Reconfiguración del Régimen Térmico y Estabilidad Pluviométrica en Manabí mediante ERA5-Land y Proyecciones Climáticas CMIP6
Resumen
La Demarcación Hidrográfica de Manabí (DHM), situada en la costa ecuatoriana del Pacífico tropical oriental, es un área con una fuerte influencia océano-atmósfera y con baja densidad de estaciones meteorológicas, lo que dificulta caracterizar de manera robusta su variabilidad climática. Esta investigación, fusiona el reanálisis ERA5-Land (procesado mediante Google Earth Engine) con datos de series históricas de diez modelos climáticos del Proyecto de Intercomparación de Modelos Acoplados fase 6 (CMIP6), para evaluar las tendencias de temperatura media, máxima y mínima, la amplitud térmica diaria (DTR), la precipitación y el balance hídrico superficial de la DHM entre 1964 y 2012, además de evaluar la fidelidad de los modelos climáticos frente a las observaciones satelitales. Las tendencias se identificaron mediante la prueba no paramétrica de Mann-Kendall y el estimador de pendiente de Sen. Los resultados revelan que la temperatura media anual fue estable (pendiente de Sen = +0,013 °C década⁻¹; p = 0,845), aunque la temperatura máxima disminuyó (−0151 °C década⁻¹; p = 0,063) y la mínima aumentó (+0,070 °C década⁻¹; p = 0,062), y se asociaron con la amplitud térmica diaria que mostró una disminución significativa (−0,236 °C década⁻¹; p = 0,001). La precipitación anual mostró una tendencia ligeramente positiva (+53,85 mm década⁻¹; τ = 0,115; p = 0,248). La evaluación del conjunto CMIP6 mostró un sesgo cálido sistemático en la amplitud térmica (sesgo promedio = +3,30 °C) y un sesgo seco en la precipitación (PBIAS promedio = −5,3%), siendo los modelos con el mejor rendimiento relativo GFDL-ESM4, EC-Earth3 y ACCESS-ESM1-5. Demostrando que, el cambio climático en la DHM no se refleja en un calentamiento uniforme, sino que es una reestructuración del régimen térmico diario modulado por la dinámica del Pacífico oriental, la Oscilación del Sur de El Niño y el balance energético superficial, situación que los modelos CMIP6 reproducen parcialmente.
Descargas
Citas
Albergel, C., Dutra, E., Munier, S., Calvet, J.-C., Munoz-Sabater, J., de Rosnay, P., & Balsamo, G. (2020). ERA5-Land: A state-of-the-art global reanalysis dataset for land applications. Earth System Science Data, 13(9), 4349–4383. https://doi.org/10.5194/essd-13-4349-2021, 2021
Amani, M., Ghorbanian, A., Ahmadi, S. A., Kakooei, M., Moghimi, A., Mirmazloumi, S. M., Moghaddam, S. H. A., Mahdavi, S., Ghahremanloo, M., Parsian, S., Wu, Q., & Brisco, B. (2020). Google Earth Engine cloud computing platform for remote sensing big data applications: A comprehensive review. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 13, 5326–5350.
