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Computer climatologist Salil Mahajan simulates the complex and chaotic aspects of the climate at the Oak Ridge National Laboratory. (Photo by ORNL / US Department of Energy)
By Ashley C. Huff, Oak Ridge National Laboratory
High resolution global climate simulation at multiple scales will help answer questions about future global and regional climates. However, as performance expectations increase for Earth system models, so do IT challenges.
Salil Mahajan, a computer climatologist in the Computational Earth Sciences group at the US Department of Energy’s Oak Ridge National Laboratory, tackles some of these challenges in high performance computing for climate science.
The climate is a chaotic system. It includes complex interactions between the atmosphere, oceans, sea ice and land.
“As we include more dynamic coupled interactions between these spheres and incorporate more biological, chemical and physical processes into our models, the calculations become more complicated,†said Mahajan. “We need to take a step-by-step approach to understand cause and effect and ensure that our simulations accurately represent our observational measurements. “
The validation and verification of models are now the daily bread of his daily life. But Mahajan’s affinity for atmospheric science and computer architectures developed along a roundabout route.
From architecture to atmosphere
The journey began in India, where Mahajan first studied architecture of a different genre. Mahajan obtained his undergraduate degree in traditional architecture.
“I was interested in physics, but when it came time to choose a career, I thought architecture might be a better path,†he said. “I was young at the time and thought I might start my own business.”
The functional architectural design appeals to him, but the aesthetic aspects do not suit his temperament. He became dissatisfied with the subjectivity inherent in the discipline. Nonetheless, he continued to expand his education by pursuing graduate studies in urban planning at Texas A&M University. Seeking greater objectivity, Mahajan also began to explore other career options there. After a fascinating meeting with the head of the Department of Atmospheric Sciences, Gerald North, Mahajan switched fields to study climate. Climate modeling and climate statistics provided an intriguing level of complexity as well as objectivity desired by Mahajan at the time.
As a graduate student, Mahajan attended a summer internship at ORNL through the Oak Ridge Center for Advanced Studies (ORCAS). The ORCAS program partnered him with Forrest Hoffman on the DOE’s Atmospheric Radiation Measurement (ARM) program. Hoffman, currently a climatologist in the Division of Computer Sciences and Engineering and formerly in the Division of Environmental Sciences, used data mining techniques to compare climate data from the ARM site in Lamont, Oklahoma. , with the results of the global climate model.
“The aim was to compare the site’s observations with climate models to assess their performance,†said Mahajan. “Model validation is an important aspect of climate research, and it continues to be a part of what I do at ORNL. “
Mahajan returned to Texas A&M, where he completed his doctorate in 2008. Subsequently, he traveled to Princeton University as a post-doctorate and spent two years working in the Geophysical Fluid Dynamics Laboratory. This venture aligned perfectly with the emergence of the Climate Change Science Institute (CCSI) in 2009. Mahajan joined the institute in 2010 under the leadership of its founding director, Jim Hack, who now heads the National Center for Computational Sciences at ORNL. Mahajan was drawn to CCSI by the lab’s reputation for cutting-edge computing power and climate research, but also by his admiration for the researchers there, especially Hack.
“He is a star scientist and I was fortunate enough to work with him at CCSI,†said Mahajan. “We always follow his ‘visions’ of climate modeling as we move forward in our research. “
Climate modeling for science and energy
Mahajan is now involved in a software modernization effort (ACME-SM) for the DOE’s Accelerated Climate Modeling for Energy (ACME) project, a multi-lab mission to develop the most sophisticated Earth system model to date, able to function effectively on a leadership class. computers, with the aim of improving understanding of climate change and its future impacts on energy.
As the site principal investigator for ACME-SM, Mahajan applies machine learning techniques to ensure that climate model development efforts to accelerate the performance of climate models on the latest high-performance computers do not alter model results. . New hybrid computing architectures will boost climate modeling with faster processing times, but because the models were designed for older architectures, the upgrade involves significant code refactoring and optimization to allow models to use. efficiently high performance systems.
As computer architectures evolve towards exascale and its promise of exponential increase in computing power, computer scientists like Mahajan are busy behind the scenes making sure all code is working properly.
See the original story, published by ORNL on August 30, here.
More information will be added as it becomes available.
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