Creating a cyber training curriculum driven by the need to acquire expertise in data access, geo-processing, time series analysis, computational simulation, visualization and publication.
The objective is to teach students how to conduct data analyses and modeling experiments to produce Findable, Accessible, Interoperable and Reusable (FAIR) science in hydrological, weather and climate studies.
Solving the grand challenges posed by improving food and water security, in the face of growing population pressure, natural disasters, and climate change, requires expert knowledge of science and engineering fundamentals as well as advanced data analytics and computational methods.
This online resource contains materials for teaching an intro level undergraduate course on the FAIR science principles and applications within the field of climate and water science.
There will be an upcoming virtual FAIR Cyber Training workshop on June 1-2. Details and registration link are here.