Intra-seasonal asymmetry in satellite-observed vegetation greenness changes and their climatic associations in arid Northwest China.

Arid ecosystems are highly sensitive to climate change, yet it remains unclear whether regional greening is accompanied by consistent changes in vegetation greenness throughout the growing season. Using SPOT/VEGETATION NDVI and meteorological data from 1999 to 2018, we applied a month-to-month NDVI difference metric (VNDVI) to characterize intra-seasonal variation in satellite-observed vegetation greenness and to examine its relationships with concurrent and antecedent climatic conditions across arid Northwest China. May-October was defined as the common analytical window for regional comparison, with May-July representing the early-to-peak growing season and August-October representing the late growing season. Although NDVI exhibited positive long-term trends in most months, VNDVI trends showed pronounced intra-seasonal asymmetry. VNDVI increased significantly in June and July but decreased significantly in October, indicating that regional greening was accompanied by a redistribution of month-to-month vegetation greenness changes rather than a uniform enhancement throughout the growing season. These trends also exhibited marked spatial heterogeneity. Negative VNDVI trends in May were concentrated in the Altai Mountains and the western Tianshan Mountains, whereas positive trends in June and July were most evident in the central Tianshan Mountains and along the northern margin of the Tarim Basin. The relationships between VNDVI and climatic variables varied among months and regions. Precipitation was generally positively associated with month-to-month vegetation greenness changes, whereas temperature and radiation showed negative associations in several months and regions. Hierarchical partitioning further revealed that the relative independent contributions of climatic variables to NDVI variability differed among vegetation types, with temperature accounting for a particularly large proportion of the explained variation in croplands during the early growing season.