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Each CDF plot displays the latest forecast along with the sub-seasonal range model climate (https://confluence.ecmwf.int/display/FUG/Section+5.3.2+SUBS-M-Climate%2C+the+sub-seasonal+model+climateClimate) corresponding to it, and also all previous sub-seasonal range ensemble forecasts valid for the same 7-day period. The following percentiles are used to draw both SUBS-M-Climate and ensemble forecast CDFs: 0 (minimum), 1, 2, 5, 10, 25, 50 (median), 75, 90, 95, 98, 99 and 100 (maximum). For the forecasts, which have far fewer realisations than the SUBS-M-Climate, percentiles 0, 1 and 2 all take the same value, as do 98, 99 and 100.

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Example of Temperature CDFs: Upper tail positive SOT

Fig8.2.4-7:  The large positive EFI shows the ensemble temperature anomaly distribution is for warmer anomalies much above the CDF of the ensemble forecasts (red curve) lies to the right of the  SUBS-M-Climate anomaly distribution .  The (black curve).  The ensemble temperature anomaly distribution shows warm anomalies.  The area between the lines shows a large positive EFI.  The positive upper tail SOT (quantile 90) indicates there are several ensemble members predicting with an extreme warm temperature anomalies (anomaly above the 99th SUBS-M-Climate percentile shown by the (dashed green line).  This suggests a warm temperature anomaly may be confidently forecast  

The diagram implies a confident forecast of a warm (large positive EFI), probably exceptional but not necessarily extreme (SOT positive ~ +0.4).  Confidence ) but not necessarily extreme temperature anomaly, compared with SUBS-M-Climate.  Confidence in extreme temperatures rises as SOT values increase - users should focus on SOT values >0.5.

Example of Temperature CDFs: Upper tail positive SOT

Fig8.2.4-8: The large positive EFI shows the ensemble temperature anomaly distribution is for warmer anomalies much above the CDF of the ensemble forecasts (red curve) lies to the right of the  SUBS-M-Climate anomaly distribution (black curve).  The negative upper tail SOT (quantile 90) indicates generally ensemble members are not predicting an extreme temperature anomaly (temperature anomaly distribution shows warm anomalies.  The area between the lines shows a large positive EFI.  The negative upper tail SOT (quantile 90) indicates generally ensemble members are not predicting an extreme temperature anomaly above the 99th SUBS-M-Climate percentile shown by the (dashed green line) - however.  Note, note one ensemble member (extreme top end of red curve) is predicting predicts an extreme temperature anomaly (above the 99th SUBS-M-Climate percentile) though .  However, it is less extreme than the extreme of SUBS-M-Climate anomaly .   This suggests a warm temperature anomaly is confidently forecast (extreme top end of black curve).   

The diagram implies a confident forecast of a warm (fairly large positive EFI), but will be unexceptional (SOT –0negative ~ -0.7) temperature anomaly, compared with SUBS-M-Climate - but nevertheless .  However, one member does suggest suggests a possible near exceptional warm anomaly is possible.

Example of Temperature CDFs: Lower tail negative SOT

Fig8.2.4-9:The small positive EFI suggests the frequencies of ensemble temperature anomaly distribution is near or a little above the CDF of the ensemble forecasts (red curve) lies partly to the right and partly to the left of the  SUBS-M-Climate anomaly distribution (black curve).  The ensemble temperature anomaly distribution .  The shows varying anomalies.  The area between the lines shows only a small EFI.  The negative lower tail SOT (quantile 10) indicates generally ensemble members are not predicting an extreme temperature anomaly ( below the 1st SUBS-M-Climate percentile shown by the (dashed green line) - however note .  Note, one ensemble member (extreme bottom lower end of red red curve)  is predicting predicts an extreme temperature anomaly (below the 1st SUBS-M-climate Climate percentile) though .  However, it is less extreme than the extreme of SUBS-M-Climate anomaly .   This suggests (extreme lower end of black curve).   

The diagram implies the temperature anomalies are similar to the SUBS-M-Climate anomaly distribution Climate (small positive/negative EFI), and a cold anomaly, if it occurs, will  be unexceptional but unexceptional (SOT negative ~ -1.7) temperature anomaly, compared with SUBS-M-Climate (SOT –1.7) - but nevertheless one member does suggest an .  However, one member suggests a possible near exceptional cold anomaly is possible.

A similar CDF diagram would be obtained at Nizhniy at Nizhniy Novgorod in Fig8.2.4-6 above.

Example of Temperature CDFs: Lower tail negative SOT

Fig8.2.4-10:  The large negative EFI shows the frequencies of ensemble temperature anomaly distribution is for colder anomalies well below the CDF of the ensemble forecasts (red curve) lies to the left of the  SUBS-M-Climate anomaly distribution (black curve).  The positive lower tail SOT (quantile 10)  indicates there are several ensemble members predicting extreme cold temperature anomalies (ensemble temperature anomaly distribution shows cold anomalies.  The area between the lines shows a large negative EFI.  The positive lower tail SOT (quantile 10) indicates there are several ensemble members with an extreme temperature anomaly below the 1st SUBS-M-Climate percentile shown by the (dashed green line).    This suggests a cold temperature anomaly may be confidently forecast

The diagram implies a confident forecast of a cold (large negative EFI), exceptional and probably extreme (SOT positive ~ +0.95), compared with SUBS-M-Climate.  Confidence in extreme temperatures rises as SOT values increase - users should focus on SOT values >0.5.

A similar CDF diagram would be obtained at Nizhniy at Nizhniy Novgorod in Fig8.2.4-5 above.

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Fig8.2.4-11: An example CDF for snowfall - snowfall is just considered as equivalent rainfall.   

CDF of the ensemble anomaly forecasts (red curve) lies to the right of the  SUBS-M-Climate anomaly distribution (black curve).  The ensemble rainfall anomaly distribution shows anomalies greater than SUBS-M-Climate anomaly distribution.  The area between the lines shows a large positive EFI.  The positive upper tail SOT (quantile 90) indicates there are several ensemble members with an st of a warm (large positive EFI), probably exceptional (SOT positive ~ +0.4)) but not necessarily extreme temperature anomaly, compared with SUBS-M-Climate.  Confidence in extreme temperatures rises as SOT values increase - users should focus on SOT values >0.5.

Moderately large positive EFI shows the equivalent rainfall Moderately large positive EFI shows the equivalent rainfall anomaly distribution is above the SUBS-M-Climate anomaly distribution.  The positive upper tail SOT (quantile 90) indicates there are several ensemble members predicting extreme equivalent rainfall anomalies (above the 99th SUBS-M-Climate percentile shown by the dashed green line).  This suggests uncertainty that a significant equivalent rainfall anomaly is forecast (moderate EFI.  Note: 50% of ensemble members forecast less than about 1mm precipitation (the lower part of the SUBS-M-Climate only just above 0mm), but equally 25% of ensemble members forecast more than about 2mm precipitation (significantly above SUBS-M-Climate where about 97% of precipitation less than 2mm). If a significant rainfall occurs it could be an exceptional rainfall equivalent (SOT 0.8).  Confidence in extreme rainfall rises as SOT values increase - users should focus on SOT values >0.5.

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