As PV systems are becoming more common in regions with significant snow cover during winter, improving the accuracy of the snow loss prediction and monitoring is crucial. In this work, we propose a novel hybrid snow loss model that differentiates between snow loss discrepancies in full-cell and half-cell modules. Snow coverage on PV modules is evaluated using an image processing algorithm, and the interconnection between PV cells and modules is incorporated through a cell-level electrical model. Using these methods, we performed an analysis of PV snow losses for both module types in a testing system situated in southern Finland during the winter of 2023-2024. The results show that half-cell modules reduce annual snow losses by approximately 26% compared to full-cell modules. In contrast to the Marion model, this mitigating effect of half-cell modules is well reflected in our modeling results. Furthermore, our model outperforms the Marion model in predicting time-dependent snow losses, reducing the RMSE by a factor of around 3. This improvement is essential for accurate performance monitoring and forecasting in snow-affected PV systems.