Thornthwaite Moisture Index for the Triângulo Mineiro, Brazilian Cerrado Region, Under Climate Change
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Palavras-chave

IPCC
Water deficit
Water surplus
Climate zones

Como Citar

FISCHER FILHO, J. A.; ROSA, G. B.; VIEIRA, J. C. A.; FUZZO, D. F. da S. Thornthwaite Moisture Index for the Triângulo Mineiro, Brazilian Cerrado Region, Under Climate Change. Sociedade & Natureza, [S. l.], v. 37, n. 1, 2025. DOI: 10.14393/SN-v37-2025-73957. Disponível em: https://seer.ufu.br/index.php/sociedadenatureza/article/view/73957. Acesso em: 15 jan. 2025.

Resumo

Climate change represents one of the main challenges of the 21st century for planning and sustainable development. However, little is known about how climate change can affect a region's climate zones. The objective was to evaluate probable changes in climatic zones using the Thornthwaite climate classification (1948). Historical series between 1981 and 2021 of rainfall and air temperature were used. The water balance was calculated from Thornthwaite and Mather. Thornthwaite's humidity index (1948) was used to classify localities according to their level of humidity and the scenarios RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5 to analyze projections for the 21st century (period 2081–2100). The current characterization, with historical data, of the region's climate presented air temperature, rainfall and average potential evapotranspiration, respectively, of 22.4ºC, 1,318.8 mm and 1,123.74 mm, in addition to a water surplus of 391.04 mm and water deficit of 195.04 mm. The region currently has five climate indices, with a prevalence of more humid classes (B1, B2 and B3), corresponding to 62% of the territory. The results derived from the projections indicate reductions in climate classes and an increase in the area occupied by drier climates. For example, the percentage of area occupied by class C1 (dry subhumid) would increase from the current 8.4% to 69.68% in the RCP 8.5 scenario. The study of these change projections is important since profound consequences for the hydrology, ecology and social area of the region will take place, potentially harming agriculture, the region's main economic activity.

https://doi.org/10.14393/SN-v37-2025-73957
PDF-en (English)

Referências

ARAÚJO, D. F. C.; ARAÚJO SOBRINHO, F. L. A dinâmica do setor sucroenergético no Triângulo Mineiro/Alto Paranaíba. Cerrados, v. 18, n. 1, p. 248-277, 2020. https://doi.org/10.46551/rc24482692202001

BARONETTI, A.; DUBREUIL, V.; PROVENZALE, A.; FRATIANNI, S. Future droughts in northern Italy: high-resolution projections using EURO-CORDEX and MED-CORDEX ensembles. Climatic Change, v. 172, p. 22, 2022. https://doi.org/10.1007/s10584-022-03370-7

BIENIEK, P. A.; BHATT, U. S.; THOMAN, R. L.; ANGELOFF, H.; PARTAIN, J.; PAPINEAU, J.; FRITSCH, F.; HOLLOWAY, E.; WALSH, J. E.; DALY, C.; SHULSKI, M. Climate divisions for Alaska based on objective methods. Journal of Applied Meteorology and Climatology, v. 51, p. 1276–1289, 2012. https://doi.org/10.1175/JAMC-D-11-0168.1

ELGUINDI, N.; GRUNDSTEIN, A.; BERNARDES, S.; TURUNCOGLU, U.; FEDDEMA, J. Assessment of CMIP5 global model simulations and climate change projections for the 21 st century using a modified Thornthwaite climate classification. Climatic change, v. 122, p. 523-538, 2014. https://doi.org/10.1007/s10584-013-1020-0

FENG, S.; HU, Q.; HUANG, W.; HO, C. H.; LI, R.; TANG, Z. (2014). Projected climate regime shift under future global warming from multi-model, multi-scenario CMIP5 simulations. Global and Planetary Change, v. 112, p. 41-52, 2014. https://doi.org/10.1016/j.gloplacha.2013.11.002

