Abstract
In this chapter, a notion of Earth System (ES) as a complex dynamical system of interacting components (subsystems) is presented and discussed. Weather and climate systems are introduced as subsystems of the ES. It is shown that any subsystem of ES can be considered as a multidimensional relationship or mapping, which is usually complex and nonlinear. Evolution of approaches to ES and its subsystems is discussed, and the neural network (NN) technique as a powerful nonlinear tool for emulating subsystems of ES is introduced. Multiple NN applications, which have been developed in ES sciences, are categorized and briefly reviewed. The chapter contains an extensive list of references giving extended background and further detail to the interested reader on each examined topic.
Keywords
- Earth System
- Neural Network Approach
- Partial Differential Equation
- Numerical Weather Prediction Model
- Neural Network Technique
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
Life was simple before World War II. After that, we had systems.
– Grace Murray Hopper
There are no separate systems. The world is continuum. Where to draw a boundary around a system depends on the purpose of the discussion.
– Donella H. Meadows, Thinking in Systems: A Primer
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Krasnopolsky, V.M. (2013). Introduction. In: The Application of Neural Networks in the Earth System Sciences. Atmospheric and Oceanographic Sciences Library, vol 46. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-6073-8_1
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DOI: https://doi.org/10.1007/978-94-007-6073-8_1
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