Análisis de las series históricas de precipitación en la Cuenca Hidrográfica del Camaquã, RS, Brasil, a partir de datos observados y numéricos de alta resolución.

Autores/as

DOI:

https://doi.org/10.55761/abclima.v37i21.19261

Palabras clave:

ERA5. Tendencias de Precipitación. Recursos Hídricos.

Resumen

El presente artículo aborda el análisis de las series históricas de precipitación en la Cuenca Hidrográfica del Camaquã (BHC), ubicada en Rio Grande do Sul, Brasil. El estudio destaca la relevancia del monitoreo climático, especialmente para entender las variaciones en la precipitación, que impactan en actividades económicas locales como la agricultura y la ganadería. El objetivo principal es identificar y llenar las brechas en los datos históricos de precipitación, utilizando métodos estadísticos como la regresión lineal múltiple, y verificar las tendencias de precipitación a lo largo de 40 años (1981-2020). La investigación también correlaciona datos históricos con el reanálisis, con el fin de evaluar la precisión de este modelo. Los resultados indican una distribución media casi homogénea a lo largo de los meses, con valores ligeramente superiores en la primavera. La serie histórica no mostró tendencias significativas. Cabe destacar que el ERA5 presenta una fuerte correlación con los datos observados, aunque tiende a sobreestimar la precipitación, especialmente en los meses más cálidos.

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Biografía del autor/a

Taís Pegoraro Scaglioni, Graduate Program in Water Resources, Federal University of Pelotas (UFPel); Tapes Unit, State University of Rio Grande do Sul (UERGS);

Possui graduação em Meteorologia pela Universidade Federal de Pelotas (2003), mestrado em Meteorologia pela Universidade Federal de Pelotas (2006) e doutorado em Recursos Hídricos pela UFPel (2025). Desde 2011 é professora da Universidade Estadual do Rio Grande do Sul (UERGS) - Unidade em Tapes, atuando em disciplinas na área da ciências exatas para os cursos de Graduação em Gestão Ambiental e Administração, atualmente está na coordenação do Curso de Graduação em Administração. Na pesquisa tem interesse em assuntos que envolvam eventos extremos, oscilações climáticas e fluxos de umidade.

Mateus Menezes Straceione , Undergraduate Student in Business Administration, Tapes Unit; State University of Rio Grande do Sul (UERGS);

He holds a Bachelor's degree in Environmental Management from the State University of Rio Grande do Sul (completed in 2019) and a Specialization in Socio-Environmental Education from Uergs (completed in 2021). Currently studying a degree in Administration at the State University of Rio Grande do Sul. Experience is mainly focused on agricultural areas and geosciences, standing out in topics such as environmental management, agricultural education, ecological corridors, Mbya Guarani communities, community gardens and indigenous lands.

André Becker Nunes , School of Meteorology, Federal University of Pelotas (UFPel);

Degree in Meteorology from the Federal University of Pelotas (UFPEL) (2000), Master's degree in Meteorology from UFPEL (2002) in the area of ​​planetary boundary layer physics and PhD in Meteorology from the National Institute for Space Research (2008) in the area of ​​micrometeorology modeling . Participation in the CCST-INPE Climate Change Group between 2008 and 2009. Professor of higher education at the Faculty of Meteorology at UFPEL since November 2009. Member of the Postgraduate Program in Meteorology (PPGMET) and the Postgraduate Program in Water Resources (PPGRH). Doctoral, master's and scientific initiation guidance in the areas of climatology, climate change, synoptic meteorology, agrometeorology and micrometeorology. Co-supervision in the Postgraduate Program in Agronomy (UFPEL), the Postgraduate Program in Remote Sensing (UFRGS) and the Postgraduate Program in Meteorology (UFSM). Head of the Meteorology Department at UFPel (2010-2014). Tutor of the PET-Meteorology Group (2016-2021). Associate Professor at the Department of Meteorology at UFPEL. Coordinator of the Postgraduate Program in Water Resources at UFPEL (2022-2024).

