climate system modeling, programming, data analysis, high-performance computing
WHAT WE DO
Key Points:
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We will model earth systems in a changing climate.
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Our techniques involve pre- and post-processing of weather and climate data.
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Data will come from observations, model output, and reanalyses.
Detailed Description:
In 2022 one of the projects had students in the stream using artificial intelligence and machine learning algorithms to recognize polar lows in satellite imagery. One technique based solely on visible satellite images used Google's teachable machine to sort satellite images into polar lows and nonpolar lows. Another technique incorporated metadata such as the storm's latitude and longitude into decision tree classifiers. Finally, students worked to refine these models by applying transfer learning and comparing which model performs best under which conditions.
The stream will now turn its focus to weather, climate, and climate system modeling exploring the interactions between the ocean, atmosphere, and cryosphere systems in a changing climate. We will gather and analyze input data and use state-of-the-art climate system models and supercomputing clusters to answer questions about how our climate system works and will work as anthropogenic climate change evolves.
WHY IT MATTERS
Key Points:
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The impacts of climate change are observed in real-time with real-life implications around the world to human health, wealth, and safety.
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Applying key research methods to this variety of data gives you valuable transferable experience and skills while investigating important parts of the climate system.
Detailed Description:
Weather and climate impact nearly every aspect of society including transportation, food supply, renewable energy, tourism, infrastructure standards, natural resource availability, and national security.
The fields of atmospheric and computer science came into their own around the same time and have remained tightly linked, with advances in one pushing forward advances in the other. The cutting-edge of atmospheric computational science utilizes principles of artificial intelligence, big data analysis, and high-performance computing to harness the information contained in the ever-growing collection of model output and observations. Developing experience in these computing and analysis skills will prepare you for careers in the ever-growing field of data science, regardless of the subject matter.
WHAT YOU LEARN
Key Points:
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Understand climate change and how different systems interact.
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Employ weather and climate system models to investigate research questions.
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Linux environment navigation and programming for pre and post-processing of data and model output.
Detailed Description:
Students in this stream will learn basic principles of earth system and atmospheric science. They will explore topics involving climate change, polar climate, and earth system interactions.
They will also learn the role of different types of observations and models in understanding and predicting weather and climate, including how different
parameterization and direct modeling schemes come together to model the
atmosphere, ocean, cryosphere, and land surface.
To analyze such data and model output, we will employ basic Python programming and shell scripting in a
supercomputing environment.
