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Software engineers monitor problems that threaten climate simulations. The climate debate has shifted. The large majority of scientists accept data that show the world is getting warmer as the result of human activity. The discussion now focuses on a variety of questions about how climate change will proceed and how the process can be slowed and mitigated. Should forests and food croplands be converted to produce plants for biofuels? What technologies best capture and store carbon? How intense will hurricanes and heat waves be? Will the release of methane trapped in permafrost accelerate climate change?
Answers to these and other questions depend increasingly on sophisticated climate simulations, a digitized world that mirrors our past and probes the future. Unlike the conventional laboratories of test tubes and microscopes, this new world would not function without software applications such as the Community Climate System Model (CCSM), a megamodel coupling four independent models whose codes describe Earth's atmosphere, oceans, lands, and sea ice. Such simulation tools are now commonplace on ORNL’s supercomputers. Indeed, much of the U.S. climate community conducts simulations in Oak Ridge, including the Department of Energy, the National Center for Atmospheric Research, the National Oceanic and Atmospheric Administration and the National Aeronautics and Space Administration. Among the most prominent climate simulations were those conducted at ORNL in 2004 and 2005 that were cited in the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC). Using the latest version of the CCSM, researchers also carried out computations on resources at the National Center for Atmospheric Research (NCAR), the National Energy Research Scientific Computing Center, and the Japanese Earth Simulator. John Drake, an ORNL scientist working at the intersections of computer science, climate science, and applied mathematics, called the simulations “a watershed event for climate science and for the way in which we provide computational simulation results to the community.” Drake leads ORNL’s contribution to the Climate Science Computational End Station, which will support the IPCC’s fifth assessment report, due in 2014. "A small team has been building the models, and an even smaller team performs the simulations and posts the material on the Earth System Grid for others to retrieve," he said. "Very few sites in the world can field the kind of computational horsepower that the NCCS does and that various other large climate and weather centers have internationally. The fact that you can perform these simulations and then make the results quickly available to university researchers and others who do not have access to the machines or the wherewithal to build the models multiplies the productivity of the science enterprise." One validation of the climate simulations lies in the volume of publications. In the months after simulation data were posted, scientists produced approximately 300 journal articles. The IPCC cited the studies in the Fourth Assessment Report, which concluded planetary warming during the twentieth century was likely the result of human activities. In 2007 the IPCC shared the Nobel Peace Prize with Al Gore. Weather versus climate Drake frames the question that drives the project. "How can we simulate climate 100 years from now if we do not know what the weather will be 100 days from now? Climate is statistical, or average, weather," Drake explains. "Climate data can tell us if hurricanes will be more likely, less likely, or stronger, but the data cannot tell us when they will occur. With weather, small changes can contribute to large changes days or even weeks later. "We cannot forecast weather beyond 10 to 15 days because it's based on chaos theory," Drake said. "In Earth system modeling and climate studies, we are always aware of the effect of chaos—the butterfly flaps its wings, and that changes the path weather is going on, the fundamental dynamics of the atmosphere. Some people throw up their hands and say, ‘You can't do this problem.'" But if scientists use supercomputers to study climate from a statistical standpoint—in essence sampling multiple flaps of the butterfly's wing—the problem becomes manageable. "An ensemble of paths is then averaged to get the most likely path," Drake said. Just how well do statistics model reality? "To the extent that we can reproduce the paleoclimate record or recent historical record, if emission scenarios and forcings are accurate, then we believe the models are reasonably accurate," says ORNL's Jim Hack, a climate researcher who implements global models on high-performance computing systems. "But we know that they are not reliable on smaller than subcontinental space scales. In fact, on space scales similar to the North American continent, there is divergence in the models about what happens to precipitation over North America 100 years from now." To answer questions about climate change at local levels, such as what will happen in the Tennessee Valley in a decade, scientists need higher-resolution models. "We want to employ numerical algorithms that can scale to use many, many more processors and keep the time to solution about the same," Hack said. "To evaluate local or regional impacts of climate change, the computational requirements for climate modeling go up sharply," says ORNL computational scientist Patrick Worley. "The models are currently not able to exploit efficiently the computing resources that will be available in the near future. To take advantage of those, we need to modify some of the models dramatically."
Performance police When scientists want more accurate or more detailed simulations, they turn to modeling experts and software engineers who upgrade the capabilities of the simulation models. When the software engineers need help, they turn to Worley, who leads a project through the Department of Energy’s Scientific Discovery through Advanced Computing program. Worley conducts the project with Arthur Mirin of Lawrence Livermore National Laboratory and Raymond Loy of Argonne National Laboratory to scale up climate codes, enabling them to solve larger problems by using more processors and to evaluate software and new high-performance computing platforms such as the Cray XT4 and IBM Blue Gene/P supercomputers. "An important practical aspect of climate science is figuring how much science we can get in the model and still complete the simulations in time," says Worley, whose team works with researchers and manufacturers to identify bugs in CCSM codes, performance bottlenecks in the algorithms used in the CCSM, and glitches in a machine's software. "Our contribution is getting the component models to run as efficiently as possible. The software engineering aspects of the code are always changing, and often the new code has unexpected performance issues. We monitor things. We're the performance police." Worley and his colleagues push codes to their limits. If a code runs slowly on 1,000 processors but quickly on 2,000, they might assign more processors to work on a problem. If, due to algorithmic restrictions, the code cannot use more than 1,000 processors, changing algorithms may be the only option to improve performance. Different science also imposes different performance requirements. Ocean scientists may choose to run a high-resolution ocean model coupled to a low-resolution atmosphere model, whereas atmospheric scientists may pick the converse. Changes to the codes to improve performance for one scenario must not slow down the code for another or hurt performance on a different (or future) platform. Often the performance team introduces algorithm or implementation options that scientists can chose to optimize performance for a given simulation run or on a particular computer system. On Cray and IBM systems, the group has improved performance through both algorithmic and implementation efforts. Recent work improved performance 2.5-fold on benchmark problems on ORNL's Cray XT4 Jaguar. "With the improvements to the scalability of the CCSM software by Pat and his colleagues, along with the dramatic growth in the performance of Jaguar, the CCSM developers are seriously considering model resolutions and advanced physical processes that were not on the table before," said Trey White, who as ORNL's liaison to the CCSM project helps the scientists maximize the machines' capabilities. "Pat Worley's group has provided critical support in improving the scalability and performance of the CCSM across a wide range of architectures," said NCAR's Mariana Vertenstein, head of the engineering group responsible for CCSM's software development, support and periodic community releases. "The CCSM project played a major role for the International Panel on Climate Change through an extensive series of modeling experiments and in fact resulted in the most extensive ensemble of any of the international global coupled models run for the panel's award-winning Fourth Assessment Report. This accomplishment could not have occurred without Pat's contributions." Worley's team is currently working with a large multilab project to extend the physical climate model by including chemical and ecological processes. The computer allocations are provided through the Climate Science Computational End Station, an Innovative and Novel Computational Impact on Theory and Experiment program award led by NCAR's Warren Washington on Jaguar at Oak Ridge. "For the Department of Energy, which is very concerned with the carbon cycle and with the impact of climate change on ecology and ecosystem services, this kind of Earth system model is invaluable," Drake said. "We are doing everything we can to get there as quickly as possible."—Dawn Levy
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