Predictability and skill of boreal winter forecasts made with the ECMWF Seasonal Forecasting System II

The performance of boreal winter forecasts made with the European Centre for Medium‐Range Weather Forecasts (ECMWF) System II Seasonal Forecasting System is investigated through analyses of ensemble hindcasts for the period 1987–2001. The predictability, or signal‐to‐noise ratio, associated with the...

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Published in:Quarterly journal of the Royal Meteorological Society Vol. 132; no. 619; pp. 2031 - 2053
Main Authors: George, S. E., Sutton, R. T.
Format: Journal Article
Language:English
Published: Chichester, UK John Wiley & Sons, Ltd 01-07-2006
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Abstract The performance of boreal winter forecasts made with the European Centre for Medium‐Range Weather Forecasts (ECMWF) System II Seasonal Forecasting System is investigated through analyses of ensemble hindcasts for the period 1987–2001. The predictability, or signal‐to‐noise ratio, associated with the forecasts, and the forecast skill are examined. On average, forecasts of 500 hPa geopotential height (GPH) have skill in most of the Tropics and in a few regions of the extratropics. There is broad, but not perfect, agreement between regions of high predictability and regions of high skill. However, model errors are also identified, in particular regions where the forecast ensemble spread appears too small. For individual winters the information provided by t‐values, a simple measure of the forecast signal‐to‐noise ratio, is investigated. For 2 m surface air temperature (T2m), highest t‐values are found in the Tropics but there is considerable interannual variability, and in the tropical Atlantic and Indian basins this variability is not directly tied to the El Niño Southern Oscillation. For GPH there is also large interannual variability in t‐values, but these variations cannot easily be predicted from the strength of the tropical sea‐surface‐temperature anomalies. It is argued that the t‐values for 500 hPa GPH can give valuable insight into the oceanic forcing of the atmosphere that generates predictable signals in the model. Consequently, t‐values may be a useful tool for understanding, at a mechanistic level, forecast successes and failures. Lastly, the extent to which t‐values are useful as a predictor of forecast skill is investigated. For T2m, t‐values provide a useful predictor of forecast skill in both the Tropics and extratropics. Except in the equatorial east Pacific, most of the information in t‐values is associated with interannual variability of the ensemble‐mean forecast rather than interannual variability of the ensemble spread. For GPH, however, t‐values provide a useful predictor of forecast skill only in the tropical Pacific region. Copyright © 2006 Royal Meteorological Society
AbstractList The performance of boreal winter forecasts made with the European Centre for Medium-Range Weather Forecasts (ECMWF) System II Seasonal Forecasting System is investigated through analyses of ensemble hindcasts for the period 1987-2001. The predictability, or signal-to-noise ratio, associated with the forecasts, and the forecast skill are examined. On average, forecasts of 500 hPa geopotential height (GPH) have skill in most of the Tropics and in a few regions of the extratropics. There is broad, but not perfect, agreement between regions of high predictability and regions of high skill. However, model errors are also identified, in particular regions where the forecast ensemble spread appears too small. For individual winters the information provided by t-values, a simple measure of the forecast signal-to-noise ratio, is investigated. For 2 m surface air temperature (T2m), highest t-values are found in the Tropics but there is considerable interannual variability, and in the tropical Atlantic and Indian basins this variability is not directly tied to the el Nino Southern Oscillation. For GPH there is also large interannual variability in t- values, but these variations cannot easily be predicted from the strength of the tropical sea-surface-temperature anomalies. It is argued that the t-values for 500 hPa GPH can give valuable insight into the oceanic forcing of the atmosphere that generates predictable signals in the model. Consequently, t- values may be a useful tool for understanding, at a mechanistic level, forecast successes and failures. Lastly, the extent to which t-values are useful as a predictor of forecast skill is investigated. For T2m, t-values provide a useful predictor of forecast skill in both the Tropics and extratropics. Except in the equatorial east Pacific, most of the information in t-values is associated with interannual variability of the ensemble-mean forecast rather than interannual variability of the ensemble spread. For GPH, however, t- values provide a useful predictor of forecast skill only in the tropical Pacific region. Copyright 2006 Royal Meteorological Society
The performance of boreal winter forecasts made with the European Centre for Medium‐Range Weather Forecasts (ECMWF) System II Seasonal Forecasting System is investigated through analyses of ensemble hindcasts for the period 1987–2001. The predictability, or signal‐to‐noise ratio, associated with the forecasts, and the forecast skill are examined. On average, forecasts of 500 hPa geopotential height (GPH) have skill in most of the Tropics and in a few regions of the extratropics. There is broad, but not perfect, agreement between regions of high predictability and regions of high skill. However, model errors are also identified, in particular regions where the forecast ensemble spread appears too small. For individual winters the information provided by t‐values, a simple measure of the forecast signal‐to‐noise ratio, is investigated. For 2 m surface air temperature (T2m), highest t‐values are found in the Tropics but there is considerable interannual variability, and in the tropical Atlantic and Indian basins this variability is not directly tied to the El Niño Southern Oscillation. For GPH there is also large interannual variability in t‐values, but these variations cannot easily be predicted from the strength of the tropical sea‐surface‐temperature anomalies. It is argued that the t‐values for 500 hPa GPH can give valuable insight into the oceanic forcing of the atmosphere that generates predictable signals in the model. Consequently, t‐values may be a useful tool for understanding, at a mechanistic level, forecast successes and failures. Lastly, the extent to which t‐values are useful as a predictor of forecast skill is investigated. For T2m, t‐values provide a useful predictor of forecast skill in both the Tropics and extratropics. Except in the equatorial east Pacific, most of the information in t‐values is associated with interannual variability of the ensemble‐mean forecast rather than interannual variability of the ensemble spread. For GPH, however, t‐values provide a useful predictor of forecast skill only in the tropical Pacific region. Copyright © 2006 Royal Meteorological Society
Author George, S. E.
Sutton, R. T.
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Cites_doi 10.1175/BAMS-84-12-1783
10.1126/science.289.5477.270
10.1016/0079-6611(91)90009-B
10.1175/1520-0477(2000)081<2593:DSP>2.3.CO;2
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10.1029/2003JD004151
10.1038/32861
10.1175/1520-0442(2003)016<3629:POTSMA>2.0.CO;2
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Issue 619
Keywords Ensemble simulation
Seasonal forecast
Coupled model
Weather forecast
Geopotential height
Predictor
Surface temperature
Verification
Interannual variation
Atmospheric temperature
Winter
Northern Hemisphere
Predictability
Forecast skill
signal-to-noise ratio
Language English
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Snippet The performance of boreal winter forecasts made with the European Centre for Medium‐Range Weather Forecasts (ECMWF) System II Seasonal Forecasting System is...
The performance of boreal winter forecasts made with the European Centre for Medium-Range Weather Forecasts (ECMWF) System II Seasonal Forecasting System is...
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SubjectTerms Coupled model
Earth, ocean, space
Exact sciences and technology
External geophysics
Meteorology
Signal‐to‐noise ratio
Verification
Weather analysis and prediction
Title Predictability and skill of boreal winter forecasts made with the ECMWF Seasonal Forecasting System II
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