Climate change in the Earth System

Climate change is more than just an atmospheric phenomenon. The atmosphere is closely coupled with the land and ocean surface, exchanging fluxes of carbon, energy, water and trace substances. Climate change profoundly affects these fluxes, and these fluxes in turn can profoundly affect climate change. Further, human actions have, and continue to, greatly modify how the land surface interacts with the atmosphere and thus, climate. However, human actions are always taken in the context of the environment in which they live. To understand the response of any part of this system to a particular forcing, it is necessary to consider the interactions and feedbacks between all the other parts. This module will introduce the key aspects of this system, building an appreciation of the uncertainties and complexities in the projections of global climate and climate impacts. You will directly analyse state-of-the-art environmental data such as that underling the latest IPCC assessment report. You will thus develop an appreciation of current modelling and measurement techniques used in research, along with the ability to manipulate and interpret environmental big data. 

The basis for analysis in this module will be the R programming language. You will be introduced to all necessary R techniques in the first weeks of the module, so no prior experience is necessary.

By the end of the module you will be able to:

  • Understand the main elements of the Earth system and how they interact and feedback on each other through cycles of carbon, nutrients, water and energy.
  • Appraise the current state of scientific knowledge of Earth system processes, including identifying uncertainties and knowledge gaps.
  • Formulate hypotheses describing the response of Earth system components and design methods to test them.
  • Investigate the effects of climate policy options in terms of both their efficacy and their wider consequences within the Earth system.
  • Manipulate and interpret large environmental datasets using appropriate computational techniques.