Development of DRIP - drought representation index for CMIP climate model performance, application to Southeast Brazil.

With the escalating impacts of drought events driven by climate change, reducing the uncertainty of drought projections becomes critical for enhancing risk management and adaptation strategies. This study aimed to develop an index for assessing the performance of CMIP6 Global Climate Models in simulating meteorological drought scenarios across regional hydrological systems, intended to provide more reliable information for management purposes. Named the 'Drought Representation Index for CMIP Climate Model Performance' (DRIP), this index evaluates CMIP models' performance to represent drought severity, duration, and return period.

Evaluating tropical drought risk by combining open access gridded vulnerability and hazard data products.

Droughts are causing severe damages to tropical countries worldwide. Although water abundant, their resilience to water shortages during dry periods is often low. As there is little knowledge about tropical drought characteristics, reliable methodologies to evaluate drought risk in data scarce tropical regions are needed.