Impact of channel selection on SST retrievals from passive microwave observations

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Impact of channel selection on SST retrievals from passive microwave observations. / Nielsen-Englyst, Pia; Høyer, Jacob L.; Alerskans, Emy; Pedersen, Leif Toudal; Donlon, Craig.

In: Remote Sensing of Environment, Vol. 254, 112252, 2021.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

Nielsen-Englyst, P, Høyer, JL, Alerskans, E, Pedersen, LT & Donlon, C 2021, 'Impact of channel selection on SST retrievals from passive microwave observations', Remote Sensing of Environment, vol. 254, 112252. https://doi.org/10.1016/j.rse.2020.112252

APA

Nielsen-Englyst, P., Høyer, J. L., Alerskans, E., Pedersen, L. T., & Donlon, C. (2021). Impact of channel selection on SST retrievals from passive microwave observations. Remote Sensing of Environment, 254, [112252]. https://doi.org/10.1016/j.rse.2020.112252

Vancouver

Nielsen-Englyst P, Høyer JL, Alerskans E, Pedersen LT, Donlon C. Impact of channel selection on SST retrievals from passive microwave observations. Remote Sensing of Environment. 2021;254. 112252. https://doi.org/10.1016/j.rse.2020.112252

Author

Nielsen-Englyst, Pia ; Høyer, Jacob L. ; Alerskans, Emy ; Pedersen, Leif Toudal ; Donlon, Craig. / Impact of channel selection on SST retrievals from passive microwave observations. In: Remote Sensing of Environment. 2021 ; Vol. 254.

Bibtex

@article{724f67c39ee5406b8b02ab1bf57d3172,
title = "Impact of channel selection on SST retrievals from passive microwave observations",
abstract = "Two retrieval algorithms developed as a part of the European Space Agency Climate Change Initiative (ESA-CCI) project are used to assess the effects of withholding observations from selected frequency channels on the retrieved subskin Sea Surface Temperature (SST) from AQUA's Advanced Microwave Scanning Radiometer—Earth Observing System (AMSR-E) and to evaluate a Copernicus Imaging Microwave Radiometer (CIMR) like channel configuration. The first algorithm is a statistical regression-based retrieval algorithm, while the second is a physically based optimal estimation (OE) algorithm. A database with matching satellite and drifting buoy observations is used to test the performance of each channel configuration using both retrieval algorithms to identify the most optimal channel selection for accurate SST retrievals. The evaluation against in situ observations allows identification of the strengths and weaknesses of the two retrieval algorithms, and demonstrates the importance of using in situ observations to evaluate existing theoretical retrieval uncertainty studies. Overall, the performance increases as expected when more channels are included in the retrieval. In particular, more channels allow a better performance for the range of different observing conditions (e.g. cold waters). The two retrieval algorithms agree that for a three-channel configuration, the 6, 10, 18 GHz (V and H polarization) is better than the 6, 10, 23 GHz configuration (V and H polarization). This is demonstrated for different geographical regions and throughout all seasons. Of the different combinations tested here, it is evident that withholding observations from the 23 and 36 GHz channels from the retrieval has the least impact on the SST performance. Overall, this analysis shows that the CIMR like channel configuration performs very well when compared to an AMSR-E like constellation using both retrieval algorithms.",
keywords = "AMSR-E, Channel selection, Copernicus imaging microwave radiometer (CIMR), Optimal estimation (OE), Passive microwaves, Remote sensing, Sea surface temperature (SST)",
author = "Pia Nielsen-Englyst and H{\o}yer, {Jacob L.} and Emy Alerskans and Pedersen, {Leif Toudal} and Craig Donlon",
note = "Publisher Copyright: {\textcopyright} 2020 The Author(s)",
year = "2021",
doi = "10.1016/j.rse.2020.112252",
language = "English",
volume = "254",
journal = "Remote Sensing of Environment",
issn = "0034-4257",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - Impact of channel selection on SST retrievals from passive microwave observations

AU - Nielsen-Englyst, Pia

AU - Høyer, Jacob L.

