Abstract: The Clumping Index (CI), a key structural parameter that characterizes the spatial aggregation of vegetation foliage, plays an important role in regulating canopy radiation interception, global carbon and water cycles． Long-term CI products have been operationally generated from the MODIS BRDF/albedo product． In this study, we selected 20-year (2001–2020) MODIS monthly CI products to explore the long-term variation trend of vegetation CI during the growing season, because CI can capture leaf clumping structures during the growing season in a more effective way． First, based on previous studies, we used the MODIS phenology product (MCD12Q2) to mask the full-year monthly CI data, acquiring the representative CI values for the growing season． Then, to address the potential outliers in the CI product, we improved Theil–Sen Median trend analysis method that was probably more appropriate to examine long-term CI variations trend． Finally, we explored the relationships between CI and Leaf Area Index (LAI) and Fractional Vegetation Coverage (FVC), respectively． The results indicate that the CI data quality during the growing season is improved compared to CI yearly means． A 30% of these selected representative CIs show significant long-term variation trend, mostly falling within −0.005 to 0.005 per year． Such a trend is related to the trends of LAI and FVC to varying degrees, particularly in a case when CIs present negative correlations with LAI and FVC, respectively． This study is useful and valuable for potential users to optimize CI product data for their probable studies, and helps to an improved understanding regarding the long-term trend of MODIS CI products, thereby supporting potential applications in relation to the CIs as one of important inputs in global carbon and water cycle.