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Model Verification Charts


Billabong

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I can infer the higher the numbers, the better the performance.... but can someone give a good explanation on how to properly read these verification charts and what the numbers mean? Also, what model are the blue plots from?

Lastly, does anyone have the link to the main page for these charts?

Thanks in advance!

2s10pbn.png

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The charts are showing the correlation of the respective modeled anomalies to a 30-year climo anomalies (1959-1988) for the specific variable selected. In this case, H5. Basically, how well the model did outside of the climo mean. The FNO is the NOGAPS.

These two pages have the charts and more info...

http://www.emc.ncep....TATS/STATS.html

http://www.emc.ncep....gmb/STATS_vsdb/

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To add a little to that... an anomaly correlation coefficient (ACC) greater than 0.6 is usually considered skillful. This idea came around when the ECMWF started looking at ACC and they determined that the number which separated subjectively good forecasts vs. bad forecasts was 0.6.

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The charts are showing the correlation of the respective modeled anomalies to a 30-year climo anomalies (1959-1988) for the specific variable selected. In this case, H5. Basically, how well the model did outside of the climo mean. The FNO is the NOGAPS.

These two pages have the charts and more info...

http://www.emc.ncep....TATS/STATS.html

http://www.emc.ncep....gmb/STATS_vsdb/

Also, note that the figures/numbers from the old (first) website and second ("vsdb") are not the same. The newer site (which we have going back to 2006) uses the actual 30 year climo (the old statistics do not) from reanalysis as well as unfiltered/untruncated forecast output. There is a powerpoint linked from the first URL above that describes how the methodology has been update from the old to new method/webpage.

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It's also important to note that this is not a perfect measurement of verification. Nothing is. The ACC rewards spatial similarities more than value similarities, which leads to higher scores when the flow is amplified (waves).

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It's also important to note that this is not a perfect measurement of verification. Nothing is. The ACC rewards spatial similarities more than value similarities, which leads to higher scores when the flow is amplified (waves).

Haha...yeah that'd be impossible.

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