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- deep-learning
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- high-resolution
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# HR-Extreme Dataset
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## Overview
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HR-Extreme is a high-resolution dataset designed to evaluate the performance of state-of-the-art models in predicting extreme weather events. The dataset contains 17 types of extreme weather events from 2020, based on High-Resolution Rapid Refresh (HRRR) data. It is intended for researchers in weather forecasting, encompassing both physical and deep learning methods.
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## Dataset Structure
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The dataset is divided into two main folders:
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- `202001_202006`: Contains data from January 2020 to June 2020.
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- deep-learning
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- high-resolution
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# HR-Extreme Dataset
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## Overview
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HR-Extreme is a high-resolution dataset designed to evaluate the performance of state-of-the-art models in predicting extreme weather events. The dataset contains 17 types of extreme weather events from 2020, based on High-Resolution Rapid Refresh (HRRR) data. It is intended for researchers in weather forecasting, encompassing both physical and deep learning methods.
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[Github Link](github_link: https://github.com/HuskyNian/HR-Extreme)
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## Dataset Structure
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The dataset is divided into two main folders:
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- `202001_202006`: Contains data from January 2020 to June 2020.
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