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Related Concept Videos

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Throughout its ~4.5 billion year history, the Earth has experienced periods of warming and cooling. However, the current drastic increase in global temperatures is well outside of the Earth’s cyclic norms, and evidence for human-caused global climate change is compelling. Paleoclimatology, the study of ancient climate conditions, provides ample evidence for human-caused global climate change by comparing recent conditions with those in the past.
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Random or indeterminate errors originate from various uncontrollable variables, such as variations in environmental conditions, instrument imperfections, or the inherent variability of the phenomena being measured. Usually, these errors cannot be predicted, estimated, or characterized because their direction and magnitude often vary in magnitude and direction even during consecutive measurements. As a result, they are difficult to eliminate. However, the aggregate effect of these errors can be...
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Animal organs and organ systems constantly adjust to internal and external changes through a process called homeostasis ("steady state"). Examples of these changes include regulation of the level of glucose or calcium in the blood or internal responses to external temperatures. Homeostasis requires  maintaining an internal dynamic equilibrium:
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Scientists always try their best to record measurements with the utmost accuracy and precision. However, sometimes errors do occur. These errors can be random or systematic. Random errors are observed due to the inconsistency or fluctuation in the measurement process, or variations in the quantity itself that is being measured. Such errors fluctuate from being greater than or less than the true value in repeated measurements. Consider a scientist measuring the length of an earthworm using a...
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Related Experiment Video

Updated: Apr 18, 2026

Simulating Temperature in a Soil Incubation Experiment
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Forcing, feedback and internal variability in global temperature trends.

Jochem Marotzke1, Piers M Forster2

  • 1Max Planck Institute for Meteorology, Bundesstrasse 53, 20146 Hamburg, Germany.

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|January 30, 2015
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Summary
This summary is machine-generated.

Climate models accurately simulate global warming trends, with discrepancies attributed to natural climate variability and variations in radiative forcings, not model biases.

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Area of Science:

  • Climate Science
  • Earth System Science
  • Atmospheric Science

Background:

  • Current climate models often project warming inconsistent with observed global-mean surface temperature (GMST) trends since 1998.
  • The reasons for this mismatch, including model forcing, response, or internal variability, remain debated.

Observation:

  • Analysis of GMST simulations and observations from 1900 to 2012 was conducted.
  • A multiple regression approach, grounded in surface energy balance, was employed to analyze trends.

Findings:

  • Simulated 15-year GMST trends show no systematic bias compared to observations.
  • Differences between simulated and observed trends are primarily driven by internal climate variability on shorter timescales and variations in radiative forcings on longer timescales.
  • Spread in simulated climate feedback does not significantly impact GMST trends or the discrepancies observed.

Implications:

  • The assertion that climate models systematically overestimate the response to greenhouse gas radiative forcing appears unfounded.
  • Understanding the role of internal variability and radiative forcing variations is crucial for reconciling model projections with observed climate change.