This study evaluates the performance of subseasonal forecasts for dry spells and heatwaves at a regional scale in Brazil. The forecasts’ verification was designed to provide end-users with relevant information about the forecasts’ quality. The U.K. Met Office model was assessed using a significant sample of weekly forecasts: 552 for dry spells and 240 for heatwaves. The analysis reveals that the overall performance of the forecasts is low, with a chance of detecting an event close to 0.2, indicating that only one out of five observed dry spells is accurately predicted on average. The application of quantile mapping corrections demonstrates improvements in predicting shorter dry spells (up to 5 days) and longer lead times, although the timing of these forecasts often remains inaccurate, leading to increased false alarms. A significant improvement in the forecast quality occurs when categorization by duration is disregarded. The detection chances increase to 0.5−0.7 for dry spells and 0.5 for heatwaves. The Brier Score indicates that the probabilistic forecasts issued by the model are equivalent or less skilful than climatological probabilities. Overall, the findings underscore the challenges in forecasting dry spells and heatwaves in Brazil and highlight the need for ongoing improvements in forecasting methodologies to enhance their reliability and utility for regional decision-making. This research contributes to understanding subseasonal climate forecasting and its implications for managing climate-related risks in Brazil.
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