The temperature profile of white dwarf (WD) mergers is crucial for understanding where and how a detonation might occur in stellar simulations. However, achieving both high accuracy and low computational cost in temperature profiling for detonation determination remains challenging. Existing methods with low cost often lack the precision needed for comprehensive analysis, while high-accuracy approaches tend to be computationally expensive. To address this, we developed a novel temperature profiling method tailored for WD mergers. Our approach enhances accuracy by incorporating additional data, such as the size and average distance of hotspots on the star’s surface, providing a more detailed analysis. To reduce computational cost, we implemented real-time and in-situ temperature profiling, minimizing the workload from input/output (I/O) operations and data modeling. We applied our method to Castro’s wdmerger simulation and found that the results were easily interpretable, enabling precise detonation determination. In comparison to Seitenzahl’s method, our approach maintained the same level of accuracy across multiple WD detonation cases, while achieving a significant 8.55 \(\times \) speed-up in execution time. The overhead, ranging from 0.11% to 2.28% of the total simulation time, was minimal and insignificant.