Identificação de Preditores Para as Chuvas do Setor Leste do Nordeste do Brasil Utilizando Análise de Correlação Canônica

Geber Barbosa de Albuquerque Moura, José Ivaldo Barbosa de Brito, Francisco de Assis Salviano de Sousa, Enilson Palmeira Cavalcanti, Jhon Lennon Bezerra da Silva, Cristina Rodrigues Nascimento, Pabrício Marcos Oliveria Lopes

Resumo


O objetivo deste trabalho foi encontrar as melhores variáveis preditoras através de análise de correlação canônica nos ventos alísios, Temperatura da Superfície do Mar (TSM), Pressão atmosférica à superfície no Oceano Pacífico Equatorial e TSM no Atlântico Tropical (área do Dipolo), de forma que se possam elaborar modelos de previsão da precipitação pluvial (período chuvoso) do setor leste do Nordeste do Brasil para os quatro meses mais chuvosos dos três grupos homogêneos, com antecedência de três meses. Os grupos foram escolhidos a partir de análise de agrupamento utilizando o método hierárquico. Para estudar as correlações canônicas entre a precipitação dos grupos com os dados padronizados de TSM, vento e pressão atmosférica, as análises fundamentaram-se na série dos totais de precipitação de abril a julho e dados defasados de médias de três meses (média de Novembro a Janeiro) de TSM, vento em 850 hPa no Pacífico Equatorial e pressão da atmosfera em Tahiti e Darwin para o período de 1986 a 2017. Percebe-se que os principais preditores para os grupos homogêneos foram, por ordem de maior importância: Média de três meses de atraso do índice de ventos alísios Equatorial central (MedWC), Média da pressão atmosférica à superfície em Darwin (Mdarwin), Média do EN 34 (MEN34), Média da pressão atmosférica à superfície em Tahiti (Mtahiti) e Média de índice de ventos alísios leste (MedWE). Nota-se deste atraso que a principal influência está no Pacífico, no ENOS.

 

Predictors identification for rain in the east sector of the Northeast Brazil using canonical correlation analysis

 

A B S T R A C T

The objective of this work was to find the best predictor variables through canonical correlation analysis in trade winds, Sea Surface Temperature (SST), Atmospheric pressure at the surface in the Equatorial Pacific Ocean and SST in the Tropical Atlantic (Dipole area), that models for forecasting rainfall (rainy season) in the eastern sector of northeastern Brazil can be developed for the four rainiest months of the three homogeneous groups, three months in advance. The groups were chosen from the cluster analysis using the hierarchical method. To study the canonical correlations between the precipitation of the groups with the standardized data of SST, wind and atmospheric pressure, the analyzes were based on the series of precipitation totals from April to July and lagged data of three-month averages (average from November to July). January) of SST, wind at 850 hPa in the Equatorial Pacific and atmospheric pressure in Tahiti and Darwin for the period from 1986 to 2017. It can be seen that the main predictors for homogeneous groups were, in order of greatest importance: Average of three months delay of the central Equatorial trade winds index (MedWC), mean of the atmospheric pressure at the surface in Darwin (Mdarwin), mean of the EN 34 (MEN34), mean of the atmospheric pressure at the surface in Tahiti (Mtahiti) and mean of the east trade winds (MedWE). It is noted from this delay that the main influence is in the Pacific, in the ENSO.

Keywords: wind, SST, precipitation.


Palavras-chave


Vento; TSM; Precipitação.

Texto completo:

PDF

Referências


Alves, J.M.B., Repelli, C.A., Mello, N.S., 1993. A pré-estação chuvosa do setor norte do Nordeste Brasileiro e sua relação com a temperatura dos oceanos adjacentes. Revista Brasileira de Meteorologia 8, 22-30. Disponível: http://www.rbmet.org.br/port/revista/revista_artigo.php?id_artigo=419

Anderson, T.W., 1984. An Introduction to Multivariate Statistical Analysis. 2th edition. John Wiley. New York. 439-449.

Andreoli, R.V., Oliveira, S.S., Kayano, M.T., Viegas, J., Souza, R.A.F., Candido, L.A., 2016. The influence of different el Niño types on the south American rainfall. International Journal of Climatology 37, 1374-1390. https://doi.org/10.1002/joc.4783

Aragão, J.O.R., Roucou, P., Harzallah, A., Fontaine, B; Janicot, S., 1994. Variabilité atmosphérique sur le Nordeste brésilien dans le modèle de circulation générale du LMD (1970-1988). Publications de l'Association Internationale de Climatologie 7, 432-438.

