Over the weekend I made some substantial changes to my GEFS maps. They are listed below in list form for your convenience.
1. The maps are now much bigger.
2. The entire page has been re-designed, hopefully it’s easier to use. There is a new menu navigation system. You can still get to it by going to: www.KyleMacRitchie.com/gefs . Please send me an e-mail if you have comments or questions!
3. I made the climo line on the spaghetti plots darker. Hopefully it helps.
4. New height anomalies! Instead of only shading spread, you can now view shaded height anomalies from climatology. Standardized versions of these maps will be available very soon.
5. Projection changes: Indian Ocean view expanded below Equator and North Atlantic view has been zoomed out and renamed to just “Atlantic”.
Information about the spread maps (From old post)
I’ve made some more tweaks to the GFS ensembles. Firstly, I’ve added an “Asia” domain to help out some viewers from that region. Secondly, I’ve added a new type of standardized anomalies that use sigma values instead of percentiles.
The new anomalies are created by assuming that the ensemble spread data follows a lognormal distribution. This isn’t really as fancy as it seems, it just means that when one takes the log of the data, it appears more normally distributed. The standardized anomalies are created by:
1. Obtain ensemble spread for each forecast time for each day from 1985 through 2010.
2. Take the natural log of these data.
3. Calculate the long term mean and first four harmonics of the seasonal cycle for each gridpoint at each forecast time over the climatology.
4. Use the climo data from (3) to create the standardized anomalies using typical z-score techniques: z = log(ens_spread) – (mean + seasonal cycle) / standard_deviation(seasonal cycle).
This allows us to take into account the fact that ensemble spread changes quite a bit throughout the year. It is important to note that these new maps don’t necessarily show new information that is not on the percentile maps, rather they show the same thing in a different way. It’s a matter of personal preference, but I think a lot of us, myself included, are used to looking at sigma anomalies over percentiles.
Because these are approximately normally distributed, you can apply your familiar 68-95-99.7 rules from statistics.
For each tail the corresponding percentages are, approximately:
1 sigma = 15.8% of the data lie above/below this.
2 sigma = 2.2% of the data lie above/below this.
3 sigma = 0.1% of the date lie above/below this.
Hopefully you can all choose your poison! I’ve updated the /gefs link to now go to the sigma plots, but the percentile plots will still be around and updated at the same time. Enjoy!
Information about Spaghetti Plots (from old post)
I have updated the GEFS spaghetti plots to show more information. There is now a solid black line, labeled, that shows the ensemble mean position for each of the three contour levels. There is also a colored line, labeled, which shows the climatological position of the contour level (Note: this is accurate to within +/- 12 hours since my climatology is daily. Luckily, height climos don’t change much in 12 hours.).