Global climate change will have great effects on ecological systems, natural resources, food security, climate extremes, cryosphere and the damage to human social living conditions. Scientific assessment of projected climate change impacts is a vital way for stakeholder and policymaker to adjust strategies at the local scale. Outline of contents and related methods and key issues are discussed for climate change impacts study on RCP45 and RCP85 scenarios of Coupled Model Intercomparison Project Phase 5 (CMIP5) climate models by the summary of the current literatures. The article investigates the necessity of applicability evaluation before using the climate models from CMIP5 at the region and summarizes the methods applied to metric whether the model is reasonable to project the climate scenarios in the region. Downscaling methods that can bridge the gap between the coarse spatial resolution of global circulation model (GCM) and high resolution of climate variables are required for impacts evaluation at the local scale. The review introduces the fundamental principles and current main methods for downscaling climate variables, especially for statistical downscaling, and summarizes the latest progresses in this field. The GCM often show significant biases that include systematic model errors caused by imperfect conceptualization, discretization and spatial averaging within the grid cell. So bias correction methods are applied to remedy the biased output of GCM, RCM and downscaled them. We conclude with the commonly using bias correction method and recent development in this field. How to deal with uncertainties from GCM, downscaling method and bias correction is also a challenge for impact study. The article discusses the uncertainties in every step of the whole process. The review will provide the guideline for projection of climate change impacts in the region.