Tree-ring width (TRW) and stable carbon isotope (δ¹³C) in tree-ring cellulose of subalpine fir (Abies fabri) were used to develop high-resolution climate proxy data to indicate snow-depth variations in the Gongga Mountain, west China. Tree radial growth- and δ¹³C-climate response analyses demonstrated that the TRW and δ¹³C at the timberline (3,400 m.a.s.l.) are mainly influenced by temperature and precipitation of previous growth seasons and current summer (June to August) under cold and humid conditions. Considering the analogous control factors on both tree growth and carbon isotope discrimination (Δ¹³C) and snow accumulation, the negative and significant relationships between tree-ring parameters (TRW and Δ¹³C) and mean monthly snowpack depth were found. Herein, by combining two tree-ring parameters, a primary snow-depth reconstruction (previous October to current May) over the reliable period A.D. 1880–2004 was estimated. The reconstruction explains 58.0% of the variance in the instrumental record, and in particular captures the longer-term fluctuations successfully. Except the period with extreme higher snowpack depth around 1990, the snowpack depth seems to fluctuate in a normal way. The reconstruction agrees with the nearby snowpack depth record in Kangding and the mean observed snowpack-depth variations of the stations on the Tibetan Plateau, particularly at long-term scales. The snowpack depth in low-frequency fluctuations, during the past century, agrees quite well with the Eastern India precipitation covering the period of previous October–current May. Our results suggest that combing tree-ring width and δ¹³C in certain subalpine tree species growing on the Tibetan Plateau may be an effective way for reconstructing regional snowpack variations.