Climatic extremes in Brazil: a parallel analysis of historical trends and socioeconomical impacts
DOI:
https://doi.org/10.5902/2179460X90742Keywords:
Extreme events, Disasters, Human and financial costs, Brazil, Data analysisAbstract
An important consequence of human-induced climate change is the increase in extreme weather events. This study contributes to the understanding of Brazil’s climate change by examining historical temperature and precipitation patterns. Extreme events of temperature and precipitation are identified using data from the Brazilian Institute of Meteorology, which includes records from 634 meteorological stations operating intermittently since 1961. Using the first 30 years (1961–1990) as the reference period, our results show a significant increase in warm days and a corresponding decrease in cold days over the last 30 years (1991–2020), in agreement with previous works. In terms of precipitation, it indicates a trend toward drier conditions in the Northeast region of Brazil, whereas the South is experiencing wetter conditions, with an increase in the number of heavy precipitation days in South and in the extremely dry periods in the Northeast. These results have been verified for consistency with several extreme climate indices measured in this study. Additionally, data from S2iD is analyzed, an official database that records natural disasters in Brazil, to estimate their impact in terms of human losses and financial costs over the past decade. Our findings indicate that drought events are the most economically costly, with multiple instances causing damages exceeding a billion USD, whereas storms have the greatest impact on people. Although it is not possible to directly attribute the natural disasters recorded in the S2iD database to the extreme weather events identified through meteorological data, discussion is done on potential implications of these events in the frequency and location of the disasters.
Downloads
References
Almeida, C. T., Oliveira‐Júnior, J. F., Delgado, R. C., Cubo, P., & Ramos, M. C. (2017). Spatiotemporal rainfall and temperature trends throughout the Brazilian Legal Amazon, 1973–2013. International Journal of Climatology, 37(4), 2013-2026. https://doi.org/10.1002/joc.4831
Ávila, A., Justino, F., Wilson, A., Bromwich, D., & Amorim, M. (2016). Recent precipitation trends, flash floods and landslides in southern Brazil. Environmental Research Letters, 11(11), 114029. https://doi.org/10.1088/1748-9326/11/11/114029
Avila-Diaz, A., Benezoli, V., Justino, F., Torres, R., & Wilson, A. (2020). Assessing current and' future trends of climate extremes across Brazil based on reanalyses and earth system model projections. Climate Dynamics, 55(5), 1403-1426. https://doi.org/10.1007/s00382-020-05333-z
Bador, M., Donat, M. G., Geoffroy, O., & Alexander, L. V. (2018). Assessing the robustness of future extreme precipitation intensification in the CMIP5 ensemble. Journal of Climate, 31(16), 6505-6525. https://doi.org/10.1175/JCLI-D-17-0683.1
Caleffi, F., Viegas, C. V. ., Lima, K. B., & Bonato, S. V. (2024). Os impactos de eventos climáticos extremos: uma análise abrangente das enchentes de 2024 no Rio Grande do Sul. Redes, 29(1), 1-27. https://doi.org/10.17058/redes.v29i1.19660
Cardona, O. D., van Aalst, M. K., Birkmann, J., Fordham, M., Mc Gregor, G., Perez, R., Pulwarty, R. S., Schipper, E. L. F. & Sihn, B. T. (2012). Determinants of risk: exposure and vulnerability. In C. B. Field et al. (Eds.), Managing the risks of extreme events and disasters to advance climate change adaptation: special report of the intergovernmental panel on climate change (pp. 65-108). Cambridge University Press. https://doi.org/10.1017/CBO9781139177245.005
Carvalho, I. C. D. H. (2019). Análise de recorrências de eventos de desastres naturais com base no Sistema Integrado de Informações sobre Desastres (S2iD) e séries históricas de precipitação no Brasil: uma contribuição metodológica. [Doctoral Dissertation, Universidade de Brasília].
