Deep Learning Models Ratify ENSO's Substantial Impact on Antarctic Sea Ice Subseasonal Predictability: supplemental data ...
cor_spatial38c.hdf contains SIPNet skill information, comprising four subsets: 'mid', 'nino', 'nina', and 'all', representing model skill under neutral conditions, El Niño, La Niña, and the entire time range, respectively.acc_per_spatial38.hdf is similar to co...
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| Format: | Dataset |
| Language: | unknown |
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figshare
2024
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| Online Access: | https://dx.doi.org/10.6084/m9.figshare.24572866.v2 https://figshare.com/articles/dataset/AI_Model_Affirms_ENSO_s_Boost_to_Subseasonal_Predictability_of_Antarctic_Sea_Ice_supplemental_data/24572866/2 |
| Summary: | cor_spatial38c.hdf contains SIPNet skill information, comprising four subsets: 'mid', 'nino', 'nina', and 'all', representing model skill under neutral conditions, El Niño, La Niña, and the entire time range, respectively.acc_per_spatial38.hdf is similar to cor_spatial38c but represents the model skill for anomaly persistence.cor_spatial38_linear.hdf, like cor_spatial38c, represents the model skill but specifically for the linear SIPNet model.sic_stddev.hdf contains sea ice variability information with three subsets: 'nino', 'mid', and 'nina', denoting sea ice variability under El Niño, neutral conditions, and La Niña, respectively.t2m_composite38.hdf: Surface air temperature composite dataset, containing composites for four seasons.sst_composite38.hdf: Similar to t2m_composite38, but for sea surface temperature.mslp_composite38.hdf: Similar to t2m_composite38, but for sea level pressure.obser_sic_composite.hdf: Similar to t2m_composite38, but for observed sea ice concentration.predi_sic_composite.hdf: ... |
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