  Modern weather forecasts are commonly issued as consistent multi-day forecast
trajectories with a time resolution of 1-3 hours. Prior to issuing, statistical
post-processing is routinely used to correct systematic errors and
misrepresentations of the forecast uncertainty. However, once the forecast has
been issued, it is rarely updated before it is replaced in the next forecast
cycle of the numerical weather prediction (NWP) model. This paper shows that
the error correlation structure within the forecast trajectory can be utilized
to substantially improve the forecast between the NWP forecast cycles by
applying additional post-processing steps each time new observations become
available. The proposed rapid adjustment is applied to temperature forecast
trajectories from the UK Met Office's convective-scale ensemble MOGREPS-UK.
MOGREPS-UK is run four times daily and produces hourly forecasts for up to 36
hours ahead. Our results indicate that the rapidly adjusted forecast from the
previous NWP forecast cycle outperforms the new forecast for the first few
hours of the next cycle, or until the new forecast itself can be rapidly
adjusted, suggesting a new strategy for updating the forecast cycle.
