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Updated: Nov 23, 2025
09:55
Surface Renewal: An Advanced Micrometeorological Method for Measuring and Processing Field-Scale Energy Flux Density Data
Published on: December 12, 2013
9.0K
Analysis of 20th century surface air temperature using linear dynamical modes.
A Gavrilov1, S Kravtsov1, D Mukhin1
1Institute of Applied Physics, Russian Academy of Sciences, 46 Ulyanov Str., Nizhny Novgorod 603950, Russia.
Chaos (Woodbury, N.Y.)
|December 31, 2020
Summary
A Bayesian method identified five climate variability modes in surface air temperature (SAT) data. These modes, including multidecadal and El Niño-Southern Oscillation related patterns, help explain climate signals missing in models.
Area of Science:
- Climate Science
- Atmospheric Science
- Data Analysis
Background:
- Observed surface air temperature (SAT) data contains complex variability.
- Climate models often struggle to capture all aspects of observed climate signals.
- Understanding internal climate variability is crucial for accurate climate projections.
Purpose of the Study:
- To apply a Bayesian Linear Dynamical Mode (LDM) decomposition to observed SAT data.
- To identify and characterize modes of internal climate variability.
- To incorporate the forced climate response into the decomposition for improved optimality.
Main Methods:
- Bayesian Linear Dynamical Mode (LDM) decomposition.
- Incorporation of forced climate response estimated from climate model simulations.
- Analysis of surface air temperature (SAT) field variability.
Main Results:
- Identified five distinct LDMs of internal climate variability.
- Three modes exhibit multidecadal scales, two are linked to El Niño-Southern Oscillation (ENSO).
- These modes contribute to a secular climate signal (global stadium wave) absent in climate models.
Conclusions:
- The identified LDMs, including Atlantic Multidecadal Oscillation, explain significant SAT variability.
- Secular climate modes contribute to global SAT patterns and modulate interdecadal Pacific oscillation.
- Further research is needed on the teleconnectivity and influence of these modes on the forced climate response.
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