In this paper, an innovative threshold measurement equation is proposed to be employed in a Realized-GARCH framework. The proposed framework employs a nonlinear threshold regression specification to consider the leverage effect and model the contemporaneous dependence between the observed realized measures and hidden volatility. A Bayesian Markov Chain Monte Carlo method is adapted and employed for the model estimation and forecasting, with its validity assessed via a simulation study. The usefulness of the proposed measurement equation in a Realized-GARCH model has been evaluated via a comprehensive empirical study, by forecasting the 1% and 2.5% Value-at-Risk and Expected Shortfall on six market indices. The proposed framework is shown to be capable of producing competitive tail risk forecasting results, compared to the original Realized-GARCH. Especially, the proposed model is favoured during the high volatility 2008 Global Financial Crisis period.