Observed surface hydroclimatic variations in Cuba during the period 1961-2022
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Abstract
Surface hydroclimatic conditions exert a decisive influence on multiple economic, social, and environmental sectors, making their study crucial. This research was conducted to analyze variations in precipitation, potential evapotranspiration (ET0), the climatic water balance (P-ET0), and drought in Cuba during the period 1961-2022, with an emphasis on temporal and spatial scales. To this end, gridded precipitation and ET0 datasets with a 4 km resolution were used. Trends were calculated using the Mann-Kendall and Sen tests, and drought was analyzed using the Standardized Precipitation Index (SPI3). The main results showed that precipitation did not exhibit statistically significant trends at the national scale, although areas with notable reductions were detected in the eastern region. ET0 showed a statistically significant increase throughout the country, especially during the dry season. The water balance did not reflect a statistically significant national trend, but it did evidence notable local reductions in several regions. Drought did not increase, although its duration and intensity showed heterogeneous spatial patterns. It was concluded that hydroclimatic variations in Cuba are spatially complex, underscoring the need for spatially detailed analyses for water resource management and climate adaptation.
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References
Allan, R. P., Liu, C., Zahn, M., Lavers, D. A., Koukouvagias, E., & Bodas-Salcedo, A. (2014). Physically consistent responses of the global atmospheric hydrological cycle in models and observations. Surveys in Geophysics, 35(3), 533-552. https://doi.org/10.1007/s10712-012-9213-z
Ault, T. R. (2020). On the essentials of drought in a changing climate. Science, 368(6488), 256-260. https://doi.org/10.1126/science.aaz5492
Ay, M., & Kisi, O. (2015). Investigation of trend analysis of monthly total precipitation by an innovative method. Theoretical and Applied Climatology, 120, 617-629. https://doi.org/10.1007/s00704-014-1198-8
Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society: Series B, 57, 289-300. https://doi.org/10.1111/j.2517-6161.1995.tb02031.x
Cavus, Y., & Aksoy, H. (2020). Critical drought severity/intensity-duration-frequency curves based on precipitation deficit. Journal of Hydrology, 584, 124312. https://doi.org/10.1016/j.jhydrol.2019.124312
Centella, A., Naranjo, L., Paz, L., Cárdenas, P., Alfonso, A., Ballester, M., Lapinel, B., González, C., Pérez, R., Limia, M., & Sosa, M. (1997). Variaciones y cambios del clima en Cuba (Informe del Centro Nacional del Clima). Instituto de Meteorología.
Centella-Artola, A., Fonseca-Rivera, C., & González-García, I. (2023). R_SVsequia: Nuevo servicio climático automatizado para el monitoreo de la sequía meteorológica en Cuba. Revista Cubana de Meteorología, 29(4), Epub December 01, 2023. Retrieved October 14, 2025.
CITMA. (2015). Segunda Comunicación Nacional a la Convención Marco de Naciones Unidas sobre Cambio Climático. https://unfccc.int/documents/104917
CITMA. (2020). Tercera Comunicación Nacional a la Convención Marco de Naciones Unidas sobre Cambio Climático.
Cortés, J., Mahecha, M., Reichstein, M., & Brenning, A. (2020). Accounting for multiple testing in the analysis of spatio-temporal environmental data. Environmental and Ecological Statistics, 27, 293-318. https://doi.org/10.1007/s10651-020-00452-4
Dunn, O. J. (1961). Multiple comparisons among means. Journal of the American Statistical Association, 56(293), 54-64. https://doi.org/10.1080/01621459.1961.10482090
Dunn, O. J. (1964). Multiple comparisons using rank sums. Technometrics, 6(3), 241-252. https://doi.org/10.2307/1266041
Fuentes, I., Padarian, J., & Vervoort, R. W. (2022). Spatial and temporal global patterns of drought propagation. Frontiers in Environmental Science, 10. https://doi.org/10.3389/fenvs.2022.979848
Haktanir, T., & Citakoglu, H. (2014). Trend, independence, stationarity, and homogeneity tests on maximum rainfall series of standard durations recorded in Turkey. Journal of Hydrologic Engineering, 19, 9. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000973
Halwatura, D., Lechner, A. M., & Arnold, S. (2015). Drought severity-duration-frequency curves: A foundation for risk assessment and planning tool for ecosystem establishment in post-mining landscapes. Hydrology and Earth System Sciences, 19(2), 1069-1091. https://doi.org/10.5194/hess-19-1069-2015
Herrera, D. A., Cook, B. I., Fasullo, J., Anchukaitis, K. J., Alessi, M., Martinez, C. J., & coautores. (2023). Observed changes in hydroclimate attributed to human forcing. PLOS Climate, 2(11), e0000303. https://doi.org/10.1371/journal.pclm.0000303
INSMET (2025). Variaciones y cambios del clima en Cuba. Presente y futuro. Reporte Final de Proyecto. Instituto de Meteorología, La Habana, Cuba. 260 pp.
