Abstract
Abstract. The NASA Eulerian Snow On Sea Ice Model (NESOSIM) is a new, open-source snow budget model that is currently configured to produce daily estimates of the depth and density of snow on sea ice across the Arctic Ocean through the accumulation season. NESOSIM has been developed in a three-dimensional Eulerian framework and includes two (vertical) snow layers and several simple parameterizations (accumulation, wind packing, advection–divergence, blowing snow lost to leads) to represent key sources and sinks of snow on sea ice. The model is forced with daily inputs of snowfall and near-surface winds (from reanalyses), sea ice concentration (from satellite passive microwave data) and sea ice drift (from satellite feature tracking) during the accumulation season (August through April). In this study, we present the NESOSIM formulation, calibration efforts, sensitivity studies and validation efforts across an Arctic Ocean domain (100 km horizontal resolution). The simulated snow depth and density are calibrated with in situ data collected on drifting ice stations during the 1980s. NESOSIM shows strong agreement with the in situ seasonal cycles of snow depth and density, and shows good (moderate) agreement with the regional snow depth (density) distributions. NESOSIM is run for a contemporary period (2000 to 2015), with the results showing strong sensitivity to the reanalysis-derived snowfall forcing data, with the Modern-Era Retrospective analysis for Research and Applications (MERRA) and the Japanese Meteorological Agency 55-year reanalysis (JRA-55) forced snow depths generally higher than ERA-Interim, and the Arctic System Reanalysis (ASR) generally lower. We also generate and force NESOSIM with a consensus median daily snowfall dataset from these reanalyses. The results are compared against snow depth estimates derived from NASA's Operation IceBridge (OIB) snow radar data from 2009 to 2015, showing moderate–strong correlations and root mean squared errors of ∼ 10 cm depending on the OIB snow depth product analyzed, similar to the comparisons between OIB snow depths and the commonly used modified Warren snow depth climatology. Potential improvements to this initial NESOSIM formulation are discussed in the hopes of improving the accuracy and reliability of these simulated snow depths and densities.
Highlights
Snow on sea ice is a crucial component of the polar climate system
We show results of NASA Eulerian Snow On Sea Ice Model (NESOSIM) forced with no ice drift (NODRIFT), which demonstrates that including ice drift appears not to be a crucial process for capturing the variability in snow depth at this regional scale; i.e., ice dynamics appear to be a clear second-order term compared to snowfall when analyzed at this regional scale
We presented the newly developed NASA Eulerian Snow On Sea Ice Model (NESOSIM) version 1.0
Summary
Snow on sea ice is a crucial component of the polar climate system. Its low thermal conductivity modulates sea ice growth through the cold winter months (e.g., Maykut and Untersteiner, 1971; Sturm et al, 2002), while its high surface albedo limits solar radiation absorption and inhibits sea ice melt in spring and summer (e.g., Warren, 1982; Grenfell and Perovich, 1984; Perovich et al, 2002). The Soviet drifting station data provide the only observationally based basin-scale assessment of snow density currently available This snow climatology is expected to be outdated due to the rapid changes experienced in the Arctic climate system over the last few decades (Webster et al, 2014), recent efforts have been made to modify this climatology based on ice type (halving the climatology over first-year ice, e.g., Laxon et al, 2013; Kwok and Cunningham, 2015). We conclude by looking ahead to potential improvements in the model physics and planned future activities related to our efforts to improve our understanding of snow on sea ice
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