238 - Providing Undergraduate Students with Training on Evaluating Climate Change Projections within the Framework of Open-source Software Infrastructure

In this study, we develop an open-source online computing infrastructure using a cloud based computational platform, (Google Earth Engine) and the NEX-GDDP-CMIP6, a recently downscaled global datasets at 25 km spatial resolution by National Aeronautics and Space Administration (NASA), to assess future projections of climate change and climate variability in comparison to hindcasts. The climate model outputs are analyzed through a series of spatiotemporal techniques to derive meaningful insights on climate change impacts. Climate models are classified into four extreme categories (dry and warm, dry and cold, wet and warm, wet and cold) based on thresholds calculated from deviations using definite percentiles. We compute projected deviations for various decision-relevant climate indices, including maximum precipitation during the 5-day stretch of the year (RX5day), the one-day maximum precipitation of the year (RX1day), the total yearly precipitation (PRCPTOT), the hottest day of the year (TXx), the coldest day of the year (TNn), number of frost days (FD), number of summer days (SU), among other indices.
The primary objective of this study is to create an easily expandable training program for undergraduate students, with a specific focus on analyzing the effects of climate change. This program incorporates both fundamental and advanced courses utilizing the Google Earth Engine and Google Colaboratory, with a primary emphasis on using Java Script and Python for conducting assessments of climate change impacts. While the case study is centered on the Mississippi River basin, the techniques and training materials can be applied and customized for other regions within the USA and internationally. Seven undergraduate students from various departments, including Civil & Environment, Computer Science, and Meteorology, evaluated the tool across seven different watersheds in the Mississippi River basin. The resulting tool offers opportunities for computational research to undergraduate students. By arming students with hands-on skills and knowledge derived from detailed climate projections, the project aims to deepen their understanding of the impacts of climate change and empower them to address climate-related challenges.