Barbosa, H.A., Lakshmi Kumar, T., Paredes, F., Elliott, S., Ayuga, J.G., 2018. Assessment of Caatinga response to drought using Meteosat-SEVIRI Normalized Difference Vegetation Index (2008-2016). ISPRS Journal of Photogrammetry and Remote Sensing 148, 235-252. https://doi.org/10.1016/j.isprsjprs.2018.12.014

Barnett, T.P., Preisendorfer, R., 1987. Origins and levels of monthly and seasonal forecast skill for United States surface air temperatures determined by canonical correlation analysis. Monthly Weather Review 115, 1825-1849. https://doi.org/10.1175/1520-0493(1987)115<1825:OALOMA>2.0.CO;2

Builes‑Jaramillo, A., Marwan, N., Poveda, G., Kurths, J., 2018. Nonlinear interactions between the Amazon River basin and the Tropical North Atlantic at interannual timescales. Climate Dynamics 50, 2951-2969. https://doi.org/10.1007/s00382-017-3785-8

Capotondi, A., Wittenberg, A.T., Newman, M., Di Lorenzo, E., Yu, J., et al., … Yeh, S.W., 2015. Understanding enso diversity. American Meteorological Society 921-938. https://doi.org/10.1175/BAMS-D-13-00117.1

Dias, F.J.S., Castro, B.M., Lacerda, L.D., 2018. Tidal and low-frequency currents off the Jaguaribe River estuary (4° S, 37° 4′ W), Northeastern Brazil. Ocean Dynamics 68, 967-985. https://doi.org/10.1007/s10236-018-1172-6

Fedorova, N., Levit, V., Campos, A.M.V., 2018. Brazilian Northeast Jet Stream: association with synoptic‐scale systems. Meteorological Applications 25, 261-268. https://doi.org/10.1002/met.1693

Forootan, E., Khandu., Awange, J.L., Schumacher, M., Anyah, R.O., Van Dijk, A.I.J.M., Kusche, J., 2016. Quantifying the impacts of ENSO and IOD on rain gauge and remotely sensed precipitation products over Australia. Remote Sensing of Environment 172, 50-66. https://doi.org/10.1016/j.rse.2015.10.027

Gomes, H.B., Ambrizzi, T., Herdies, D.L., Hodges, K., Pontes da Silva, B.F., 2015. Easterly wave Disturbances over northeast Brazil: an observational analysis. Advances in Meteorology 2015, 1-20. https://doi.org/10.1155/2015/176238

Gonzalez, R.A., Andreoli, R.V., Candido, L.A., Kayano, M.T., Souza, R.A.F., 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 Amazônica 43, 469-480. http://dx.doi.org/10.1590/S0044-59672013000400009

Grimm, A.M., Tedeschi, R.G., 2009. ENSO and Extreme Rainfall Events in South America. Journal of Climate 22, 1589-1609. https://doi.org/10.1175/2008JCLI2429.1

Hair, J.F., Black, W.C., Babin, B.J., Anderson, R.E., 1998. Multivariate data analysis. Upper Saddle River, NJ: Prentice hall. 5, 207-219.

Harzallah, A., Aragão, J.O.R., Sadourny, R., 1996. Interannual rainfall variability in Northeast Brazil: Observation and model simulation. International Journal of Climatology 16, 861-878. https://doi.org/10.1002/(SICI)1097-0088(199608)16:8<861::AID-JOC59>3.0.CO;2-D

Hastenrath, S., Greischar, L., 1993. Further work on the prediction of Northeast Brazil rainfall anomalies. Journal of Climate 6, 743-758. https://doi.org/10.1175/1520-0442(1993)006<0743:FWOTPO>2.0.CO;2

Hounsou-Gbo G.A., Araujo, M., Bourlès, B., Veleda, D., Servain, J., 2015. Tropical Atlantic Contributions to Strong Rainfall Variability Along the Northeast Brazilian Coast. Advances in Meteorology 2015, 1-13. http://dx.doi.org/10.1155/2015/902084.

Hounsou-Gbo. G.A., Servain, J., Araujo, M., Martins, E.S., Bourles, B., Canaix, G., 2016. Oceanic Indices for Forecasting Seasonal Rainfall over the Northern Part of Brazilian Northeast. Am J Clim Change 5, 261-274. http://dx.doi.org/10.4236/ajcc.2016.52022

Kayano, M.T., Andreoli, R.V., Souza, R.A.F., 2011. Evolving anomalous SST patterns leading to ENSO extremes: relations between the tropical Pacific and Atlantic Oceans and the influence on the South American rainfall. International Journal of Climatology 31, 1119-1134. https://doi.org/10.1002/joc.2135

Kayano, M.T., Capistrano, V.B., 2014. How the Atlantic multidecadal oscillation (AMO) modifies the ENSO influence on the South American rainfall. International Journal of Climatology 34, 162-178. https://doi.org/10.1002/joc.3674

L’Heureux, M.L., Tippett, M.K., Barnston, A.G., 2015. Characterizing ENSO coupled variability and its impact on North American seasonal precipitation and temperature. Journal Climate 28, 4231-4245. https://doi.org/10.1175/JCLI-D-14-00508.1

Marengo, J.A., Alves, L.M., Alvala, R., Cunha, A.P., Brito, S., Moraes, O.L., 2018. Climatic characteristics of the 2010-2016 drought in the semiarid Northeast Brazil region. Anais da Academia Brasileira de Ciências 90, 1973-1985. http://dx.doi.org/10.1590/0001-3765201720170206

Mingoti, S.A., 2005. Análise de dados através de métodos de estatística multivariada: uma abordagem aplicada. Belo Horizonte: Editora UFMG. 297 p.