https://doi.org/10.1109/JSTARS.2020.3021052
Balsamo, G., Agusti-Panareda, A., Albergel, C., Arduini, G., Beljaars, A., Bidlot, J., Blyth, E., Bousserez, N., Boussetta, S., Brown, A., Buizza, R., Buontempo, C., Chevallier, F., Choulga, M., Cloke, H., Cronin, M. F., Dahoui, M., De Rosnay, P., Dirmeyer, P. A., … Zsoter, E. (2018). Satellite and in situ observations for advancing global Earth surface modelling: A review. Remote Sensing, 10(12), 2038. https://doi.org/10.3390/rs11080941
Barkhordarian, A., Saatchi, S. S., Behrangi, A., Loikith, P. C., & Mechoso, C. R. (2022). A recent systematic increase in vapor pressure deficit over tropical South America. Scientific Reports, 12, 15331. https://doi.org/10.1038/s41598-019-51857-8
Cai, W., McPhaden, M. J., Grimm, A. M., Rodrigues, R. R., Taschetto, A. S., Garreaud, R. D., Dewitte, B., Poveda, G., Ham, Y.-G., Santoso, A., Ng, B., Anderson, W., Wang, G., Geng, T., Jo, H.-S., Marengo, J. A., Alves, L. M., Osman, M., Li, S., … Vera, C. (2020). Climate impacts of the El Niño–Southern Oscillation on South America. Nature Reviews Earth & Environment, 1, 215–231. https://doi.org/10.1038/s43017-020-0040-3
Campozano, L., Ballari, D., Montenegro, M., & Avilés, A. (2020). Future meteorological droughts in Ecuador: Decadal probabilities of below-normal precipitation under climate change scenarios. Journal of Hydrology: Regional Studies, 28, 100667. https://doi.org/10.3389/feart.2020.00017
Collaud Coen, M., Andrews, E., Aliaga, D., Andrade, M., Angelov, H., Bukowiecki, N., Ealo, M., Fialho, P., Flentje, H., Hallar, A. G., Hooda, R., Kalapov, I., Krejci, R., Lin, N.-H., Marinoni, A., Ming, J., Nguyen, N. A., Pandolfi, M., Pont, V., … Laj, P. (2020). Long-term trend analysis of aerosol variables at background sites: Statistical methods and uncertainty assessment. Atmospheric Chemistry and Physics, 20(15), 8867–8908. https://doi.org/10.5194/acp-20-8867-2020
Copernicus Climate Change Service. (2024). Global Climate Highlights 2023. European Centre for Medium-Range Weather Forecasts. https://climate.copernicus.eu/global-climate-highlights-2023
Chen, X., Wang, D., & Sivapalan, M. (2022). Data-guided exploration of the energy partitioning at land surface in the contiguous US. Water Resources Research, 58(8), e2021WR031006.
https://doi.org/10.1029/2021WR031006
Doan, Q.-V., Kusaka, H., & Trieu, T.-N. Q. (2022). Causes for asymmetric warming of sub-diurnal temperature responding to global warming. Geophysical Research Letters, 49(18), e2022GL100029. https://doi.org/10.1029/2022GL100029
Forster, P. M., Maycock, A. C., McKenna, C. M., & Smith, C. J. (2020). Latest climate models confirm need for urgent mitigation. Nature Climate Change, 10, 7–10. https://doi.org/10.1038/s41558-019-0660-0
Garreaud, R. D., Boisier, J. P., Rondanelli, R., Montecinos, A., Sepúlveda, H. H., & Veloso-Aguila, D. (2020). The Central Chile Mega Drought (2010–2018): A climate dynamics perspective. International Journal of Climatology, 40(1), 421–439. https://doi.org/10.1002/joc.6219
Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., & Moore, R. (2017). Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sensing of Environment, 202, 18–27. https://doi.org/10.1016/j.rse.2017.06.031
Hamed, K. H., & Rao, A. R. (1998). A modified Mann-Kendall trend test for autocorrelated data. Journal of Hydrology, 204(1–4), 182–196. https://doi.org/10.1016/S0022-1694(97)00125-X
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., … Thépaut, J.-N. (2020). The ERA5 global reanalysis. Quarterly Journal of the Royal Meteorological Society, 146(730), 1999–2049.
https://doi.org/10.1002/qj.3803
IPCC, 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[Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, In press, https://doi.org/10.1017/9781009157896
Intergovernmental Panel on Climate Change [IPCC]. (2023). Climate Change 2023: Synthesis Report. Contribution of Working Groups I, II and III to the Sixth Assessment Report of the IPCC. [Core Writing Team, H. Lee and J. Romero (eds.)]. IPCC, Geneva, Switzerland,184 pp.,
https://doi.org/10.59327/IPCC/AR6-9789291691647
Kaiser-Flores, B. J., Pilozo-Jiménez, K. K., Hernández-Cajas, J. D., & Burgos-Chiriguay, E. T. (2026). Servicios ecosistémicos de los bosques tropicales frente al cambio climático. Innova Science Journal, 4(1), 371–382. https://doi.org/10.63618/omd/isj/v4/n1/235
Kendall, M. G. (1975). Rank Correlation Methods (4th ed.). Charles Griffin, London.
