hotspell 0.1.5.3

Detect heat waves from weather station data

About

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.

Installation

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

Quick Start

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:

1999	8	29	23.2	37.1
1999	8	31	24.1	37.7
…	…	…	…	…

4. Find the heat wave events

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

Acknowledgements

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

License

Hotspell is licensed under the BSD 3-clause license.