Seasonality of the rainfall regime in the mesoregions of the Pernambuco state, Brazil
DOI:
https://doi.org/10.33448/rsd-v12i12.43835Keywords:
Rainfall regimes; Seasonality indices; Mann-Kendall test; Sen’s slope test.Abstract
This research aims to classify the rainfall regimes in the Pernambuco municipalities of Petrolina (Sertão of São Francisco), Araripina (Sertão of Pernambuco), Garanhuns (Agreste), Rio Formoso (Zona da Mata) and Abreu e Lima (Metropolitan region of Recife) based on the extraction of seasonality from monthly precipitation data. The study is carried out using the seasonality method, with which the seasonality indices (individual and general) and the replicability index (RI) are calculated, and in the trend analysis using the Mann-Kendall and Sen’s slope methods. The data analyzed were made available by the Agência Pernambucana de Águas e Clima – APAC, and correspond to monthly precipitation records captured between 1995 and 2020 at meteorological stations located in each municipality. Results of the Mann-Kendall and Sen’s slope tests indicated that there was no statistically significant trend in the annual seasonality of rainfall regimes for any of the rainfall stations investigated. According to the general seasonality index, the average rainfall regimes in the municipalities of Garanhuns (Agreste), Rio Formoso (Zona da Mata) and Abreu e Lima (Metropolitan region of Recife) for the analyzed period were classified as rather seasonal with a short dry season, while in the municipalities of Araripina (Sertão of Pernambuco) and Petrolina (Sertão of São Francisco), they were classified as markedly seasonal with a long dry season. Furthermore, all municipalities presented average rainfall regimes with high replicability, the lowest being in Petrolina (with RI = 0.69) and the highest in Rio Formoso (with RI = 0.80).
References
Asfora, M. C., Lima, M., & Lacerd, M. R. de S. (2017). Diagnóstico da seca 2011-2016 em Pernambuco: impactos e políticas de mitigação. Parcerias Estratégicas, 22(44), 247–273.
Bari, S. H., Hussain, M. M., & Husna, N.-E.-A. (2017). Rainfall variability and seasonality in northern Bangladesh. Theoretical and Applied Climatology, 129(3–4), 995–1001. https://doi.org/10.1007/s00704-016-1823-9
Barros, V. da S., Gomes, V. K. I., Silva Júnior, I. B. da, Silva, A. S. V. da, Silva, A. S. A. da, Bejan, L. B., & Stosic, T. (2021). Análise de tendência do índice de precipitação padronizado em Recife–PE. Research, Society and Development, 10(8), e52310817458. https://doi.org/10.33448/rsd-v10i8.17458
Birsan, M.-V., Dumitrescu, A., Micu, D. M., & Cheval, S. (2014). Changes in annual temperature extremes in the Carpathians since AD 1961. Natural Hazards, 74(3), 1899–1910. https://doi.org/10.1007/s11069-014-1290-5
da Silva, A. S. A., Stosic, B., Menezes, R. S. C., & Singh, V. P. (2019). Comparison of Interpolation Methods for Spatial Distribution of Monthly Precipitation in the State of Pernambuco, Brazil. Journal of Hydrologic Engineering, 24(3). https://doi.org/10.1061/(ASCE)HE.1943-5584.0001743
da Silva Araújo, L., da Silva, A. S. A., Menezes, R. S. C., Stosic, B., & Stosic, T. (2023). Analysis of rainfall seasonality in Pernambuco, Brazil. Theoretical and Applied Climatology. https://doi.org/10.1007/s00704-023-04462-9
Dos Santos, W. M., Silva Souza, R. M., De Souza, E. S., De Almeida, A. Q., & Dantas Antonino, A. C. (2017). Variabilidade espacial da sazonalidade da chuva no semiárido brasileiro. Journal of Environmental Analysis and Progress, 2(4), 368–376. https://doi.org/10.24221/jeap.2.4.2017.1466.368-376
Doyle, M. E. (2020). Observed and simulated changes in precipitation seasonality in Argentina. International Journal of Climatology, 40(3), 1716–1737. https://doi.org/10.1002/joc.6297
Garrick, D., & Hall, J. W. (2014). Water Security and Society: Risks, Metrics, and Pathways. Annual Review of Environment and Resources, 39(1), 611–639. https://doi.org/10.1146/annurev-environ-013012-093817
Gocic, M., & Trajkovic, S. (2013). Analysis of changes in meteorological variables using Mann-Kendall and Sen’s slope estimator statistical tests in Serbia. Global and Planetary Change, 100, 172–182. https://doi.org/10.1016/j.gloplacha.2012.10.014
Hoekstra, A. Y., Buurman, J., & van Ginkel, K. C. H. (2018). Urban water security: A review. Environmental Research Letters, 13(5), 053002. https://doi.org/10.1088/1748-9326/aaba52
Kendall, M. G. (1975). Rank correlation methods. Charles Griffin.
