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Related Concept Videos

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Climate refers to the prevailing weather conditions in a specific area over an extended period. As the saying goes, “Climate is what you expect. Weather is what you get.” Climate is influenced by geographic factors, such as latitude, terrain, and proximity to bodies of water.
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Temperature Response of Soil Organic Matter Decomposition Rates: Construction and Applications of a Temperature Gradient Block
07:46

Temperature Response of Soil Organic Matter Decomposition Rates: Construction and Applications of a Temperature Gradient Block

Published on: January 30, 2026

Identifying human influences on atmospheric temperature.

Benjamin D Santer1, Jeffrey F Painter, Carl A Mears

  • 1Program for Climate Model Diagnosis and Intercomparison (PCMDI), Lawrence Livermore National Laboratory, Livermore, CA 94550, USA. santer1@llnl.gov

Proceedings of the National Academy of Sciences of the United States of America
|December 1, 2012
PubMed
Summary
This summary is machine-generated.

Climate models show distinct temperature fingerprints in observations, with significant signal-to-noise ratios for stratospheric cooling and tropospheric warming. However, models often underestimate stratospheric cooling and overestimate tropospheric warming.

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Simulating Temperature in a Soil Incubation Experiment
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Last Updated: May 16, 2026

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Published on: October 28, 2022

Area of Science:

  • Climate Science
  • Atmospheric Physics
  • Climate Modeling

Background:

  • Detecting and attributing climate change requires distinguishing human-caused signals from natural climate variability.
  • Climate model intercomparison projects provide crucial data for understanding climate change drivers and patterns.

Purpose of the Study:

  • To perform a multimodel detection and attribution study of tropospheric and stratospheric temperature changes.
  • To quantify the strength of the climate change 'fingerprint' in observations relative to model-simulated natural variability.
  • To assess the ability of climate models to replicate observed temperature trends.

Main Methods:

  • Utilized output from 20 climate models from phase 5 of the Coupled Model Intercomparison Project.
  • Employed satellite-based measurements of tropospheric and stratospheric temperature change.
  • Calculated signal-to-noise (S/N) ratios to compare observed fingerprint strength with model-simulated noise.

Main Results:

  • High S/N ratios (26–36) were found for lower stratospheric temperature changes (1979–2011), indicating a strong fingerprint.
  • Significant S/N ratios (3–8) were observed for lower tropospheric temperature changes, significant at the 1% level.
  • Model fingerprints were identifiable in 70% of tropospheric temperature change tests, but models generally underestimated stratospheric cooling and overestimated tropospheric warming.

Conclusions:

  • The study successfully detected and attributed temperature changes in the troposphere and stratosphere using a multimodel approach.
  • While models capture large-scale patterns, biases exist in the magnitude of simulated temperature trends, particularly in the stratosphere.
  • Improving model treatment of stratospheric ozone depletion and volcanic aerosols may reduce biases in stratospheric temperature trends.