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Envisioning U.S. Climate Predictions and Projections to Meet New Challenges
  • +9
  • Annarita Mariotti,
  • David Craig Bader,
  • Susanne E. Bauer,
  • Gokhan Danabasoglu,
  • John P. Patrick Dunne,
  • Brian Gross,
  • L. Ruby Leung,
  • Steven Pawson,
  • William M Putman,
  • V Ramaswamy,
  • Gavin A. Schmidt,
  • Vijay Tallapragada
Annarita Mariotti
National Oceanic and Atmospheric Administration (NOAA)

Corresponding Author:[email protected]

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David Craig Bader
Lawrence Livermore National Laboratory
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Susanne E. Bauer
NASA Goddard Institute for Space Studies, New York, NY, USA
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Gokhan Danabasoglu
National Center for Atmospheric Research (NCAR)
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John P. Patrick Dunne
Geophysical Fluid Dynamics Laboratory
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Brian Gross
Environmental Modeling Center
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L. Ruby Leung
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Steven Pawson
NASA Goddard Space Flight Center
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William M Putman
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V Ramaswamy
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Gavin A. Schmidt
NASA Goddard Institute for Space Studies
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Vijay Tallapragada
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In the face of a changing climate, the understanding, predictions and projections of natural and human systems are increasingly crucial to prepare and cope with extremes and cascading hazards, determine unexpected feedbacks and potential tipping points, inform long-term adaptation strategies, and guide mitigation approaches. Increasingly complex socio-economic systems require enhanced predictive information to support advanced practices. Such new predictive challenges drive the need to fully capitalize on ambitious scientific and technological opportunities. These include the unrealized potential for very high-resolution modeling of global-to-local Earth system processes across timescales, a reduction of model biases, enhanced integration of human systems and the Earth Systems, better quantification of predictability and uncertainties; expedited science-to-service pathways and co-production of actionable information with stakeholders. Enabling technological opportunities include exascale computing, advanced data storage, novel observations and powerful data analytics, including artificial intelligence and machine learning. Looking to generate community discussions on how to accelerate progress on U.S. climate predictions and projections, representatives of Federally-funded U.S. modeling groups outline here perspectives on a six-pillar national approach grounded in climate science that builds on the strengths of the U.S. modeling community and agency goals. This calls for an unprecedented level of coordination to capitalize on transformative opportunities, augmenting and complementing current modeling center capabilities and plans to support agency missions. Tangible outcomes include projections with horizontal spatial resolutions finer than 10 km, representing extremes and associated risks in greater detail, reduced model errors, better predictability estimates, and more customized projections to support the next generation of climate services.
03 Nov 2023Submitted to ESS Open Archive
08 Nov 2023Published in ESS Open Archive