In recent decades, the frequency of compound dry and hot events (CDHEs) has increased markedly, posing a substantial threat to vegetation productivity in Inner Mongolia. To quantitatively assess these impacts, we adopted the Standardized Dry and Hot Index (SDHI) to characterize the intensity of CDHEs, and employed gross primary productivity (GPP) as a proxy for vegetation productivity. We assessed the relationship between the SDHI and GPP ( R gpp-sdhi ) using a factor detector and event coincidence analysis. Then, we employed structural equation modeling and multiwavelet coherence to elucidate the regulatory mechanisms of four large-scale atmospheric circulation patterns on R gpp-sdhi . The results showed that between 1982 and 2018, the suppressive effects of CDHEs on GPP intensified progressively, with scrublands being the most sensitive and forests the least sensitive. The Pacific Decadal Oscillation exerted a dominant and positively reinforcing influence on the SDHI–GPP coupling. In contrast, the El Niño–Southern Oscillation, North Atlantic Oscillation, and Atlantic Multidecadal Oscillation showed relatively weaker and mainly negative effects, with ENSO contributing the least. The correlations between the four large-scale circulation patterns and R gpp-sdhi were more pronounced at intermediate timescales, characterized by periods of 8–32 months. This study enhances the understanding of how vegetation responds to compound climate extremes and highlights the role of large-scale atmospheric circulation in regulating these responses. • Multiple wavelet coherence was introduced to study the responses of atmosphere-vegetation-compound event. • The Pacific Decadal Oscillation exerts the strongest influence on the relationship between compound dry and hot events and vegetation in Inner Mongolia. • Large-scale circulation patterns have a greater impact on the relationship between compound dry and hot events and vegetation at 8–32 months.
Kang et al. (2026) studied this question.