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Towards operational predictions of the near-term climate

Author

Listed:
  • Yochanan Kushnir

    (Columbia University)

  • Adam A. Scaife

    (Met Office Hadley Centre for Climate Prediction and Research
    University of Exeter)

  • Raymond Arritt

    (Iowa State University)

  • Gianpaolo Balsamo

    (European Centre for Medium-range Weather Forecasts)

  • George Boer

    (Environment Canada and Climate Change)

  • Francisco Doblas-Reyes

    (Pg. Lluis Companys
    Barcelona Supercomputing Center)

  • Ed Hawkins

    (University of Reading)

  • Masahide Kimoto

    (University of Tokyo)

  • Rupa Kumar Kolli

    (World Meteorological Organization)

  • Arun Kumar

    (Climate Prediction Center)

  • Daniela Matei

    (Max Planck Institute for Meteorology)

  • Katja Matthes

    (GEOMAR Helmholtz Centre for Ocean Research Kiel
    Christian-Albrechts-Universität zu Kiel)

  • Wolfgang A. Müller

    (Max Planck Institute for Meteorology
    Deutscher Wetterdienst)

  • Terence O’Kane

    (CSIRO Oceans and Atmosphere)

  • Judith Perlwitz

    (University of Colorado
    NOAA/Earth System Research Laboratory)

  • Scott Power

    (Bureau of Meteorology)

  • Marilyn Raphael

    (University of California, Los Angeles)

  • Akihiko Shimpo

    (Japan Meteorological Agency)

  • Doug Smith

    (Met Office Hadley Centre for Climate Prediction and Research)

  • Matthias Tuma

    (WCRP/WMO)

  • Bo Wu

    (Chinese Academy of Sciences)

Abstract

Near-term climate predictions — which operate on annual to decadal timescales — offer benefits for climate adaptation and resilience, and are thus important for society. Although skilful near-term predictions are now possible, particularly when coupled models are initialized from the current climate state (most importantly from the ocean), several scientific challenges remain, including gaps in understanding and modelling the underlying physical mechanisms. This Perspective discusses how these challenges can be overcome, outlining concrete steps towards the provision of operational near-term climate predictions. Progress in this endeavour will bridge the gap between current seasonal forecasts and century-scale climate change projections, allowing a seamless climate service delivery chain to be established.

Suggested Citation

  • Yochanan Kushnir & Adam A. Scaife & Raymond Arritt & Gianpaolo Balsamo & George Boer & Francisco Doblas-Reyes & Ed Hawkins & Masahide Kimoto & Rupa Kumar Kolli & Arun Kumar & Daniela Matei & Katja Mat, 2019. "Towards operational predictions of the near-term climate," Nature Climate Change, Nature, vol. 9(2), pages 94-101, February.
    • Handle: RePEc:nat:natcli:v:9:y:2019:i:2:d:10.1038_s41558-018-0359-7
    DOI: 10.1038/s41558-018-0359-7
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    Cited by:

    1. Mark R. Payne & Gokhan Danabasoglu & Noel Keenlyside & Daniela Matei & Anna K. Miesner & Shuting Yang & Stephen G. Yeager, 2022. "Skilful decadal-scale prediction of fish habitat and distribution shifts," Nature Communications, Nature, vol. 13(1), pages 1-9, December.

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