Weather and Climate Extremes (Jun 2022)
Climate projections at a convection-permitting scale of extreme temperature indices for an archipelago with a complex microclimate structure
Abstract
In island systems with complex orography (e.g. Canary Islands), obtaining projections of climate extremes throughout the 21st century is necessary to evaluate the possible adverse effects of climate change. In this work, a dynamic downscaling methodology was applied to obtain the projections of temperature extremes indices. The WRF modeling system was properly configured with a spatial resolution of 3 km, for the periods: 2030–2059 (MID) and 2070–2099 (END), and for the RCPs 4.5 and 8.5 scenarios. This spatial-temporal resolution allows better modeling of the land-surface coupling processes (e.g., latent and sensible heat fluxes), which are one of the main sources of uncertainties in temperature extremes modeling. The initial and boundary conditions were defined by three CMIP5 Earth Systems Models: GFDL-ESM2M, MIROC-ESM, and IPSL-CM5. The future changes were calculated against the modeled reference period was 1980–2009 (HIS). The selected extremes indices were those defined by the Team of Experts on Climate Change Detection and Indices (ETCCDI) and were: monthly absolute maximum and minimum temperature respectively (TX and TN), monthly maximum of the diurnal temperature range (DTR), tropical nights (TR), warm days (TX90P), cold nights (TN10P), warm-spell duration index (WSDI) and cold-spell duration index (CSDI). Also, the return levels and return periods for annual maximum temperature were analyzed using the Generalized Extreme Value distribution (GEV).The modeled indices were compared with those obtained from observations at nine ground-based stations for the HIS period. Despite the high spatial and temporal resolution of the models a bias is still observed between the modeled and observational values for the absolute indices, even when the simulations are driven by reanalysis data. However, the comparison of these indices around their previously unbiased means yields values on average of 0.85 with a standard deviation of 0.06 on a Perkins-based skill score. Regarding the 20-year return levels for maximum temperature, differences between the average of the models and observations are below 2 °C for all sites, except for the highest stations IZO and TFN, which reach 2.9 and 4.2 °C, respectively.The analyses of the results indicate that the future projections of the indices obtained using any of the models remain constant from the mid-century to the end of the century for the RCP45 whereas they continue to increase if the RCP85 is considered. This finding shows that all models closely follow the variation in the CO2-equivalent concentrations used as input. Thus, TX and TN are expected to increase, with an average change for the END period and RCP8.5 of 4.0 ± 0.5 °C and 4.4 ± 0.4 °C for TN. TX90p increases considerably (30 percentage points), and the TN10p index will be close to zero. The increase in temperatures is mainly due to, in addition to the modification of the synoptic patterns, a decrease in total cloud cover and soil moisture.This decrease in soil moisture has a direct effect on the decrease in latent heat flux and an increase in sensible heat flux, associated with a projected increase of DTR. Also, the 20-year return levels for maximum temperature obtained for the HIS period will correspond to return periods between 1 and 6 years at the END period and RCP8.5.