Mann, H. B. (1945). Nonparametric tests against trend. Econometrica, 13(3), 245–259.
McPhaden, M. J., Santoso, A., & Cai, W. (Eds.). (2020). El Niño Southern Oscillation in a Changing Climate (Geophysical Monograph Series, Vol. 253). American Geophysical Union & John Wiley & Sons. https://doi.org/10.1002/9781119548164
Lima, D. M. C., Gomes, H. B., Ray, P., Watanabe, M., da Silva, M. C. L., Torres, R. R., Silva, M. T., Lyra, M. J. A., … Bezerra, K. F. D. S. (2026). Projected (2015–2100) nighttime-enhanced warming and regional contrasts in diurnal temperature range across South America: Sub-regional assessments from CMIP6. Earth Systems and Environment.
https://doi.org/10.1007/s41748-026-01214-3
Muñoz-Sabater, J., Dutra, E., Agustí-Panareda, A., Albergel, C., Arduini, G., Balsamo, G., Boussetta, S., Choulga, M., Harrigan, S., Hersbach, H., Martens, B., Miralles, D. G., Piles, M., Rodríguez-Fernández, N. J., Zsoter, E., Buontempo, C., & Thépaut, J.-N. (2021). ERA5-Land: A state-of-the-art global reanalysis dataset for land applications. Earth System Science Data, 13(9), 4349–4383. https://doi.org/10.5194/essd-13-4349-2021
Nouri, M., Hatzaki, M., Nojarov, P., Asimakopoulos, D. N., & Maheras, P. (2022). Reliability of the ERA5 in replicating mean and extreme temperatures across Europe. Water, 14(4), 543. https://doi.org/10.3390/w14040543 Organización Meteorológica Mundial [OMM]. (2022). State of the Global Climate 2021 (WMO-No. 1290). OMM.
Palacios-López, L. A., Pinargote-Bravo, V. J., Mieles-Giler, J. W., & Zapata-Velasco, M. L. (2026). Medidas de adaptación al cambio climático frente a inundaciones y sequías en contextos urbanos y rurales de países en desarrollo. Innova Science Journal, 4(1), 227–240.
https://doi.org/10.63618/omd/isj/v4/n1/224
Panwar, A., & Kleidon, A. (2022). Evaluating the response of diurnal variations in surface and air temperature to evaporative conditions across vegetation types in FLUXNET and ERA5. Journal of Climate, 35(19), 6301–6328. https://doi.org/10.1175/JCLI-D-21-0345.1
Quesada, B., Vautard, R., Yiou, P. et al. Asymmetric European summer heat predictability from wet and dry southern winters and springs. Nature Clim Change 2, 736–741 (2012).
https://doi.org/10.1038/nclimate1536
Reichle, R. H., Liu, Q., Koster, R. D., Draper, C. S., Mahanama, S. P. P., & Partyka, G. S. (2019). Land surface precipitation in MERRA-2. Journal of Climate, 32(11), 3327–3346.
https://doi.org/10.1175/JCLI-D-16-0570.1
Rivadeneira Vera, J. F., Zambrano Mera, Y. E., & Pérez-Martín, M. Á. (2020). Adapting water resources systems to climate change in tropical areas: Ecuadorian coast. Science of the Total Environment, 703, 135554. https://doi.org/10.1016/j.scitotenv.2019.135554
Rivera JA, Otta S, Lauro C and Zazulie N (2021) A Decade of Hydrological Drought in Central-Western Argentina. Front. Water 3:640544. https://doi.org/10.3389/frwa.2021.640544
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
Seneviratne, S.I., X. Zhang, M. Adnan, W. Badi, C. Dereczynski, A. Di Luca, S. Ghosh, I. Iskandar, J. Kossin, S. Lewis, F. Otto, I. Pinto, M. Satoh, S.M. Vicente-Serrano, M. Wehner, and B. Zhou, 2021: Weather and Climate Extreme Events in a Changing Climate. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change[Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 1513–1766, https://doi.org/10.1017/9781009157896.013
Sun, X., Ren, G., You, Q., Ren, Y., Xu, W., Xue, X., Zhan, Y., Zhang, S., & Zhang, P. (2019). Global diurnal temperature range (DTR) changes since 1901. Climate Dynamics, 52, 3343–3356.
