Earth’s climate is one of the fundamental boundary conditions on many Earth surface processes. For this reason, global climate models (GCMs) are often a critical part of Earth science research. However, they remain highly computationally expensive to run, and often access to a super-computer is needed to run a GCM in a reasonable amount of time. This motivates the question: is it possible to reasonably predict climate without an expensive GCM?Continue reading “Using machine learning and simple features to predict climate – part 1”
Tambien Group article published!
Our recent work that builds upon data obtained from the ~800-700 million year old Tambien Group of Ethiopia was recently published in GSA Bulletin:
The lead-up to the Sturtian Snowball Earth: Neoproterozoic chemostratigraphy time-calibrated by the Tambien Group of EthiopiaContinue reading “Tambien Group article published!”