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More reliable coastal SST forecasts from the North American multimodel ensemble

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Abstract

The skill of monthly sea surface temperature (SST) anomaly predictions for large marine ecosystems (LMEs) in coastal regions of the United States and Canada is assessed using simulations from the climate models in the North American Multimodel Ensemble (NMME). The forecasts based on the full ensemble are generally more skillful than predictions from even the best single model. The improvement in skill is particularly noteworthy for probability forecasts that categorize SST anomalies into upper (warm) and lower (cold) terciles. The ensemble provides a better estimate of the full range of forecast values than any individual model, thereby correcting for the systematic over-confidence (under-dispersion) of predictions from an individual model. Probability forecasts, including tercile predictions from the NMME, are used frequently in seasonal forecasts for atmospheric variables and may have many uses in marine resource management.

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Acknowledgements

We thank the NOAA Climate Program Office (CPO) for providing funding for this research. DT was funded by a Special Early-Stage Exploration and Development grant from NOAA’s office of oceanic and atmospheric research (OAR) with additional support from NOAA’s National Marine Fisheries Service.

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Authors and Affiliations

  1. Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO, 80309, USA

    G. Hervieux

  2. NOAA Earth System Research Laboratory, Physical Sciences Division, 325 Broadway R/PSD1, Boulder, CO, 80305-3328, USA

    G. Hervieux & M. A. Alexander

  3. NOAA Geophysical Fluid Dynamics Laboratory, Princeton University Forrestal Campus, 201 Forrestal Road, Princeton, NJ, 08540-6649, USA

    C. A. Stock

  4. Institute of Marine Sciences, University of California, Santa Cruz, CA, 95064, USA

    M. G. Jacox

  5. NOAA Southwest Fisheries Science Center, Environmental Research Division, 99 Pacific St., Ste. 255A, Monterey, CA, 93940, USA

    M. G. Jacox

  6. Department of Atmospheric, Oceanic and Earth Sciences, George Mason University, 4400 University Drive, MS6C5, Fairfax, VA, 22030, USA

    K. Pegion

  7. NOAA/Climate Prediction Center and INNOVIM LLC, 5830 University Research Court, College Park, MD, 20740, USA

    E. Becker

  8. NCAR/Climate and Global Dynamics, 1850 Table Mesa Drive, Boulder, CO, 80305, USA

    F. Castruccio

  9. Atmospheric and Oceanic Sciences Program, Princeton University, 300 Forrestal Road, Sayre Hall, Princeton, NJ, 08544, USA

    D. Tommasi

Authors
  1. G. Hervieux
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  2. M. A. Alexander
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  4. M. G. Jacox
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  5. K. Pegion
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  6. E. Becker
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  7. F. Castruccio
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  8. D. Tommasi
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Corresponding author

Correspondence to G. Hervieux.

Additional information

This paper is a contribution to the special collection on the North American Multi-Model Ensemble (NMME) seasonal prediction experiment. The special collection focuses on documenting the use of the NMME system database for research ranging from predictability studies, to multi-model prediction evaluation and diagnostics, to emerging applications of climate predictability for subseasonal to seasonal predictions.This special issue is coordinated by Annarita Mariotti (NOAA), Heather Archambault (NOAA), Jin Huang (NOAA), Ben Kirtman (University of Miami) and Gabriele Villarini (University of Iowa).

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Hervieux, G., Alexander, M.A., Stock, C.A. et al. More reliable coastal SST forecasts from the North American multimodel ensemble. Clim Dyn 53, 7153–7168 (2019). https://doi.org/10.1007/s00382-017-3652-7

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