Quantifying the influence of the seasonal cycle on heatwave hotspots in China

As extreme events with severe impacts on society and ecosystems, heatwaves demand thorough investigation. While previous studies have recognized the influence of the seasonal cycle on extreme temperature analysis, its specific effect on heatwave characteristics and hotspot distributions across China remains largely unquantified, particularly given the pronounced seasonal gradients in this region. This study addresses this gap by integrating the Euclidean norm-based hotspot index with a comparative analysis of data before and after the removal of the seasonal cycle, thereby isolating its specific influence on heatwave patterns across China. We demonstrate that the influence of the seasonal cycle on heatwaves is spatially heterogeneous and temporally variable. Spatially, the impact is most pronounced in northern China, where it leads to a systematic underestimation of heatwave metrics, distorts the apparent trends of heatwaves, and biases the integrated hotspot index. Temporally, the effect varies significantly across seasons due to differences in seasonal temperature gradients, with the greatest biases occurring in transitional seasons. Notably, the substantial underestimation of extremes during the baseline period in autumn artificially amplifies the perceived magnitude of heatwave changes and even generates spurious hotspot regions. By quantifying the impact of the seasonal cycle on heatwaves in China, this research advances the methodological framework for heatwave assessment and underscores the critical need to integrate seasonal variations into climate change risk evaluation.