Food truck owners expect to face a variety of challenges daily. But perhaps one of the biggest challenges they face is terrible weather. Keeping the truck open and customers satisfied can be extra demanding when it’s freezing or pouring outside.

This episode is about how we designed the game’s weather system to simulate city-specific weather conditions.

The Challenge

As you know, there are several major cities in the game. To improve the player experience and game difficulty, we had to ensure that each city’s in-game weather mirrors the historical weather conditions of their real-life counterpart.

Getting this right was quite the challenge. ๐Ÿ˜…


We first tried to implement a replica of historical weather conditions in each city. But we quickly realized this would pose a problem with replayability as players would eventually find our data source ๐Ÿ˜จ and have an unfair advantage on the leaderboards.

So we decided to discard this method. ๐Ÿšฎ

Our second and final approach was to use the normal distribution and the average temperature and precipitation values in a city to generate the weather condition. For example, let’s take Washington, DC, as a case study.

Below is the actual data for Washington, DC:

By taking the average temperature as a mean and using a standard deviation of one, we randomly generated the temperature to fit within the high and low ranges. The Boxโ€“Muller transform was particularly useful here.

This method helped us account for the rare occurrence of a very high ๐Ÿฅต or very low ๐Ÿฅถ temperature, which happens in reality. Similarly, for the precipitation, we used the average as a mean and a standard deviation of two to generate the amount of rain ๐ŸŒง๏ธ, which directs the cloud volume. โ˜๏ธ



You can observe a clear jump โฌ†๏ธ in averages as we move from month to month, which shouldnโ€™t be so. To resolve this, we employed weekly peak averages instead of monthly, which made it work as intended.

Below is a yearly temperature simulation for Washington DC for the morning ๐ŸŒ…, afternoon ๐Ÿ•‘, and evening ๐ŸŒ†.

The simulation for the rain/cloud below is for the mornings alone in Washington, DC. As you can see, most mornings, there is a light shower or an overcast, followed by sunny conditions and light rain.

We think this method strikes the right balance between fun ๐Ÿ•บ๐Ÿ’ƒ and computing requirements. ๐Ÿ’ป

In-game impact

The presence of rain โ˜” and snow ๐ŸŒจ๏ธ reduces the outdoor population in the game, thus reducing the number of sales possible during the period, just like in real life. You can always invest in upgrades to reduce the impact of weather on your business.

However, it might not be a profitable investment if your chosen customer segment is not big enough. It will take strategic thinking ๐Ÿค” and astute decision-making to discern the best time for such an investment.

That’s it for this episode!

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Live Long and Prosper ๐Ÿ‘‹,
Team Visionaries