Published May 4, 2022
| Version v2
Dataset
Open
Data corresponding to "The Impact of Multi-sensor Land Data Assimilation on River Discharge Estimation"
Authors/Creators
- 1. Lawrence Livermore National Laboratory: Livermore, CA, US
- 2. University of Texas at Austin: Austin, TX, US
- 3. Southwest University: Chongqing, CN
- 4. Peking University: Beijing, Beijing, CN
Description
This dataset is corresponding to the input and output files that were used in this study:
Wu, W.-Y., Z.-L. Yang, L. Zhao, P. Lin (2022), Joint Multi-sensor Data Assimilation for Constraining Water Storages and its Impact on Global Discharge Estimation (in revision, RSE)
Notes
Please contact the author when using this dataset for publication.
Files
Wu-RSE-2022-data.zip
Files
(30.3 GB)
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md5:18b9613ee9a0b119cd359b249ba60385
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md5:99e5e1a845dc2287edbbbd93638d51b1
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md5:d94ba28af4d1073f70570e74eab3db43
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18.6 MB | Download |
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md5:46626ce548031578349feaea51706bb8
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md5:6e5b081e4f2535a85f7cd2a71c531edd
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md5:6be454a7e073356d29368d1883c1107e
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18.6 MB | Download |
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md5:063f01668add657a3b177d24bfcc46f9
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3.7 MB | Download |
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md5:9fb3ff82255be5254fe0f4c588c322f5
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120.5 kB | Download |
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md5:22ce31007b8347d322cdaf57a64c0ed2
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14.3 kB | Download |
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md5:74b9ca10edc0f17c961ac53e4cd08662
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18.6 MB | Download |
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md5:7acd99f7d2f552a44f5d0652c8cd8b40
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30.1 GB | Preview Download |