Studying the impact of extreme climate events on vegetation dynamics is crucial for maintaining ecosystem stability. Based on ERA5-Land temperature and precipitation data, as well as MOD13C2 data, this study employs Pearson correlation analysis, wavelet analysis, and the XGBoost-SHAP model to analyze the response of the Normalized Difference Vegetation Index (NDVI) in China to extreme climate variations. The findings reveal the following. (1) NDVI increased steadily at a rate of 0.021/10 yr from 2001 to 2024. Extreme temperature and precipitation indices show an increasing trend in most regions. (2) NDVI was positively correlated with most extreme temperature and precipitation indices, and showed a significant negative correlation exclusively with Frost Days FDO (Frost Days) and CDD (Consecutive Dry Days). (3) R25 (Number of Heavy Precipitation Days) and SDII (Simple daily intensity index) are the primary drivers of nationwide NDVI changes, with contribution rates of 31.6% and 12.5%. Extreme climate indices can significantly affect vegetation growth when surpassing certain thresholds. For instance, the thresholds for R25 and SDII are 1.85 days and 4.35 mm/day. This study provides a scientific basis for understanding and managing vegetation responses to increasing climate extremes.
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Li et al. (2026) studied this question.
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