Arctic sea surface height maps from multi-altimeter combination
<p>We present a new Arctic sea level anomaly dataset based on the combination of three altimeter missions using an optimal interpolation scheme. Measurements from SARAL/AltiKa, CryoSat-2 and Sentinel-3A are blended together, providing an unprecedented resolution for this type of product. Such...
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| Autores principales: | , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Copernicus Publications
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/702bd31bdcdc400a88e8665432954f68 |
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| Sumario: | <p>We present a new Arctic sea level anomaly dataset based on the combination of three altimeter missions using an optimal interpolation
scheme. Measurements from SARAL/AltiKa, CryoSat-2 and Sentinel-3A are blended together, providing an unprecedented resolution for this type of
product. Such high-resolution products are necessary to tackle some contemporaneous science questions in the basin. We use the adaptive retracker
to process both open ocean and lead echoes on SARAL/AltiKa, thus removing the need to estimate a bias between open ocean and ice-covered areas. The
usual processing approach, involving an empirical retracking algorithm on specular echoes, is applied on CryoSat-2 and Sentinel-3A synthetic aperture radar (SAR) mode
echoes. SARAL/AltiKa also provides the baseline for the cross-calibration of CryoSat-2 and Sentinel-3A data. The final gridded fields cover all
latitudes north of 50<span class="inline-formula"><sup>∘</sup></span> N, on a 25 <span class="inline-formula">km</span> EASE2 grid, with one grid every 3 d over 3 years from July 2016 to April 2019. When
compared to tide gauge measurements available in the Arctic Ocean, the combined product exhibits a much better performance than mono-mission
datasets with a mean correlation of 0.78 and a mean root-mean-square deviation (RMSd) of 5 <span class="inline-formula">cm</span>. The effective temporal resolution of the combined product is 3 times
better than a single mission analysis. This dataset can be downloaded from <a href="https://doi.org/10.24400/527896/a01-2020.001">https://doi.org/10.24400/527896/a01-2020.001</a> <span class="cit" id="xref_paren.1">(<a href="#bib1.bibx38">Prandi</a>, <a href="#bib1.bibx38">2020</a>)</span>.</p> |
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