Abstract
Based on decadal hindcast experiments of BCC-CSM1.1, FGOALS-g2, FOAM-EAKF, FOAM-NUDGING, GFDL-CM2.1 and MPI-M initialized every five years during 1960-2005, the hindcast skills of surface air temperature (2mT) over East Asia are evaluated. The results show that the skill of the 2mT hindcasts of each model is pretty low over the Tibetan Plateau due to complex topography there. The 2-5 year hindcast skill of climate variability based on the detrended 2mT hindcast is significantly lower than that of the original data with well predicted linear trend. The multimodel superensemble (SUP) based on cross-validation and ensemble mean (MEM) hindcast skills are much higher than those of individual models in terms of the RMSE. In addition, the SUP hindcast skill is higher than that of the MEM hindcast.
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