Niño plumes

Niño plume charts show bias corrected ensemble member forecasts of the anomaly of sea-surface temperatures within defined El Niño regions of the Pacific Ocean.  This allows forecasters to assess consistency of the forecasts for the upcoming months, to see the strength of a forecast El Niño (or ENSO) event or La Niña event, and to use the spread of results as an indicator of confidence.


Fig8.3.4.1-1: Location of the Niño regions for measuring sea-surface temperature in the eastern and central tropical Pacific Ocean. 

 

Anomaly Plumes

Niño plumes are provided for forecasts starting on the first of every month.  The chart provides information on the predicted evolution of the sea surface temperature (SST) anomalies for four different pre-defined “El Niño Regions” over the coming seven months to give an indication of potential ENSO (El Niño - Southern oscillation).  

Fig8.3.4.1-2:  El Niño plume from 7 month SEAS5 ensemble forecast.  The plume shows bias-corrected ensemble member sea-surface temperature forecasts as an anomaly from climatological values (produced by ERA5) within the Niño Region 3.4 in the Pacific Ocean (red lines).  In this case almost  all ENS members show a steady increase in the sea surface temperature anomaly.  Just two or three members show a weaker rise.  A confident forecast of the onset of an El Niño event can be made.    Blue dots are previously observed values.


Niño annual plumes are provided for forecasts starting on 1 February, May, August and November.  For these dates, some ensemble members are continued to 13 months to give an outlook for ENSO (El Niño - Southern oscillation).

The chart provides information on the predicted evolution of the sea surface temperature (SST) anomalies for four different pre-defined “El Niño Regions” over the coming thirteen months.  

Fig8.3.4.1-3:  El Niño plume from 13 month (outlook) SEAS5 ensemble forecast.  The plume shows bias-corrected ensemble member sea-surface temperature forecasts as an anomaly from climatological values (produced by ERA5) within the Niño Region 3.4 in the Pacific Ocean (red lines).  In this case almost all ENS members show a steady increase in the sea surface temperature anomaly followed by steady fall.  Just two or three members show a weaker rise and subsequent fall in the anomaly while three members maintain the higher temperature anomaly with no indication of a fall .  A confident forecast of the onset of an El Niño event can be made followed fairly confidently of a weakening of El Niño later.    Blue dots are previously observed values.

Verification Plots

Verification plots for the Niño plumes and Niño annual plumes are also provided. They are updated with the forecast every month and show verification statistics for forecasts from 1993 to the previous year, starting in the specified month.  The charts summarise the evolution of forecast skill with time for the ensemble mean of forecasts made with the same calendar start month in previous years.

Root mean square errors

The diagram shows:

  • the Root Mean Square (RMS) sea surface temperature error of the ensemble (red line).
  • the spread of the RMS sea surface temperature error of the ensemble (red dashed line).
  • the error obtained by persisting the initial sea surface temperature anomaly (black dot-dashed line).  

This allows an assessment of the reliability of the width of the Niño plumes.  Comparison of the size of the spread with the forecast error shows the extent to which the forecast plume tends to be over- or under-dispersive.


Fig8.3.4.1-4: The sea surface temperature root mean square errors - 7 month SEAS5 forecast.

  

Fig8.3.4.1-5: The sea surface temperature root mean square errors - 13 month (outlook) SEAS5 forecast.  

Root mean square skill scores

The diagram shows the skill score:

  • of SEAS5 forecast of sea surface temperature (red line).
  • by persisting the initial anomaly (black dot-dashed line).

Inspection of the diagram:

  • indicates how much of the variation of observed sea surface temperature is being correctly forecast.
  • gives a sense of the lead time over which the forecast retains useful skill.

This gives an overall measure of the skill of the forecast (1 = perfect forecast , 0 = no better than climatology).

It shows how much of the variation of observed sea surface temperatures is being correctly forecast, and gives a sense of the lead time over which the forecast retains useful skill. 


Fig8.3.4.1-6: The sea surface temperature mean square skill scores - 7 month SEAS5 forecast.

 

Fig8.3.4.1-7: The sea surface temperature mean square skill scores - 13 month (outlook) SEAS5 forecast.  

Absolute error scores

The time series shows a time history of forecast errors for SEAS5 sea surface temperature forecasts starting at the given calendar month. 

  • Mean Absolute Error (MAE)  (plotted in red) is the absolute difference between the ensemble mean forecast, and the verification.
  • Best Absolute Error (BAE)  (plotted in pink) is the average across lead times of:
    • either zero (when the verification lies within the predicted range). Or
    • the absolute difference between the verification and the outer limits of the predicted range. 

For a perfect forecasting system, BAE will be near zero most of the time. 

The MAE and BAE time-series plots give a sense of how much variation there is in the errors.  They give some indication whether errors:

  • have tended to decrease with time
  • have tended to be associated with certain phases of ENSO.

Observation anomalies are also shown(plotted in grey).

This diagram complements the other scores, which are averaged across the whole of the re-forecast period.

These plots can be used to monitor whether:

  • there are any trends in forecast errors.
  • recent results are in line with expected sampling variations.


Fig8.3.4.1-8: Niño3.4 sea surface temperature absolute error time series - 7 months SEAS5 forecasts.


Fig8.3.4.1-9: Niño3.4 sea surface temperature absolute error time series - 13 months SEAS5 forecasts.


Anomaly amplitude ratio

This is the ratio of the amplitude of the sea surface temperature anomalies from the re-forecasts to the amplitude of the corresponding anomalies of the observations.

The anomaly amplitude ratio is calculated from individual members.  If the ratio is:

  • close to 1, the forecast anomalies have a realistic amplitude.
  •  >1, the forecast anomalies are greater than observed.
  •  <1, the forecast anomalies are less than observed.

This information should be used to interpret the Niño plumes appropriately.  It should be taken account of in interpreting the plume plots.  If at a certain time of year the model is known to overestimate the amplitude of ENSO variability then any anomaly it is predicting should be scaled appropriately.

The plots also show the amplitude ratio of an anomaly persistence forecast (black dashed line) – this differs from one because observed ENSO amplitudes vary according to the time of year.


Fig8.3.4.1-10: Niño3.4 Sea surface temperature anomaly amplitude ratio - 7 months SEAS5 forecasts.


Fig8.3.4.1-11: Niño3.4 Sea surface temperature anomaly amplitude ratio - 13 months SEAS5 forecasts.