This app allows to create temperature and precipitation (rain, showers, and snowfall) graphs that compare the values of a given location in a given year to the values of a reference period at the same place.
The reference period defaults to 1961-1990 which according to the World Meteorological Organization (WMO) is currently the best "long-term climate change assessment". Other reference periods of 30 years each can be selected, too.
The peaks on the graph show how the displayed year's values deviate from the mean of the reference period. For temperature graphs, this means that the more and the higher the red peaks, the more "hotter days than usual" have been observed. The blue peaks indicate days colder than the historical mean. Precipitation graphs show blue peaks on top which means "more precipitation than normal" and in red "less than normal".
The interactive plot is created using Python's Plotly library. In a first version with static images, Matplotlib came to use.
By default, mean values of the reference period are smoothed using Locally Weighted Scatterplot Smoothing (LOWESS). The value can be adjusted under "advanced settings" in the app.
In the latest version (first published on 17 August 2023), the graphs are displayed interactively on larger screens. That means you can hover over the graph and get the exact values displayed for every day. You can also zoom in to see parts of the plot.
To create the graph, data from the open-source weather API Open-Meteo is used. According to them, "the Historical Weather API is based on reanalysis datasets and uses a combination of weather station, aircraft, buoy, radar, and satellite observations to create a comprehensive record of past weather conditions. These datasets are able to fill in gaps by using mathematical models to estimate the values of various weather variables. As a result, reanalysis datasets are able to provide detailed historical weather information for locations that may not have had weather stations nearby, such as rural areas or the open ocean."
To get location data (lat/lon) for the input location, Openstreetmap's Nominatim is used.
Available metrics are:
The app and the plots it produces are published under a Creative Commons license (CC by-sa-nc 4.0).
You can try the app at https://yotka.org/meteo-hist/
To use the app on your machine, there are two simple ways:
1. Set up a Python environment, clone the repository, and run app.py using streamlit:
git clone https://github.com/yotkadata/meteo_hist/ cd meteo_hist/ pip install -r requirements.txt streamlit run app.py
This should open a page in your default browser at http://localhost:8501 that shows the app.
2. Set up Docker and run it in a container (you can change the name and the tag, of course):
docker build -t meteo_hist:latest github.com/yotkadata/meteo_hist docker run -d --name meteo_hist -p 8501:8501 meteo_hist:latest
To save the generated files outside the Docker container, you can add a binding to a folder on your hard drive when you start the container:
/home/user/path/output/ with the path to the folder to be used).
docker run -d --name meteo_hist -p 8501:8501 -v /home/user/path/output/:/app/output meteo_hist:latest
It is also possible to use the Python class directly, without the web app. See the
notebooks directory for examples.