Assimilation of MODIS snow cover and NASA MEaSUREs landscape freeze/thaw observations into the Noah-MP model across High Mountain Asia

In order to better quantify hydrologic changes in the High Mountain Asia (HMA) region, this study explores the use of a hyper-resolution (1km) land data assimilation (DA) framework developed within the NASA Land Information System using the Noah Multi-parameterization Land Surface Model forced by the Modern-Era Retrospective analysis for Research and Applications, Version 2. Two different sets of DA experiments are conducted, including the satellite-derived snow cover map (MOD10A1) assimilation, and the NASA MEaSUREs landscape freeze/thaw state assimilation. The performance of the snow cover assimilation system is evaluated via comparisons to state-of-the-art, satellite-based snow water equivalent product as well as available ground-based snow depth measurements. The performance of the freeze/thaw assimilation system is evaluated via comparisons to the satellite-based skin temperature product (MOD11A1) as well as available ground-based skin temperature, and top two layers (0-10cm, and 10cm-30cm) of soil temperature measurements. The goodness-of-fit statistics are slightly improved as a result of DA. For example, in the comparison against ground-based soil temperature measurements along the Himalayas in Water Year 2008, the bias and root-mean-squared errors in the top-layer soil temperature are reduced (on average) by 6% and 5%, respectively. The improvements in the top-layer soil estimates also propagate through the deeper soil layers, where the bias and root-mean-squared errors in the second-layer soil temperature are reduced (on average) by 7% and 4%, respectively. Therefore, the proposed DA schemes show promise in improving the predictability of snow and soil related states across HMA, but more ground-based measurements are still required to further evaluate the proposed methodology.