Detect heat waves from weather station data
Project description
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.
Installation
Required dependencies are:
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
Import the hotspell package
import hotspell
Choose the heat wave index CTX90PCT
index_name = "ctx90pct"
hw_index = hotspell.index(name=index_name)
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 |
… |
… |
… |
… |
… |
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.
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