Towards a better understanding of hydrological interactions between the land surface and atmosphere, land surface models are routinely used to simulate hydro-meteorological fluxes. However, there is a lack of observations available for model forcing, to estimate the hydro-meteorological fluxes in East Asia. In this study, Common Land Model(CLM) was used in offline-mode during the summer monsoon period of 2006 in East Asia, with different forcings from Asiaflux, Korea Land Data Assimilation System(KLDAS), and Global Land Data Assimilation System(GLDAS), at point and regional scales,separately. The CLM results were compared with observations from Asiaflux sites. The estimated net radiation showed good agreement, with r = 0.99 for the point scale and 0.85 for the regional scale. The estimated sensible and latent heat fluxes using Asiaflux and KLDAS data indicated reasonable agreement, with r = 0.70. The estimated soil moisture and soil temperature showed similar patterns to observations, although the estimated water fluxes using KLDAS showed larger discrepancies than those of Asiaflux because of scale mismatch. The spatial distribution of hydro-meteorological fluxes according to KLDAS for East Asia were compared to the CLM results with GLDAS, and the GLDAS provided online. The spatial distributions of CLM with KLDAS were analogous to CLM with GLDAS, and the standalone GLDAS data. The results indicate that KLDAS is a good potential source of high spatial resolution forcing data. Therefore, the KLDAS is a promising alternative product,capable of compensating for the lack of observations and low resolution grid data for East Asia. Towards a better understanding of hydrological interactions between the land surface and atmosphere, land surface models are routinely used to simulate hydro-meteorological fluxes. However, there is a lack of observations available for model forcing, to estimate the hydro-meteorological fluxes in East Asia . In this study, Common Land Model (CLM) was used in offline-mode during the summer monsoon period of 2006 in East Asia, with different forcings from Asiaflux, Korea Land Data Assimilation System (KLDAS), and Global Land Data Assimilation System The estimated net radiation showed good agreement, with r = 0.99 for the point scale and 0.85 for the regional scale. The estimated sensible and latent heat fluxes using Asiaflux and KLDAS data indicated reasonable agreement, with r = 0.70. The estimated soil moisture and soil temperature showed similar patterns to observations, although the estimated water fluxes using KLDAS showed larger discrepancies than those of Asiaflux because of scale mismatch. The spatial distribution of hydro-meteorological fluxes according to KLDAS for East Asia were compared to the CLM results with GLDAS, and the GLDAS provided online. The spatial distributions of CLM with KLDAS were analogous to CLM with GLDAS, and the standalone GLDAS data. The results indicate that KLDAS is a good potential source of high spatial resolution forcing data. Therefore, the KLDAS is a promising alternative product, capable of compensating for the lack of observations and low resolution grid data for East Asia.