Centro de Estudos Avançados em Economia Aplicada. (2024). Cepea-USP/CNA: PIB do agronegócio brasileiro – junho de 2024. https://www.cepea.esalq.usp.br/br/pib-do-agronegociobrasileiro.aspx
Chagas, V. B., Chaffe, P. L., & Blöschl, G. (2022). Climate and land management accelerate the Brazilian water cycle. Nature Communications, 13(1), 5136. https://doi.org/10.1038/s41467-022-32580-x
Costa, R. L., de Mello Baptista, G. M., Gomes, H. B., dos Santos Silva, F. D., da Rocha Junior, R. L., de Araújo Salvador, M., & Herdies, D. L. (2020). Analysis of climate extremes indices over northeast Brazil from 1961 to 2014. Weather and Climate Extremes, 28, 100254. https://doi.org/10.1016/j.wace.2020.100254
Centre for Research on the Epidemiology of Disasters. (2022). 2021 disasters in numbers. https://www.emdat.be
Dalagnol, R., Gramcianinov, C. B., Crespo, N. M., Luiz, R., Chiquetto, J. B., Marques, M. T., Neto, G. D., Abreu, R. C., Li, S., Lott, F. C., Anderson, L. O., & Sparrow, S. (2022). Extreme rainfall and its impacts in the Brazilian Minas Gerais state in January 2020: Can we blame climate change?. Climate Resilience and Sustainability, 1(1), e15. https://doi.org/10.1002/cli2.15
Dufek, A. S., & Ambrizzi, T. (2008). Precipitation variability in São Paulo State, Brazil. Theoretical and Applied Climatology, 93(3), 167-178. https://doi.org/10.1007/s00704-007-0348-7
Ebi, K. L., Vanos, J., Baldwin, J. W., Bell, J. E., Hondula, D. M., Errett, N. A., Hayes, K., Reid, C. E., Saha, S., Spector, J., & Berry, P. (2021). Extreme weather and climate change: population health and health system implications. Annual Review of Public Health, 42(1), 293-315. https://doi.org/10.1146/annurev-publhealth-012420-105026
Governo do Estado do Rio Grande do Sul (2024). Boletins sobre o impacto das chuvas no RS. https://www.estado.rs.gov.br/boletins-sobre-o-impacto-das-chuvas-no-rs
Hänsel, S., Schucknecht, A., & Matschullat, J. (2016). The Modified Rainfall Anomaly Index (mRAI)—is this an alternative to the Standardised Precipitation Index (SPI) in evaluating future extreme precipitation characteristics?. Theoretical and Applied Climatology, 123(3), 827-844. https://doi.org/10.1007/s00704-015-1389-y
Haylock, M. R., Peterson, T. C., Alves, L. M., Ambrizzi, T., Anunciação, Y. M. T., Baez, J., Barros, V. R., Berlato, M. A., Bidegain, M., Coronel, G., Corradi, V., Garcia, V.J., Grimm, A. M., Karoly, D., Marengo, J. A., Marino, M. B., Moncunill, D. F., Nechet, D., Quintana, J., Rebello, E., Rusticucci, M., Santos, J. L., Trebejo, I., Vincent, L. A. (2006). Trends in total and extreme South American rainfall in 1960–2000 and links with sea surface temperature. Journal of Climate, 19(8), 1490-1512. https://doi.org/10.1175/JCLI3695.1
Instituto Brasileiro de Geografia e Estatística (IBGE). (2023). Contas nacionais trimestrais: indicadores de volume e valores correntes. https://agenciadenoticias.ibge.gov.br/agenciasala-de-imprensa/2013-agencia-de-noticias/releases/39303-pib-cresce-2-9-em-2023-efecha-o-ano-em-r-10-9-trilhoes
Instituto Brasileiro de Geografia e Estatística (IBGE). (2022). Censo demográfico 2022. IBGE.
