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Niño plumes

Niño Nino 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.

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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

Nino 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).  

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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 Nino Niño event can be made.    Blue dots are previously observed values.

Nino 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).

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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 Nino Niño event can be made followed fairly confidently of a weakening of El Nino Niño later.    Blue dots are previously observed values.

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Verification plots for the Nino Niño plumes and Nino 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.

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This allows an assessment of the reliability of the width of the NINO 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.

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

Fig8.3.4.1-8: NINO3 Niño3.4 sea surface temperature absolute error time series - 7 months SEAS5 forecasts.

Fig8.3.4.1-9: NINO3Niño3.4 sea surface temperature absolute error time series - 13 months SEAS5 forecasts.

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This information should be used to interpret the Nino 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: NINO3Niño3.4 Sea surface temperature anomaly amplitude ratio - 7 months SEAS5 forecasts.

Fig8.3.4.1-11: NINO3Niño3.4 Sea surface temperature anomaly amplitude ratio - 13 months SEAS5 forecasts.

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