In these exercises we will look at a case study using a forecast ensemble. You will start by studying the evolution of the ECMWF HIRES forecast and the ECMWF ensemble forecast for this event. Then you will run your own OpenIFS forecast for a single ensemble member at lower resolutions and work in groups to study the OpenIFS ensemble forecasts.
metview |
St. Judes storm..... (see separate sheet?)
ECMWF operational forecasts consist of:
(following approach in metview training course ensemble forecast)
Dates 24th - 29th.
Ensemble spread is ....
(see separate handout?)
OpenIFS running at T319 (resolution of second leg of ECMWF's forecast ensemble).
Each participant runs one ensemble.
(possibly including Filip's coding exercise here).
At the end of this, participants will have a single member ensemble run with SPPT+SKEB enabled (model error only).
Need steps to process the data for metview - macro or grib tools?
Aim is to understand the impact of these different methods on the ensemble
(point out this is a case study and the correct approach would be to use more cases to get better statistics)
Experiments available:
Ensemble perturbations are applied in positive and negative pairs. For each perturbation computed, the initial fields are CNTL +/- PERT.
RMSE & CDF (needs explanation)
Discuss concept of ensemble reliability.
These will disappear in the final handout.
|
Retrieve data from MARS for all apart from the OpenIFS experiment the participants will run themselves.
Centre analysis at 28/10/15 12Z with +/- 3hr, 6hrs either side.
Question. How best to organise the experiments? Each user has an account or use one account with multiple directories? Linus suggested running a script that reorders the data to have 1 file with all ensemble members for each field of interest. |
Linus explained that with the OpenIFS runs will have differing amounts of uncertainty, so the spread should noticeably change for points near the track in the analysis. This is particularly because of (a) timing error between the analysis and the (b) ensemble tracks being more to the north of the analysis track. So Amsterdram for instance should see much less spread. |