Evaluating and enhancing snow compaction process in the Noah-MP land surface model

However, there has been little research that has focused on enhancing snow compaction in operationally used LSMs. A baseline snow simulation with the widely used Noah-MP LSM systematically overestimates snow depth by 55 mm even after removing daily snow water equivalent (SWE) biases.

To reduce uncertainties associated with snow compaction, we enhance the most sensitive Noah-MP snow compaction parameter-the empirical parameter for compaction due to overburden (Cbd)-such that Cbd is calculated as a function of surface air temperature as opposed to a fixed value in the baseline simulation. This enhancement improves accuracy in simulated snow compaction across the majority of western U.S. (WUS) SNOTEL test sites (biases reduced at 88% of test sites), with modest bias reductions in cooler accumulation periods (biases reduced at 70% of test sites) and substantial improvements during warmer ablation periods (biases reduced at 99% of test sites).