in Oceanography of Medium and High Latitudes” (Process 23038.004304/2014–28) and “Use and Development of the Brazilian Earth System Model for the Study of the Ocean-Atmosphere-Cryosphere System in High and Medium Latitudes – BESM/SOAC” (Process 145668/2017–00) and the funding of CNPq to the Projects “Impactos do Aumento do Gelo Marinho da Antártica no Clima da América do Sul: Simulações por Conjunto x Reanálises” (Process 420406/2016–6). This publication was also supported by the Fundação de Amparo à Pesquisa e ao Desenvolvimento Científico e Tecnológico do Maranhão - FAPEMA (Process 00850/17). We also thank the reviewers for their careful reading of the manuscript and their constructive remarks.

Edited by

Associate Editor:

Ronald Souza

Publication Dates

  • Publication in this collection
    04 Dec 2023
  • Date of issue
    2023

History

  • Received
    30 May 2022
  • Accepted
    14 June 2023
Instituto Oceanográfico da Universidade de São Paulo Praça do Oceanográfico 191, CEP: 05508-120, São Paulo, SP - Brasil, Tel.: (11) 3091-6501 - São Paulo - SP - Brazil
E-mail: diretoria.io@usp.br