conditions ensuring a central limit theorem for strongly mixing triangular arrays are given. larger samples can show longer range dependence than shorter samples. the result is obtained by constraining the rate growth of dependence as a function of the sample size, with the usual trade-off of memory and moment conditions. an application to heteroskedasticity and autocorrelation consistent estimators is proposed.