Identificação de seca com os índices SPI e SPEI em Mato Grosso e suas relações com a temperatura dos oceanos Pacífico e Atlântico

Abstract

The precipitation has been decreasing, and air temperature has been increasing in the three biomes (Amazon - AMZ, Cerrado - CER, and Pantanal - PAN) of the Mato Grosso state, making them susceptible to an increase in drought phenomena. The aim of this study was to analyze the trends in severity, intensity, and duration of drought events between 1970 and 2022 in the Mato Grosso state using the Standardized Precipitation Index (SPI) and the Standardized Precipitation and Evapotranspiration Index (SPEI), and their relationships with Sea Surface Temperature Anomalies (SSTA) and the Southern Oscillation Index (SOI). The SPI and SPEI were calculated using precipitation and air temperature data from the ERA5-land product. The trends of SPI and SPEI were obtained through the Mann Kendal (MK) test, and the number of occurrences, severity, intensity, and duration were obtained through the Run-Theory method. The SPI and SPEI tended to decrease in the three biomes between 1970 and 2022. Moderate, severe, and extreme drought events occurred in all biomes, with the Pantanal experiencing the highest severity of drought between 2019 and 2022. The highest number of occurrences of extreme droughts by SPI happened in AMZ and CER between 2020 and 2022, and the highest values of severity, duration, and intensity occurred in CER and PAN during the same period. However, severity, duration, and intensity values by SPEI were observed in AMZ and CER. The SPI and SPEI showed a similar correlation pattern with the SSTA and SOI. The SPI had a weak negative correlation with indices such as the Atlantic Multidecadal Oscillation (AMO), Southern Oscillation Index (SOI), Tropical Northern Atlantic Index (TNAI), and Tropical Southern Atlantic Index (TSAI), whereas the SPEI exhibited a moderate negative correlation with AMO and TSAI. This study highlights that drought intensity and not all SST anomalies influence the seasonal and interannual dynamics of droughts in Mato Grosso.