Examining the performance of along-track multi-mission satellite altimetry – A case study for Sentinel-6

Satellite altimetry (SA) is one of the most valuable techniques that measure the sea level data at both the near-coast and offshore. There exists, however, multiple challenges and hindrances in determining and using accurate sea level data. The most pertinent is that evaluation of SA performance req...

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Main Authors: Heinoja Lenne-Liisa, Delpeche-Ellmann Nicole, Ellmann Artu
Format: Article
Language:English
Published: De Gruyter 2023-12-01
Series:Journal of Geodetic Science
Subjects:
Online Access:https://doi.org/10.1515/jogs-2022-0159
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author Heinoja Lenne-Liisa
Delpeche-Ellmann Nicole
Ellmann Artu
author_facet Heinoja Lenne-Liisa
Delpeche-Ellmann Nicole
Ellmann Artu
author_sort Heinoja Lenne-Liisa
collection DOAJ
description Satellite altimetry (SA) is one of the most valuable techniques that measure the sea level data at both the near-coast and offshore. There exists, however, multiple challenges and hindrances in determining and using accurate sea level data. The most pertinent is that evaluation of SA performance requires that all data sources (such as tide gauges (TG) and hydrodynamic models (HDMs)) refer to the same vertical datum. Thus, knowledge of the geoid (equipotential surface of the earth) is essential in linking different sources of sea level. Accordingly, this study examines performance of along-track data for three satellite missions (Sentinel-3A, Jason-3, and Sentinel-6A) to obtain realistic sea level variation and to determine the accuracy of the various missions in the complex area of the eastern Baltic Sea. The methodology consisted of utilizing SA, HDM, and TG data and a high-resolution geoid model. Results show that root-mean-square error (RMSE) varied for Jason-3 within a range of 1.68–50.14 cm, Sentinel 3A with a range of 2.8–46.27 cm, and Sentinel 6A with a range of 3.5–43.90 cm. Sentinel 6A was determined to be the most accurate and reliable satellite mission. Results also showed higher RMSE (15.7–46.2 cm) during (i) the seasonal sea ice month (e.g. March 2018); (ii) at locations of several islands (e.g. eastern section of Gulf); and (iii) at locations where rivers discharged into the Gulf (e.g. Nava, Kemi, Luga, and Neva rivers). These features tended to show up as peaks in the final results even though robust data processing for outliers were undertaken. These results suggests that improvements can still be made in the SA retrackers and also in the data-processing techniques utilized.
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spelling doaj.art-3d20dfe2b4e347738e9aeecc335b853c2024-01-22T07:04:39ZengDe GruyterJournal of Geodetic Science2081-99432023-12-01131233210.1515/jogs-2022-0159Examining the performance of along-track multi-mission satellite altimetry – A case study for Sentinel-6Heinoja Lenne-Liisa0Delpeche-Ellmann Nicole1Ellmann Artu2Department of Civil Engineering and Architecture, Tallinn University of Technology, Ehitajate Tee 5, Tallinn, 19086, EstoniaDepartment of Cybernetics, Tallinn University of Technology, Tallinn, EstoniaDepartment of Civil Engineering and Architecture, Tallinn University of Technology, Ehitajate Tee 5, Tallinn, 19086, EstoniaSatellite altimetry (SA) is one of the most valuable techniques that measure the sea level data at both the near-coast and offshore. There exists, however, multiple challenges and hindrances in determining and using accurate sea level data. The most pertinent is that evaluation of SA performance requires that all data sources (such as tide gauges (TG) and hydrodynamic models (HDMs)) refer to the same vertical datum. Thus, knowledge of the geoid (equipotential surface of the earth) is essential in linking different sources of sea level. Accordingly, this study examines performance of along-track data for three satellite missions (Sentinel-3A, Jason-3, and Sentinel-6A) to obtain realistic sea level variation and to determine the accuracy of the various missions in the complex area of the eastern Baltic Sea. The methodology consisted of utilizing SA, HDM, and TG data and a high-resolution geoid model. Results show that root-mean-square error (RMSE) varied for Jason-3 within a range of 1.68–50.14 cm, Sentinel 3A with a range of 2.8–46.27 cm, and Sentinel 6A with a range of 3.5–43.90 cm. Sentinel 6A was determined to be the most accurate and reliable satellite mission. Results also showed higher RMSE (15.7–46.2 cm) during (i) the seasonal sea ice month (e.g. March 2018); (ii) at locations of several islands (e.g. eastern section of Gulf); and (iii) at locations where rivers discharged into the Gulf (e.g. Nava, Kemi, Luga, and Neva rivers). These features tended to show up as peaks in the final results even though robust data processing for outliers were undertaken. These results suggests that improvements can still be made in the SA retrackers and also in the data-processing techniques utilized.https://doi.org/10.1515/jogs-2022-0159baltic seageoidgulf of finlandhydrodynamic modelhydro geodesyjasonsentineltide gauge
spellingShingle Heinoja Lenne-Liisa
Delpeche-Ellmann Nicole
Ellmann Artu
Examining the performance of along-track multi-mission satellite altimetry – A case study for Sentinel-6
Journal of Geodetic Science
baltic sea
geoid
gulf of finland
hydrodynamic model
hydro geodesy
jason
sentinel
tide gauge
title Examining the performance of along-track multi-mission satellite altimetry – A case study for Sentinel-6
title_full Examining the performance of along-track multi-mission satellite altimetry – A case study for Sentinel-6
title_fullStr Examining the performance of along-track multi-mission satellite altimetry – A case study for Sentinel-6
title_full_unstemmed Examining the performance of along-track multi-mission satellite altimetry – A case study for Sentinel-6
title_short Examining the performance of along-track multi-mission satellite altimetry – A case study for Sentinel-6
title_sort examining the performance of along track multi mission satellite altimetry a case study for sentinel 6
topic baltic sea
geoid
gulf of finland
hydrodynamic model
hydro geodesy
jason
sentinel
tide gauge
url https://doi.org/10.1515/jogs-2022-0159
work_keys_str_mv AT heinojalenneliisa examiningtheperformanceofalongtrackmultimissionsatellitealtimetryacasestudyforsentinel6
AT delpecheellmannnicole examiningtheperformanceofalongtrackmultimissionsatellitealtimetryacasestudyforsentinel6
AT ellmannartu examiningtheperformanceofalongtrackmultimissionsatellitealtimetryacasestudyforsentinel6