Global Snow Mass Measurements and the Effect of Stratigraphic Detail on 2 Inversion of Microwave Brightness Temperatures

Snow provides large seasonal storage of freshwater, and information about the distribution 6 of snow mass as Snow Water Equivalent (SWE) is important for hydrological planning and detecting 7 climate change impacts. Large regional disagreements remain between estimates from reanalyses, 8 remote sensing and modelling. Assimilating passive microwave information improves SWE estimates 9 in many regions but the assimilation must account for how microwave scattering depends on snow 10 stratigraphy. Physical snow models can estimate snow stratigraphy, but users must consider the 11 computational expense of model complexity versus acceptable errors. Using data from the National 12 Aeronautics and Space Administration Cold Land Processes Experiment (NASA CLPX) and the 13 Helsinki University of Technology (HUT) microwave emission model of layered snowpacks, it is 14 shown that simulations of the brightness temperature difference between 19 GHz and 37 GHz 15 vertically polarised microwaves are consistent with Advanced Microwave Scanning Radiometer-Earth 16 Observing System (AMSR-E) and Special Sensor Microwave Imager (SSM/I) retrievals once known 17 stratigraphic information is used. Simulated brightness temperature differences for an individual snow 18 profile depend on the provided stratigraphic detail. Relative to a profile defined at the 10 cm 19 resolution of density and temperature measurements, the error introduced by simplification to a single 20 layer of average properties increases approximately linearly with snow mass. If this brightness 21 temperature error is converted into SWE using a traditional retrieval method then it is equivalent to 22 ±13 mm SWE (7% of total) at a depth of 100 cm. This error is reduced to ±5.6 mm SWE (3 % of 23 total) for a two-layer model. 24 25