Slow and significant stochastic variations named "a2-drift" variations are observed in this contribution, which are discovered during the estimation of frequency aging of BeiDou-3 rubidium (Rb) clocks. The magnitude of the variations suffered on BeiDou-3 Rbs is distinctly larger than GPS and appears to exhibit a systematic drift associated with time. The phenomenon is widely ignored and will compromise the long-term (one day and beyond) autonomy of the onboard clock units. Random run frequency modulation (RRFM) noise, which may induce similar variations, can be detected and identified by lag 1 autocorrelation function (lag 1 ACF) and Hadamard deviation. To retrace the origin of the variations, the Hadamard deviations, broadcast clock model parameter a1, and frequency drift of BeiDou-3 Rbs are estimated with reference to GPS. The variations result in long-term fluctuations on the broadcast clock parameters (a1 and a2) and arise an increase in the Hadamard deviation when the averaging time is greater than 1e(5) s. Furthermore, the simulations of the power-law noises reproduce the variations, and the lag 1 ACF supports that the variations are caused by RRFM. Besides this, many conclusions are also related to this variation. Using two years of multi-global navigation satellite system (GNSS) experiment (MGEX) clock offsets from 2019 to 2021, the following conclusions are drawn: 1) the RRFM emerges as dominant noise and causes a decline in the frequency stability when the averaging time is greater than 1e(5) s; 2) the variations on the estimated series of BeiDou-3 Rbs broadcast clock model a1 and frequency drift are more visible than those of GPS; 3) when the averaging time is approximately one day, the frequency stability of BeiDou-3 Rbs is similar to that of GPS; however, when the averaging time reaches 1e(6) s, the frequency stability of BeiDou-3 Rbs deteriorates because of the RRFM and is nearly ten times lower than that of GPS Rbs; and 4) the GPS Rbs are free from RRFM, but the BeiDou-3 Rbs contain significant features of random-walk frequency modulation (RWFM) and RRFM noise.