A future-ready Open Global Glacier Model (OGGM)

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Glaciers form prominent features of many landscapes, and their global shrinking has become an icon of climate change. Glaciers are a source of geohazards, are important regulators of water availability for downstream populations in many regions of the world, and are a major contributor to sea-level rise. With recent advances in Earth observation and numerical modelling, a new branch of glaciology (“global scale glaciology”) emerged to estimate the volume of all 200 000 glaciers of the world, as well as their past and future evolution. Past glacier change can be estimated from direct measurements and from space, but to generate projections of future glacier change and associated impacts, scientists use numerical models of glacier evolution. The Open Global Glacier Model (OGGM, http://oggm.org) is one of the leading models for such applications. The model is open-source and modular (meaning that anyone can access its code and make additions to it), and therefore is already used by several research groups worldwide. However, it is currently developed by a small group of scientists, and the model development faces new challenges as its user base is growing. It is crucial to ensure that OGGM is ready to be used to address future global challenges. With this project, we seek to hire a trained software developer or a scientist with strong software engineering skills to work in team with the OGGM developers for a period of two years. We plan to significantly increase the robustness of the model by adding innovative testing protocols, removing and refactoring outdated code, and by developing new uncertainty estimation routines. Our goal is increase the model’s capacity to work with alternative and innovative modeling approaches originating from the greater science community, to model processes such as glacier calving or glacier dynamics. We will also encourage new users and developers to adopt the model by offering interactive online tutorials and training workshops, and, thanks to modern cloud technologies, we will offer specific training and resources to scientists less likely to have access to high performance computing resources.