How does dynamical downscaling affect model biases and future projections of explosive extratropical cyclones along North America’s Atlantic coast?

Abstract

Explosive extratropical cyclones (EETCs) are rapidly intensifying low pressure systems that generate severe weather along North America’s Atlantic coast. Global climate models (GCMs) tend to simulate too few EETCs, perhaps partly due to their coarse horizontal resolution and poorly resolved moist diabatic processes. This study explores whether dynamical downscaling can reduce EETC frequency biases, and whether this affects future projections of storms along North America’s Atlantic coast. A regional climate model (CanRCM4) is forced with the CanESM2 GCM for the periods 1981 to 2000 and 2081 to 2100. EETCs are tracked from relative vorticity using an objective feature tracking algorithm. CanESM2 simulates 38% fewer EETC tracks compared to reanalysis data, which is consistent with a negative Eady growth rate bias (−0.1 day$^{-1}$). Downscaling CanESM2 with CanRCM4 increases EETC frequency by one third, which reduces the frequency bias to −22%, and increases maximum EETC precipitation by 22%. Anthropogenic greenhouse gas forcing is projected to decrease EETC frequency (−15%, −18%) and Eady growth rate (−0.2 day$^{-1}$, −0.2 day$^{-1}$), and increase maximum EETC precipitation (46%, 52%) in CanESM2 and CanRCM4, respectively. The limited effect of dynamical downscaling on EETC frequency projections is consistent with the lack of impact on the maximum Eady growth rate. The coarse spatial resolution of GCMs presents an important limitation for simulating extreme ETCs, but Eady growth rate biases are likely just as relevant. Further bias reductions could be achieved by addressing processes that lead to an underestimation of lower tropospheric meridional temperature gradients.