Tropical cyclones (TCs) are able to produce a variety of impacts to populated areas that threaten human life and property. However, the extreme amounts of precipitation associated with tropical cyclones leads to more harm to human life than any other impact associated with TCs. Due to the difficulty of forecasting extreme rainfall associated with TCs, this remains a priority within the Weather Prediction Center (WPC) and the entire weather community. While many studies have focused their efforts for improving forecast skill for these events over CONUS, this study analyzes the Caribbean and surrounding regions. Although this area experiences equally significant impacts, the skill of forecasts within this region is much less understood due to sparse observational datasets. Through relationships with international meteorological institutes, established in part by WPC’s International Desk, a collection of rain gauge observational networks was obtained for the region. The goal of this study is to analyze the performance of the Hurricane Analysis and Forecasting System (HAFS) quantitative precipitation forecasts (QPF) for the 2020 hurricane season. More specifically, we aim to develop an understanding of the QPF skill for the 2020 hurricane season using v0.1A to then produce a bias-corrected guidance method for evaluation on v0.2A. A portion of this work also focuses on the locations within the region with elevated terrain to understand the relationship between orographic and rainfall characteristics within the model and observations.  This presentation examines the HAFS v0.1A QPF performance and looks ahead to the next steps in the process of constructing a bias-corrected QPF guidance for possible implementation into future versions of the model.