Abstract
AbstractSea ice thickness is a critical variable, both as a climate indicator and for forecasting sea ice conditions on seasonal and longer time scales. The lack of snow depth and density information is a major source of uncertainty in current thickness retrievals from laser and radar altimetry. In response to this data gap, a new Lagrangian snow evolution model (SnowModel‐LG) was developed to simulate snow depth, density, and grain size on a pan‐Arctic scale, daily from August 1980 through July 2018. In this study, we evaluate the results from this effort against various data sets, including those from Operation IceBridge, ice mass balance buoys, snow buoys, MagnaProbes, and rulers. We further compare modeled snow depths forced by two reanalysis products (Modern Era Retrospective‐Analysis for Research and Applications, Version 2 and European Centre for Medium‐Range Weather Forecasts Reanalysis, 5th Generation) with those from two historical climatologies, as well as estimates over first‐year and multiyear ice from satellite passive microwave observations. Our results highlight the ability of our SnowModel‐LG implementation to capture observed spatial and seasonal variability in Arctic snow depth and density, as well as the sensitivity to the choice of reanalysis system used to simulate snow depths. Since 1980, snow depth is found to decrease throughout most regions of the Arctic Ocean, with statistically significant trends during the cold season months in the marginal ice zones around the Arctic Ocean and slight positive trends north of Greenland and near the pole.
Highlights
Sea ice plays a fundamental role in the Earth's climate system, influencing the amount of heat and moisture exchanged between the ocean and the atmosphere, and plays an important role in deepwater formation, a major driver of the global thermohaline circulation
As described in Part I, annual mean precipitation from each of the reanalysis was adjusted using mean calibration scaling factors averaged over 8 years (2009 through 2016) determined by comparing SnowModel‐LG snow depths with Operation IceBridge (OIB) snow depths from the QuickLook product
These aggregated OIB snow depths are compared with SnowModel‐LG snow depths for 1 April, and the reanalysis precipitation is adjusted by a scaling factor so that the difference between OIB and SnowModel‐LG is minimized
Summary
Sea ice plays a fundamental role in the Earth's climate system, influencing the amount of heat and moisture exchanged between the ocean and the atmosphere, and plays an important role in deepwater formation, a major driver of the global thermohaline circulation. Sea ice protects coastal regions from wind waves and storm surges and influences coastal and marine ecosystems, as well as a number of economic and societal activities. Once the melt season ends, new snow will start to accumulate on the ice, increasing its insulative properties and impacting thermodynamic ice growth. The snow cover limits the amount of photosynthetic light reaching the bottom of the ice, impacting underice biota (Mundy et al, 2007). When the melt season starts, the snowmelts provides water for melt pond development (Eicken et al, 2004; Iacozza & Barber, 2001; Perovich et al, 2002).
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