SOCAT+USV sampling masks for ML reconstruction of surface ocean pCO2 using the Large Ensemble Testbed
Authors/Creators
Description
Here we provide sampling masks used in the study "Assessing improvements in global ocean pCO2 machine learning reconstructions with Southern Ocean autonomous sampling" (Heimdal et al., 2023, https://doi.org/10.5194/bg-2023-160). In this paper, we reconstruct surface ocean pCO2 using the Large Ensemble Testbed (Gloege et al., 2021, https://doi.org/10.1029/2020GB006788) and the pCO2-Residual method (Bennington et al., 2022, https://doi.org/10.1029/2021MS002960). We provide 11 different sampling masks that correspond to the experiments presented in Heimdal et al. (2023), which include different sampling patterns of USV Saildrones in the Southern Ocean (SOCAT+USV sampling).
Files
Files
(2.4 GB)
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md5:4d89c5b531b16172d9bb7d39ef0d2a02
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md5:589fde2b23259a7d68d9777c1bc92c56
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218.3 MB | Download |
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md5:d4efdc051aef0f094b7843d55d4e64c4
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218.3 MB | Download |
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md5:c084a4c38956f6c2d08a8daf7409b912
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218.3 MB | Download |
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md5:58aad8a2cba5b3529e6755f8fa377fed
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218.3 MB | Download |
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md5:93657fb8e08c5541da0a93262b39c868
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218.3 MB | Download |
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md5:10ad3b91cde9f9116e518384844b967c
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218.3 MB | Download |
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md5:6716ea392216d5ff68b0df8780af4e0e
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218.3 MB | Download |
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md5:df2adfe41e6924bf95c3776323b8ebf1
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218.3 MB | Download |
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md5:ae06b5857d9f6ed4ca7222b5f34f2c12
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218.3 MB | Download |
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md5:56448af14abed7a029e08bb682dea4ef
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218.3 MB | Download |
Additional details
Related works
- Is supplement to
- Journal article: 10.5194/bg-2023-160 (DOI)
Software
- Programming language
- Python , Jupyter Notebook