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What is Climate?

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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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Exploring the Effects of Atmospheric Forcings on Evaporation: Experimental Integration of the Atmospheric Boundary Layer and Shallow Subsurface
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Coupling functions in climate.

Woosok Moon1,2, John S Wettlaufer2,3

  • 1Department of Mathematics, Stockholm University, 10691 Stockholm, Sweden.

Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences
|October 29, 2019
PubMed
Summary
This summary is machine-generated.

Dynamical systems theory uses coupling functions to model climate interactions. This study shows El Niño-Southern Oscillation (ENSO) influences the Indian Ocean Dipole (IOD), enabling network models for climate variability.

Keywords:
El-Niño–Southern OscillationIndian Ocean Dipolestochastic dynamicstropical variability

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Area of Science:

  • Climate dynamics
  • Dynamical systems theory
  • Stochastic modeling

Background:

  • Dynamical systems theory offers quantitative insights into climate dynamics.
  • Previous work simulated surface air temperature using 1D stochastic systems.
  • This study extends the approach to 2D systems for subsystem interactions.

Purpose of the Study:

  • To apply coupling functions to analyze interactions between climate subsystems.
  • To investigate the relationship between the El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD).
  • To demonstrate the construction of network models for climate variability.

Main Methods:

  • Utilizing two-dimensional dynamical systems to model climate interactions.
  • Constructing coupling functions based on the covariance of data from climate subsystems.
  • Applying the method to analyze the ENSO and IOD climate indices.

Main Results:

  • Coupling functions quantitatively reveal interactions between climate subsystems.
  • The El Niño-Southern Oscillation (ENSO) was found to primarily control the Indian Ocean Dipole (IOD) during its mature phase.
  • Demonstrated the construction of a network model for climate system variability.

Conclusions:

  • Coupling functions derived from data covariance are effective for modeling climate interactions.
  • The ENSO significantly influences the IOD, highlighting a key driver in tropical climate dynamics.
  • The findings support the development of network models for understanding seasonal climate variability.