Articles | Volume 18, issue 6
https://doi.org/10.5194/essd-18-4155-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-18-4155-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
PolyU2025 SLA: a global 0.25° × 0.25° monthly sea-level anomaly dataset (1993–2024) determined from satellite altimetry for sea-level and climate change research
Jiajia Yuan
CORRESPONDING AUTHOR
Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hong Kong, China
Jianli Chen
Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hong Kong, China
State Key Laboratory of Climate Resilience for Coastal Cities, The Hong Kong Polytechnic University, Hong Kong, China
The Hong Kong Polytechnic University Shenzhen Research Institute, The Hong Kong Polytechnic University, Shenzhen, China
Dongju Peng
Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hong Kong, China
State Key Laboratory of Climate Resilience for Coastal Cities, The Hong Kong Polytechnic University, Hong Kong, China
The Hong Kong Polytechnic University Shenzhen Research Institute, The Hong Kong Polytechnic University, Shenzhen, China
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Short summary
In this study, we present a new global monthly gridded sea level anomaly dataset for sea-level and climate change research. The dataset is produced using a fully independent data-processing framework and is based on measurements from at least two satellites operating at the same time each month. Comparisons with existing global datasets and coastal measurements show close agreement in long-term sea level rise, while also revealing differences in regions with strong ocean variability.
In this study, we present a new global monthly gridded sea level anomaly dataset for sea-level...
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