Strength Outlooks for the El Niño–Southern Oscillation

Michelle L. L’Heureux NOAA/NWS/NCEP/Climate Prediction Center, College Park, Maryland

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Michael K. Tippett Department of Applied Physics and Applied Mathematics, Columbia University, New York, New York

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Ken Takahashi Servicio Nacional de Meteorología e Hidrología del Perú, Instituto Geofísico del Perú, Lima, Peru

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Anthony G. Barnston International Research Institute for Climate and Society, Columbia University, New York, New York

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Emily J. Becker NOAA/NWS/NCEP/Climate Prediction Center, College Park, Maryland
Innovim, College Park, Maryland

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Gerald D. Bell NOAA/NWS/NCEP/Climate Prediction Center, College Park, Maryland

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Tom E. Di Liberto NOAA/Climate Program Office, Silver Spring, Maryland
CollabraLink Technologies, Silver Spring, Maryland

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Jon Gottschalck NOAA/NWS/NCEP/Climate Prediction Center, College Park, Maryland

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Michael S. Halpert NOAA/NWS/NCEP/Climate Prediction Center, College Park, Maryland

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Zeng-Zhen Hu NOAA/NWS/NCEP/Climate Prediction Center, College Park, Maryland

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Nathaniel C. Johnson NOAA/Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey
Atmospheric and Oceanic Sciences Program, Princeton University, Princeton, New Jersey

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Yan Xue NOAA/NWS/NCEP/Climate Prediction Center, College Park, Maryland

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Wanqiu Wang NOAA/NWS/NCEP/Climate Prediction Center, College Park, Maryland

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Abstract

Three strategies for creating probabilistic forecast outlooks for El Niño–Southern Oscillation (ENSO) are compared. One is subjective and is currently used by the NOAA/Climate Prediction Center (CPC) to produce official ENSO outlooks. A second is purely objective and is based on the North American Multimodel Ensemble (NMME). A new third strategy is proposed in which the forecaster only provides the expected value of the Niño-3.4 index, and then categorical probabilities are objectively determined based on past skill. The new strategy results in more confident probabilities compared to the subjective approach and higher verification scores, while avoiding the significant forecast busts that sometimes afflict the NMME-based objective approach. The higher verification scores of the new strategy appear to result from the added value that forecasters provide in predicting the mean, combined with more reliable representations of uncertainty, which is difficult to represent because forecasters often assume less confidence than is justified. Moreover, the new approach can produce higher-resolution probabilistic forecasts that include ENSO strength information and that are difficult, if not impossible, for forecasters to produce. To illustrate, a nine-category ENSO outlook based on the new strategy is assessed and found to be skillful. The new approach can be applied to other outlooks where users desire higher-resolution probabilistic forecasts, including the extremes.

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/WAF-D-18-0126.s1.

© 2019 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Michelle L’Heureux, michelle.lheureux@noaa.gov

Abstract

Three strategies for creating probabilistic forecast outlooks for El Niño–Southern Oscillation (ENSO) are compared. One is subjective and is currently used by the NOAA/Climate Prediction Center (CPC) to produce official ENSO outlooks. A second is purely objective and is based on the North American Multimodel Ensemble (NMME). A new third strategy is proposed in which the forecaster only provides the expected value of the Niño-3.4 index, and then categorical probabilities are objectively determined based on past skill. The new strategy results in more confident probabilities compared to the subjective approach and higher verification scores, while avoiding the significant forecast busts that sometimes afflict the NMME-based objective approach. The higher verification scores of the new strategy appear to result from the added value that forecasters provide in predicting the mean, combined with more reliable representations of uncertainty, which is difficult to represent because forecasters often assume less confidence than is justified. Moreover, the new approach can produce higher-resolution probabilistic forecasts that include ENSO strength information and that are difficult, if not impossible, for forecasters to produce. To illustrate, a nine-category ENSO outlook based on the new strategy is assessed and found to be skillful. The new approach can be applied to other outlooks where users desire higher-resolution probabilistic forecasts, including the extremes.

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/WAF-D-18-0126.s1.

© 2019 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Michelle L’Heureux, michelle.lheureux@noaa.gov

Supplementary Materials

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