FUZZO, D. F. S.; ASSUNÇÃO, F. J. M.; FUZZO, B. E.; FISCHER FILHO, J. A. Tendências e padrões de variação em séries temporais de temperatura do ar e precipitação na microrregião de Frutal – MG. Revista Brasileira De Geografia Física, v. 17, n. 3, p. 1977–1991, 2024. https://doi.org/10.26848/rbgf.v17.3.p1977-1991

FUZZO, D. F. S.; FERREIRA DA SILVA, L.; FISCHER FILHO, J. A. Google Earth Engine applied to rainfall mapping in Triângulo Sul Mineiro – Brazil. Agua Y Territorio Water and Landscape, v. 23, e7282, 2023. https://doi.org/10.17561/at.23.7282

HARTIN, C. A.; PATEL, P.; SCHWARBER, A.; LINK, R. P.; BOND-LAMBERTY, B. P. A simple object-oriented and open-source model for scientific and policy analyses of the global climate system–Hector v1. 0. Geoscientific Model Development, v, 8, n. 4, p. 939-955, 2015. https://doi.org/10.5194/gmd-8-939-2015

IBGE. INSTITUTO BRASILEIRO DE GEOGRAFIA E ESTATÍSTICA. Cidades e estados: Minas Gerais. 2022. Available: https://www.ibge.gov.br/cidades-e-estados/mg.html. Accessed on: May 8, 2024. IPCC. INTERGOVERNMENTAL PANEL ON CLIMATE CHANGE. Summary for policymakers. IN: LEE, H.; ROMERO, J. (Eds.). Climate change 2023: synthesis report: contribution of working groups I, II and III to the sixth assessment report of the Intergovernmental Panel on Climate Change. Geneva: IPCC, 2023. p. 1-34.

KARIM, M. R.; RAHMAN, M. M.; NGUYEN, K.; CAMERON, D.; IQBAL, A.; AHENKORAH, I. Changes in Thornthwaite Moisture Index and reactive soil movements under current and future climate scenarios—A case study. Energies, v. 14, n. 20, p. 6760, 2021. https://doi.org/10.3390/en14206760

LI, Y.; QIN, Y.; RONG, P. Evolution of potential evapotranspiration and its sensitivity to climate change based on the Thornthwaite, Hargreaves, and Penman–Monteith equation in environmental sensitive areas of China. Atmospheric Research, v. 273, p. 106178, 2022. https://doi.org/10.1016/j.atmosres.2022.106178

LORENÇONE, J. A.; APARECIDO, L. E. D. O; LORENÇONE, P. A.; LIMA, R. F. D.; TORSONI, G. B. Assessment of climate change using humidity index of Thornthwaite climate classification in Pantanal biome. Revista Brasileira de Meteorologia, v. 37, p. 99-119, 2022. https://doi.org/10.1590/0102-7786370075

MA, D.; DENG, H.; YIN, Y.; WU, S.; ZHENG, D. Sensitivity of arid/humid patterns in China to future climate change under a high-emissions scenario. Journal of Geographical Sciences, v. 29, p. 29-48, 2019. https://doi.org/10.1007/s11442-019-1582-5

MAHLSTEIN, I.; DANIEL, J. S.; SOLOMON, S. Pace of shifts in climate regions increases with global temperature. Nature Climate Change, v. 3, n. 8, p. 739-743, 2013. https://doi.org/10.1038/nclimate1876

MALDONADO JÚNIOR, W.; VALERIANO, T. T. B.; DE SOUZA ROLIM, G. EVAPO: A smartphone application to estimate potential evapotranspiration using cloud gridded meteorological data from NASA-POWER system. Computers and Electronics in Agriculture, v. 156, p. 187-192, 2019. https://doi.org/10.1016/j.compag.2018.10.032

MARTINS, F. B.; GONZAGA, G.; DOS SANTOS, D. F.; REBOITA, M. S. Classificação climática de Köppen e de Thornthwaite para Minas Gerais: cenário atual e projeções futuras. Revista Brasileira de Climatologia, v. 14, p. 129-156, 2018. https://doi.org/10.5380/abclima.v1i0.60896