Citas

APARECIDO, L. E. O.; ROLIM, G. S.; MORAES, J. R. S. C. Validation of ECMWF climatic data, 1979-2017, and implications for modelling water balance for tropical climates. International Journal of Climatology, v. 40, n. 15, p. 1- 20, 2020. DOI: https://doi.org/10.1002/joc.6604

ARRUDA, A. M. D.; CENTENO, L. N.; NUNES, A. B. Relation Between Major Climatic Indices and Subseasonal Precipitation in Rio Grande do Sul State, Brazil. Meteorology, v. 4, n. 5, 2025. Available at: https://doi.org/10.3390/meteorology4010005. Accessed on: Sep. 10. 2025. DOI: https://doi.org/10.3390/meteorology4010005

BARBOSA, S. E. S. et al. Generation of regionalization models of maximum, long-term average, and seven-day minimum flows for the Carmo River Basin, Minas Gerais. Engenharia Sanitária e Ambiental, v. 10, p. 64-71, 2005. DOI: https://doi.org/10.1590/S1413-41522005000100008

BARROS, V. S. et al. Trend analysis of the standardized precipitation index in Recife–PE. Research, Society and Development, v. 10, n. 8, p. e52310817458-e52310817458, 2021. DOI: https://doi.org/10.33448/rsd-v10i8.17458

BERTONI, J. C.; TUCCI, C. E. M. Precipitation. In: TUCCI, C. E. M. Hydrology Science and Application. 4th ed. 9th imp., Porto Alegre: Ufrgs, 2020. Chap. 5. p.177-241.

BRUBACHER, J. P. et al. Gap filling in daily precipitation time series in Rio Grande do Sul. Revista Brasileira de Meteorologia, v. 35, p. 335-344, 2020. DOI: https://doi.org/10.1590/0102-7786352035

CARDOSO, I. P. et al. Validation of precipitation data generated by ERA5 reanalysis for the Mirim-São Gonçalo watershed, Brazil. Revista Brasileira de Geografia Física, [S. l.], v. 17, n. 2, p. 824–837, 2024. DOI: 10.26848/rbgf.v17.2.p824-837. Available at: https://periodicos.ufpe.br/revistas/index.php/rbgfe/article/view/259340. Accessed on: Abr. 8. 2024. DOI: https://doi.org/10.26848/rbgf.v17.2.p824-837

CAVALCANTI, I. F. A. Weather and climate in Brazil. Text workshop, 2016.

COLLISCHONN, W.; DORNELES, F. Hydrology for engineering and environmental sciences. 2a ed. Porto Alegre: ABRH, p. 210, 2013.

COPERNICUS CLIMATE CHANGE SERVICE (C3S). 2024. ERA5: Fifth generation of ECMWF atmospheric reanalyses of the global climate. Copernicus Climate Change Service Climate Data Store (CDS). Available at: https://climate.copernicus.eu/climate-reanalysis. Accessed on: Jul. 16. 2024.

COUTINHO, E. R. et al. Application of artificial neural networks (ANNs) in the gap filling of meteorological time series. Revista Brasileira de Meteorologia, v. 33, n. 2, p. 317-328, 2018. DOI: https://doi.org/10.1590/0102-7786332013

CUNHA JÚNIOR, R. O; FIRMINO, P. R. A. Simulation of missing values in precipitation time series for evaluation of imputation methods. Revista Brasileira de Climatologia, v. 30, n. 18, p. 691–714, 2022.

DIAZ, C. C. F.; PEREIRA, J. A. S.; NÓBREGA, R. S. Comparison of data estimated by two different methods for filling rainfall gaps in the Pajeú River basin, Pernambuco, Brazil. Revista Brasileira de Climatologia, v. 22, p. 324-339, 2018.

FERREIRA, G.W.S.; REBOITA, M.S.A. New Look into the South America Precipitation Regimes: Observation and Forecast. Atmosphere, v.13, n.6, 2022. DOI: https://doi.org/10.3390/atmos13060873

FREITAS, I. G. F. de; et al. Assessment of wind speed using hindcast developed by Climatempo for the application of wind resources in Brazil. In: BRAZIL WINDPOWER, 2023. Proceedings [...]. [S.l.: s.n.], 2023. Available at: https://abeeolica.org.br/wp-content/uploads/2023/11/1.3AP_1690574718-Avaliacao-da-Velocidade-do-Vento-Utilizando-Hindcast-Desenvolvido-pela-Climatempo-para-a-Aplicacao-dos-Recursos-Eolicos-no-Brasil.pdf. Accessed on: June 20. 2024.

