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Abstract Snow is the most reflective natural surface on Earth. Since fresh snow on bare sea ice increases the surface albedo, the impact of summer snow accumulation can have a negative radiative forcing effect, which would inhibit sea ice surface melt and potentially slow sea‐ice loss. However, it is not well known how often, where, and when summer snowfall events occur on Arctic sea ice. In this study, we used in situ and model snow depth data paired with surface albedo and atmospheric conditions from satellite retrievals to characterize summer snow accumulation on Arctic sea ice from 2003 to 2017. We found that, across the Arctic, ∼2 snow accumulation events occurred on initially snow‐free conditions each year. The average snow depth and albedo increases were ∼2 cm and 0.08, respectively. 16.5% of the snow accumulation events were optically thick (>3 cm deep) and lasted 2.9 days longer than the average snow accumulation event (3.4 days). Based on a simple, multiple scattering radiative transfer model, we estimated a −0.086 ± 0.020 W m−2change in the annual average top‐of‐the‐atmosphere radiative forcing for summer snowfall events in 2003–2017. The following work provides new information on the frequency, distribution, and duration of observed snow accumulation events over Arctic sea ice in summer. Such results may be particularly useful in understanding the impacts of ephemeral summer weather on surface albedo and their propagating effects on the radiative forcing over Arctic sea ice, as well as assessing climate model simulations of summer atmosphere‐ice processes.
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The Effect of Atmospheric Transmissivity on Model and Observational Estimates of the Sea Ice Albedo Feedback
Abstract The sea ice-albedo feedback (SIAF) is the product of the ice sensitivity (IS), that is, how much the surface albedo in sea ice regions changes as the planet warms, and the radiative sensitivity (RS), that is, how much the top-of-atmosphere radiation changes as the surface albedo changes. We demonstrate that the RS calculated from radiative kernels in climate models is reproduced from calculations using the “approximate partial radiative perturbation” method that uses the climatological radiative fluxes at the top of the atmosphere and the assumption that the atmosphere is isotropic to shortwave radiation. This method facilitates the comparison of RS from satellite-based estimates of climatological radiative fluxes with RS estimates across a full suite of coupled climate models and, thus, allows model evaluation of a quantity important in characterizing the climate impact of sea ice concentration changes. The satellite-based RS is within the model range of RS that differs by a factor of 2 across climate models in both the Arctic and Southern Ocean. Observed trends in Arctic sea ice are used to estimate IS, which, in conjunction with the satellite-based RS, yields an SIAF of 0.16 ± 0.04 W m −2 K −1 . This Arctic SIAF estimate suggests a modest amplification of future global surface temperature change by approximately 14% relative to a climate system with no SIAF. We calculate the global albedo feedback in climate models using model-specific RS and IS and find a model mean feedback parameter of 0.37 W m −2 K −1 , which is 40% larger than the IPCC AR5 estimate based on using RS calculated from radiative kernel calculations in a single climate model.
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- Award ID(s):
- 1643436
- PAR ID:
- 10226095
- Date Published:
- Journal Name:
- Journal of Climate
- Volume:
- 33
- Issue:
- 13
- ISSN:
- 0894-8755
- Page Range / eLocation ID:
- 5743 to 5765
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript
- Journal Article:
- https://doi.org/10.1175/JCLI-D-19-0674.1
