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The fastest university supercomputer in the world, Pritchard can run his models on Frontera at a time- and length-scale accessible only on a handful of systems in the U.S. Pritchard's research and new approach is made possible in part by the NSF-funded Frontera supercomputer at the Texas Advanced Computing Center (TACC). "Each GPU has the horsepower to run hundreds of the micromodels while still matching the throughput of the coarse-grained lower-resolution planetary model." "The Multiscale Modeling Framework approach is also ideal for DOE's upcoming GPU-based exascale computers," said Mark Taylor, Chief Computational Scientist for the DOE's Energy Exascale Earth System Model (E3SM) project and a research scientist at Sandia National Laboratories. Michael Pritchard, professor of Earth System science at UC Irvine, studies how the planetary water cycle and climate work, and how it may change in the future, focusing on cloud physics and moist convection processes. "It has thousands of little micromodels that capture things like realistic shallow cloud formation that only emerge in very high resolution." "The model does an end-run around the hardest problem – whole planet modeling," Pritchard explained. Pritchard's co-author Walter Hannah from the Lawrence Livermore national laboratory helps lead this effort. The idea has lately been enjoying a renaissance at the Department of Energy, where researchers from the Energy Exascale Earth System Model (E3SM) have been pushing it to new computational frontiers as part of the Exascale Computing Project. This climate simulation method, called a ‘Multiscale Modeling Framework (MMF),' has been around since 2000 and has long been an option within the Community Earth System Model (CESM) model, developed at the National Center for Atmospheric Research. The research is supported by grants from the National Science Foundation (NSF) and the Department of Energy (DOE).

His team's reported the results of these efforts in the Journal of Advances in Modeling Earth Systems in April 2022.

The two simulations run independently and then exchange data every 30 minutes to make sure that neither simulation goes off-track nor becomes unrealistic. Pritchard is working to fix this glaring gap by breaking the climate modeling problem into two parts: a coarse-grained, lower-resolution (100km) planetary model and many small patches with 100 to 200 meter resolution. It could take until 2060, according to Moore's law, before the computing power is available to capture this level of detail. global climate model are struggling to approach 4 kilometer global resolution, Pritchard estimates that models need a resolution of at least 100 meters to capture the fine-scale turbulent eddies that form shallow cloud systems - 40 times more resolved in every direction. They are therefore included in models through a variety of approximations.Īnalyses of global climate models consistently show that clouds constitute the biggest source of uncertainty and instability. The problem is these phenomena occur on a length- and time-scale that today's models can't come close to reproducing.

No one denies that clouds and aerosols - bits of soot and dust that nucleate cloud droplets - are an important part of the climate equation. And the key reason for this is the way clouds are included in climate models." "If you ask two different climate models what the future will be like when we add a lot more CO2, you get two very different answers. And that, Pritchard says, is part of the problem. These two scenarios would result in very different future climates. "Or they could thicken and become more reflective." "Low clouds could dry up and shrink like the ice sheets," says Michael Pritchard, professor of Earth System science at UC Irvine. We hear a lot about how climate change will change the land, sea, and ice. Researchers are using advanced computing to add higher-resolution cloud dynamics into global simulations. Shallow clouds formed by fine-scale eddies as observed in nature.