Constellation Evaluation Tools for a New Snow Observing Strategy

Snow water equivalent (SWE) measurements are crucial for efficiently managing the effects of snow on the environment and human activities. The limitations of providing global snow water equivalent data required to address essential hydrological science questions from existing satellite sensors could potentially be overcome by the emergence of commercial small-satellite platforms, like CubeSats. This research develops a snow observing framework that considers high-resolution observations in critical areas and operational tasking requests from commercial small-satellite platforms by analyzing historical SWE data from the ERA5-Land reanalysis data set. The study finds that going from 4 to 12 satellites in a constellation, not only increases the maximum SWE data observed by 170 mm/hr, but it also does it in a more cost-effective way, increasing the cost only 35%.