MELLO, C. R. D.; SÁ, M. A. C. D.; CURI, N.; MELLO, J. M. D.; VIOLA, M. R.; SILVA, A. M. D. Erosividade mensal e anual da chuva no Estado de Minas Gerais. Pesquisa Agropecuária Brasileira, v. 42, p. 537-545, 2007. https://doi.org/10.1590/S0100-204X2007000400012

MICHALAK, D. Adapting to climate change and effective water management in Polish agriculture–At the level of government institutions and farms. Ecohydrology & Hydrobiology, v. 20, n. 1, p. 134-141, 2020. https://doi.org/10.1016/j.ecohyd.2019.12.004

MONTES-VEGA, M. J.; GUARDIOLA-ALBERT, C.; RODRÍGUEZ-RODRÍGUEZ, M. Calculation of the SPI, SPEI, and GRDI Indices for Historical Climatic Data from Doñana National Park: Forecasting Climatic Series (2030–2059) Using Two Climatic Scenarios RCP 4.5 and RCP 8.5 by IPCC. Water, v. 15, n. 13, p. 2369, 2023. https://doi.org/10.3390/w15132369

NOVAIS, G. T.; BRITO, J. L. S.; SANCHES, F. O. Unidades climáticas do Triângulo Mineiro/Alto Paranaíba. Revista Brasileira De Climatologia, v. 23, p. 223-243, 2018. https://doi.org/10.5380/abclima.v23i0.58520

NOVAIS, G. T.; MACHADO, L. A. Os climas do Brasil: segundo a classificação climática de Novais. Revista Brasileira de Climatologia, v. 32, p. 1-39, 2023. https://doi.org/10.55761/abclima.v32i19.16163

PHUMKOKRUX, N.; TRIVEJ, P. Investigation of Temperature, Precipitation, Evapotranspiration, and New Thornthwaite Climate Classification in Thailand. Atmosphere, v. 15, n. 3, p. 379, 2024. https://doi.org/10.3390/atmos15030379

PULKKINEN, J.; LOUIS, J. N.; DEBUSSCHERE, V.; PONGRÁCZ, E. Near-, medium-and long-term impacts of climate change on the thermal energy consumption of buildings in Finland under RCP climate scenarios. Energy, v. 302, p. 131636, 2024. https://doi.org/10.1016/j.energy.2024.131636

RAHIMI, J.; KHALILI, A.; BUTTERBACH‐BAHL, K. Projected changes in modified Thornthwaite climate zones over Southwest Asia using a CMIP5 multi‐model ensemble. International Journal of Climatology, v. 39, n. 12, p. 4575-4594, 2019. https://doi.org/10.1002/joc.6088

ROLIM, G. D. S.; CAMARGO, M. B. P. D.; LANIA, D. G.; MORAES, J. F. L. D. Climatic classification of Köppen and Thornthwaite sistems and their applicability in the determination of agroclimatic zonning for the state of São Paulo, Brazil. Bragantia, v. 66, p. 711-720, 2007. https://doi.org/10.1590/S0006-87052007000400022

ROSA, G. B.; SILVA FUZZO, D. F.; FISCHER FILHO, J. A. Modelos de estimativa da evapotranspiração de referência para a região sul do Triângulo Mineiro, Brasil. Revista Brasileira de Climatologia, v. 33, p. 81-97, 2023. https://doi.org/10.55761/abclima.v33i19.16965

SANCHES, F. O.; DA SILVA, R. V.; FERREIRA, R. V.; CAMPOS, C. A. A. Climate change in the Triângulo Mineiro region–Brazil. Revista Brasileira de Climatologia, v. 21, p. 570-587, 2017. http://doi.org/10.5380/abclima.v21i0.51867

SHEN, M.; CHEN, J.; ZHUAN, M.; CHEN, H.; XU, C. Y.; XIONG, L. Estimating uncertainty and its temporal variation related to global climate models in quantifying climate change impacts on hydrology. Journal of Hydrology, v. 556, p. 10-24, 2018. https://doi.org/10.1016/j.jhydrol.2017.11.004

