About Our Curriculum
The impacts of climate change on agriculture are expected to tremendous. The approaches used to study and anticipate these impacts are driven by climate data, yet many agronomists, soil scientists, and other researchers lack the computational training to make effective use of downscaled climate projections, re-analysis datasets, or satellite remote sensing data. At the same time, climate data and remote-sensing data volumes are steadily increasing; the latest Coupled Model Intercomparison Project (CMIP), CMIP6, produced an estimated 20-40 petabytes of data. Despite the utility and prevalence of these model outputs, the vast majority of domain scientists who use computer-generated datasets and algorithms are self-taught.
We are a group of climate scientists, agronomists, and ecologists that have first-hand experience both teaching and learning how to use the tools and techniques of Open Science. Our curriculum will cover the fundamentals of how climate datasets are produced and how prevailing climate and climate anomalies can be analyzed using NASA SMD datasets. We also introduce the fundamental components of agricultural systems as subsequent modules: Water Resources, Healthy Soils, and Crops. Each module explores how NASA SMD data, especially cloud-ready datasets, can be used to answer specific, applied questions related to food security in the Middle East and Northern Africa (MENA) region. Specifically, NASA’s investments including the Earth Observing System, Soil Moisture Active Passive (SMAP), the Gravity Recovery and Climate Experiment (GRACE), and ECOSTRESS will demonstrate their value for analyzing agricultural water availability, soil health, crop condition, and production.
The five (5) ScienceCore modules we will develop as part of our curriculum will be based entirely in open-source software, implemented in Python, and distributed using literate programming tools like Jupyter Notebooks.