Help Needed: Weather Forecasting and Rain Probability Calculation Using Ecowitt Data

Hello everyone!
I’m currently working on a weather forecasting project using data from my Ecowitt weather station. I’d like to achieve two main goals, but I’m having trouble getting accurate results and would appreciate guidance from the community.

Goal 1: Rain Probability Calculation

I’m trying to calculate the probability of rain (in %) using data collected by the weather station, such as:

  • Dew point
  • Temperature
  • Atmospheric pressure

The problem I am facing is that I cannot find a reliable mathematical formula to calculate the probability of rainfall by combining dew point, temperature, and atmospheric pressure

Goal 2: Short-Term Weather Forecast (1 to 3 Days)

The second thing I’d like to achieve is generating a short-term weather forecast (up to 3 days) based solely on data from a single weather station. I understand that accurate forecasts typically require data from multiple locations, but I’d like to explore whether a localized forecast is possible with just one station’s data.

Context:

  • I’m using Home Assistant to collect and analyze the data from my Ecowitt weather station.
  • I’ve already set up the integration to pull data like temperature, dew point, and atmospheric pressure, but I’m struggling with the logic to achieve the above goals.

What I’ve Tried:

  1. Creating formulas using temperature, dew point, and pressure to calculate rain probability. Results are inconsistent.
  2. Reading documentation and forums about weather forecasting algorithms, but most examples rely on external APIs .

What I Need Help With:

  1. Suggestions for more accurate algorithms or methods to calculate rain probability.
  2. Guidance on whether short-term forecasting with one weather station is feasible, and if so, any tips or starting points.
  3. Any examples, resources, or relevant tools that could help me better analyze the data from the station.

The UK Met Office use a Cray XC40 for forecasting. I don’t think you’re going to get far without one.

Edit: Why is this a feature request? Changed to “Share your projects”.

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for local precipitation forecasting I find it relatively simple for an rpi. I am not asking for high data accuracy. Forecasting is definitely difficult, but there are weather stations with a screen that shows the weather for the next few days. That’s what I’m looking for.

There is no formula. Forecasters use an ensemble of climate models running on super computers to predict this.

For example each one of the lines in these graphs (except the dashed pink line) is a prediction by a complex forecasting model. Only when they all agree is the probability high:

The old “stormy”, “change”, “clear” makings you see on barometers are basically meaningless.

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I understand what we see in the ensemble, but if the air is saturated with moisture, don’t the chances of rain increase? yes… so depending on how saturated it is why can’t we calculate the chance of rain? I’m not looking for a way to replace weather broadcasting :slight_smile:

I assumed from this post that you had already cracked the rain goal.

I calculate the height of clouds, and the percentage of cloud cover quite satisfactorily so far. subject to rain. but that’s what I’m looking for