Low-dimensional Energybalance models

Introduction

This project is a python-implementation of low-dimensional energy balance models (EBMs), built up from a set of physical functions, combined to represent the behaviour of earth’s climate through space and time. EBMs are one of the most basic climate models, able to reconstruct past climate conditions and predict future ones aswell. (some Examples)

The implementations of this project are based on a set of publications, especially from Michail Budyko () and William Sellers (). (For the full list see References).

This documentation primarily aims on explaining the structure of the sourcecode and show how to use it four your own purpose. It is now the most well documented sourcecode, so if questions or concerns about implementations come up, please contact me (contact).

• Physical Background / Model Types
  • Physical Background
  • Model Types
• Installation
  • Python Package
  • Dependecies
• How to use
  • Step 0: Import packages
  • First Step: Import model configuration
  • Second Step: Import variables
  • Third Step: Let the model/algorithm run
  • Final Step: Evaluating the output
  • Putting it together
• Input
• Output
• Tutorials
  • 0D EBM (simple)
  • 0D EBM (\(CO_2\) forced)
  • 0D EBM (volcanic forced)
  • 1D EBM Budyko-type (static albedo)
  • 1D EBM Budyko-type (temperature-dependant albedo)
  • 1D EBM Sellers-type (static albedo)
  • 1D EBM Sellers-type (temperature-dependant albedo)
• Source Code
  • The numerical integrator
  • The basic model equation
  • Functions
  • Configuration
  • Variables
• References
  • Keeling-curve