Medeiros, F. J., de Oliveira, C. P., & Avila-Diaz, A. (2022). Evaluation of extreme precipitation climate indices and their projected changes for Brazil: From CMIP3 to CMIP6. Weather and Climate Extremes, 38, 100511. https://doi.org/10.1016/j.wace.2022.100511
Kuhn, C. E., Reis, F. A., Oliveira, V. G., Cabral, V. C., Gabelini, B. M., & Veloso, V. Q. (2022). Evolution of public policies on natural disasters in brazil and worldwide. Anais da Academia Brasileira de Ciências, 94, e20210869. https://doi.org/10.1590/0001-3765202220210869
de Lima, J. A. G., & Alcântara, C. R. (2019). Comparison between ERA Interim/ECMWF, CFSR, NCEP/NCAR reanalysis, and observational datasets over the eastern part of the Brazilian Northeast Region. Theoretical and Applied Climatology, 138(3), 2021-2041. https://doi.org/10.1007/s00704-019-02921-w
Lagos-Zúñiga, M., Balmaceda-Huarte, R., Regoto, P., Torrez, P., Olmo, M., Lyra, A., Quispe-Pareja, D., & Bertolli, M. L. (2024). Extreme indices of temperature and precipitation in South America: Trends and intercomparison of regional climate models. Climate Dynamics, 62, 4541–4562. https://doi.org/10.1007/s00382-022-06598-2
Luiz-Silva, W., & Oscar-Júnior, A. C. (2022). Climate extremes related with rainfall in the State of Rio de Janeiro, Brazil: A review of climatological characteristics and recorded trends. Natural Hazards, 114(1), 713–732. https://doi.org/10.1007/s11069-022-05409-5
Majumdar, S. N., Pal, A., & Schehr, G. (2020). Extreme value statistics of correlated random variables: a pedagogical review. Physics Reports, 840, 1-32. https://doi.org/10.1016/j.physrep.2019.10.005
Mann, H. B. (1945). Nonparametric tests against trend. Econometrica: Journal of the Econometric Society, 245-259. https://doi.org/10.2307/1907187
Marengo, J. A., Torres, R. R., & Alves, L. M. (2017). Drought in Northeast Brazil—past, present, and future. Theoretical and Applied Climatology, 129(3), 1189-1200. https://doi.org/10.1007/s00704-016-1840-8
Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L., Pean, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield, T., Yelekci, O., Yu, R., & Zhou, B. (2021). Climate change 2021: the physical science basis. Contribution of working group I to the sixth assessment report of the intergovernmental panel on climate change, 2(1), 2391. https://www.ipcc.ch/report/ar6/wg1/downloads/report/IPCC_AR6_WGI_FrontMatter.pdf
McKee, T. B., Doesken, N. J., & Kleist, J. (1993. The relationship of drought frequency and duration to time scales. In Proceedings of the 8th Conference on Applied Climatology (pp. 179-183). American Meteorological Society. https://climate.colostate.edu/pdfs/relationshipofdroughtfrequency.pdf
de los Milagros Skansi, M., Brunet, M., Sigró, J., Aguilar, E., Arevalo Groening, J. A., Bentancur, O. J., Castellón Geier, Y. R., Correa Amaya, R. L., Jácome, H., Malheiros Ramos, A., Oria Rojas, C., Pasten, A. M., Sallons Mitro, S., Villaroel Jiménez, C., Martínez, R., Alexander, L. V., Jones, P. (2013). Warming and wetting signals emerging from analysis of changes in climate extreme indices over South America. Global and Planetary Change, 100, 295-307. https://doi.org/10.1016/j.gloplacha.2012.11.004
