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Stochastic contributions to global temperature changes
1Department of Physics, Yale University, PO Box 208121, New Haven, Connecticut 06520-8121, USA.
Physical Review Letters
|June 4, 2008
Summary
Global surface temperatures from 1850-1970 followed a random walk, influenced by prior years. Rising carbon dioxide levels since 1890 explain current temperature variations, challenging complex climate models.
Area of Science:
- Climate Science
- Environmental Science
- Statistical Modeling
Background:
- Historical global surface temperature records (1850-1970) exhibit patterns suggesting correlation with preceding years.
- Previous analyses have explored various models to explain temperature fluctuations.
Purpose of the Study:
- To model global surface temperatures using a simplified statistical approach.
- To investigate the relationship between historical temperatures and carbon dioxide concentrations.
- To evaluate the statistical validity of complex climate models against observed data.
Main Methods:
- Analysis of mean annual global surface temperatures from 1850 to 1970.
- Application of a one-dimensional random walk model with limiting feedback.
- Correlation of temperature variations with the increase in carbon dioxide concentration above 1890 levels.
Main Results:
- The one-dimensional random walk model with limiting feedback accurately describes temperature variations from 1850 to 1970.
- A base temperature proportional to the increase in carbon dioxide concentration over 1890 levels accounts for observed temperature variations.
- Climate models offering a better fit to observed variations are statistically improbable.
Conclusions:
- A simple statistical model, incorporating carbon dioxide increases, effectively explains global temperature trends.
- Complex climate models may be statistically improbable and potentially represent artifacts rather than accurate representations of climate dynamics.
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