Abstract. This study examines the uncertainty in calculating the fundamental climatological characteristics of precipitation in the East Asia region from multiple fine-resolution gridded analysis data sets based on in situ rain gauge observations and data assimilations. Five observation-based gridded precipitation data sets are used to derive the long-term means, standard deviations in lieu of interannual variability and linear trends over the 28-year period from 1980 to 2007. Both the annual and summer (June-July-August) mean precipitation is examined. The agreement amongst these precipitation data sets is examined using two metrics including the signal-to-noise ratio (SNR) defined as the ratio between long-term means and the corresponding standard deviations, and Taylor diagrams, which allow examinations of the pattern correlation, the standard deviation, and the centered root mean square error. It is found that the five gauge-based precipitation analysis data sets agree well in the long-term mean and interannual variability in most of the East Asia region including eastern China, Manchuria, South Korea, and Japan, which are densely populated and have fairly highdensity observation networks. The regions of large interdata-set variations include Tibetan Plateau, Mongolia, northern Indo-China, and North Korea. The regions of large uncertainties are typically lightly populated and are characterized by severe terrain and/or extremely high elevations. Unlike the long-term mean and interannual variability, agreement between data sets in the linear trend is weak, both for the annual and summer mean values. In most of the East Asia region, the SNR for the linear trend is below 0.5: the interdata-set variability exceeds the multi-data ensemble mean.The uncertainty in the spatial distribution of long-term means among these data sets occurs both in the spatial pattern and variability, but the uncertainty for the interannual variability and time trend is much larger in the variability than in the pattern correlation. Thus, care must be taken in using long-term trends calculated from gridded precipitation analysis data for climate studies over the East Asia region.

Abstract. The Tibetan Plateau is a critical region in the research of biosphere-atmosphere interactions on both regional and global scales due to its relation to Asian summer monsoon and El Niño. The unique environment on the Plateau provides valuable information for the evaluation of the models' surface energy partitioning associated with the summer monsoon. In this study, we investigated the surface energy partitioning on this important area through comparative analysis of two biosphere models constrained by the in-situ observation data. Indeed, the characteristics of the Plateau provide a unique opportunity to clarify the structural deficiencies of biosphere models as well as new insight into the surface energy partitioning on the Plateau. Our analysis showed that the observed inconsistency between the two biosphere models was mainly related to: 1) the parameterization for soil evaporation; 2) the way to deal with roughness lengths of momentum and scalars; and 3) the parameterization of subgrid velocity scale for aerodynamic conductance. Our study demonstrates that one should carefully interpret the modeling results on the Plateau especially during the pre-monsoon period.