Published June 18, 2025
| Version v2
Dataset
Open
Data for "A multimodal machine learning fused global 0.1° daily evapotranspiration dataset from 1950-2022" (2000-2024)
Description
The data contains simulation results from 2000-2024, 25 years total.
You can access the remaining part of the dataset via Qingchen Xu and Lu Li (2025) using the following reference:
Qingchen Xu, & Lu Li. (2025). Data for "A multimodal machine learning fused global 0.1° daily evapotranspiration dataset from 1950-2022" (1950-1974) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.15671245
Qingchen Xu, & Lu Li. (2025). Data for "A multimodal machine learning fused global 0.1° daily evapotranspiration dataset from 1950-2022" (1975-1999) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.15671253
Files
Files
(41.1 GB)
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md5:0fedcd024fb59cb547caf619e2378996
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1.6 GB | Download |
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md5:1a7e8aca3468e7e3f58fd7340e3c9cd4
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1.6 GB | Download |
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md5:7d9d14f49eb6b659e00baa7526e61f2e
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1.6 GB | Download |
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md5:1e3a2da48a4d47a00af89e7acebcb92d
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1.7 GB | Download |
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md5:e4ee667c14ed6e471790c7a13cd74e90
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1.6 GB | Download |
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md5:3f5dd51a47c771328dab415bd22003cf
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1.7 GB | Download |
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md5:b5af19459bd8b0fae8af80d1534db014
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1.7 GB | Download |
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md5:3aef0a3f0210dcfd960886ab2905a0d6
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1.6 GB | Download |
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md5:0f1ba8974efd2e05b82a15e3904eef3f
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1.6 GB | Download |
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md5:9a324a93707772faee33cde725f14c37
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1.6 GB | Download |
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md5:40b13f620765b8dba0ab1b9042357dde
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1.6 GB | Download |
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md5:42a3de3d0b87fd601dd40f7cd3acee36
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1.6 GB | Download |
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md5:f125b3493ba8a860d66f71c6269ca500
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1.7 GB | Download |
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md5:30247a633801fc815aa1f82fc927a1ab
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1.6 GB | Download |
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md5:c5192581080f966a0230f28380764405
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1.6 GB | Download |
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md5:a194fc11eecd3a67d262f1e1429c8b79
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1.7 GB | Download |
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md5:27e1a2a1e9dfe27baeffc7c8c9f6940b
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1.7 GB | Download |
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md5:9a976edb5b7b2c807ae1713a2eecdef1
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1.6 GB | Download |
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md5:ecd3a34330e7cf6d01a63e4c69f1b890
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1.7 GB | Download |
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md5:056ce1b50b046436354081578a810e09
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1.6 GB | Download |
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md5:378f7803bd264d23a065bde6b9078f02
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1.6 GB | Download |
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md5:9340167e8e4b0c940f8676cd85adb14b
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1.6 GB | Download |
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md5:03806d95002ca876af2b44c088fb14aa
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1.6 GB | Download |
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md5:b966c86a88f8a289d6a89b528ced7da2
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1.6 GB | Download |
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md5:6c292b1e1c9438b72be1a56b7ef8d44d
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1.7 GB | Download |
Additional details
Related works
- Cites
- Publication: 10.1016/j.agrformet.2025.110645 (DOI)