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NianRan1
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HR-Extreme

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weather-forecasting

extreme-weather

high-resolution

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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.
 [Github Link](github_link: https://github.com/HuskyNian/HR-Extreme)
 ## Dataset Structure
-The dataset is divided into two main folders:
-- `202001_202006`: Contains data from January 2020 to June 2020.
 - `202007_202012`: Contains data from July 2020 to December 2020.
 Each folder stores the dataset in the WebDataset format, following Hugging Face's recommendations. Every 10 `.npz` files are aggregated into a single `.tar` file, named sequentially as `i.tar` (e.g., `0001.tar`).

 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.
 [Github Link](github_link: https://github.com/HuskyNian/HR-Extreme)
 ## Dataset Structure
+The dataset is in the following folder:
 - `202007_202012`: Contains data from July 2020 to December 2020.
 Each folder stores the dataset in the WebDataset format, following Hugging Face's recommendations. Every 10 `.npz` files are aggregated into a single `.tar` file, named sequentially as `i.tar` (e.g., `0001.tar`).