GGWS-PCNN: A global gridded wind speed dataset (1973/01-2021/12; Ongoing Update)
Profile of the dataset The GGWS-PCNN is a global gridded monthly dataset of 10-m wind speed based on an artificial intelligence algorithm (the partial convolutional neural network), observations from weather stations (the HadISD dataset), and 34 climate models from CMIP6. It has a resolution of 1.25...
| Main Authors: | , , |
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| Format: | Dataset |
| Language: | English |
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2022
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| Subjects: | |
| Online Access: | https://zenodo.org/record/6544884 https://doi.org/10.1016/j.scib.2022.09.022 |
| Summary: | Profile of the dataset The GGWS-PCNN is a global gridded monthly dataset of 10-m wind speed based on an artificial intelligence algorithm (the partial convolutional neural network), observations from weather stations (the HadISD dataset), and 34 climate models from CMIP6. It has a resolution of 1.25° × 2.5° (latitude × longitude). We will update this dataset as soon as the new HadISD version is accessible. For more details about the dataset and its reconstructed processes, please see our paper "An artificial intelligence reconstruction of global gridded surface winds" published in the Science Bulletin. Notice The HadISD discovered an issue in the wind data after 2013. So in their version 3.3.0.202201p and later, they fixed this issue. Find the website Met Office Hadley Centre observations datasets for more details. Due to the limitations of existing AI algorithms in reconstructing data with many missing values, our product has a small number of outliers (e.g. wind speeds less than zero or very high), most of which are located in the Antarctic region. We recommend you remove these outliers before using this dataset. Reference Lihong Zhou, Haofeng Liu, Xin Jiang, et al. (2022). An artificial intelligence reconstruction of global gridded surface winds. Science Bulletin. |
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