Towards higher resolution data assimilation in ECMWF IFS

Enhancing the spatial resolution of global analyses and forecasts enables weather prediction systems to more accurately capture rapidly evolving mesoscale and convective-scale atmospheric phenomena. The Integrated Forecast System (IFS) of ECMWF consists of an Earth-system model coupled with an incremental 4D-Var data assimilation (DA) system, which has recently been experimentally upgraded to higher spatial resolution.

This upgrade involved higher resolution (4.4 km) 4D-Var trajectories and higher resolution (20 km) 4D-Var minimizations using the tangent linear model (TLM) and its adjoint (ADM). This configuration requires less observation thinning and resulted in greater use of high-resolution observations, such as those from multispectral imagers aboard Himawari and Meteosat satellites. Shorter time steps in TLM and ADM further enabled the use of shorter observation time slots (400 seconds), allowing for more accurate comparison between observations and their model equivalents.

We demonstrate that this setup leads to significant improvements in the accuracy of initial conditions and enhances tropospheric forecast skill, extending medium-range predictability by 6 to 12 hours. We argue that the improved forecast skill can be attributed to a better representation of large-scale features in the stratosphere. Higher resolution DA and forecasts also lead to improved forecasting of extreme precipitation events, as well as the track and intensity of tropical cyclones. Furthermore, the improved initial conditions significantly increase the predictability machine-learning-based forecasts.

The benefits of the higher resolution DA system are demonstrated using the case of Tropical Cyclone Otis, which made landfall as a Category 5 cyclone, but was predicted by most global and regional NWP models to peak only at tropical storm intensity – a major forecasting bust. By employing higher resolution 4D-Var DA, we were able to replicate the observed rapid intensification of TC Otis.