Retrieval of Daytime Total Column Water Vapour from OLCI Measurements over Land Surfaces
A new retrieval of total column water vapour (TCWV) from daytime measurements over land of the Ocean and Land Colour Instrument (OLCI) on-board the Copernicus Sentinel-3 missions is presented. The Copernicus Sentinel-3 OLCI Water Vapour product (COWa) retrieval algorithm is based on the differential...
Published in: | Remote Sensing |
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Main Authors: | , , |
Format: | Article in Journal/Newspaper |
Language: | English |
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MDPI AG
2021
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Online Access: | https://doi.org/10.3390/rs13050932 https://doaj.org/article/714f49a3e42c4e9da2e2e563324c7c73 |
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author | René Preusker Cintia Carbajal Henken Jürgen Fischer |
author_facet | René Preusker Cintia Carbajal Henken Jürgen Fischer |
author_sort | René Preusker |
collection | Directory of Open Access Journals: DOAJ Articles |
container_issue | 5 |
container_start_page | 932 |
container_title | Remote Sensing |
container_volume | 13 |
description | A new retrieval of total column water vapour (TCWV) from daytime measurements over land of the Ocean and Land Colour Instrument (OLCI) on-board the Copernicus Sentinel-3 missions is presented. The Copernicus Sentinel-3 OLCI Water Vapour product (COWa) retrieval algorithm is based on the differential absorption technique, relating TCWV to the radiance ratio of non-absorbing band and nearby water vapour absorbing band and was previously also successfully applied to other passive imagers Medium Resolution Imaging Spectrometer (MERIS) and Moderate Resolution Imaging Spectroradiometer (MODIS). One of the main advantages of the OLCI instrument regarding improved TCWV retrievals lies in the use of more than one absorbing band. Furthermore, the COWa retrieval algorithm is based on the full Optimal Estimation (OE) method, providing pixel-based uncertainty estimates, and transferable to other Near-Infrared (NIR) based TCWV observations. Three independent global TCWV data sets, i.e., Aerosol Robotic Network (AERONET), Atmospheric Radiation Measurement (ARM) and U.S. SuomiNet, and a German Global Navigation Satellite System (GNSS) TCWV data set, all obtained from ground-based observations, serve as reference data sets for the validation. Comparisons show an overall good agreement, with absolute biases between 0.07 and 1.31 kg/m 2 and root mean square errors (RMSE) between 1.35 and 3.26 kg/m 2 . This is a clear improvement in comparison to the operational OLCI TCWV Level 2 product, for which the bias and RMSEs range between 1.10 and 2.55 kg/m 2 and 2.08 and 3.70 kg/m 2 , respectively. A first evaluation of pixel-based uncertainties indicates good estimated uncertainties for lower retrieval errors, while the uncertainties seem to be overestimated for higher retrieval errors. |
format | Article in Journal/Newspaper |
genre | Aerosol Robotic Network |
genre_facet | Aerosol Robotic Network |
id | ftdoajarticles:oai:doaj.org/article:714f49a3e42c4e9da2e2e563324c7c73 |
institution | Open Polar |
language | English |
op_collection_id | ftdoajarticles |
op_doi | https://doi.org/10.3390/rs13050932 |
op_relation | https://www.mdpi.com/2072-4292/13/5/932 https://doaj.org/toc/2072-4292 doi:10.3390/rs13050932 2072-4292 https://doaj.org/article/714f49a3e42c4e9da2e2e563324c7c73 |
op_source | Remote Sensing, Vol 13, Iss 5, p 932 (2021) |
publishDate | 2021 |
publisher | MDPI AG |
