Fine-Scale Climate Projections: What Additional Fixed Spatial Detail Is Provided by a Convection-Permitting Model?

Convection-permitting (CP) models promise much in response to the demand for increased localization of future climate information: greater resolution of influential land surface characteristics, improved representation of convective storms, and unprecedented resolution of user-relevant data. In practice, however, it is contended that the benefits of enhanced resolution cannot be fully realized due to the gap between models' computational and effective resolution. Nevertheless, where surface forcing is strongly heterogeneous, one can argue that usable information may persist close to the grid scale. Here we analyze a 4.5-km resolution CP projection for Africa, asking whether and where fine-scale projection detail is robust at sub-25-km scales, focusing on geolocated rainfall features (rather than Lagrangian motion). Statistically significant detail for seasonal means and daily extremes is most frequent in regions of high topographic variability, most prominently in East Africa throughout the annual cycle, West Africa in the monsoon season, and to a lesser extent over Southern Africa. Lake coastal features have smaller but significant impacts on projection detail, whereas ocean coastlines and urban conurbations have little or no detectable impact. The amplitude of this sub-25-km projection detail can be similar to that of the local climatology in mountainous regions (or around a third near East Africa's lake shores), so potentially beneficial for improved localization of future climate information. In flatter regions distant from coasts (the majority of Africa), spatial heterogeneity can be explained by chaotic weather variability. Here, the robustness of local climate projection information can be substantially enhanced by spatial aggregation to approximately 25-km scales, especially for daily extremes and equatorial regions. Significance StatementRecent substantial increases in the horizontal resolution of climate models bring the potential for both more reliable and more local future climate information. However, the best spatial scale on which to analyze such data for impacts assessments remains unclear. We examine a 4.5-km resolution climate projection for Africa, focusing on seasonal and daily rainfall. Spatially fixed fine-scale projection detail is found to be statistically robust at sub-25-km scales in the most mountainous regions and to a lesser extent along lake coastlines. Elsewhere, the model data may be better aggregated to at least 25-km scales to reduce sampling uncertainties. Such evolving guidance on the circumstances and extent of high-resolution data aggregation will help users gain greater benefit from climate model projections.