Understanding the double-ITCZ problem over the Atlantic with bias-corrected downscaling

The long-existing double-ITCZ problem in GCMs affects not only the models' ability in simulating the current climate, but also implies limitations regarding the assessment of climate sensitivity and global climate change. Using a regional climate model (RCM) with explicit convection at a horizontal grid spacing of 12 km in a large computational domain covering the tropical and sub-tropical Atlantic, we develop a bias-correction downscaling methodology to remove the biases of a driving GCM. The methodology is related to the pseudo-global warming (PGW) approach. Normally this method is used to impress the climate-change signal to a reanalysis-driven RCM simulation, but it can also be used to modulate the lateral-boundary conditions of a GCM, such as to remove the large-scale biases. We show that the double ITCZ problem persists with classical dynamical downscaling (i.e. when driving the RCM directly by the GCM output), but with our bias-corrected downscaling the double ITCZ problem can be removed. Detailed analysis reveals that the main cause of the double ITCZ problem can be attributed to the GCMs' SST bias. Compared to the GCMs' AMIP simulations, RCMs with higher resolution allow explicit deep convection and enable a better simulation of tropical convection and clouds. By improving the corresponding radiative forcing, vertical motion is better simulated. Subsidence stronger to the south of the ITCZ pushes the ITCZ more north in the boreal spring, which is consistent with the observation of the ITCZ. The developed methodology provides an opportunity for better constraining climate sensitivity by removing double-ITCZ biases.