0 0.2 0.4 0.6 0.8 1 0 0.2 0.4 0.6 0.8 1 (a) z Omz 0 0.2 0.4 0.6 0.8 1 0 0.2 0.4 0.6 0.8 1 (b) z Omz 0 0.2 0.4 0.6 0.8 1 0 0.2 0.4 0.6 0.8 1 (c) z Omz 0 0.2 0.4 0.6 0.8 1 0 0.2 0.4 0.6 0.8 1 (d) z Omz FIG. 4: The marginalized 1 σ and 2 σ errors of Om ( z ) reconstructed in the CPL model with SNIa+BaoR. The SNIa data used in (a)-(d) are Cstb, Cstc, Cstd, and Sdss2, respectively. Cata SNIa with BaoR, BaoZ or Bao4, so the ΛCDM model is excluded at 1 σ level if use the combination of Csta SNIa and BAO data. However, when the WMAP5 data is added, the ΛCDM model is consistent at 1 σ level. The growth in the value of Om ( z ) at low redshifts becomes smaller when we change the BAO data from BaoR to BaoZ or Bao4. In Fig. 4, we show the marginalized 1 σ and 2 σ errors of Om ( z ) reconstructed using the BaoR and different SNIa data sets. The growth in the value of Om ( z ) at low redshifts in Fig. 3a by using Csta+BaoR as observed in [11] gets flattened if we change SNIa data sets from Csta to Cstb, Cstc, Cstd and Sdss2. This shows that the finding in [11] is not a general behavior even at low z . The evolutional behavior of Om ( z ) at low redshifts is changed for different selections of the SNIa data. Thus the striking observation that our universe is slowing down [11] based on the fitting at low redshifts for CPL ansatz is caused by the systematics of the specially chosen SNIa and BAO data sets. By choosing some other data sets, the CPL 10