The experiment setting is similar to Twin Experiment 2, but with a different truth (at the upstream location, CHC and CHG are non zero in the summer).
Results
At assimilation station
Time series:
RMSE (computer over 51 analyses cycles over 2015):
At validation stations
Time series (Location 5006A40):
RMSE (Location 5006A40):
Over all locations:
Discussions
- EnKF works well in improving forecast accuracy at the assimilation station and all down stream stations, but not the upstream stations.
- The RMSE of the deterministic run from the assimilation station to down stream is more or less uniform. Yet the EnKF impact gets bigger in the downstream direction. Why?
- The RMSE at the most downstream location is especially small, even the deterministic one, as if it is not really affected by the noise defined upstream. The model has apparently a different dynamic there. Why?
- Water temperature is not included in the noise model definition nor in the state definition of the filter. Yet it is affected as it has quite a significant RMSE. The filter has also a slightly positive effect downstream on water temperature. It is likely due to the inclusion of solar radiation in both the noise model and state definition of the filter.
- Can we say anything about optimality of the filter? Have we reached the maximum possible improvement? what can be done to improve the accuracy even more?