Moraes, M.D.C., Oliveira, F.P., Coutinho, M.D., 2015. One case of simulation of Upper Tropospheric Cyclonic vortex in the Brazil Northeast – impact in the convection parameterization. Journal of Hyperspectral Remote Sensing 1, 27-44. https://doi.org/10.29150/jhrs.v5.1.p027-044

Moura, A.D., Shukla, J., 1981. On the dynamics of droughts in Northeast Brazil: Observations, theory and numerical experiments with a general circulation model. Journal of the Atmospherical Sciences 38, 2653-2675. https://doi.org/10.1175/1520-0469(1981)038<2653:OTDODI>2.0.CO;2

Moura, G.B.A., Aragão, J.O.R., Lacerda, F.F., Passavante, J.Z.O., 2000. Relação entre a precipitação no setor leste do Nordeste do Brasil e a temperatura da superfície nos oceanos Atlântico (área do Dipolo) e Pacífico. Revista Brasileira de Engenharia Agrícola e Ambiental 4, 247-251. http://dx.doi.org/10.1590/S1415-43662000000200019

Moura, G.B.A., Aragão, J.O.R., Melo, J.S.P., Silva, A.P.N., Giongo, P.R., Lacerda, F.F., 2009. Relação entre a precipitação do leste do Nordeste do Brasil e a temperatura dos oceanos. Revista Brasileira de Engenharia Agrícola e Ambiental 14, 462-469. http://dx.doi.org/10.1590/S1415-43662009000400014

Nobre, P., Shukla, J., 1996. Variations of sea surface temperature, wind stress and rainfall over the tropical Atlantic and South America. Journal of Climate 9, 2464-2479. https://doi.org/10.1175/1520-0442(1996)009<2464:VOSSTW>2.0.CO;2

Nóbrega, J.N., Santos, C.A.C., Gomes, O.M.G., Bezerra, B.G., Brito, J.I.B., 2014. Eventos extremos de precipitação nas mesorregiões da Paraíba e suas relações com a tsm dos oceanos tropicais. Revista Brasileira de Meteorologia 29, 197-208. http://dx.doi.org/10.1590/S0102-77862014000200005

Rana, S., Renwick, J., Mcgregor, J., Ankita Singh, A., 2018. Seasonal Prediction of Winter Precipitation Anomalies over Central Southwest Asia: A Canonical Correlation Analysis Approach. Journal of Climate 31, 727-741. https://doi.org/10.1175/JCLI-D-17-0131.1

Rao, V.B.; Lima, M.C., Franchito, S.H., 1993. Seasonal and interannual variations of rainfall over eastern Northeast Brazil. Journal of Climate 6, 1754-1763. https://doi.org/10.1175/1520-0442(1993)006<1754:SAIVOR>2.0.CO;2

Ropelewski, C.F., Halpert, M.S., 1986. North American precipitation and temperature patterns associated with the El Niño Southern Oscillation (ENSO). Monthly Weather Review 114, 2352-2362. https://doi.org/10.1175/1520-0493(1986)114<2352:NAPATP>2.0.CO;2

Salgueiro, J.H.P.B., Montenegro, S.M.G.L., Pinto, E.J.A., Silva, B.B., Souza, W.M., Oliveira, L.M.M., 2016. Influence of oceanic-atmospheric interactions on extreme events of daily rainfall in the Sub-basin 39 located in Northeastern Brazil. Revista Brasileira de Recursos Hídricos 21, 685-693. http://dx.doi.org/10.1590/2318-0331.011616023

Servain, J., 1991. Simple Climatic Indices for the Tropical Atlantic Ocean and some applications. Journal of Geophysical Research 96, 137-146. https://doi.org/10.1029/91JC01046

Silva, M.T., Costa, S.C.F.E., Gomes Filho, M.F., Lucena, D.B., 2011. Estudo da Temperatura da Superfície do Mar para os Oceanos Atlântico e Pacífico Utilizando a Técnica de Análises de Componente Principal e de Agrupamento. Revista Brasileira de Geografia Física 4, 264-277. https://doi.org/10.26848/rbgf.v4.2.p264-277

Trugilho, P.F., Lima, J.T., Mori, F.A., 2003. Correlação canônica das características químicas e físicas da madeira de clones de Eucalyptus grandis e Eucalyptus saligna. Cerne 9, 81-91. Disponível: .

Ward, J.H., 1963. Hierarchical grouping to optimize an objective function. Journal American Statistical Association 58, 236-244. http://dx.doi.org/10.1080/01621459.1963.10500845

Ward, M.N., Folland, C.K., 1991. Prediction of seasonal rainfall in the north nordeste of Brazil using eigenvectors of sea-surface temperature. International Journal of Climatology 11, 711-743. https://doi.org/10.1002/joc.3370110703




DOI: https://doi.org/10.26848/rbgf.v13.4.p1463-1482

Licença Creative Commons
Esta obra está licenciada sob uma licença Creative Commons Atribuição 4.0 Internacional.

      

Revista Brasileira de Geografia Física - ISSN: 1984-2295

Creative Commons License
Esta obra está licenciada com uma Licença Creative Commons Attribution-NonCommercial 4.0 International License