Hugo Carvalho de Almeida, João Pedro Gonçalves Nobre, Eli Moisés dos Santos Silva, Fabrício Daniel dos Santos Silva


The performance of four global models, together with two scenarios of climate change, was evaluated in five municipalities of the State of Alagoas, for precipitation, minimum and maximum temperature. The input data of the model were obtained through the conventional meteorological stations of the National Institute of Meteorology (INMET), arranged between 1961 and 2016. Estimation of corn yield was obtained through the theoretical model which relates losses in productivity and water deficiency during the phenological phases of the crop. A post-processing technique of global climate model outputs (statistical downscaling) was used, thus, a better visualization in time and space. The precipitation and temperature series were used for the period 2021-2080 estimating the yield losses of maize, comparing to the historical average values of the period 1961-2016, evaluating the impacts of possible climatic changes on crop yield. The scenarios have values of losses very close to and indicate a prediction of increased productivity loss in the period 2021-2080 for Água Branca, Pão de Açúcar and Palmeira dos Índios, and decrease of losses, that is, increase of productivity, for Maceió and Mainly Porto de Pedras. This result is directly associated to the predictions of rainfall reduction in the interior of the State, encompassing the cities of Água Branca, Pão de Açúcar and Palmeira dos Índios, a slight increase in precipitation for Maceió and a more significant increase in precipitation in Porto de Pedras.


Climatology; Statistical Downscaling; Agrometeorological Model.

Texto completo:



ALLEN, R. G.; PEREIRA, L. S.; RAES, D.; SMITH, M. Crop Evapotranspiration: Guidelines for Computing Crop Water Requirements. FAO Irrigation and Drainage Paper 56, Rome. 1998.

ALVES, J. M. B.; REPELLI, C. A.; MELLO, N. G. A pré-estação chuvosa do setor norte do Nordeste Brasileiro e sua relação com a temperatura dos oceanos adjacentes. Revista Brasileira de Meteorologia, v. 8, n. 1, 1993.

CHOU, S. C.; LYRA, A.; MOURAO, C.; DERECZYNSKI, C.; PILOTTO, I.; GOMES, J.; BUSTAMANTE, J.; TAVARES, P.; SILVA, A.; RODRIGUES, D.; CAMPOS, D.; CHAGAS, D.; SUEIRO, G.; SIQUEITA, G.; MARENGO, J. Assessment of Climate Change over South America under RCP 4.5 and 8.5 Downscaling Scenarios. American Journal of Climate Change, v. 3, n. 2, 2014.

COLLINS, W. J.; BELLOUIN, N.; DOUTRIAUX-BOUCHER, M.; GEDNEY, N.; HINTON, T. C.; JONES, D.; LIDDICOAT, S.; MARTIN, G.; OCONNOR, F.; RAE, J.; SENIOR, C.; TOTTERDELL, I.; WOODWARD, S. Evaluation of the HadGEM2 model. Meteorological Office Hadley Centre, Technical Note 74, 2008.

DOORENBOS, J; KASSAM, A. H. Yield response to water. Irrigation and Drainage Paper 33, FAO, Roma, 1979, 179 p.

FRANCHITO, S. H.; REYES FERNANDEZ, J. P.; PAREJA, D. Surrogate Climate Change Scenario and Projections with a Regional Climate Model: Impact on the Aridity in South America. American Journal of Climate Change, v. 3, n. 5, 2014.

HARGREAVES, G. H.; SAMANI, Z. A. Reference crop evapotranspiration from temperature. Applied Engineering in Agriculture, v. 1, n. 2, 1985.

HALL, T.; BROOKS, H.; DOSWELL, C. Precipitation forecasting using a neural network. Weather and Forecasting, v. 14, n. 3, 1999.

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. Trends in Total and Extreme South American Rainfall in 1960–2000 and Links with Sea Surface Temperature. Journal of Climate, v. 19, n. 15, 2006.

KALNAY, E., and Coauthors. The NCEP/NCAR 40-Year Reanalysis Project. Bulletin of the American Meteorological Society, v. 77, n. 3, 1996.

KÜRBIS, K.; MUDELSEE, M.; TETZLAFF.; BRÁZDIL, R. Trends in extremes of temperature, dew point, and precipitation from long instrumental series from central Europe. Theoretical Applied of Climatology, v. 98, n. 1, 2009.

