---
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

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## 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.

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## 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.

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## 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

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## Limitations

- Monthly aggregation does not capture day-level variability
- The dataset only contains two derived climate indicators (`CDD` and `HDD`)

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