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Impact of ice surface and volume scatterings on the microwave sea ice apparent emissivity

Cited 15 time in Web of Science Cited 15 time in Scopus
Authors

Lee, Sang-Moo; Sohn, Byung-Ju; Shi, Hoyeon

Issue Date
2018-09
Publisher
American Geo
Citation
Journal of Geophysical Research-atmospheres, Vol.123 No.17, pp.9220-9237
Abstract
Emissivity retrieval for sea ice from passive microwave measurements has been an important problem in climate/environmental research because of its link to various snow/ice variables. However, so far, it has been a difficult task because of the influences of surface and snow/ice induced volume scatterings. Here we examine the influences of scatterings on the ice emissivity from 10.65, 18.7, 23.8, and 36.5GHz Advanced Microwave Scanning Radiometer (AMSR)-E brightness temperatures over the Arctic Ocean. In doing so, we use a two-dimensional roughness parameterization, modified with surface facet orientations with an assumption that the facet emission follows the Fresnel relationship. Emitting layer temperature and refractive index retrieved from AMSR-E 6.9GHz brightness temperature measurements were used in this study and applied to other channels of interest. We demonstrated that the obtained roughness index has a strong linear relationship with the root-mean-square height measured by Atmospheric Terrain Mapper on the National Aeronautics and Space Administration (NASA) P-3 aircraft. The obtained roughness index showed that surface scattering on the emissivity is generally insignificant except for some first-year ice regions in particular at higher frequencies. This fact implies that Fresnel relations can be applicable for most of sea ice at the low-frequency microwave spectrum. By contrast, volume scattering is found to be significant in emissivity retrieval in case of multiyear ice. Nonetheless, volume scattering influence over first-year ice appears to be minor. We suggest that Fresnel-type emissivity can be estimated once a correction factor is used for removing surface scattering and volume scattering contributions from the apparent emissivity.
ISSN
2169-897X
Language
ENG
URI
https://hdl.handle.net/10371/154380
DOI
https://doi.org/10.1029/2018JD028688
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  • College of Natural Sciences
  • Department of Earth and Environmental Sciences
Research Area Data Assimilation for Numerical Weather Prediction, Radiative Transfer Modeling, Satellite Remote Sensing

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