Published March 23, 2022
| Version V2.0.0
Dataset
Open
Second release of the data associated with the paper entitled 'Cluster-enhanced ensemble learning for mapping global monthly surface ozone from 2003 to 2019'
- 1. Nanjing Universiity
- 2. University of Wisconsin-Madison
Description
This is the second release of the data associated with the paper entitled 'Cluster-enhanced ensemble learning for mapping global monthly surface ozone from 2003 to 2019'.
The paper was published in Geophysical Research Letters. We provide the data that has been smoothed by moving filter and not. The data can be loaded by the raster package in R. Note that the unit is ppmv.
Please note that both of these files must be in the same directory to open in R properly.
Please get in touch with the authors if you have any issues, email: xliu21@smail.nju.edu.cn or wanghk@nju.edu.cn
Files
Files
(347.8 MB)
| Name | Size | Download all |
|---|---|---|
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md5:54db221cf364ca2341ddb5b60ae9d4ca
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9.7 kB | Download |
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md5:c4217ee2128d31703b8cb2095418551b
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173.9 MB | Download |
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md5:bfe544b8b2a7b5480ca662f65fa34583
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9.7 kB | Download |
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md5:25e9c45bd39e5e6de4b688e4e4c2240a
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173.9 MB | Download |
Additional details
References
- Liu, X., Zhu, Y., Xue, L., Desai, A. R., & Wang, H. (2022). Cluster-enhanced ensemble learning for mapping global monthly surface ozone from 2003 to 2019. Geophysical Research Letters, 49, e2022GL097947. https://doi.org/10.1029/2022GL097947