Minervino, A. C., & Duarte, E. C. (2016). Danos materiais causados à Saúde Pública e à sociedade decorrentes de inundações e enxurradas no Brasil, 2010-2014: dados originados dos sistemas de informação global e nacional. Ciência & Saúde Coletiva, 21(3), 685-694. https://doi.org/10.1590/1413-81232015213.19922015
Murara, P., Acquaotta, F., Garzena, D., & Fratianni, S. (2019). Daily precipitation extremes and their variations in the Itajaí River Basin, Brazil. Meteorology and Atmospheric Physics, 131(4), 1145-1156. https://doi.org/10.1007/s00703-018-0627-0
Otto, F. E. (2017). Attribution of weather and climate events. Annual Review of Environment and Resources, 42, 627-646. https://doi.org/10.1146/annurev-environ-102016-060847
Ramos Filho, G. M. (2021). Performance of rainfall threshold for flood identification from groundand satellite-based (sub) daily data. [Doctoral Dissertation, Universidade Federal da Paraíba]. https://repositorio.ufpb.br/jspui/handle/123456789/22729
Reboita, M. S., Mattos, E. V., Capucin, B. C., Souza, D. O. d., & Ferreira, G. W. d. S. (2024). A multi-scale analysis of the extreme precipitation in southern Brazil in April/May 2024. Atmosphere, 15(9), 1123.https://doi.org/10.3390/atmos15091123
Regoto, P., Dereczynski, C., Chou, S. C., & Bazzanela, A. C. (2021). Observed changes in air temperature and precipitation extremes over Brazil. International Journal of Climatology, 41(11), 5125-5142. https://doi.org/10.1002/joc.7119
Rohde, R. A., & Hausfather, Z. (2020). The Berkeley Earth land/ocean temperature record. Earth System Science Data, 2020, 1-16. https://doi.org/10.5194/essd-12-3469-2020 Rooy, M. (1965). A rainfall anomaly index independent of time and space. Notos, 14, 43–48.
Rosso, F. V., Boiaski, N. T., Ferraz, S. E., Dewes, C. F., & Tatsch, J. D. (2015). Trends and decadal variability in air temperature over Southern Brazil. American Journal of Environmental Engineering, 5(1A), 85-95.
Schossler, V., Simões, J. C., Aquino, F. E., & Viana, D. R. (2018). Precipitation anomalies in the Brazilian southern coast related to the SAM and ENSO climate variability modes. RBRH, 23, e14. https://doi.org/10.1590/2318-0331.231820170081
Sen, P. K. (1968). Estimates of the regression coefficient based on Kendall’s tau. Journal of the American Statistical Association, 63(324), 1379-1389. https://doi.org/10.1080/01621459.1968.10480934
Silva Dias, M. A., Dias, J., Carvalho, L. M., Freitas, E. D., & Silva Dias, P. L. (2013). Changes in extreme daily rainfall for São Paulo, Brazil. Climatic Change, 116(3), 705-722. https://doi.org/10.1007/s10584-012-0504-7
Sippel, S., Zscheischler, J., Heimann, M., Otto, F. E., Peters, J., & Mahecha, M. D. (2015). Quantifying changes in climate variability and extremes: Pitfalls and their overcoming. Geophysical Research Letters, 42(22), 9990-9998. https://doi.org/10.1002/2015GL066307
Solberg, K. (2010). Worst floods in living memory leave Pakistan in paralysis. The Lancet (London, England), 376(9746), 1039-1040. https://doi.org/10.1016/s0140-6736(10)61469-9
Svoboda, M., Hayes, M., Wood, D. (2012). Standardized precipitation index: user guide. (WMO-No. 1090). World Meteorological Organization.
Tank, A., Zwiers, F., Zhang, X. (2009). Guidelines on analysis of extremes in a changing climate in support of informed decisions for adaptation. World Meteorological Organization.