https://doi.org/10.1007/s00382-018-4329-6
Tamiminia, H., Salehi, B., Mahdianpari, M., Quackenbush, L., Adeli, S., & Brisco, B. (2020). Google Earth Engine for geo-big data applications: A meta-analysis and systematic review. ISPRS Journal of Photogrammetry and Remote Sensing, 164, 152–170.
https://doi.org/10.1016/j.isprsjprs.2020.04.001
Tarek, M., Brissette, F. P., & Arsenault, R. (2021). Uncertainty of gridded precipitation and temperature reference datasets in climate change impact studies. Hydrology and Earth System Sciences, 27(3), 685–699. https://doi.org/10.5194/hess-25-3331-2021
Timmermann, A., An, S.-I., Kug, J.-S., Jin, F.-F., Cai, W., Capotondi, A., Cobb, K. M., Lengaigne, M., McPhaden, M. J., Stuecker, M. F., Stein, K., Wittenberg, A. T., Yun, K.-S., Bayr, T., Chen, H.-C., Chikamoto, Y., Dewitte, B., Dommenget, D., Grothe, P., … Zhang, X. (2018). El Niño–Southern Oscillation complexity. Nature, 559, 535–545. https://doi.org/10.1038/s41586-018-0252-6
Vuille, M., Carey, M., Huggel, C., Buytaert, W., Rabatel, A., Jacobsen, D., Soruco, A., Villacís, M., Yarleque, C., Elison Timm, O., Condom, T., Salzmann, N., & Sicart, J.-E. (2022). Rapid decline of snow and ice in the tropical Andes: Impacts, uncertainties and challenges ahead. Earth-Science Reviews, 176, 195–213. https://doi.org/10.1016/j.earscirev.2017.09.019
Wang, Y.-R., Samset, B. H., Stordal, F., Bryn, A., & Hessen, D. O. (2023). Past and future trends of diurnal temperature range and their correlation with vegetation assessed by MODIS and CMIP6. Science of the Total Environment, 904, 166727.
https://doi.org/10.1016/j.scitotenv.2023.166727
Wild, M. (2009). Global dimming and brightening: A review. Journal of Geophysical Research, 114, D00D16. https://doi.org/10.1029/2008JD011470
Yang, J., Gong, P., Fu, R., Zhang, M., Chen, J., Liang, S., Xu, B., Shi, J., & Dickinson, R. (2013). The role of satellite remote sensing in climate change studies. Nature Climate Change, 3(10), 875–883. https://doi.org/10.1038/nclimate1908
Yue, S., & Wang, C. (2004). The Mann-Kendall test modified by effective sample size to detect trend in serially correlated hydrological series. Water Resources Management, 18, 201–218.
https://doi.org/10.1023/B:WARM.0000043140.61082.60
Zambrano Mera, Y. E., Rivadeneira Vera, J. F., & Pérez-Martín, M. Á. (2018). Linking El Niño Southern Oscillation for early drought detection in tropical climates: The Ecuadorian coast. Science of the Total Environment, 643, 193–207. https://doi.org/10.1016/j.scitotenv.2018.06.160
Zhang, W., Furtado, K., Wu, P., Zhou, T., Chadwick, R., Marzin, C., Rostron, J., & Sexton, D. (2023). Increasing precipitation variability on daily-to-multiyear timescales in a warmer world. Science Advances, 7, eabf8021. https://doi.org/10.1126/sciadv.abf8021
Derechos de autor 2026 Jonny Fernando Rivadeneira Vera , Yeriel Elizabeth Zambrano Mera
Esta obra está bajo licencia internacional Creative Commons Reconocimiento 4.0.
.png)
.png)
1.png)
