Interactive exploration of the Cambridge University Computer Laboratory weather station measurements.
If you like ComLabWeatherShiny, give it a star, or fork it and contribute!
The Digital Technology Group in the Cambridge University Computer Laboratory maintain a weather station.
I live close to this weather station. Hence my interest.
This R shiny app provides an interactive exploration of some of this data. It includes basic scatter plots, interactive plots (linked plots with data brushing) and also radial plots showing annual changes.
The weather measurements include the following variables.
| Variables | Units |
|---|---|
| Temperature | Celsius (°C) * 10 |
| Dew Point | Celsius (°C) * 10 |
| Humidity | Percent |
| Pressure | mBar |
| Wind Speed Mean | Knots * 10 |
| Wind Bearing Mean | Degrees |
| Timestamp | Data Hours:Minutes:Seconds |
Dew point is the temperature at which air, at a level of constant pressure, can no longer hold all the water it contains. Dew point is defined here and in more detail here.
There are known issues with the sunlight and rain sensors. These measurements are not included for now.
The data included in the app start on 2008-08-01 when the weather station was moved to it's current location. Unrealistically high wind speed (> 60), low humidity (< 25) and low temperature (< -20) values were removed. The Digital Technology Group list inaccuracies in the weather data. All measurements for the entire day or days was removed for each of the listed inaccuracies. Cook's distance was used to remove the remaining influential observations but some problems may remain in the data, such as long series of repeated values. The remaining measurements have no missing values.
There are two cleaning scripts included in the scripts directory:
- 1-load.R which loads the data and adds some date and time related fields.
- 2-clean.R which removes unrealistic and inaccurate measurements.
I have no affiliation with Cambridge University, the Computer Laboratory or the Digital Technology Group.
Usage is probably best done within RStudio.
# Install required libraries
install.packages("shiny")
install.packages("data.table")
library(shiny)
# Only run in interactive R sessions
if (interactive()) {
runGitHub("makeyourownmaker/ComLabWeatherShiny")
}- Update data to include 2020
- Improve documentation
- Describe each of the interactive plots in more detail
- Add tests
- Using shinytest
- Make app available on shinyapps.io
- My related weather repositories:
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.