GREMLIN CONUS1 Manually Selected Storms Dataset

The CONUS1 dataset is a \"toy\" dataset that is small enough to be able to train a convolutional neural network on a laptop computer to do image translation from geostationary satellite images to ground-based radar images. It provides three input channels from GOES-16 ABI, one input channel from GOES-16 GLM, and one output channel from MRMS., The methodology is described in detail by Hilburn et al. (2021). The ABI, GLM, and MRMS data sets were resampled to a common 3 km grid. A cloud height of 10 km was used for removing parallax displacements. Satellite and radar samples were matched in time with a maximum time difference of 2.5 minutes. GLM lightning groups were accumulated over 15-minute time periods., You may read the dataset using any software that can read NetCDF-4., , **Title**: GREMLIN CONUS1 Dataset
**Author**: Kyle Hilburn (ORCID: 0000-0002-2078-9884)
**Contact**: Kyle Hilburn, [[e-mail]](mailto:[e-mail])
**Institution**: Cooperative Institute for Research in the Atmosphere (CIRA) / Colorado State University (CSU)

**Brief Summary**: The CONUS1 dataset (conus1.nc) is a \"toy\" dataset that is small enough to be able to train a convolutional neural network on a laptop computer to do image translation from geostationary satellite images to ground-based radar images. It provides three input channels from GOES-16 ABI, one input channel from GOES-16 GLM, and one output channel from MRMS.

**Associated article citations**:

* The training dataset is described in:
Hilburn, K., S. D. Miller, and M. Marchand, 2019: Using high-resolution observations from
GOES-16 ABI to improve operational short-range forecasting. Joint Satellite Conference.
* The testing dataset is described in:
Hilburn, K., M. Marchand, Y. Lee, C. K...

CONUS1数据集是一款“玩具级”数据集，体量小巧，可在笔记本电脑上运行卷积神经网络，完成地球静止卫星图像到地面雷达图像的图像转换任务。该数据集提供来自GOES-16 ABI的3个输入通道、来自GOES-16 GLM的1个输入通道，以及来自MRMS的1个输出通道。相关研究方法由Hilburn等人（2021）详细阐述。

ABI、GLM与MRMS数据集均被重采样至统一的3公里网格。为校正视差位移，采用了10公里的云高参数。卫星与雷达样本的时间匹配最大允许时差为2.5分钟。GLM闪电群数据以15分钟为周期进行累加。

用户可通过任意支持读取NetCDF-4格式的软件加载该数据集。

**标题**：GREMLIN CONUS1 数据集
**作者**：Kyle Hilburn（ORCID：0000-0002-2078-9884）
**联系方式**：Kyle Hilburn，[[e-mail]](mailto:[e-mail])
**所属机构**：大气合作研究所（CIRA, Cooperative Institute for Research in the Atmosphere）/ 科罗拉多州立大学（CSU, Colorado State University）

**简要说明**：CONUS1数据集（conus1.nc）是一款“玩具级”数据集，体量小巧，可在笔记本电脑上运行卷积神经网络，实现地球静止卫星图像到地面雷达图像的图像转换。该数据集包含来自GOES-16 ABI的3个输入通道、来自GOES-16 GLM的1个输入通道，以及来自MRMS的1个输出通道。

**相关文献引用**：
* 训练数据集相关描述见于：
Hilburn, K., S. D. Miller, 及 M. Marchand, 2019: 利用GOES-16 ABI高分辨率观测数据改进业务短期预报. 联合卫星会议.
* 测试数据集相关描述见于：
Hilburn, K., M. Marchand, Y. Lee, C. K...