Make sure to use this tool for guaranteed sunny holidays
Code-free Data Science
In this series I show how to engage in code-free Data Science. For all the projects I use visual ETL tools (Extract, Transform, Load) where all the logic is created via drag and drop. Project files can be found here. The tool itself is here.
The best way to ensure you’ll enjoy sunny holidays is to select the right spot in the right season. How to do that? By trying to predict how the weather is going to behave using meteorological data collected over a ~10 year span.
Some years ago, I was planning with some friends to go somewhere sunny and warm for New Year’s Eve to do a bit of surfing. We were all based in Portugal and the UK and decided not to go too far to reduce time spent on travelling.
Our priority was to find a place with nice temperatures and little rain. We’re not exactly surf-pros, so wave and swell qualities came only second place.
It is easy to find weather information for the next 10 days, but how to plan for something 2–3 months into the future? Obviously no weather model can plan that far ahead, but I thought we could use averaged past meteorological data to give us an idea of what to expect.
Meet the weather map:
I started with a data set containing various meteorological data collected during a period of around 10 years of around 115k stations all around the world. Not all stations collected the same data so I chose a subset of what I considered important, such as precipitation, temperature, wind speed, and snow-fall.
One thing I find particularly important, and what was missing in the data set, is an indication of how sunny a location most likely will be. The data set had a column of sunshine-hours, but what I was looking for was more an indication of meteorological stability, i.e. how likely it would be to experience no rain at all.
I’m a big fan of leaving the house in the morning and not worrying at all that it might rain in the afternoon. Using this idea, I created an indicator that tells us the percentage of days with absolutely zero precipitation during a certain week for the 10 years of data I had at my disposal.
The Sunny Algarve
Looking through the data, I found an anomaly: a place in Europe with unusually good and stable weather around New Year’s Eve: The Algarve in Portugal.
Verifying both average temperatures and percentage of sunny days, we see an uptick during the end of the year. The percentage of sunny days during the time of our surf-trip was expected to be around 70%.
That was much better than anywhere else in Europe around that time, so we booked tickets. The trip turned out to be a blast. In fact, it didn’t rain at all and the temperatures were so good, we were out in shorts and t-shirts.
How should you use this tool?
First, check the percentage of sunny days averaged over the whole year to find generally sunny locations here.
Yearly Weather Pattern
You will be greeted with a Yearly Weather Pattern dashboard that shows a map on the left side in which the marker size and colour correspond to the percentage of sunny days.
Zoom in and select one or more markers to see how their seasonal weather patterns change. This should give you an idea where and when there are some sweet-spots.
Weekly Temperature Prediction
Then, go to the second tab Weekly Temperature Prediction, zoom into your region of interest, choose some markers and choose a week to get more information.
The map shows temperatures ranging from 0 °C in white to 10 °C in blue to 20 °C in yellow and everything above 30 °C in red. On the right side you can see averages of precipitation, snow-fall, temperature, sunny days percentage and wind speeds for your selected locations.
After you are all done, it’s time to sit back, buy tickets, and relax.
