White birch represents one of the largest standing volumes among the hardwood species in the temperate or subarctic regions of Asia. Its tree growth has experienced noticeable climate-induced changes during the past years (see: Gradel et al., 2017a; doi:10.1016/j. dendro.2016.03.005, Gradel et al., 2017b; doi:10.1186/s40663-017-0110-2 and Jiang et al., 2021; doi: 10.1186/s40663-017-0110-2). Therefore, understanding growth characteristics is crucial to managing and predicting White birch forests under future climate change. The growth rate of White birch plantations is an essential indicator for evaluating carbon dioxide storage potential. Allometry is the most reliable and commonly used method for estimating forest biomass, volume, net primary productivity, etc. (Djomo et al., 2010; doi:10.1016/j.foreco.2010.08.034, Peng et al., 2019; doi:10.3390/rs11192270 and Zhou et al., 2021; doi:10.1038/s41477-020-00815-8).However, the lack of large-diameter trees in the data samples of the previous studies limits these model's application (see: Anitha et al., 2015; doi:10.1007/s13595-015-0507-4 and Xu et al., 2021; doi:10.1016/j.foreco. 2021.119918). In addition, we were unaware of any allometric equations available at the regional scale. To implement global forest carbon sink monitoring and assessment, developing a single tree species allometric growth equation suitable for large-scale estimation has become a trend (Zeng et al., 2011; doi:10. 1038/npre. 2011.6704.1). Published papers from 1954 to 2018) on tree growth of White birch forests in East Asia were collected and critically reviewed. Subsequently, a comprehensive growth data set was obtained from 158 sites, which are distributed from 93.1° to 159.55°E in longitude, from 29.78° to 62.25°N in latitude and from 30 to 4200 m in altitude. The dataset contains 600 entries, including mean DBH (cm), mean H (m), volume (m3), and related information, i.e. geographical location (Country, province, study site, longitude, latitude, altitude, slope, and aspect), climate (mean annual precipitation-MAP and mean annual temperature-MAT), stand description (origin, age, canopy density and stand density), and sample regime (plot size, number and investigation year).