Understanding rapid climate shifts in the Midwest
Zhiying Li
Faculty Mentor
Zhiying Li (O'Neill School of Public and Environmental Affairs)
Project Description
Weather whiplash refers to rapid shifts between extremes, such as sudden transitions from drought to flooding or vice versa. For example, the Midwest experienced a sharp shift from drought in 2012 to a wet spring in 2013. These rapid changes are risky for crops like corn. In this project, you’ll help us study how often these sudden shifts happen and how they might be affecting crop yield in Midwest. You’ll work with real-world climate and crop data and learn how to find and visualize patterns.
Technology or Computational Component
The student will use Python and Jupyter notebooks on IU High-Performance Computing System to analyze weather and crop yield data. Tasks will include cleaning and organizing climate (e.g., rainfall and temperature) and corn yield datasets, identifying months with abrupt transitions and their impacts, and creating plots and maps to show patterns across the Midwest. The student will gain experience with Python packages such as pandas, matplotlib, xarray, and/or geopandas. Training will focus on developing data analysis skills using environmental datasets.