Sea ice remote sensing using AMSR‐E 89‐GHz channels
Abstract
Recent progress in sea ice concentration remote sensing by satellite microwave radiometers has been stimulated by two developments: First, the new sensor Advanced Microwave Scanning Radiometer‐EOS (AMSR‐E) offers spatial resolutions of approximately 6 × 4 km at 89 GHz, nearly 3 times the resolution of the standard sensor SSM/I at 85 GHz (15 × 13 km). Second, a new algorithm enables estimation of sea ice concentration from the channels near 90 GHz, despite the enhanced atmospheric influence in these channels. This allows full exploitation of their horizontal resolution, which is up to 4 times finer than that of the channels near 19 and 37 GHz, the frequencies used by the most widespread algorithms for sea ice retrieval, the NASA‐Team and Bootstrap algorithms. The ASI algorithm used combines a model for retrieving the sea ice concentration from SSM/I 85‐GHz data proposed by Svendsen et al. (1987) with an ocean mask derived from the 18‐, 23‐, and 37‐GHz AMSR‐E data using weather filters. During two ship campaigns, the correlation of ASI, NASA‐Team 2, and Bootstrap algorithms ice concentrations with bridge observations were 0.80, 0.79, and 0.81, respectively. Systematic differences over the complete AMSR‐E period (2002–2006) between ASI and NASA‐Team 2 are below −2 ± 8.8%, and between ASI and Bootstrap are 1.7 ± 10.8%. Among the geophysical implications of the ASI algorithm are: (1) Its higher spatial resolution allows better estimation of crucial variables in numerical atmospher…
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Spreen et al. (2008) adapted the GR3719v threshold to 0.045 and GR2219v to 0.040 when processing sea-ice concentration with AMSR-E data.
“For example, Spreen et al. (2008) adapted the GR3719v threshold to 0.045 and GR2219v to 0.040 when processing seaice concentration with AMSR-E data.”
From Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records (2019) · cites this paper as Spreen et al. (2008)
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Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records
Lavergne, T., Sørensen, A. M., Kern, S., Tonboe, R., Notz, D., Aaboe, S., Bell, L., Dybkjær, G., Eastwood, S., Gabarro, C., et al. (2019) · The Cryosphere · doi:10.5194/tc-13-49-2019 · Cited by 469 · see citing works
“This is the essence of the dynamic tuning approaches adopted in Tonboe et al. (2016) and further developed for the new CDRs (Sect.”
MethodInfluentialSelf-citationPagano, A. M., Durner, G. M., Amstrup, S. C., Simac, K. S., & York, G. S. (2012) · Canadian Journal of Zoology · doi:10.1139/z2012-033 · Cited by 98 · see citing works
- Authors
- Spreen, G., Kaleschke, L., & Heygster, G.
- Affiliations
- Universität Hamburg (DE)
- University of Bremen (DE)
- Venue
- Journal of Geophysical Research: Oceans
- Publisher
- American Geophysical Union (AGU)
- Published
- 2008-01-17
- Volume
- 113
- Issue
- C2
- ISSN
- 0148-0227 (ISSN-L)
- OpenAlex
- W1970590897
- Cited by
- 1,676
- References
- 0
- Citations by year
- 2026: 74 · 2025: 104 · 2024: 143 · 2023: 223 · 2022: 205 · 2021: 186 · 2020: 118 · 2019: 92 · 2018: 90 · 2017: 56 · 2016: 71 · 2015: 54 · 2014: 57 · 2013: 55 · 2012: 43
- FWCI
- 21.33
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Geophysical Research Atmospheres (publishedVersion)
- Max Planck Digital Library (submittedVersion)
- MPG.PuRe (Max Planck Society) (submittedVersion)
- Topics
- Physical Sciences › Earth and Planetary Sciences › Atmospheric Science › Arctic and Antarctic ice dynamics
- Physical Sciences › Earth and Planetary Sciences › Atmospheric Science › Cryospheric studies and observations
- Physical Sciences › Earth and Planetary Sciences › Oceanography › Ocean Waves and Remote Sensing
- Keywords
- sea ice concentration, AMSR-E, microwave radiometry, SSM/I, bootstrap algorithm, spatial resolution, air-sea heat flux, polynyas, satellite remote sensing
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