GONÇALVES, F. N.; BACK, A. J. Analysis of spatial and seasonal variation and trends in precipitation in the Southern region of Brazil. Revista de Ciências Agrárias, vol. 41, no. 3, pp. 592-602, 2018. Available at: https://doi.org/10.19084/RCA17204. Accessed on: June 20. 2024. DOI: https://doi.org/10.19084/RCA17204

GRIMM, A.M.; FERRAZ, S.E.T.; GOMES, J. Precipitation Anomalies in Southern Brazil Associated with El Niño and La Niña Events. Journal of Climate, v. 11, p. 2863–2880, 1998. DOI: https://doi.org/10.1175/1520-0442(1998)011<2863:PAISBA>2.0.CO;2

HAIDEN, T. et al. Use of in situ surface observations at ECMWF. Reading, UK: European Centre for Medium Range Weather Forecasts, 2018.

HERSBACH, H. et al. The ERA5 global reanalysis. Quarterly Journal of the Royal Meteorological Society, v. 146, p. 1999–2049, 2020. Available at:

https://doi.org/10.55761/abclima.v30i18.15243. Accessed on: Jul. 16. 2024. DOI: https://doi.org/10.55761/abclima.v30i18.15243

INMET. Ministry of Agriculture and Livestock. National Institute of Meteorology. Climatological Normals. [2024]. Available at: https://portal.inmet.gov.br/servicos/normais-climatol%C3%B3gicas. Accessed on: Feb. 02. 2024.

JIANG, C. et al. Evaluation of precipitation reanalysis products for regional hydrological modelling in the Yellow River Basin. Theoretical and Applied Climatology, v. 155, n. 4, p. 2605-2626, 2024. DOI: https://doi.org/10.1007/s00704-023-04758-w

KENDALL, M. G. Rank Correlation Methods. Griffin. London. 1975.

LAVERS, D. A. et al. An evaluation of ERA5 precipitation for climate monitoring. Quarterly Journal of the Royal Meteorological Society, v. 148, n. 748, p. 3152-3165, 2022. DOI: https://doi.org/10.1002/qj.4351

MANN, H. B. Nonparametric tests against trend. Econometrica. Chicago, v. 13, n. 3, p. 245-259, 1945. DOI: https://doi.org/10.2307/1907187

MENDONÇA, F.; DANNI-OLIVEIRA, I. M. Climatology: basic concepts and climates of Brazil. Oficina de Textos, 2017.

MUKAKA, M. M. Statistics Corner: A guide to appropriate use of Correlation coeficiente in medical research. Malawi Medical Journal, v. 24, n. 3, p. 69-71, 2012.

NOGUEIRA, N. C. de O., MACHADO, P. H. G., REBOITA, M. S. Climatological Study of Cold Fronts active in Southern Rio Grande do Sul and Southern Minas Gerais between 2009 and 2021. Revista Brasileira de Climatologia, vol. 34, no. 20, pp. 306–334, 2024. DOI: https://doi.org/10.55761/abclima.v34i20.16664

OLIVEIRA, L. F. C. et al. Comparison of methodologies for gap-filling in historical time series of annual precipitation. Revista Brasileira de Engenharia Agrícola e Ambiental, vol. 14, no. 11, pp. 1186-1192, 2010. DOI: https://doi.org/10.1590/S1415-43662010001100008

OLIVEIRA, T. A.; SANCHES, F. de O.; FERREIRA, C. de C. M. Application and evaluation of techniques for gap-filling of rainfall data in typical, dry, and rainy years. Revista Entre-Lugar, vol. 12, no. 24, pp. 301–320, 2021. DOI: 10.30612/rel.v12i24.15137. Available at: https://ojs.ufgd.edu.br/index.php/entre-lugar/article/view/15137. Accessed on: Mar. 10. 2024. DOI: https://doi.org/10.30612/rel.v12i24.15137

PIERSANTE, J. O. et al. A synoptic evolution comparison of the smallest and largest MCSs in subtropical South America between spring and summer. Monthly Weather Review, v. 149, n. 6, p. 1943-1966, 2021. DOI: https://doi.org/10.1175/MWR-D-20-0208.1

REBOITA, M. S.; et al. Impacts of teleconnection patterns on South America climate. Annals of the New York Academy of Sciences, v. 1504, n. 1, p. 116-153, 2021. DOI: https://doi.org/10.1111/nyas.14592

