Impact of Climate Change on Sugarcane Yield in Maceió

Abstract

In this study, a statistical downscaling model (SDSM) based on the analogous methodology was used to project future patterns of precipitation and temperature in the city of Maceió, east coast of northeastern Brazil (9.7° S; 35.7° W; 64.5m), and to evaluate its impacts on sugar cane yield. Historical observed data were used for downscaling precipitation and temperature using different global climate models (CanESM2, CNRM-CM5, IPSL-CM5A-MR, GFDL-ESM2M, MIROC-ESM, MPI-ESM-MR, and NorESM1-M) in relation to the reference period (1961-1990), and then for future scenarios from 2021 to 2080. The data were analysed in a ten days period, the same time step as the agrometeorological model used for culture. Contrary to what was expected, the combination of reduced rainfall and increased evapotranspiration in future scenarios did not decrease the estimate of yield, with an increase forecast. This effect can be attributed to the fact that the reduction in predicted rainfall, which was more pronounced in the rainy season, was not decisive for the decrease in yield, since in most MCGs there is a forecast of increased rainfall in the dry period from September to December, which is crucial for the initial growth of the crop, which has a planting schedule from the first ten-day period of September.

Keywords:
statistical downscaling; rainfall; evapotranspiration; agrometeorology