AU - Alerskans, Emy

AU - Pedersen, Leif Toudal

AU - Donlon, Craig

N1 - Publisher Copyright: © 2020 The Author(s)

PY - 2021

Y1 - 2021

N2 - Two retrieval algorithms developed as a part of the European Space Agency Climate Change Initiative (ESA-CCI) project are used to assess the effects of withholding observations from selected frequency channels on the retrieved subskin Sea Surface Temperature (SST) from AQUA's Advanced Microwave Scanning Radiometer—Earth Observing System (AMSR-E) and to evaluate a Copernicus Imaging Microwave Radiometer (CIMR) like channel configuration. The first algorithm is a statistical regression-based retrieval algorithm, while the second is a physically based optimal estimation (OE) algorithm. A database with matching satellite and drifting buoy observations is used to test the performance of each channel configuration using both retrieval algorithms to identify the most optimal channel selection for accurate SST retrievals. The evaluation against in situ observations allows identification of the strengths and weaknesses of the two retrieval algorithms, and demonstrates the importance of using in situ observations to evaluate existing theoretical retrieval uncertainty studies. Overall, the performance increases as expected when more channels are included in the retrieval. In particular, more channels allow a better performance for the range of different observing conditions (e.g. cold waters). The two retrieval algorithms agree that for a three-channel configuration, the 6, 10, 18 GHz (V and H polarization) is better than the 6, 10, 23 GHz configuration (V and H polarization). This is demonstrated for different geographical regions and throughout all seasons. Of the different combinations tested here, it is evident that withholding observations from the 23 and 36 GHz channels from the retrieval has the least impact on the SST performance. Overall, this analysis shows that the CIMR like channel configuration performs very well when compared to an AMSR-E like constellation using both retrieval algorithms.

AB - Two retrieval algorithms developed as a part of the European Space Agency Climate Change Initiative (ESA-CCI) project are used to assess the effects of withholding observations from selected frequency channels on the retrieved subskin Sea Surface Temperature (SST) from AQUA's Advanced Microwave Scanning Radiometer—Earth Observing System (AMSR-E) and to evaluate a Copernicus Imaging Microwave Radiometer (CIMR) like channel configuration. The first algorithm is a statistical regression-based retrieval algorithm, while the second is a physically based optimal estimation (OE) algorithm. A database with matching satellite and drifting buoy observations is used to test the performance of each channel configuration using both retrieval algorithms to identify the most optimal channel selection for accurate SST retrievals. The evaluation against in situ observations allows identification of the strengths and weaknesses of the two retrieval algorithms, and demonstrates the importance of using in situ observations to evaluate existing theoretical retrieval uncertainty studies. Overall, the performance increases as expected when more channels are included in the retrieval. In particular, more channels allow a better performance for the range of different observing conditions (e.g. cold waters). The two retrieval algorithms agree that for a three-channel configuration, the 6, 10, 18 GHz (V and H polarization) is better than the 6, 10, 23 GHz configuration (V and H polarization). This is demonstrated for different geographical regions and throughout all seasons. Of the different combinations tested here, it is evident that withholding observations from the 23 and 36 GHz channels from the retrieval has the least impact on the SST performance. Overall, this analysis shows that the CIMR like channel configuration performs very well when compared to an AMSR-E like constellation using both retrieval algorithms.

KW - AMSR-E

KW - Channel selection

KW - Copernicus imaging microwave radiometer (CIMR)

KW - Optimal estimation (OE)

KW - Passive microwaves

KW - Remote sensing

KW - Sea surface temperature (SST)

U2 - 10.1016/j.rse.2020.112252

DO - 10.1016/j.rse.2020.112252

M3 - Journal article

AN - SCOPUS:85098683662

VL - 254

JO - Remote Sensing of Environment

JF - Remote Sensing of Environment

SN - 0034-4257

M1 - 112252

ER -

ID: 306965210