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Message: <blockquote data-quote="The Firebird" data-source="post: 9856534" data-attributes="member: 7015803">Hi folks, I’ve been working on a project generating weather in RPGs and I wanted to share it. The concept is—given some environment, can we realistically generate its weather in a way that is easy to use at the table? I'll start out with my answer, which looks something like this. The idea is, each day is reduced to a weather code, giving temperature, cloud cover, and rain. Then you get a d100 table for that type of day, which determines how you transition to the next day. (The percentages on the first column give the average probability of encountering that type of day).  [ATTACH=full]429377[/ATTACH]Now the background: I wanted to make a system that (1) relies on real data; (2) is algorithmic; and (3) is easy to apply to new environments. The idea being, then I can make it work anywhere we want.To do so, I took data from the <a href="https://cds.climate.copernicus.eu/datasets/reanalysis-era5-single-levels?tab=download" target="_blank">ERA5</a> dataset (accessed via <a href="https://open-meteo.com/en/docs/historical-weather-api" target="_blank">Open-Meteo</a>)—this is a big global weather database, that has weather for any location in the world since 1940. People generated this by taking weather records from different stations, combined with modeling efforts, to get global coverage. That means there is a record we can use for the weather of any place we want, with decades of data.Then, I reduced each data to a code, for temperature, precipitation, and cloud cover. (I missed out on wind—which is complicated—and fog—where the data is poor). I then computed the day-by-day transition probabilities: e.g., if it is hot and overcast today, how likely is it to be hot, overcast, and rainy, tomorrow?Here is a breakdown of the thresholds I used:Temperature[spoiler=Temperature]Over 100 F: Extreme HeatOver 80 F: HotOver 55 F: WarmOver 35 F: CoolOver 0 F: ColdUnder 0 F: Extreme Cold[/spoiler]Cloud Cover[spoiler=Cloud Cover]Over 60%: OvercastOver 25%: Partly CloudyUnder 25%: Clear[/spoiler]Precipitation[spoiler=Precipitation]Over 0.8” rain: Heavy rainOver 0.2” rain: RainOver 3” snow: Heavy snowOver 0.3” snow: SnowUnder 0.2” rain and Under 0.3” snow: No precipitation[/spoiler]Doing this, and ignoring low probability (<1%) days, gives you a ‘transition matrix’ for a particular locale. I then cast these into d100 tables. The idea here is, you find the type of day you are on, roll on the corresponding column, and use it to pick the new kind of day.With a d100 transition matrix, you end up matching the transition probabilities pretty exactly. Here, for example, are the transition probabilities you get by rolling vs the data for Chicago winter (NB: transposed from the above). Match to Real Data[spoiler=Match to Real Data][ATTACH=full]429378[/ATTACH][/spoiler]And some other examples that I've generated. Cairo Summer:[Spoiler=Cairo Summer][ATTACH=full]429379[/ATTACH][/spoiler]Seattle Autumn[spoiler=Seattle Autumn][ATTACH=full]429380[/ATTACH][/spoiler]Singapore Spring[spoiler=Singapore Spring][ATTACH=full]429381[/ATTACH][/spoiler]I’m planning to build these for a wider variety of locales (e.g., 1 for each of the major climate classifications). But before I do I wanted to share these and get feedback about parts that are missing or ways they could be improved. I’ve written more about the process, mostly for my own edification, if anyone is interested in more depth (<a href="https://thefirebirdslair.blogspot.com/2025/11/weather-generation-1-what-i-want-in.html" target="_blank">part 1</a>, <a href="https://thefirebirdslair.blogspot.com/2026/02/weather-generation-2-what-are-we-trying.html" target="_blank">part 2</a>, <a href="https://thefirebirdslair.blogspot.com/2026/02/weather-generation-3-single-tables-with.html" target="_blank">part 3</a>, <a href="https://thefirebirdslair.blogspot.com/2026/02/weather-generation-3-weather-matrices.html" target="_blank">part 4</a>, <a href="https://thefirebirdslair.blogspot.com/2026/02/weather-generation-5-temperature-swings.html" target="_blank">part 5</a>). I’d love to hear any feedback or comments, positive or negative.Some outstanding questions I have:- Seasons will differ for different locales. How do I move past Spring/Summer/Autumn/Winter? I suppose location specific?-Are the temperature, precipitation, and cloud cover cutoffs reasonable? Does anyone have clever ideas to get fog or wind?-Is the presentation intuitive or confusing? Are there ways to improve it?-Is 1% a reasonable cutoff, or would including more extreme (or less extreme) weather be preferable?-Are there any locations you’re interested in seeing a table for?</blockquote>

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