| --- |
| license: cc-by-4.0 |
| pretty_name: "Italian Forecast Climate Indicators Dataset" |
| dataset_type: "tabular" |
| task_categories: |
| - time-series-forecasting |
| - tabular-regression |
| language: |
| - en |
| tags: |
| - agriculture |
| - climate |
| - italy |
| - heating-degree-days |
| - cooling-degree-days |
| --- |
| |
| # Italian Forecast Climate Indicators Dataset |
|
|
| ## Dataset Description |
|
|
| This dataset contains a filtered and processed selection of monthly climate indicators retrieved from the European Commission Joint Research Centre (JRC): |
|
|
| The released version of the dataset has been simplified for downstream use: |
| - the original `YEAR` and `MONTH` fields were merged into a single `date` column |
| - the dataset fields are now `date`, `CDD`, and `HDD` |
|
|
| - **Geographical Coverage**: Italy |
| - **Temporal Coverage**: 1978-01-01 to 2024-07-01 |
| - **Frequency**: Monthly |
| - **Data Type**: Tabular time-series |
|
|
| --- |
|
|
| ## Dataset Structure |
|
|
| The dataset is distributed as an Excel file and can be easily exported to CSV or parquet. |
|
|
| ### Columns |
|
|
| - `date`: Monthly timestamp in `YYYY-MM-DD` format, using the first day of each month |
| - `CDD`: Cooling Degree Days |
| - `HDD`: Heating Degree Days |
|
|
| ### Notes on Indicators |
|
|
| - **Cooling Degree Days (CDD)** measure how much and for how long temperature is above a base threshold. |
| - **Heating Degree Days (HDD)** measure how much and for how long temperature is below a base threshold. |
|
|
| --- |
|
|
| ## Preprocessing |
|
|
| The dataset was transformed as follows: |
|
|
| 1. Removed the original split temporal representation (`YEAR`, `MONTH`) |
| 2. Created a single monthly datetime field named `date` |
| 3. Kept the climate indicators `CDD` and `HDD` |
|
|
| This makes the dataset easier to load in machine learning and forecasting pipelines. |
|
|
| --- |
|
|
| ## Intended Use |
|
|
| This dataset is suitable for: |
|
|
| - climate-aware agricultural modeling |
| - seasonal and long-range forecasting |
| - energy demand estimation |
| - time-series benchmarking |
| - climate trend analysis |
|
|
| --- |
|
|
| ## Limitations |
|
|
| - Monthly aggregation does not capture day-level variability |
| - The dataset only contains two derived climate indicators (`CDD` and `HDD`) |
|
|
| --- |