Kilimani, N., van Heerden, J., Bohlmann, H., & Roos, L. (2018). Economy-wide impact of drought induced productivity losses. Disaster Prevention and Management: An International Journal, 27(5), 636–648. https://doi.org/10.1108/DPM-05-2018-0155
Mann, H. B. (1945). Nonparametric Tests Against Trend. Econometrica, 13(3), 245–259.
Marengo, J. A., Galdos, M. V., Challinor, A., Cunha, A. P., Marin, F. R., Vianna, M. dos S., Alvala, R. C. S., Alves, L. M., Moraes, O. L., & Bender, F. (2022). Drought in Northeast Brazil: A review of agricultural and policy adaptation options for food security. Climate Resilience and Sustainability, 1(1). https://doi.org/10.1002/cli2.17
Marengo, J. A., Torres, R. R., & Alves, L. M. (2017). Drought in Northeast Brazil—past, present, and future. Theoretical and Applied Climatology, 129(3–4), 1189–1200. https://doi.org/10.1007/s00704-016-1840-8
Rai, P., & Dimri, A. P. (2020). Changes in rainfall seasonality pattern over India. Meteorological Applications, 27(1), 1–6. https://doi.org/10.1002/met.1823
Raziei, T. (2018). An analysis of daily and monthly precipitation seasonality and regimes in Iran and the associated changes in 1951–2014. Theoretical and Applied Climatology, 134(3–4), 913–934. https://doi.org/10.1007/s00704-017-2317-0
Raziei, T., Daryabari, J., Bordi, I., & Pereira, L. S. (2014). Spatial patterns and temporal trends of precipitation in Iran. Theoretical and Applied Climatology, 115(3–4), 531–540. https://doi.org/10.1007/s00704-013-0919-8
Sen, P. K. (1968). Estimates of the Regression Coefficient Based on Kendall’s Tau. Source: Journal of the American Statistical Association, 63(324), 1379–1389.
Sharma, S., & Singh, P. K. (2019). Spatial trends in rainfall seasonality: a case study in Jharkhand, India. Weather, 74(1), 31–39. https://doi.org/10.1002/wea.3231
Silva, A. S. A., Cunha Filho, M., Menezes, R. S. C., Stosic, T., & Stosic, B. (2020). Trends and Persistence of Dry–Wet Conditions in Northeast Brazil. Atmosphere, 11(10), 1134. https://doi.org/10.3390/atmos11101134
Walsh, R. P. D., & Lawler, D. M. (1981). Rainfall seasonality spatial patterns and change through time. Weather, 36(7), 201–208. https://doi.org/10.1002/j.1477-8696.1981.tb05400.x
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Copyright (c) 2023 Wenderson Gomes Barbosa; Jaine de Moura Carvalho; Denise Honorato Lopes da Silva; Arundo Nunes da Silva Júnior; Lidiane da Silva Araújo; Antonio Samuel Alves da Silva; Tiago Alessandro Espínola Ferreira; Claudio Tadeu Cristino; Tatijana Stosic
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