Impact of the GCM Errors on Dynamic Downscaling in the Tibetan Plateau
Friday, 19 December 2014
Tibet Plateau (TP) is one of the most sensitive areas responding to global climate change due to its high altitude and the presence of permafrost and glaciers. Climate change research and terrestrial responses to climate change over the TP is limited to a large extends due to the harsh nature condition and limited in-situ observations. GCMs are useful tools to be implemented in climate change study but with lots deficiency. GCMs could not provide regional information due to the coarse resolution. Using a regional climate model and driven by GCMs, dynamic downscaling could provide physics-based high-resolution information for the related researches. Downscaling is expected to perform better than the coarse resolution forcing. However, GCMs possess biases themselves due to various factors. GCMs biases will be passed over to RCMs nevertheless. Therefore, it is worth to consider to what extends the GCMs biases impact the downscaling results? Recently, a 120-years dynamic downscaling driven by CCSM4 was conducted in the Asia. To address the impact of GCMs biases, the 25-years (1980-2005) historical downscaling results will be compared to simulations driven by the reanalysis in the TP.