Abstract's details
Quality flag and uncertainties of water surface height over Inland waters
Event: 2022 Ocean Surface Topography Science Team Meeting
Session: Quantifying Errors and Uncertainties in Altimetry data
Presentation type: Poster
Inland waters are essential for environmental, societal and economic services such as transport, drinking water, agriculture or power generation. But inland waters are also one of the most affected resources by climate change and human populations growth.
Altimetry, which has been used since 1992 for oceanography, has also proven to be a useful tool to estimate inland water surfaces such a rivers and lakes, which are considered Essential Climate Variables (ECVs). the heterogeneity of the targets size, surfaces roughness etc… and the surrounding environment near the water targets make the interpretation of the measurements more complex. In addition, the availability of a measurement must be complemented by the confidence that it can be attributed to the estimation of the water surface height and providing the uncertainty associated with this measurement will be useful for assimilations and downstream products.
The aim of this presentation is to describe the use of a waveform classification method, based on neural network algorithms, on level 2 data in order to identify reliable measurements on water body targets. This classification can be used as a metric for data quality and is therefore incorporated in the data processing to define a quality flag in the inland product. The quality flag is being implemented in two ESA projects using data for the reprocessing of several missions data: FDR4ALTwith data from ENVISAT, ERS-2 and ERS-1 missions and CryoTempo with data from Cryosat2. Secondly, it aims at the presenting the methodology for estimating the uncertainty on the estimated water level.
References:
Birkett C. M. (1995). Contribution of TOPEX/POSEIDON to the global monitoring of climatically sensitive lakes, Journal of Geophysical Research, 100, C12, 25, 179-25, 204
J.F. Cretaux, W. Jelinski, S. Calmant, A. Kouraev, V. Vuglinski, M. Berge-Nguyen, M.C. Gennero, F. Nino, R.A. Del Rio, A. Cazenave, P. Maisongrande: SOLS: A lake database to monitor in the Near Real Time water level and storage variation from remote sensing data, Advances in Space Research, N47, ELSEVIER, 2011,pp. 1497-1507
Crétaux J-F and C. Birkett, lake studies from satellite altimetry, C R Geoscience, Vol 338, 14-15, 1098-1112, doi: 10.1016/J.cre.2006.08.002, 2006
Poisson, Jean-Christophe & Quartly, Graham & Kurekin, Andrey & Thibaut, Pierre & Hoang, Duc & Nencioli, Francesco. (2018). Development of an ENVISAT Altimetry Processor Providing Sea Level Continuity Between Open Ocean and Arctic Leads. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-21. 10.1109/TGRS.2018.2813061.
N. Longépé et al., Comparative Evaluation of Sea Ice Lead Detection Based on SAR Imagery and Altimeter Data, in IEEE Transactions on Geoscience and Remote Sensing, vol. 57, no. 6, pp. 4050-4061, June 2019, doi: 10.1109/TGRS.2018.2889519.
Altimetry, which has been used since 1992 for oceanography, has also proven to be a useful tool to estimate inland water surfaces such a rivers and lakes, which are considered Essential Climate Variables (ECVs). the heterogeneity of the targets size, surfaces roughness etc… and the surrounding environment near the water targets make the interpretation of the measurements more complex. In addition, the availability of a measurement must be complemented by the confidence that it can be attributed to the estimation of the water surface height and providing the uncertainty associated with this measurement will be useful for assimilations and downstream products.
The aim of this presentation is to describe the use of a waveform classification method, based on neural network algorithms, on level 2 data in order to identify reliable measurements on water body targets. This classification can be used as a metric for data quality and is therefore incorporated in the data processing to define a quality flag in the inland product. The quality flag is being implemented in two ESA projects using data for the reprocessing of several missions data: FDR4ALTwith data from ENVISAT, ERS-2 and ERS-1 missions and CryoTempo with data from Cryosat2. Secondly, it aims at the presenting the methodology for estimating the uncertainty on the estimated water level.
References:
Birkett C. M. (1995). Contribution of TOPEX/POSEIDON to the global monitoring of climatically sensitive lakes, Journal of Geophysical Research, 100, C12, 25, 179-25, 204
J.F. Cretaux, W. Jelinski, S. Calmant, A. Kouraev, V. Vuglinski, M. Berge-Nguyen, M.C. Gennero, F. Nino, R.A. Del Rio, A. Cazenave, P. Maisongrande: SOLS: A lake database to monitor in the Near Real Time water level and storage variation from remote sensing data, Advances in Space Research, N47, ELSEVIER, 2011,pp. 1497-1507
Crétaux J-F and C. Birkett, lake studies from satellite altimetry, C R Geoscience, Vol 338, 14-15, 1098-1112, doi: 10.1016/J.cre.2006.08.002, 2006
Poisson, Jean-Christophe & Quartly, Graham & Kurekin, Andrey & Thibaut, Pierre & Hoang, Duc & Nencioli, Francesco. (2018). Development of an ENVISAT Altimetry Processor Providing Sea Level Continuity Between Open Ocean and Arctic Leads. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-21. 10.1109/TGRS.2018.2813061.
N. Longépé et al., Comparative Evaluation of Sea Ice Lead Detection Based on SAR Imagery and Altimeter Data, in IEEE Transactions on Geoscience and Remote Sensing, vol. 57, no. 6, pp. 4050-4061, June 2019, doi: 10.1109/TGRS.2018.2889519.
Contribution: ERR2022-Quality_flag_and_uncertainties_of_water_surface_height_over_Inland_waters.pdf (pdf, 1319 ko)
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