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Area of Science:

  • Climate Science
  • Atmospheric Science
  • Global Warming Research

Background:

  • Assessing climate model reliability often relies on simulating current climate, but direct links to future projections are debated.
  • Greenhouse gas (GHG)-induced climate change may involve processes not critical for present-day climate simulation.

Purpose of the Study:

  • To investigate the relationship between present-day climate variability and projected future climate change.
  • To determine if models simulating current climate variability accurately predict future warming patterns.

Main Methods:

  • Analyzed spatial patterns of GHG-induced warming in 21st-century climate models.
  • Correlated these patterns with year-to-year surface air temperature variations (1950-1979).
  • Examined relationships in other climate fields (e.g., water vapor) and observed temperature data (1950-2010).

Main Results:

  • A strong correlation exists between areas of high year-to-year temperature variation today and greater projected GHG-induced warming.
  • This relationship holds across multiple climate models and for other climate variables like atmospheric water vapor.
  • The observed temperature record from 1950-2010 supports this correlation.

Conclusions:

  • Physical processes influencing current climate variability may also drive long-term 21st-century climate change.
  • Models demonstrating better simulation of present-day climate variability are likely more reliable for future climate change predictions.
  • This finding provides a stronger basis for using current climate simulation performance to validate climate models.