Current and future climate conditions over Canary islands and Madeira: an overview of two different km-scale COSMO-CLM simulations

Islands, especially those with complex topography, are exceptionally vulnerable to climate change due to the dependency of their economies on climate-sensitive sectors like tourism and agriculture. These regions face significant challenges, including rising sea levels, tropical and extratropical cyclones, increasing temperatures, and shifting rainfall patterns. Despite these pressing threats, global climate models (GCMs) often lack the necessary resolution to capture the critical local processes that shape island climates. Similarly, conventional regional climate models (RCMs) frequently fall short in providing the robustness required to address the unique dynamics of these areas. This study seeks to explore two new km-scale regional climate simulations prepared through the European Climate Prediction project over the Madeira and Canary Islands, which are Portuguese and Spanish archipelagos located in the North Atlantic, off the African coast. The simulations are based on two models using different modelling approaches. One simulation was run by the Euro-Mediterranean Center on Climate Change (CMCC) Foundation with a horizontal grid spacing of around 3 km, based on a time slice approach. The RCM COSMO-CLM is used with a three-step nesting at 50, 25 and 3 km grid spacing based on a time-slice approach driven by a global climate model. The other simulation was run by the Swiss Federal Institute of Technology (ETH) in Zurich. The RCM COSMO-crCLIM is used with a two-step nesting at 12 and a grid spacing of around 1 km. This model was using the pseudo-global warming approach for the future-climate simulation, while the current-day simulations are driven by ERA-Interim reanalysis. Both models parameterize shallow convection, while the parameterization is switched off for deep convection. 

The analyses focus on the representation of hourly precipitation and temperature indices for the current and future climate: frequency, intensity, mean, and extreme values for the former, and mean and daily maximum values for the latter.

Although the modelling approaches are different, several findings are highlighted: (1) the use of km-scale simulation is essential to properly represent temperature and precipitation mean and extremes over small islands that are characterized by complex topography; (2) the projected changes in temperature and precipitation mean and extremes are qualitatively similar in all seasons except autumn; (3) the differences in the autumn projections are shown to be due to the large-scale driving conditions, which are different for the three simulations. The differences when comparing the signals between the two experimental designs might be related to the configuration of the respective forcing models and parameterizations. This suggests a careful selection of the former and opens up possible extensions of the analysis to other important factors. 

The results hope to set the cornerstone in filling an important gap for local climate services, highlighting the need for further coordinated kilometer-scale projections over regions of similar character, that are often neglected by large modelling initiatives. The presented work contributes to filling this gap for local policy makers, stakeholders and climate services.