Abstract
Abstract. Projections of coastal sea level (SL) changes are of great interest for coastal risk assessment and decision making. SL projections are typically produced using global climate models (GCMs), which cannot fully resolve SL changes at the coast due to their coarse resolution and lack of representation of some relevant processes (tides, atmospheric surface pressure forcing, waves). To overcome these limitations and refine projections at regional scales, GCMs can be dynamically downscaled through the implementation of a high-resolution regional climate model (RCM). In this study, we developed the IBI-CCS (Iberian–Biscay–Ireland Climate Change Scenarios) regional ocean model based on a 1/12∘ northeastern Atlantic Nucleus for European Modelling of the Ocean (NEMO) model configuration to dynamically downscale CNRM-CM6-1-HR, a GCM with a 1/4∘ resolution ocean model component participating in the sixth phase of the Coupled Model Intercomparison Project (CMIP6) by the Centre National de Recherches Météorologiques (CNRM). For a more complete representation of the processes driving coastal SL changes, tides and atmospheric surface pressure forcing are explicitly resolved in IBI-CCS in addition to the ocean general circulation. To limit the propagation of climate drifts and biases from the GCM into the regional simulations, several corrections are applied to the GCM fields used to force the RCM. The regional simulations are performed over the 1950 to 2100 period for two climate change scenarios (SSP1-2.6 and SSP5-8.5). To validate the dynamical downscaling method, the RCM and GCM simulations are compared to reanalyses and observations over the 1993–2014 period for a selection of ocean variables including SL. Results indicate that large-scale performance of IBI-CCS is better than that of the GCM thanks to the corrections applied to the RCM. Extreme SLs are also satisfactorily represented in the IBI-CCS historical simulation. Comparison of the RCM and GCM 21st century projections shows a limited impact of increased resolution (1/4 to 1/12∘) on SL changes. Overall, bias corrections have a moderate impact on projected coastal SL changes, except in the Mediterranean Sea, where GCM biases were substantial.
Highlights
Sea level (SL) changes are a major threat for coastal and lowlying regions
To validate the dynamical downscaling method, the IBICCS_raw, Iberian–Biscay– Ireland (IBI)-CCS_corr and Centre National de Recherches Météorologiques (CNRM)-CM6-1-HR historical simulations are compared to the reanalysis IBIRYS, the IBIERAi (Sect. 2.2.2) regional simulation and observational datasets over the 1993–2014 period
Previous dynamical downscaling studies have provided regional projections of SL based on low-resolution CMIP5 global climate models (GCMs) (e.g., Hermans et al, 2020b; Liu et al, 2016; Zhang et al, 2017; Gomis et al, 2016, Jin et al, 2021)
Summary
Sea level (SL) changes are a major threat for coastal and lowlying regions. Risks associated with sea level rise (SLR) are even more important because coastal regions are subject to increasing anthropogenic pressure, with 10 % of the world’s population living in low elevation coastal zones (McGranahan et al, 2007). In Europe, the coastal population represents 50 million people (Neumann et al, 2015). The annual number of Europeans exposed to coastal flooding could reach 1.5 to 3.6 million by the end of the century and the associated expected annual damage could reach EUR 90–960 billion (Vousdoukas et al, 2018a). Projections of coastal SL changes are of great interest for coastal risk assessment and decision making
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