Passive microwave sea ice concentration biases in the Southern Hemisphere revealed by ICESat-2 linear ice fraction

Gridded sea ice concentration (SIC) data are fundamental for understanding long-term polar climate. Since 1978, daily SIC data have been derived from passive microwave (PM) satellite observations. As SIC is not directly observed, it is obtained through an algorithmic inversion of PM brightness temperatures. Differences between PM-SIC algorithms lead to uncertainty in SIC data. Here we examine differences between several PM-SIC products and focus primarily on two: the National Snow and Ice Data Center (NSIDC) Climate Data Record (CDR), which over our study period is derived from Special Sensor Microwave Imager/Sounder (SSMIS) data, and over the Southern Ocean is largely based on the Bootstrap (BT) PM-SIC algorithm, and the Advanced Microwave Scanning Radiometer 2 (AMSR2)-based NASATeam2 (NT2) product. On individual days, changes in integrated Antarctic sea ice area (SIA) can reach as high as 1.6 million km 2 in summer with relative differences up to 37% at the annual sea ice minimum. Using more than 1.8 million coincident observations of the ICESat-2 Linear Ice Fraction (LIF) from 2018 to 2024, we find BT-based PM-SIC data underestimate Antarctic SIC by a median of 0.2 in areas classified as the marginal ice zone (MIZ), corresponding to a median relative difference in SIC of 31%. This offset is seasonally, spatially, and parametrically consistent and yields differences in apparent MIZ extent as high as 4.4 million km 2 . The offset exceeds reported CDR uncertainties that average 0.07 and cannot be explained as a consequence of sensor differences. The parametric simplicity of the observed bias means these offsets can be parameterized as a function of BT SIC alone, which could lead to an improved SIC dataset for Antarctic studies.

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Publication Details

Journal
Remote Sensing of Environment
Published
2026-10-15
DOI
https://doi.org/10.1016/j.rse.2026.115723
Primary Topic
Arctic and Antarctic ice dynamics
Type
article
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article

Passive microwave sea ice concentration biases in the Southern Hemisphere revealed by ICESat-2 linear ice fraction

Aikaterini Tavri, Christopher Horvat, Kimia Mohammadnezhad
Remote Sensing of Environment
Arctic and Antarctic ice dynamics
article

Passive microwave sea ice concentration biases in the Southern Hemisphere revealed by ICESat-2 linear ice fraction

Aikaterini Tavri, Christopher Horvat, Kimia Mohammadnezhad
article en

Abstract

Gridded sea ice concentration (SIC) data are fundamental for understanding long-term polar climate. Since 1978, daily SIC data have been derived from passive microwave (PM) satellite observations. As SIC is not directly observed, it is obtained through an algorithmic inversion of PM brightness temperatures. Differences between PM-SIC algorithms lead to uncertainty in SIC data. Here we examine differences between several PM-SIC products and focus primarily on two: the National Snow and Ice Data Center (NSIDC) Climate Data Record (CDR), which over our study period is derived from Special Sensor Microwave Imager/Sounder (SSMIS) data, and over the Southern Ocean is largely based on the Bootstrap (BT) PM-SIC algorithm, and the Advanced Microwave Scanning Radiometer 2 (AMSR2)-based NASATeam2 (NT2) product. On individual days, changes in integrated Antarctic sea ice area (SIA) can reach as high as 1.6 million km 2 in summer with relative differences up to 37% at the annual sea ice minimum. Using more than 1.8 million coincident observations of the ICESat-2 Linear Ice Fraction (LIF) from 2018 to 2024, we find BT-based PM-SIC data underestimate Antarctic SIC by a median of 0.2 in areas classified as the marginal ice zone (MIZ), corresponding to a median relative difference in SIC of 31%. This offset is seasonally, spatially, and parametrically consistent and yields differences in apparent MIZ extent as high as 4.4 million km 2 . The offset exceeds reported CDR uncertainties that average 0.07 and cannot be explained as a consequence of sensor differences. The parametric simplicity of the observed bias means these offsets can be parameterized as a function of BT SIC alone, which could lead to an improved SIC dataset for Antarctic studies.

Remote Sensing of EnvironmentVol. 348
Brown University (US)
Climate action
Openalex Percentile: Top 20%
Arctic and Antarctic ice dynamics
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