Update README.md

README.md

@@ -9,12 +9,36 @@ tags:
 - zarr
 - climate
 license: cc-by-4.0
+annotations_creators:
+- expert-generated
+language_creators:
+- other
+multilinguality:
+- monolingual
+size_categories:
+- 10K<n<100K
+source_datasets:
+- original
+task_categories:
+- time-series-forecasting
+task_ids:
+- multivariate-time-series-forecasting
+configs:
+- config_name: met-office-uk-deterministic-zarr
+  name: met-office-uk-deterministic-zarr
+  splits: []
+  description: This dataset contains Zarr files uploaded as TAR archives.
 ---
 
 ![CC-BY-4.0](https://img.shields.io/badge/license-CC--BY--4.0-blue)
 
 # Met Office UK Deterministic Dataset (Zarr Format)
 
+## Description
+This dataset is a **subset** of the [Met Office UK Deterministic Dataset](https://registry.opendata.aws/met-office-uk-deterministic/), converted from the original **NetCDF format** into **Zarr format** for modern data analysis. The Zarr files are packaged as **tar archives** for efficient storage and transfer.
+
+The subset focuses on specific variables and configurations, which are detailed in the `met_office_uk_data_config.yaml` file included in this repository. Researchers and developers can use this subset for applications in climate science, weather forecasting, and renewable energy modeling.
+
 ## Usage
 This dataset is provided under the **Creative Commons Attribution 4.0 International License (CC-BY-4.0)**. When using this dataset, you must provide proper attribution to the Met Office as outlined below.
 
@@ -25,4 +49,22 @@ This dataset is derived from the [Met Office UK Deterministic Dataset](https://r
 - **Copyright**: British Crown copyright © Met Office
 
 ## Details
-This version of the dataset has been converted from the original **NetCDF format** to **Zarr format** for ease of use with modern data analysis tools.
+### Zarr Format and Tar Archives
+- **Format**: The dataset files are in Zarr format, a modern storage format optimized for analytics and machine learning workflows.
+- **Packaging**: Zarr files are stored as `.tar.gz` archives. Each archive corresponds to a specific time interval, such as `2022-12-01-00.tar.gz`.
+
+### Subset Configuration
+- The dataset includes a subset of variables and configurations chosen for targeted use cases.
+- For details on the variables and configurations included in this dataset, please refer to the [`met_office_uk_data_config.yaml`](./met_office_uk_data_config.yaml) file.
+
+## How to Access
+You can download and extract the tar archives using the following Python snippet:
+
+```python
+import tarfile
+
+# Example: Extracting a tar.gz archive
+archive_path = "2022-12-01-00.tar.gz"
+with tarfile.open(archive_path, "r:gz") as tar:
+    tar.extractall(path="extracted_zarr")
+```