As the first application of the coupled DART and CLM framework, this work is focused on assimilating the Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover fraction data. The 0.05ºMOD10C1 data were preprocessed by binning up to 0.94º×1.25º to match the model grid. Results show that the coupled DART and CLM tends to adjust the snow water equivalent (SWE) fields where the largest snow variability exists. The assimilation within this framework is properly reducing the Root Mean Square Error of SWE at each assimilation step. The effectiveness of the assimilation is further assessed by evaluating the 24‐hour forecasts against the observations before they are assimilated. Further explorations are made to choose the best localization value for CLM4 snow data assimilation through perfect model experiments. A series of different error variance values for MODIS observation data sets are applied to test the sensitivity of the data assimilation system to observation error variance.