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spelling | ftdoajarticles:oai:doaj.org/article:714f49a3e42c4e9da2e2e563324c7c73 2025-01-16T18:38:38+00:00 Retrieval of Daytime Total Column Water Vapour from OLCI Measurements over Land Surfaces René Preusker Cintia Carbajal Henken Jürgen Fischer 2021-03-01T00:00:00Z https://doi.org/10.3390/rs13050932 https://doaj.org/article/714f49a3e42c4e9da2e2e563324c7c73 EN eng MDPI AG https://www.mdpi.com/2072-4292/13/5/932 https://doaj.org/toc/2072-4292 doi:10.3390/rs13050932 2072-4292 https://doaj.org/article/714f49a3e42c4e9da2e2e563324c7c73 Remote Sensing, Vol 13, Iss 5, p 932 (2021) OLCI Sentinel-3 total column water vapour retrieval algorithm validation AERONET Science Q article 2021 ftdoajarticles https://doi.org/10.3390/rs13050932 2023-12-10T01:48:26Z A new retrieval of total column water vapour (TCWV) from daytime measurements over land of the Ocean and Land Colour Instrument (OLCI) on-board the Copernicus Sentinel-3 missions is presented. The Copernicus Sentinel-3 OLCI Water Vapour product (COWa) retrieval algorithm is based on the differential absorption technique, relating TCWV to the radiance ratio of non-absorbing band and nearby water vapour absorbing band and was previously also successfully applied to other passive imagers Medium Resolution Imaging Spectrometer (MERIS) and Moderate Resolution Imaging Spectroradiometer (MODIS). One of the main advantages of the OLCI instrument regarding improved TCWV retrievals lies in the use of more than one absorbing band. Furthermore, the COWa retrieval algorithm is based on the full Optimal Estimation (OE) method, providing pixel-based uncertainty estimates, and transferable to other Near-Infrared (NIR) based TCWV observations. Three independent global TCWV data sets, i.e., Aerosol Robotic Network (AERONET), Atmospheric Radiation Measurement (ARM) and U.S. SuomiNet, and a German Global Navigation Satellite System (GNSS) TCWV data set, all obtained from ground-based observations, serve as reference data sets for the validation. Comparisons show an overall good agreement, with absolute biases between 0.07 and 1.31 kg/m 2 and root mean square errors (RMSE) between 1.35 and 3.26 kg/m 2 . This is a clear improvement in comparison to the operational OLCI TCWV Level 2 product, for which the bias and RMSEs range between 1.10 and 2.55 kg/m 2 and 2.08 and 3.70 kg/m 2 , respectively. A first evaluation of pixel-based uncertainties indicates good estimated uncertainties for lower retrieval errors, while the uncertainties seem to be overestimated for higher retrieval errors. Article in Journal/Newspaper Aerosol Robotic Network Directory of Open Access Journals: DOAJ Articles Remote Sensing 13 5 932 |
spellingShingle | OLCI Sentinel-3 total column water vapour retrieval algorithm validation AERONET Science Q René Preusker Cintia Carbajal Henken Jürgen Fischer Retrieval of Daytime Total Column Water Vapour from OLCI Measurements over Land Surfaces |
title | Retrieval of Daytime Total Column Water Vapour from OLCI Measurements over Land Surfaces |
title_full | Retrieval of Daytime Total Column Water Vapour from OLCI Measurements over Land Surfaces |
title_fullStr | Retrieval of Daytime Total Column Water Vapour from OLCI Measurements over Land Surfaces |
title_full_unstemmed | Retrieval of Daytime Total Column Water Vapour from OLCI Measurements over Land Surfaces |
title_short | Retrieval of Daytime Total Column Water Vapour from OLCI Measurements over Land Surfaces |
title_sort | retrieval of daytime total column water vapour from olci measurements over land surfaces |
topic | OLCI Sentinel-3 total column water vapour retrieval algorithm validation AERONET Science Q |
topic_facet | OLCI Sentinel-3 total column water vapour retrieval algorithm validation AERONET Science Q |
url | https://doi.org/10.3390/rs13050932 https://doaj.org/article/714f49a3e42c4e9da2e2e563324c7c73 |