An open source glacier model in Python

About

OGGM is an open source model for glacier dynamics

Extending Marzeion et al., (2012), the model accounts for glacier geometry (including contributory branches) and includes an explicit ice dynamics module. It can simulate past and future mass-balance, volume and geometry of (almost) any glacier in the world in a fully automated workflow. We rely exclusively on publicly available data for calibration and validation.

Please get in touch with us if you are interested in using the model or if you’d like to contribute to the project!

Mission

"Develop a global scale, modular, and open source numerical model framework for consistently simulating past and future global scale glacier change"

Global not only in the sense of leading to meaningful results for all glaciers combined, but also for any small ensemble of glaciers, e.g. at the headwater catchment scale. Modular to allow different approaches to the representation of ice flow and surface mass balance to be combined and compared against each other. Open source so that the code can be read and used by anyone and so that new modules can be added and discussed by the community, following the principles of transparency and open governance. Consistent in order to provide well-defined uncertainty measures at all realizable scales.

Motivation

Our project is motivated by the far reaching goal of contributing (and helping others to contribute) to answers of some of the “big questions” in Earth Sciences:

  • How much ice is stored on the glaciers on Earth?
  • How much ice was present on Earth at the beginning of the 20th century, and how much ice will be lost by the end of the 21st?
  • What are the uncertainties associated with these numbers, and where do they originate?
  • How much model complexity is just right?

We envision the model as a seed that has high potential to grow into a self-sustained, community-driven global scale model for glaciers. It will enable regional and global studies of glacier-climate interactions without the need for a self-developed tool, and open new possibilities to run model or parameterization intercomparisons in a controlled environment.

Get involved

We welcome anyone to contribute to the project!