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Projected precipitation from climate models is used in a wide range of fields for climate change impact assessment. However, the spatial pattern of uncertainty across latitudes and the global uncertainty hotspots are not well understood despite their importance for regional adaptation planning. In this study, we describe uncertainties in projected extreme precipitation changes per K global warming across latitudes, and decompose the overall uncertainty into climate model and internal variability uncertainties. We then identify global uncertainty hotspots and discuss the broader implications. Our results show that both uncertainty sources are highly heterogeneous across latitudes, while climate model uncertainty exceeds internal variability uncertainty for all seasons and precipitation intensities. The largest difference between model and internal variability uncertainties is found in tropical regions where model uncertainty is thrice as large as internal variability uncertainty in June–July–August season and twice as large as that in the other seasons. Tropical and subtropical regions are identified as the global uncertainty hotspots, with the Sahara desert and the southern part of the Middle East being the local hotspots. The large uncertainty in the tropics and subtropics is primarily due to the convective nature of rainstorms which cannot be adequately represented by coarse-scale climate models, and also to sparse observation networks based on which climate models can be tuned and improved. The results highlight areas where future model development and improvement efforts should focus to reduce the overall uncertainties in projected precipitation extremes.

Latitudinal heterogeneity and hotspots of uncertainty in projected extreme precipitation