RODRIGUES, A. A. et al. Rainfall trend and variability in Rio Grande do Sul, Brazil. Revista Brasileira de Climatologia, v. 32, 2023. Available at: https://doi.org/10.55761/abclima.v32i19.16179. Acessed on: Jun. 19. 2024. DOI: https://doi.org/10.55761/abclima.v32i19.16179

ROSA, A (Ed.); SILVA, C. S. da (Ed.); SILVA, J. A. O. da (Ed.). Camaquã river basin plan 2015/2035. Porto Alegre: SEMA, 2016. Available at: https://drive.google.com/file/d/0Byn_B-4Lg7RGQXN4SldKRVM1VVk/view. Accessed on: Mar. 10. 2024.

ROSSATO, M. S. The climates of Rio Grande do Sul: a proposal for climatic classification. Revista Entre-Lugar, vol. 11, no. 22, pp. 57-85, 2020. DOI: https://doi.org/10.30612/el.v11i22.12781

SALES, E. S. G.; et al. Relationship between NDVI and EVI with climatic indices in Northeast Brazil. Geoambiente On-line, no. 47, pp. 394-422, 2023. Available at: https://www.researchgate.net/publication/376597127_RELACAO_DO_NDVI_E_EVI_COM_OS_INDICES_CLIMATICOS_DO_NORDESTE_DO_BRASIL. Accessed on: Sep. 12. 2025.

SANCHES, F. O.; VERDUM, R.; FISCH, G. Long-term trend of daily rainfall in Southwestern Rio Grande do Sul: extreme events and arenization. Revista Brasileira de Geografia Física, Recife, vol. 7, no. 6, pp. 1100-1109, 2014. DOI: https://doi.org/10.5935/1984-2295.20140012

SANTOS, F. A., et al. Long-term variability and trend analysis of the rainfall distribution in the state of Bahia, Northeast Brazil. Theoretical and Applied Climatology, v. 148, n. 3-4, p. 1423-1433, 2022. Available at: https://doi.org/10.1007/s00704-021-03838-4. Acessed on: Mar. 12. 2024.

SARKAR, D. et al. Compiling non-parametric tests along with CA-ANN model for precipitation trends and variability analysis: A case study of Eastern India. Water Cycle, v. 2, p. 71-84, 2021. DOI: https://doi.org/10.1016/j.watcyc.2021.11.002

SCAGLIONI, T. P. et al. Climatic oscillations and the relationship with extreme precipitation events in the Camaquã river basin/RS. Revista Brasileira de Climatologia, vol. 33, pp. 260-277, 2023. DOI: https://doi.org/10.55761/abclima.v33i19.16649

SCAGLIONI, T. P.; FERNANDES, R. K. U.; NUNES, A. B. Extreme events of precipitation excess and deficit in the Camaquã River Basin from 1991-2020. Conjecturas, vol. 22, no. 2, pp. 672-686, 2022. DOI: https://doi.org/10.53660/CONJ-565-A21

SEN, P. K. Estimates of the regression coeficiente based on Kendall’s Tau. Journal of the American Statistical Association, v. 63, p. 1379-1389, 1968. DOI: https://doi.org/10.1080/01621459.1968.10480934

SILVA, M. V.; CAMPOS, C. R. J. Decadal anomalies of the hydrological regime of RS from 1977 to 2006. Ciência e Natura, UFSM, vol. 22, no. 1, pp. 75-89, 2011.

TANG, G.; et al. Em-Earth: The Ensemble Meteorological Dataset for Planet Earth. Bulletin of the American Meteorological Society, v. 103, n.4, p. E996–E1018, 2022. DOI: https://doi.org/10.1175/BAMS-D-21-0106.1

WMO. Guide to climatological practices. Geneva: World Meteorological Organization, 2018.

Publicado

27/09/2025

Cómo citar

Scaglioni, T. P., Straceione , M. M., & Nunes , A. B. (2025). Análisis de las series históricas de precipitación en la Cuenca Hidrográfica del Camaquã, RS, Brasil, a partir de datos observados y numéricos de alta resolución. Revista Brasileña De Climatología, 37(21), 385–404. https://doi.org/10.55761/abclima.v37i21.19261

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