Investigations into the Reaction of the Pangu ML Weather Model to Different Initial Conditions

Investigations have been carried out into the initiation of the Pangu weather model, initiating the model with both ERA5 data (on which it was trained) and with the Met Office’s Global UM model data. There are many consistent local biases at ground level between these two sets of initial conditions. The geographically local biases are not dissipated by the Pangu model with timestep but instead remain geographically fixed and gradually decrease with lead time. Whilst the Pangu model initiated with UM initial conditions remains further from the ERA5 truth than the ERA5-initiated Pangu model at all timesteps, it initially moves towards the ERA5 truth with timestep, as the geographically static differences in initiation decrease, before moving further away from the ERA5 truth as differences in large-scale systems begin to dominate.

Also investigated was the difference between the Pangu model 24-hour timesteps and 6-hour timesteps; it was found that the 6-hour timesteps were better able to reduce the geographically static initial differences than the 24-hour timesteps.

If time permits, a similar analysis will be made of the FastNet and GraphCast models.