Instituto Nacional de Meteorologia. (2022). Banco de dados meteorológicos: Normais climatológicas (1961–1990). https://portal.inmet.gov.br/
Governo Federal do Brasil. (2025). Sistema integrado de informações sobre desastres (S2iD). Ministério da Integração e do Desenvolvimento Regional. http://S2iD.mi.gov.br/
Vicente-Serrano, S. M., Beguería, S., & López-Moreno, J. I. (2010). A multiscalar drought index sensitive to global warming: the standardized precipitation evapotranspiration index. Journal of climate, 23(7), 1696-1718. https://doi.org/10.1175/2009JCLI2909.1
World Bank. (2022). The World Bank annual report 2022: Helping countries adapt to a changing world. World Bank Group. http://documents.worldbank.org/curated/en/099030009272214630
World Meteorological Organization. (2024). State of the climate 2024 (WMO-No. 1300). https://library.wmo.int/records/item/69075-state-of-the-climate-2024
Xavier, A. C., King, C. W., & Scanlon, B. R. (2016). Daily gridded meteorological variables in Brazil (1980–2013). International Journal of Climatology, 36(6), 2644-2659. https://doi.org/10.1002/joc.4518
Zhang, X., & Yang, F. (2004). RClimDex (1.0) user manual. Climate Research Branch Environment Canada, 22, 13-14. https://rcc.acmad.org/procedure/RClimDexUserManual.pdf
Zhang, D. L., Lin, Y., Zhao, P., Yu, X., Wang, S., Kang, H., & Ding, Y. (2013). The Beijing extreme rainfall of 21 July 2012: “Right results” but for wrong reasons. Geophysical Research Letters, 40(7), 1426-1431. https://doi.org/10.1002/grl.50304
Zhang, X., Hegerl, G., Zwiers, F. W., & Kenyon, J. (2005). Avoiding inhomogeneity in percentilebased indices of temperature extremes. Journal of Climate, 18(11), 1641-1651. https://doi.org/10.1175/JCLI3366.1
Zhang, X., Alexander, L., Hegerl, G. C., Jones, P., Tank, A. K., Peterson, T. C., Trewin, B., & Zwiers, F . W . ( 2 0 1 1 ) . Indices for monitoring changes in extremes based on daily temperature and precipitation data. Wiley Interdisciplinary Reviews: Climate Change, 2(6), 851-870. https://doi.org/10.1002/wcc.147
Zilli, M. T., Carvalho, L. M., Liebmann, B., & Silva Dias, M. A. (2017). A comprehensive analysis of trends in extreme precipitation over southeastern coast of Brazil. International Journal of Climatology, 37(5), 2269-2279. https://doi.org/10.1002/joc.4840
Published
Issue
Section
License
Copyright (c) 2026 Ciência e Natura
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
To access the DECLARATION AND TRANSFER OF COPYRIGHT AUTHOR’S DECLARATION AND COPYRIGHT LICENSE click here.
Ethical Guidelines for Journal Publication
The Ciência e Natura journal is committed to ensuring ethics in publication and quality of articles.
Conformance to standards of ethical behavior is therefore expected of all parties involved: Authors, Editors, Reviewers, and the Publisher.
In particular,
Authors: Authors should present an objective discussion of the significance of research work as well as sufficient detail and references to permit others to replicate the experiments. Fraudulent or knowingly inaccurate statements constitute unethical behavior and are unacceptable. Review Articles should also be objective, comprehensive, and accurate accounts of the state of the art. The Authors should ensure that their work is entirely original works, and if the work and/or words of others have been used, this has been appropriately acknowledged. Plagiarism in all its forms constitutes unethical publishing behavior and is unacceptable. Submitting the same manuscript to more than one journal concurrently constitutes unethical publishing behavior and is unacceptable. Authors should not submit articles describing essentially the same research to more than one journal. The corresponding Author should ensure that there is a full consensus of all Co-authors in approving the final version of the paper and its submission for publication.
Editors: Editors should evaluate manuscripts exclusively on the basis of their academic merit. An Editor must not use unpublished information in the editor's own research without the express written consent of the Author. Editors should take reasonable responsive measures when ethical complaints have been presented concerning a submitted manuscript or published paper.
Reviewers: Any manuscripts received for review must be treated as confidential documents. Privileged information or ideas obtained through peer review must be kept confidential and not used for personal advantage. Reviewers should be conducted objectively, and observations should be formulated clearly with supporting arguments, so that Authors can use them for improving the paper. Any selected Reviewer who feels unqualified to review the research reported in a manuscript or knows that its prompt review will be impossible should notify the Editor and excuse himself from the review process. Reviewers should not consider manuscripts in which they have conflicts of interest resulting from competitive, collaborative, or other relationships or connections with any of the authors, companies, or institutions connected to the papers.
