Advanced tropical cyclone prediction using the experimental global ECMWF and operational regional COAMPS-TC systems

Abstract

Structure and intensity forecasts of 19 tropical cyclones (TCs) during the 2020 Atlantic hurricane season are investigated using two NWP systems. An experimental 4-km global ECMWF model (“EC4”) with upgraded moist physics is compared against a 9-km version (“EC9”) to evaluate the influence of resolution. EC4 is then benchmarked against the 4-km regional COAMPS-TC system (“CO4”) to compare systems with similar resolutions. EC4 produced stronger TCs than EC9, with a >30% reduction of the maximum wind speed bias in EC4 resulting in lower forecast errors. However, both ECMWF predictions struggled to intensify initially weak TCs, and the radius of maximum wind (RMW) was often too large. In contrast, CO4 had lower biases in central pressure, maximum wind speed, and RMW. Regardless, minimal statistical differences between CO4 and EC4 intensity errors were found for ≥36 h forecasts. Rapid intensification cases yielded especially large intensity errors. CO4 produced superior forecasts of RMW, together with an excellent pressure-wind relationship. Differences in the results are due to contrasting physics and initialization schemes. ECMWF uses a global data assimilation with no special treatment of TCs, whereas COAMPS-TC constructs a vortex (for TCs with initial intensity ≥55 kt) based on data provided by forecasters. Two additional ECMWF experiments were conducted. The first yielded improvements when the drag coefficient was reduced at high wind speeds, thereby weakening the coupling between the low-level winds and the surface. The second produced overly intense TCs when explicit deep convection was used, due to unrealistic mid-upper-tropospheric heating.