Adaptation of emerging computational technology for carbon and palaeoclimate modeling

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One of the grand challenges to human civilization is man-made climate change, much of which is caused by the burning of fossil fuels that releases CO2 to the atmosphere. Current research in climate science is aiming to better understand the relationship between natural changes of atmospheric CO2 levels and natural climate change over the long course of Earth's history. Reconstructions based on sediment cores recovered from the deep ocean demonstrate that over the last ~50 million years Earth's climate has unsteadily transitioned from warm "greenhouse" conditions with no ice in Greenland and Antarctica to the modern "icehouse" state with continental-scale ice caps near the poles. Other types of measurements on these deep sea sediments indicate that atmospheric CO2 levels and ocean acidity have broadly declined over the same timeframe, thereby raising the possibility that atmospheric CO2 decline may have been a key reason for ~50 million years of global cooling. The central aim of the work proposed here is to improve our understanding of the role of atmospheric CO2 in regulating the state of the climate system.Because of the complexity of the involved physical, chemical and biological processes computer models have become a central tool in climate research. Considering the vastness of our planet and the many million years of Earth history, it becomes clear that Earth System modeling is a computational challenge that requires the use of ever-faster supercomputers. The greatest change in high-performance computing over the last decade and the foreseeable future is the development of "General Purpose computing on Graphics Processing Units" (GPGPU), which greatly reduces the size and energy consumption a given computer needs to do a given calculation in a given amount of time. Thus, within the limited space and power supply of a building that houses a supercomputer much larger computational problems can be solved using GPGPU rather than the classical approach that relies on CPU (Central Processing Unit) hardware. However, the existing Earth System models were developed for CPU-architectures and are therefore unable to fully exploit the benefits from GPGPU. The approach of the work proposed here is to develop GPU-native model components (marine biology, chemical mixing by physical ocean circulation, CO2-exchange between ocean and atmosphere, etc.) that enjoy the full computational benefit from GPGPU. This aspect of the work builds on the collaboration of and the exchange of knowledge between scientists in the fields of high-performance computing and the Earth sciences.Ultimately, a better understanding of Earth history and climate change must be derived from reconstructions based on the sedimentary record as evidence. These observations are frequently compared to model simulations as a way of verifying that a particular simulation is in agreement with data of different types. With the work proposed here it will become possible to systematically compute thousands of simulations, followed by meticulous comparison to observations. Based on this advance, the cross-comparison between data and models (and between data and data) will help to better understand how the Earth System has changed in the past, and what were the driving processes. This knowledge of the past will then inform our outlook for the climate and the carbon cycle of the future.