Jiménez Cisneros, B. E., Oki, T., Arnell, N. W., Benito, B., Cogley, J. G., Döll, P., Jiang, T., & Mwakalila, S. S. (2014). Freshwater resources. En C. B. Field, V. R. Barros, D. J. Dokken, K. J. Mach, M. D. Mastrandrea, T. E. Bilir, M. Chatterjee, K. L. Ebi, Y. O. Estrada, R. C. Genova, B. Girma, E. S. Kissel, A. N. Levy, S. MacCracken, P. R. Mastrandrea, & L. L. White (Eds.), Climate change 2014: Impacts, adaptation, and vulnerability. Part A: Global and sectoral aspects (pp. 229-269). Cambridge University Press. http://www.ipcc.ch/pdf/assessment-report/ar5/wg2/WGIIAR5-Chap3_FINAL.pdf
Kendall, M. G. (1970). Rank correlation methods (4th ed.). Charles Griffin.
Kisi, O., & Ay, M. (2014). Comparison of Mann-Kendall and innovative trend method for water quality parameters of the Kizilirmak River, Turkey. Journal of Hydrology, 513, 362-375. https://doi.org/10.1016/j.jhydrol.2014.03.005
Kruskal, W. H., & Wallis, W. A. (1952). Use of ranks in one-criterion variance analysis. Journal of the American Statistical Association, 47(260), 583-621. https://doi.org/10.1080/01621459.1952.10483441
Lapinel, B. P., Rivero, R.E., Rivero, R.R., Varela, N., Cutié, V. y Fonseca, C. (2006): El Sistema Nacional de Vigilancia y Predicción de la Sequía en Cuba: Caso de Estudio. En “Solano, O., H. Shannon y R. Villalobos (Eds.) (2006): Informe del Grupo de Trabajo sobre Meteorología Agrícola de la AR IV”.
Lapinel, B., Fonseca, C., Cutié, V., Boudet, D. (2007). Movimientos troposféricos verticales sobre Cuba y sus características en condiciones de lluvias medias y extremas. Centro del Clima, Instituto de Meteorología.
Lapinel, B. P., Fonseca, C., González, I., González, C., & coautores. (2014). Metodología para el estudio de peligro, vulnerabilidad y riesgo por intensa sequía. En Cuba: Metodologías para la determinación de riesgos de desastre a nivel territorial. PNUD-Cuba. https://www.undp.org/es/cuba/publicaciones/metodologias-para-la-determinacion-de-riesgos-de-desastres-parte-1
Livezey, R. E., & Chen, W. Y. (1983). Statistical field significance and its determination by Monte Carlo techniques. Monthly Weather Review, 111, 46-59. https://doi.org/10.1175/1520-0493(1983)111<0046:SFSAID>2.0.CO;2
Mann, H. B. (1945). Nonparametric tests against trend. Econometrica, 13(3), 245-259.
McKee, T. B., Doesken, N. J., & Kleist, J. (1993). The relationship of drought frequency and duration to time scales. En Proceedings of the Eighth Conference on Applied Climatology (pp. 179-184). American Meteorological Society. https://www.droughtmanagement.info/literature/AMS_Relationship_Drought_Frequency_Duration_Time_Scales_1993.pdf
Murray, M., & Blume, J. (2022). FDRestimation: Estimate, plot, and summarize false discovery rates (Versión 1.0.1) [Paquete de R]. CRAN. https://CRAN.R-project.org/package=FDRestimation
Pérez, R., Fonseca, F., Lapinel, B., González, C., González, I., Planos, E., Cutié, V., Mitrani, I., Aguilar, Gisell., Carnesoltas, M., Ballester, M., Limia, M., Vega, R., Vichot, A., Díaz, O., Pérez, A., Coangas, R., Álvarez, L., Morales, A., Viamontes, J., Pérez J. (2013). Variaciones y cambios en el clima. en Impacto del cambio climático y medidas de adaptación en Cuba [Planos, Rivero, R., Guevara, V. (editores)]. Editorial AMA. Agencia de Medio Ambiente, Ministerio de Ciencia Tecnología y Medio Ambiente. 430 pp. ISBN: 978-959-300-039-0.
Planos, E. (2022). Aproximación a los recursos hídricos potenciales en Cuba al 2030. Ingeniería Hidráulica y Ambiental, 43(1), 48-62. https://dialnet.unirioja.es/servlet/articulo?codigo=10076063