Views provided by UsageCountsTraining and Testing Data, Associated Code, and SCAM Validations Code and Data for ResNet in moist physics
Han, Yilun; Zhang, Guang J.; Huang, Xiaomeng; Wang, Yong;
Training and Testing Data, Associated Code, and SCAM Validations Code and Data for ResNet in moist physics
Data and code for a deep convolutional residual neural network moist physics parameterization (ResNet-MP). Here we provide 3 parts of data and code: 1, SPCAM setups and simulations; 2, ResNet-MP training and testing; 3, SCAM validations. Please generate the training and testing data according to the instruction in README. We can't directly provide the 800 GB one-year independent testing data and 50 GB training data.
- Scripps Institution of Oceanography United States
- Tsinghua University China (People's Republic of)
- University of California, San Diego United States
selected citations These citations are derived from selected sources.This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).0 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average views 2 - 2views
selected citations
Citations provided by BIP!
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
Citations provided by BIP!popularityPopularity provided by BIP!
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
Popularity provided by BIP!influenceInfluence provided by BIP!
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
Influence provided by BIP!impulseImpulse provided by BIP!
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
Impulse provided by BIP!viewsViews provided by UsageCounts
Views provided by UsageCounts 0
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