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This completes the first exercise. You have now learnt how to use the key macros, alter fields for plotting and animate fields. The next exercises use similar macros. |
Exercise 2: The operational HRES forecast
Recap
The ECMWF operational deterministic forecast is called HRES. At the time of this case study, the model ran with a spectral resolution of T1279, equivalent to 16km grid spacing.
Only a single forecast is run at this resolution as the computational resources required are demanding. The ensemble forecasts are run at a lower resolution.
Before looking at the ensemble forecasts, first understand the performance of the operational HRES forecast of the time.
Available forecast
Data is provided for a single forecast starting from 20th Sept 2012, as used in the paper by Pantillon et al.
HRES data is provided at the same resolution as the operational model, in order to give the best representation of the Hurricane and cut-off low interations.
Questions
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Available plot types
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For this exercise, you will use the metview icons in the row labelled 'HRES forecast' as shown above. hres_rmse.mv : this plots the root-mean-square-error growth curves for the operational HRES forecast for the different lead times.
hres_to_an_diff.mv : this plots a single parameter as a difference between the operational HRES forecast and the ECMWF analysis. Use this to understand the forecast errors from the different lead times.
Parameters & map appearance. These macros have the same choice of parameters to plot and same choice of |
Getting started
Task 1: Forecast error
In this task, we'll look at the difference between the forecast and the analysis by using "root-mean-square error" curves as a way of summarising the performance of the forecast. Root-mean square error curves are a standard measure to determine forecast error compared to the analysis and several of the exercises will use them.
Using the hres_rmse.mv icon, right-click, select 'Edit' and plot the RMSE curves for MSLP (mean-sea-level pressure). Repeat for the 10m wind-gust parameter wgust10.
Repeat for both geographical regions: mapType=0 and mapType=1.
Q. What do the RMSE curves show?
Task 2: Compare forecast to analysis
a) Use the hres_to_an_runs.mv icon (right-click -> Edit) and plot the MSLP and wind fields. This shows a comparison of 3 of the 4 forecasts to the analysis (the macro can be edited to change the choice of forecasts).
b) Use the hres_to_an_diff.mv icon and plot the difference map between a forecast date and the analysis.
We suggest looking at only one forecast lead-time (run) but when working in teams, different members of the team could choose a different forecast.
If you want to change the default date, edit the following line:
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#Model run
run=2013-10-24 |
Task 3: Team working
As a team, discuss the plots & parameters to address the questions above given what you see in the error growth curves and maps from task 2.
Look at the difference between forecast and analysis to understand the error in the forecast, particularly the starting formation and final error.
Team members can limit to a certain date and choose particular parameters for team discussion.
Remember to save (or print) plots of interest for later group discussion.
- Plot and animate MSL + 500hPa maps showing track of Nadine
> 1 : Nadine MSLP and T2m (or better SST) tracking 15-20 september
> 2 : Satellite views on the 20th (provided by Etienne, if possible to put on the VM)
> 3 : Studying of the horizontal maps (analysis + forecasts)
> 4 : Studying and building of the vertical x-sections (analysis + forecasts)
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