Abstract: Clumping Index (CI), a key structural parameter characterizing 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 variations in vegetation CI in the growing season, because CI can capture leaf clumping structures more effectively． The MODIS phenology product (MCD12Q2) was used to mask full-year monthly CI data, acquiring representative CI values for the growing season． To address 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． We explored the relationships between CI and leaf area index (LAI) and fractional vegetation coverage (FVC), respectively． The CI data quality in the growing season is improved compared to CI yearly means． Thirty percent (30%) of selected representative CIs show significant long-term variation trend, mostly falling within −0.005 per year to 0.005 per year． Such a trend is related to the trends of LAI and FVC to varying degrees, particularly when CIs present negative correlations with LAI and FVC． This study helps potential users to optimize CI product data, improves understanding of long-term trend of MODIS CI products, thereby supports potential applications in relation to CIs as input in global carbon and water cycle．