SOUZA, A. P.; MOTA, L. L.; ZAMADEI, T.; MARTIN, C. C.; ALMEIDA, F. T.; PAULINO, J. Classificação climática e balanço hídrico climatológico no estado de Mato Grosso. Nativa, v. 1, n. 1, p. 34-43, 2013. https://doi.org/10.14583/2318-7670.v01n01a07

SRIVASTAVA, A. K.; MBOH, C. M.; ZHAO, G.; GAISER, T.; EWERT, F. Climate change impact under alternate realizations of climate scenarios on maize yield and biomass in Ghana. Agricultural Systems, v. 159, p. 157-174, 2018. https://doi.org/10.1016/j.agsy.2017.03.011

STACKHOUSE, P. W.; WESTBERG, D.; HOELL, J. M.; CHANDLER, W. S.; ZHANG, T. Prediction of Worldwide Energy Resource (POWER)-Agroclimatology methodology-(1.0 latitude by 1.0 longitude spatial resolution). Hampton: NASA Langely Research Cente. 2015.

SYLLA, M. B.; GIORGI, F.; PAL, J. S.; GIBBA, P.; KEBE, I.; NIKIEMA, M. Projected changes in the annual cycle of high-intensity precipitation events over West Africa for the late twenty-first century. Journal of Climate, v. 28, n. 16, p. 6475-6488, 2015. https://doi.org/10.1175/JCLI-D-14-00854.1

TALCHABHADEL, R.; KARKI, R. Assessing climate boundary shifting under climate change scenarios across Nepal. Environmental monitoring and assessment, v. 191, p. 1-17, 2019. https://doi.org/10.1007/s10661-019-7644-4

THAYER, A. W.; VARGAS, A.; CASTELLANOS, A. A.; LAFON, C. W.; MCCARL, B. A.; ROELKE, D. L.; WINEMILLER, K. O.; LACHER, T. E. Integrating agriculture and ecosystems to find suitable adaptations to climate change. Climate, v. 8, n. 1, p. 10, 2020. https://doi.org/10.3390/cli8010010

This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

THORNTHWAITE, C. W. An approach toward a rational classification of climate. Geographical Review, v. 38, n. 1, p. 55-94, 1948. https://doi.org/10.2307/210739

THORNTHWAITE, C. W.; MATHER, J. R. The water balance. Centerton: Drexel Institute of Technology, Laboratory of Climatology, 1955.

VALJAREVIĆ, A.; MILANOVIĆ, M.; GULTEPE, I.; FILIPOVIĆ, D.; LUKIĆ, T. Updated Trewartha climate classification with four climate change scenarios. The Geographical Journal, v. 188, n. 4, p. 506-517, 2022. https://doi.org/10.1111/geoj.12458

WHEELER, T.; VON BRAUN, J. Climate change impacts on global food security. Science, v. 341, p. 508-513, 2013. https://doi.org/10.1126/science.1239402

WORLDCLIM. Global climate and weather data. Available: https://www.worldclim.org/data/index.html. Accessed on: Jun. 15, 2023.

XIANG, K.; LI, Y.; HORTON, R.; FENG, H. Similarity and difference of potential evapotranspiration and reference crop evapotranspiration–a review. Agricultural Water Management, v. 232, p. 106043, 2020. https://doi.org/10.1016/j.agwat.2020.106043

YANG, H.; LOHMANN, G.; WEI, W.; DIMA, M.; IONITA, M.; LIU, J. Intensification and poleward shift of subtropical western boundary currents in a warming climate. Journal of Geophysical Research: Oceans, v. 121, n. 7, p. 4928-4945, 2016. https://doi.org/10.1002/2015JC011513

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Copyright (c) 2024 João Alberto Fischer Filho, Giovani Bonício Rosa, Julia Cristina Amâncio Vieira, Daniela Fernanda da Silva Fuzzo

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