Recent multiscale models of cardiac calcium dynamics have demonstrated that stochastic channel behavior can be captured using aggregated calcium release units (CaRUs), bridging subcellular variability and whole-cell responses (Marchena and Echebarria, 2018 ; Novaes et. al, 2026). However, such mean-field approaches do not explicitly resolve spatial interactions between microdomains, limiting their ability to assess how local stochastic dynamics give rise to coherent global behavior (Colman et al., 2022). In this work, we introduce a two-dimensional spatial extension of a previously validated Scalable Aggregate Calcium Release Unit (SA-CaRU) framework, enabling explicit modeling of diffusion-mediated coupling between calcium release sites. The cell is represented as a 2D network of coupled units, each incorporating stochastic Markov Chain formulations for L-type Calcium Channels (LCCs) and Ryanodine Receptors (RyRs) within a modified human ventricular electrophysiological model. The computational strategy combines domain decomposition and operator splitting. Local stochastic dynamics are independently solved for each unit using a binomial tau-leaping scheme (Tian and Burrage, 2004), while a global diffusion step updates cytosolic calcium concentrations and mediates coupling between neighboring units. This approach is implemented in parallel, allowing efficient simulation of large spatial networks while preserving stochastic fidelity at the subcellular level. Simulations demonstrate that diffusion-mediated coupling promotes synchronization across calcium release units, leading to the emergence of deterministic-like global calcium dynamics despite intrinsically stochastic local behavior. This transition is accompanied by a marked reduction in variability and recovers coherent whole-cell calcium transients consistent with previously reported multiscale behavior. This work extends mean-field multiscale models by incorporating explicit spatial structure, providing a scalable framework to investigate how microdomain coupling shapes the emergence of global cardiac dynamics and enabling future studies in physiologically realistic geometries.