Understanding tropical precipitation extremes is crucial for capturing the complexities of global climate dynamics. In this study, we employ a novel methodology to examine these extremes in spatial and temporal resolutions that have not previously been explored in global climate modeling. High-resolution data from nextGEMS Cycle 3 and preliminary DestinE simulations are our primary sources. We thoroughly analyzed advanced models from different historical periods, including ICON, IFS-FESOM, and IFS-NEMO. The research also includes a range of observational data sources, such as the MSWEP, ERA5, and EMERG datasets, to create a robust framework for comparison. Our methodological approach includes zonal mean analysis and probability distribution functions (PDFs), applied to data re-gridded to both standard 1° monthly and finer high-resolution 0.1° scales. This dual-resolution strategy is key for revealing detailed patterns and extremes in tropical precipitation. The study uncovers notable alignments and discrepancies between model simulations and observational data. Some models show a high degree of accuracy in reflecting real-world observations, whereas models like ICON demonstrate significant biases, especially in extreme precipitation rates. Such variations in precipitation peaks and rates across different models underscore the need for adjusting simulation parameters to enhance accuracy.
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Nazarova et al. (2024) studied this question.
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