Evaluating HAFS Model Microphysics Schemes Using GOES-R Satellite Imagery for Atlantic Hurricanes

This study demonstrates the utility of GOES-R satellite observations for evaluating microphysics schemes within the Hurricane Analysis and Forecast System (HAFS). Direct observations of storm hydrometeors are rare, creating a challenge for model validation. To overcome this, the study uses infrared brightness temperature data from the GOES-R satellite's Advanced Baseline Imager as a proxy for cloud and hydrometeor characteristics. Model forecast data is converted into synthetic satellite images using the Community Radiative Transfer Model (CRTM), which simulates the interaction of radiation with the atmosphere. This technique facilitates a direct comparison between the model's simulated hydrometeors and actual satellite imagery.
This comparison was applied to two HAFS configurations for three 2023 Atlantic hurricanes. By analyzing the observed and synthetic images with statistical tools, the methodology effectively assesses the models' ability to simulate vortex structures, cloud coverage, and cloud height. The process reveals systematic model biases, such as the overestimation of coldness in brightness temperatures, which indicates higher, colder clouds than were actually observed. This approach of comparing synthetic and real GOES-R imagery provides valuable, actionable insights for validating and refining the complex microphysics parameterizations essential for improving hurricane prediction capabilities