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Precipitation measurements in the Mekong River Basin (MRB) are full of variability due to this domain's varied weather systems, climate conditions, elevation, and specific land–atmosphere interactions. This study provides an in‐depth evaluation of the differences between four gridded precipitation products [i.e. Asian Precipitation—Highly‐Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE), Tropical Rainfall Measuring Mission (TRMM), CPC MORPHing technique (CMORPH), and Climatic Research Unit (CRU)] over the Greater Mekong Subregion. Precipitation data from a total of 242 stations in this domain are used to investigate the quality of the gridded products. Our analysis verifies that gauge‐based APHRODITE exhibits the highest correlations with the station data as well as the highest probability of detection of daily precipitation. The false alarm ratio, on the other hand, is slightly in favour of TRMM and CMORPH. Subtracting APHRODITE (as baseline) from TRMM and CMORPH reveals the spatial and frequency distribution of potential biases. The results indicate that TRMM appears to have a wet bias in most areas, while CMORPH shows no similar or consistent bias over APHRODITE. To utilize the higher accuracy of APHRODITE and the finer spatial and temporal footprints of CMORPH, a new restructuring algorithm is introduced in this study. The algorithm is capable of eliminating biases and possible artefacts associated with CMORPH while resolving the resolution discrepancies between the two data sets.

At a local scale, the interception capacity of the canopy depends on a variety of climatic and canopy factors. Of particular importance is the intensity of rainfall-interception capacity varies inversely with rainfall intensity. At a field or regional scale, like the scale of global climate models, the spatially averaged interception also depends significantly on the spatial variability of rainfall intensity and total precipitation depth. A new parameterization of canopy interception is developed. In the new parameterization, the spatial average of actual interception is obtained as a function of rainfall intensity and total precipitation depth, and of an interception capacity, which depends on the characteristics of the leaf surface and of the vegetation cover. In a statistical-dynamical framework, the new parameterization also accounts for the subgrid-scale spatial variability of rainfall intensity and total precipitation depth. The implications of accounting for the dependence of interception capacity on rainfall characteristics are examined by assessing the consequent responses of the energy and the water fluxes at the land surface. This is accomplished by incorporating the new parameterization into a soil-plant-atmosphere column model that is fundamentally based on the physical parameterizations of NCAR's Community Climate Model.