Hotspell is a Python package that detects past heat wave events using daily weather station data of minimum and maximum air temperature. The user can choose between a range of predefined threshold-based and percentile-based heat wave indices or alternatively can define a full customizable index.

The main output of hotspell are the dates and characteristics of heat waves found within the study period, stored in a pandas DataFrame. If selected by the user, summary statistics (i.e. annual metrics) of the heat wave events are also computed.

Documentation is available at Read the Docs.

Required dependencies are:

• NumPy
• pandas

These packages should be installed beforehand, using the conda environment management system that comes with the Anaconda/Miniconda Python distribution.

Then, hotspell can be installed from PyPI using pip:

pip install hotspell

1. Import the hotspell package

import hotspell

2. Choose the heat wave index CTX90PCT

index_name = "ctx90pct"
hw_index = hotspell.index(name=index_name)

3. Set your data path of your CSV file

mydata = "my_data/my_file.csv"

The CSV file should include the following columns

• Year
• Month
• Day
• Tmin
• Tmax

in the above order, without a header line. Each day should be in a seperate line; missing days/lines are allowed.

For example:

4. Find the heat wave events

hw = hotspell.get_heatwaves(filename=mydata, hw_index=hw_index)
heatwaves_events = hw.events
heatwaves_metrics = hw.metrics

Hotspell is developed during research under the Greek project National Network for Climate Change and its Impact, CLIMPACT.

Hotspell is licensed under the BSD 3-clause license.