GOES Satellite Verification System for the HRRR Model
The goal of this project is to develop an automated ranking method that can be used to quickly assess the accuracy of High Resolution Rapid Refresh (HRRR) model forecasts through comparison of observed and simulated Geostationary Operational Environmental Satellite (GOES) infrared brightness temperatures. The simulated brightness temperatures provide detailed information about the spatial distribution of clouds and water vapor across the continental United States. Given the hourly update cycle of the HRRR model, it is difficult for forecasters to routinely assess the accuracy of each HRRR model forecast cycle because of the large data volume. To help remedy this problem, the satellite-based model analysis tool developed during this project provides forecasters a new method to quickly assess the accuracy of the overlapping HRRR forecast cycles at the current time.
Email researchers: Jason Otkin, Justin Sieglaff, Sarah Griffin, and Lee Cronce
- Jason Otkin
- Justin Sieglaff
Funding contributors and acknowledgements
GOES-R Risk Reduction Program