Application of the Weather, Research and Forecasting (WRF) Double-Moment 6-Class (WDM6) Microphysics Scheme within the Model for Prediction across Scales.

Accurate forecasting of severe weather events in the Caribbean is critical due to the region's vulnerability to hurricanes, squall lines, and mesoscale convective systems. This study investigates the efficacy of the Weather Research and Forecasting (WRF) double-moment 6-class (WDM6) microphysics scheme within the Model for Prediction Across Scales (MPAS) in improving precipitation forecasts in the Caribbean's tropical environment. Three significant weather events were simulated: the November 2016 squall line, the June 2021 mesoscale convective complex, and Hurricane Beryl (2018). These events were selected for their varying meteorological challenges and their impacts on the region.

Simulations using the WDM6 scheme were compared against those using the WRF single-moment 6-class (WSM6) and Thompson microphysics schemes. The evaluation focused on precipitation intensity, spatial distribution, and the ability to replicate observed data. The WDM6 scheme consistently provided better matches to observed precipitation, particularly in capturing the intensity and spatial distribution of rainfall during these events. Notably, WDM6 significantly improved the forecast of Hurricane Beryl's intensity compared to the other schemes, likely due to its enhanced representation of microphysical processes within the storm's core.

The findings suggest that integrating advanced microphysics schemes like WDM6 into operational models can enhance weather prediction accuracy in tropical regions. This improvement is crucial for better disaster preparedness and response in the Caribbean, contributing to reduced vulnerability to extreme weather events. Future work should explore the application of WDM6 in other tropical contexts and further refine the integration of microphysics with other model components for comprehensive weather forecasting.