Machine Learning for High-Resolution Downscaling in the Hawaiian Islands
Description
Currently, models of global climate change lack the resolution needed to model the processes that create most of Hawai?i’s rainfall.
Detailed example
Using these improved spatial interpolation models, this project will create high-resolution, accurate historical rainfall maps. The project will also test the method for projecting future rainfall and compare predictions to existing statistical downscaling models.
AI / analytics pattern
Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
predict precipitation at locations where no measurement data is available, using rainfall measurements from nearby locations
Controls / human review
ATO: No; PIA: Not published