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scattering surface. In addition to employing the CMB shift parameter R by defining the reduced distance in the flat universe to the last scattering surface z$_{∗}$ as done in [11] 

we will add the acoustic scale l$_{a}$ in the data analysis. The acoustic scale l$_{a}$ is defined by 

where the redshift z$_{∗}$ is given by [21] 

<img src='content_image/358898.jpg'>

<img src='content_image/358897.jpg'>

<img src='content_image/358896.jpg'>

<img src='content_image/358895.jpg'>

We have three fitting parameters x$_{i}$ = ( R, l$_{a}$, z$_{∗}$ ) to include the CMB information now. Thus we have χ 2 $_{cmb}$( p , h, Ω$_{b}$ h $^{2}$) = ∑ ij Δ x$_{i}$ Cov − $^{1}$( x$_{i}$, x$_{j}$ )Δ x$_{j}$ , Δ x$_{i}$ = x$_{i}$ − x obs i and Cov( x$_{i}$, x$_{j}$ ) is the covariance matrix for the three parameters [22]. The CMB information provides a systematic check of the DE model by combining with the low redshift SNIa and BAO data sets. 

## III. FITTING RESULTS 

We employ the Monte-Carlo Markov Chain (MCMC) method to explore the parameter space p and the nuisance parameters h and Ω$_{b}$ h 2 in the data analysis. Our MCMC code [18] is based on the publicly available package COSMOMC [23]. 

We first explore the widely used CPL parametrization [9, 10] 

<img src='content_image/358894.jpg'>

In this model, the dimensionless Hubble parameter for a flat universe is 

<img src='content_image/358893.jpg'>

In this model, we have three parameters p = (Ω$_{m}$$_{0}$ , w$_{0}$, w$_{a}$ ). Knowing the expansion history of the universe, we can construct the Om diagnostic by defining 

<img src='content_image/358892.jpg'>