MARAUN, D.; WETTERHALL, F.; IRESON, A. M.; CHANDLER, R. E.; KENDON, E. J.; WIDMANN, M.; BRIENEN, S.; RUST, H. W.; SAUTER, T.; THEMEL, M.; VENEMA, V. K. C.; CHUN, K. P.; GOODESS, C. M., JONES, R. G.; ONOF, C.; VRAC, M.; THIELE-EICH, I. Precipitation downscaling under climate change: recent developments to bridge the gap between dynamical models and the end user. Reviews of Geophysics, v. 48, p. 1-38, 2010.

MENEZES, H. E. A. Influência da Zona de Convergência Secundária do Atlântico Sul sobre a ocorrência de precipitação no leste do Nordeste brasileiro. 2010. Tese (Doutorado em Meteorologia) - Universidade Federal de Campina Grande, Campina Grande, 2010.

MONTEIRO, J. E. B. A.; AZEVEDO, L. C.; ASSAD, E. D.; SENTELHAS, P. C. Rice yield estimation based on weather conditions and on technological level of production systems in Brazil. Pesquisa Agropecuária Brasileira, v. 48, n. 2, 2013.

MONTEIRO, J. E. B. A.; ASSAD, E. D.; SENTELHAS, P. C.; AZEVEDO, L. C. Modeling of corn yield in Brazil as a function of meteorological conditions and technological level. Pesquisa Agropecuária Brasileira, v. 52, n. 3, 2017.

MURPHY, J. Predictions of climate change over Europe using statistical and dynamical downscaling techniques. International Journal of Climatology, v. 20, n. 5, 2000.

NGUYEN, A. D.; SAVENIJE, H. H. Salt intrusion in multi-channel estuaries: a case study in the Mekong Delta, Vietnam, Hydrology and Earth System Sciences, v. 10, n. 5, 2006.

SAMANI, Z. Estimating Solar Radiation and Evapotranspiration Using Minimum Climatological Data. Journal of Irrigation and Drainage Engineering, v. 126, n. 4, 2000.

SILVA, N. D.; OLIVEIRA, A. S.; BORGES, T. K. S.; GOMES, F. L.; FONSECA, S. S.; GUEDES, F. A.; COUTO, J. P. C. Mapping reference crop evapotranspiration in Bahia, Brazil, using Hargreaves-Samani method. Revista Geama, v. 7, n. 1, 2016.

SILVA, K. E.; BARRETO, T. S. C. P.; SHINOHARA, N. K. S.; ANDRADE, J. S. C.O.; MACHADO, J.Precision Agriculture in the Promotion of Sustainable Development. Revista Geama, v. 9, n. 1, 2017.

SKANSI, M.; BRUNET, M.; SIGRÓ, J.; AGUILAR, E.; GROENING, J. A. A.; BENTANCUR, O. J.; GEIER, Y. R. C, AMAYA, R. L. C.; JÁCOME, H.; RAMOS, A. M.; ROJAS, C. O.; PASTEN, M. A.; MITRO, S. S.; JIMÉNEZ, C. V.; MARTÍNEZ, R.; ALEXANDER, L. V.; JONES, P. D. Warming and wetting signals emerging from analysis of changes in climate extreme indices over South America. Global and Planetary Change, v. 100, n. 1, 2013.

SOLMAN, S. A., NUÑEZ, M. N., CABRÉ, M. F. Regional climate change experiments over southern South America. I: present climate. Climate Dynamics, v. 30, n. 5, 2008.

UPPALA, S., et al. The era-40 re-analysis. Quarterly Journal of The Royal Meteorlogical Society, v. 131, n. 612 PartB, 2005.

WILBY, R. L.; WIGLEY, T. M. L. Downscaling general circulation model output: a review of methods and limitations. Progress in Physical Geography, v. 21, n. 4, 1997.

WILBY, R. L.; CHARLES, S. P.; ZORITA, E.; TIMBAL, B.; WHETTON, P.; MEARNS, L. O. 2014. Guidelines for use of climate scenarios developed from statistical downscaling methods. Access in: 08/03/2017. Available at: /dgm_no2_v1_09_2004.pdf.

WILBY, R. L, DAWSON, C. W. User manual for SDSM 4.2, 2007.

ZORITA, E.; HUGHES, J. P.; LETTENMAIER, D. P.; VON STORCH, H. Stochastic characterization of regional circulation patterns for climate model diagnosis and estimation of local precipitation. Journal of Climate, v. 8, n. 5, 1995.

ZORITA, E.; VON STORCH, H. The analog method as a simple statistical downscaling technique: Comparison with more complicated methods. Journal of Climate, v. 12, n. 8 Part 2, 1999.


  • Não há apontamentos.

Licença Creative Commons