Combining machine learning algorithms for bridging gaps in GRACE and GRACE Follow-On missions using ERA5-Land reanalysis
The Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GFO) missions have provided valuable data for monitoring global terrestrial water storage anomalies (TWSA) over the past two decades. However, the nearly one-year gap between these missions pose challenges for long-term TWSA me...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-06-01
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| Series: | Science of Remote Sensing |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666017225000045 |
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