Using a 3-km regional ensemble prediction system (EPS), this study tested a 3-dimensional (3-D) rescaling mask for initial condition (IC) perturbation. Whether the 3-D mask-based EPS improves ensemble forecasts over current 2-dimensional (2-D) mask-based EPS has been evaluated in three aspects: ensemble mean, spread and probability. The forecasts of wind, temperature, geopotential height, sea-level pressure and precipitation were examined for a summer month (1-28 July 2018) and a winter month (1-27 February 2019) over a region in North China. The EPS was run twice per day (initiated at 0000 and 1200 UTC) to 36 hours in forecast length, providing 56 warm-season forecast cases and 54 cold-season cases for verification. The warm and cold seasons are verified separately for comparison. The study found that (1) vertical profile of IC perturbation becomes closer to that of analysis uncertainty with the 3-D rescaling mask. (2) Ensemble performance is significantly improved in all three aspects. The biggest improvement is in ensemble spread, followed by probabilistic forecast, and the least improvement is in ensemble mean forecast. Larger improvements are seen in warm season than cold season. (3) More improvement is in shorter time range (<24hr) than longer range. (4) Surface and lower-level variables are improved more than upper-level ones. (5) The underlying mechanism for the improvement has been investigated. Convective instability is found to be responsible for the spread increment and, thus, overall ensemble forecast improvement. Therefore, using 3-D rescaling mask is recommended for an EPS to increase its utility especially for shorter time range and surface weather elements.