Update Readme

Removed detailed path component descriptions and examples from the README.

Author: chantreux

README.md

@@ -11,49 +11,11 @@ The repository uses a structured directory path format to organize downloaded, d
 {base_path}/{product_type}/{dataset}/{temporal_resolution}/{interpolation}/{variable}/
 ```
 
-**Path Components:**
-- `product_type`: Type of data processing
-  - `raw`: Data downloaded directly from CDS
-  - `derived`: Variables calculated from raw data (e.g., wind speed from u/v components) or interpolated to different grids
-- `dataset`: CDS dataset name (e.g., `reanalysis-era5-single-levels`, `reanalysis-cerra-single-levels`)
-- `temporal_resolution`: Time frequency of the data
-  - `hourly`: Hourly data (e.g., ERA5 with all 24 hours)
-  - `daily`: Daily data or daily statistics
-  - `3hourly`: 3-hourly data (e.g., CERRA)
-  - `6hourly`: 6-hourly data
-  - `monthly`: Monthly data
-- `interpolation`: Grid specification
-  - `native`: Original grid (no interpolation)
-  - `gr006`: 0.0625 degree grid (6.25 km)
-  - Other grid specifications as needed
-- `variable`: Variable name (e.g., `u10`, `v10`, `sfcwind`, `t2m`)
-
 **Examples:**
 
 1. **Raw ERA5 hourly wind components:**
    ```
    /lustre/.../raw/reanalysis-era5-single-levels/hourly/native/u10/
-   /lustre/.../raw/reanalysis-era5-single-levels/hourly/native/v10/
-   ```
-
-2. **Derived daily wind speed from ERA5 (calculated variable):**
-   ```
-   /lustre/.../derived/reanalysis-era5-single-levels/daily/native/sfcwind/
-   ```
-
-3. **Raw CERRA 3-hourly data:**
-   ```
-   /lustre/.../raw/reanalysis-cerra-single-levels/3hourly/native/t2m/
-   ```
-
-4. **Derived CERRA data interpolated to 0.0625 degree grid:**
-   ```
-   /lustre/.../derived/reanalysis-cerra-single-levels/3hourly/gr006/t2m/
-   ```
-
-5. **ERA5 daily statistics:**
-   ```
-   /lustre/.../raw/derived-era5-single-levels-daily-statistics/daily/native/t2m/
    ```
 
 **Note:** Interpolated data is stored under `derived` with the `interpolation` field indicating the target grid (e.g., `gr006`). This distinguishes it from calculated variables which use `interpolation=native`.
@@ -62,7 +24,7 @@ The repository uses a structured directory path format to organize downloaded, d
 Format of the files is "{var}\_{dataset}\_{date}.nc"
 With date: 
 - "{year}{month}" for big datasets like CERRA saved month by month (download is faster this way). 
-- "{year}" for the other datasets that are saved year by year. 
+- "{year}" for the other datasets the data is saved year by year. 
 
 ## Creating Directory Structure
 
@@ -79,20 +41,18 @@ python scripts/create_folder_structure.py
 The script reads all CSV files in the `requests/` directory and creates the directory structure according to the format:
 `{base_path}/{product_type}/{dataset}/{temporal_resolution}/{interpolation}/{variable}/`
 
-This is useful for:
-- Setting up the directory structure before starting downloads
-- Verifying the paths that will be used
-- Preparing storage locations in advance
 
 ## Contents
 
 | Directory | Contents |
 | :-------- | :------- |
 |  [requests](https://github.com/SantanderMetGroup/c3s-cds/tree/main/requests) | Contains one CSV file per CDS catalogue, listing the requested variables, temporal resolution, interpolation method, the target save directory, and whether the variable is raw or requires post-processing to be standardized.
-|  [scripts](https://github.com/SantanderMetGroup/c3s-cds/tree/main/scripts) | 	Python scripts to download data from the CDS.
 | [provenance](https://github.com/SantanderMetGroup/c3s-cds/tree/main/provenance) | Contains one JSON file per catalogue describing the provenance and definitions of each variable.
-| [standardization](https://github.com/SantanderMetGroup/c3s-cds/tree/main/standardization) |  Python recipes to standardize the variables.
-| [derived](https://github.com/SantanderMetGroup/c3s-cds/tree/main/derived) |  Python recipes to calculate derived products from the variables.
+|  [scripts/download](https://github.com/SantanderMetGroup/c3s-cds/tree/main/scripts/download) | 	Python scripts to download data from the CDS.
+| [scripts/standardization](https://github.com/SantanderMetGroup/c3s-cds/tree/main/scripts/standardization) |  Python recipes to standardize the variables.
+| [scripts/derived](https://github.com/SantanderMetGroup/c3s-cds/tree/main/scripts/derived) |  Python recipes to calculate derived products from the variables.
+| [scripts/interpolation](https://github.com/SantanderMetGroup/c3s-cds/tree/main/scripts/interpolation) |  Python recipes to interpolate data.
+| [scripts/catalogue](https://github.com/SantanderMetGroup/c3s-cds/tree/main/scripts/catalogue) |  Python recipes to produce the catalogues of downloaded data.
 | [catalogues](https://github.com/SantanderMetGroup/c3s-cds/tree/main/catalogues) |  	CSV catalogues of datasets consolidated in Lustre or GPFS. The catalogues are updated through a nightly CI job.