Background, aim, and scope It is essential for researchers to know more about past climate variations from the study of climatic proxy data, such as ice core, loess, tree-ring and stalagmite. Tree-ring, due to its accurate dating, continuous, high resolution and sensitive to climate change, has been widely used to reconstruct the past climatic index. Many paleoclimate series has been rebuilt based on tree-ring width by researchers. In China, tree-ring studies in the subtropical regions are much rarer than extratropical regions, which are mainly caused by the complex relationship between environmental factors and the tree-ring growth in subtropical area and the difficulty in cross dating. Our study aimed to reveal the responding mechanism of tree-rings to climate factors. Materials and methods In our study, the standardized tree-ring width chronology was developed based on 90 tree-ring cores from 42 healthy Pinus massoniana, collected from Guilin, in subtropical south China (25°22′ 25°23′N, 110°31′ 110°32′E, 480 m a.s.l) during September, 2015. All the tree-ring cores were dealt with standard dendrochronological method. The cores were visually dated and measured using the LINTAB measurement machine with resolution of 0.01 mm and cross dated by the COFECHA program. Then we use the series that successfully passed the COFECHA program to develop the standardized tree-ring chronology via the ARSTAN program. Considering the complex environment of sampling site, we use the mean meteorological data of the nearest three weather stations (Guilin station, Rongan station and Daoxian station, records from 1959 to 2014) to reduce the possible influence of micro-climate. To determine whether the climate had impact on the radial growth of Pinus massoniana and which climate factor limited tree growth most, we used Pearson correlation analyses to calculate the correlation coefficients between ring-width STD chronology and climate factors. Global Monthly Dai Palmer Drought Severity Index (PDSI) (108.75° 111.25°E, 23.75° 26.25°N, 1942 2005) were also analysed against the STD chronology. Spatial correlation patterns of the observed temperature and the STD chronology and the gridded data (land temperatures and SST) were calculated via the website http://climexp.knmi.nl. Results Growth-climate response analyses showed that the growth of Pinus massoniana negatively correlated with the monthly mean temperature variability of current June September (r= -0.51, p<0.01) and previous February November (r= -0.53, p<0.01), positively correlated with the previous October precipitation (r= 0.32, p<0.05). Tree rings also significantly correlated with the monthly relative humidity and PDSI of current June, July and August. Result of spatial correlation showed that the XGGD tree-ring STD chronology significantly correlated with the temperatures in the monsoon fringe area and north Indochina Peninsula area. Spatial correlation pattern between tree-ring STD chronology and SST also showed a shift before and after 1977. Discussion In the study, no significant correlation was found between the meteorological data and chronology in the early stage of tree growth.