Abstract
Due to associated hydrological risks, there is an urgent need to provide plausible quantified changes in future extreme rainfall rates. Convection-permitting (CP) climate simulations represent a major advance in capturing extreme rainfall and its sensitivities to atmospheric changes under global warming. However, they are computationally costly, limiting uncertainty evaluation in ensembles and covered time periods. This is in contrast to the Climate Model Intercomparison Project (CMIP) 5 and 6 ensembles, which cannot capture relevant convective processes, but provide a range of plausible projections for atmospheric drivers of rainfall change. Here, we quantify the sensitivity of extreme rainfall within West African storms to changes in atmospheric rainfall drivers, using both observations and a CP projection representing a decade under the Representative Concentration Pathway 8.5 around 2100. We illustrate how these physical relationships can then be used to reconstruct better-informed extreme rainfall changes from CMIP, including for time periods not covered by the CP model. We find reconstructed hourly extreme rainfall over the Sahel increases across all CMIP models, with a plausible range of 37%–75% for 2070–2100 (mean 55%, and 18%–30% for 2030–2060). This is considerably higher than the +0–60% (mean +30%) we obtain from a traditional extreme rainfall metric based on raw daily CMIP rainfall, suggesting such analyses can underestimate extreme rainfall intensification. We conclude that process-based rainfall scaling is a useful approach for creating time-evolving rainfall projections in line with CP model behaviour, reconstructing important information for medium-term decision making. This approach also better enables the communication of uncertainties in extreme rainfall projections that reflect our current state of knowledge on its response to global warming, away from the limitations of coarse-scale climate models alone.
Highlights
Convective rainfall dominates rainfall extremes in many regions of the world, which are set to increase with or beyond the rate of increasing water vapour in the atmosphere ce in a warming climate (Allen & Ingram, 2002; O’Gorman & Schneider, 2009)
Comparing total column water (TCW)-reconstructed (Fig. 3c-e, grey line and shading) to the combineddriver ∆Pmax95, we find that shear changes have a minor effect on future rainfall change: while the individual change related to shear still increases from +1.8 mm h−1 around 2040 to +2.4 mm h−1 by 2080 for the 90th Climate Model Intercomparison Project (CMIP) percentile, the relative contribution from strengthened shear to total ∆Pmax95,t+s decreases from
Our aim was to fuse a CP model projection, which provides us with only one possible future of how precipitation extremes from West African mesoscale convective systems (MCSs) might change, with a CMIP-based time-continuous uncertainty range
Summary
Convective rainfall dominates rainfall extremes in many regions of the world, which are set to increase with or beyond the rate of increasing water vapour in the atmosphere ce in a warming climate (Allen & Ingram, 2002; O’Gorman & Schneider, 2009). We focus on West Africa, where we have a single CP realisation of future climate (Stratton et al, 2018; Senior et al, 2021), which shows a greater increase in extreme rainfall than a parameterised version of the model, with greater intensification of ce convective updraughts (Kendon et al, 2019; Jackson et al, 2020; Berthou, Kendon, et al, 2019; Fitzpatrick et al, 2020) This CP simulation is a major advance given the dominance of large, organised thunderstorm-clusters in this region, which produce the majority of extreme rainfall (Mathon et al, 2002). This is the first attempt to combine this mixture of models and observations to better understand the response ce of future rainfall extremes to its atmospheric drivers
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