Update README.md

README.md

@@ -28,7 +28,8 @@ 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.
+  description: This dataset contains uploaded Zarr files as zip archives.
+
 ---
 
 ![CC-BY-4.0](https://img.shields.io/badge/license-CC--BY--4.0-blue)
@@ -36,9 +37,9 @@ configs:
 # 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.
+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 **.zarr.zip 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.
+The subset focuses on specific variables and configurations, which are detailed below. 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.
@@ -54,6 +55,27 @@ This dataset is derived from the [Met Office UK Deterministic Dataset](https://r
 - **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 `.zarr.zip` archives. Each archive corresponds to a specific time interval, such as `2023-01-01-00.zarr.zip`.
 
-### 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.
+### Subset Attributes
+This dataset includes a subset of numerical weather prediction (NWP) variables, categorized as follows:
+
+#### Accumulated Channels:
+- **radiation_flux_in_shortwave_total_downward_at_surface**: Downward shortwave radiation flux at the surface (W/m²)
+- **radiation_flux_in_longwave_downward_at_surface**: Downward longwave radiation flux at the surface (W/m²)
+- **surface_roughness**: Surface roughness (m) (if available, otherwise null or computed)
+- **radiation_flux_in_uv_downward_at_surface**: Downward UV radiation flux at the surface (W/m²)
+
+#### General NWP Channels:
+- **temperature_at_screen_level**: 2-meter temperature (°C)
+- **radiation_flux_in_shortwave_total_downward_at_surface**: Downward shortwave radiation flux at the surface (W/m²)
+- **radiation_flux_in_longwave_downward_at_surface**: Downward longwave radiation flux at the surface (W/m²)
+- **cloud_amount_of_high_cloud**: High cloud cover (fraction or %)
+- **cloud_amount_of_medium_cloud**: Medium cloud cover (fraction or %)
+- **cloud_amount_of_low_cloud**: Low cloud cover (fraction or %)
+- **cloud_amount_of_total_cloud**: Total cloud cover (fraction or %)
+- **snow_depth_water_equivalent**: Snow depth equivalent water content (mm)
+- **surface_roughness**: Surface roughness (m) (if available, otherwise null or computed)
+- **radiation_flux_in_uv_downward_at_surface**: Downward UV radiation flux at the surface (W/m²)
+- **wind_speed_at_10m**: 10-meter wind speed (m/s)
+- **wind_direction_at_10m**: 10-meter wind direction (degrees)
+
+This dataset provides essential meteorological variables for applications in weather prediction, climate modeling, and solar energy forecasting.