Assessment of the Stability of Passive Microwave Brightness Temperatures for NASA Team Sea Ice Concentration Retrievals
Gridded passive microwave brightness temperatures (TB) from special sensor microwave imager and sounder (SSMIS) instruments on three different satellite platforms are compared in different years to investigate the consistency between the sensors over time. The orbits of the three platforms have drif...
Published in: | Remote Sensing |
---|---|
Main Authors: | , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
MDPI AG
2020
|
Subjects: | |
Online Access: | https://doi.org/10.3390/rs12142197 https://doaj.org/article/7b5d3a40f14c495eb360ed5112bb4488 |
id |
ftdoajarticles:oai:doaj.org/article:7b5d3a40f14c495eb360ed5112bb4488 |
---|---|
record_format |
openpolar |
spelling |
ftdoajarticles:oai:doaj.org/article:7b5d3a40f14c495eb360ed5112bb4488 2023-05-15T14:00:58+02:00 Assessment of the Stability of Passive Microwave Brightness Temperatures for NASA Team Sea Ice Concentration Retrievals Walter N. Meier J. Scott Stewart 2020-07-01T00:00:00Z https://doi.org/10.3390/rs12142197 https://doaj.org/article/7b5d3a40f14c495eb360ed5112bb4488 EN eng MDPI AG https://www.mdpi.com/2072-4292/12/14/2197 https://doaj.org/toc/2072-4292 doi:10.3390/rs12142197 2072-4292 https://doaj.org/article/7b5d3a40f14c495eb360ed5112bb4488 Remote Sensing, Vol 12, Iss 2197, p 2197 (2020) sea ice passive microwave remote sensing Arctic Antarctic Science Q article 2020 ftdoajarticles https://doi.org/10.3390/rs12142197 2022-12-31T07:30:41Z Gridded passive microwave brightness temperatures (TB) from special sensor microwave imager and sounder (SSMIS) instruments on three different satellite platforms are compared in different years to investigate the consistency between the sensors over time. The orbits of the three platforms have drifted over their years of operation, resulting in changing relative observing times that could cause biases in TB estimates and near-real-time sea ice concentrations derived from the NASA Team algorithm that are produced at the National Snow and Ice Data Center. Comparisons of TB histograms and concentrations show that there are small mean differences between sensors, but variability within an individual sensor is much greater. There are some indications of small changes due to orbital drift, but these are not consistent across different frequencies. Further, the overall effect of the drift, while not definitive, is small compared to the intra- and interannual variability in individual sensors. These results suggest that, for near-real-time use, the differences in the sensors are not critical. However, for long-term time series, even the small biases should be corrected for. The strong day-to-day, seasonal, and interannual variability in TB distributions indicate that time-varying algorithm coefficients in the NASA team algorithm would lead to improved, more consistent sea ice concentration estimates. Article in Journal/Newspaper Antarc* Antarctic Arctic National Snow and Ice Data Center Sea ice Directory of Open Access Journals: DOAJ Articles Arctic Antarctic Remote Sensing 12 14 2197 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
sea ice passive microwave remote sensing Arctic Antarctic Science Q |
spellingShingle |
sea ice passive microwave remote sensing Arctic Antarctic Science Q Walter N. Meier J. Scott Stewart Assessment of the Stability of Passive Microwave Brightness Temperatures for NASA Team Sea Ice Concentration Retrievals |
topic_facet |
sea ice passive microwave remote sensing Arctic Antarctic Science Q |
description |
Gridded passive microwave brightness temperatures (TB) from special sensor microwave imager and sounder (SSMIS) instruments on three different satellite platforms are compared in different years to investigate the consistency between the sensors over time. The orbits of the three platforms have drifted over their years of operation, resulting in changing relative observing times that could cause biases in TB estimates and near-real-time sea ice concentrations derived from the NASA Team algorithm that are produced at the National Snow and Ice Data Center. Comparisons of TB histograms and concentrations show that there are small mean differences between sensors, but variability within an individual sensor is much greater. There are some indications of small changes due to orbital drift, but these are not consistent across different frequencies. Further, the overall effect of the drift, while not definitive, is small compared to the intra- and interannual variability in individual sensors. These results suggest that, for near-real-time use, the differences in the sensors are not critical. However, for long-term time series, even the small biases should be corrected for. The strong day-to-day, seasonal, and interannual variability in TB distributions indicate that time-varying algorithm coefficients in the NASA team algorithm would lead to improved, more consistent sea ice concentration estimates. |
format |
Article in Journal/Newspaper |
author |
Walter N. Meier J. Scott Stewart |
author_facet |
Walter N. Meier J. Scott Stewart |
author_sort |
Walter N. Meier |
title |
Assessment of the Stability of Passive Microwave Brightness Temperatures for NASA Team Sea Ice Concentration Retrievals |
title_short |
Assessment of the Stability of Passive Microwave Brightness Temperatures for NASA Team Sea Ice Concentration Retrievals |
title_full |
Assessment of the Stability of Passive Microwave Brightness Temperatures for NASA Team Sea Ice Concentration Retrievals |
title_fullStr |
Assessment of the Stability of Passive Microwave Brightness Temperatures for NASA Team Sea Ice Concentration Retrievals |
title_full_unstemmed |
Assessment of the Stability of Passive Microwave Brightness Temperatures for NASA Team Sea Ice Concentration Retrievals |
title_sort |
assessment of the stability of passive microwave brightness temperatures for nasa team sea ice concentration retrievals |
publisher |
MDPI AG |
publishDate |
2020 |
url |
https://doi.org/10.3390/rs12142197 https://doaj.org/article/7b5d3a40f14c495eb360ed5112bb4488 |
geographic |
Arctic Antarctic |
geographic_facet |
Arctic Antarctic |
genre |
Antarc* Antarctic Arctic National Snow and Ice Data Center Sea ice |
genre_facet |
Antarc* Antarctic Arctic National Snow and Ice Data Center Sea ice |
op_source |
Remote Sensing, Vol 12, Iss 2197, p 2197 (2020) |
op_relation |
https://www.mdpi.com/2072-4292/12/14/2197 https://doaj.org/toc/2072-4292 doi:10.3390/rs12142197 2072-4292 https://doaj.org/article/7b5d3a40f14c495eb360ed5112bb4488 |
op_doi |
https://doi.org/10.3390/rs12142197 |
container_title |
Remote Sensing |
container_volume |
12 |
container_issue |
14 |
container_start_page |
2197 |
_version_ |
1766270368546291712 |