The first-ever wind animation showing low-res GRIB data (white) and high-resolution crowdsourced measurements (purple).

Crowdsourced vs GRIB Forecasts – Test Results

Most boating apps and weather services all use weather animations and forecasts in GRIB format from the same few satellites. But weather satellites are from 500 – 22,000 miles up in space. They attempt to predict wind speed and direction using satellite imaging. This results in forecasts that are low-resolution and not accurate.

Crowdsourcing can solve these problems. As of April 2026, SailTimer has received over 111-million wind measurements from boaters around the world. We do not have coverage in every location on earth, which is what GRIB is for. But where we have crowdsourced data, it is more accurate than GRIB — and we have the data to prove it.

We archive all incoming data and index it with the GRIB forecast for that location and time. Then if the forecast for tomorrow afternoon at 2 pm says “20 knots from the South”, we know exactly how the wind will be flowing behind an island or funneling into a channel. This modeling means that we do not need live data in every possible location, to provide more accurate wind forecasts than GRIB predicted wind.

How We Did It

To evaluate the performance of crowdsourced wind prediction against NOAA’s GFS GRIB forecasts, we started with wind measurements from users. Unlike giant GRIB cells that are typically 1/4 degree (15 x 15 nautical miles), our measurements are in microcells that are 20 x 20 meters. We may have multiple observations in one cell or within the same hour, so those are averaged for the cell value for wind direction and wind speed. We used a sample of 476,784 microcells.

Our basic goal was to find microcells where we had data on different dates or times. Each wind measurement is matched with the GRIB forecast for that location and time. So we can have 2 measurements:

• The earlier observation that allows us to make a prediction about wind direction and speed at the later time (when the GRIB wind direction is the same). These repeated observations might have been 2 hours, 2 weeks or 2 years apart.
• The later measurement of the actual wind direction and speed.

Then we have the most recent GRIB forecast. One of the (many) problems with GRIB data is that they only come out 4 times a day. So they may be a forecast for 1 hour in the future, or up to 6 hours in the future. GRIB is never real-time, and is often stale. The farther out the GRIB forecast is, the less accurate it is likely to be.

The Question: Is there better accuracy for wind direction and speed with the GRIB forecast from 1-6 hours ago, or from the crowdsourced forecast model, which uses actual measurements to model how wind flows around landforms, behind islands and funnels into channels?

Ironically, the crowdsourced forecasts depend on the GRIB forecast, which we know is inaccurate. If we are going to predict wind direction and speed for tomorrow afternoon at 2 pm behind a certain peninsula, out on the open water, or in a narrow channel, we have the wind measurements and the GRIB forecast for that location. So if the GRIB forecast for tomorrow at 2pm says “wind from the South West at 14 knots”, which is the closer match: our prediction based on how the wind flowed there on a previous occasion with the same GRIB forecast, or the GRIB forecast made tomorrow just before that time?

Results and Interpretation

There were 28,183 repeating microcells, with wind measurements on different days or times. When we compared a later measurement against the GRIB prediction and the crowdsourced prediction, the crowdsourcing is more accurate:

Modeling wind flow in coastal areas with crowdsourced data substantially improves both wind direction and wind speed accuracy compared to the GRIB marine weather forecast.

These results demonstrate that the crowdsourced model and wind maps are more accurate than forecasts or animations based on GFS GRIB data.

1. Wind direction: The mean absolute error in the crowdsourced model is nearly 30 degrees less than the GRIB forecast.
2. Wind speed: The mean absolute error is 30% less with crowdsourced predictions than the GRIB marine weather forecast.

This may appear paradoxical, since we index every crowdsourced wind measurement with the limited accuracy of the GRIB forecast for the same time and location. But that is the point: when we use previous observations along with the GRIB satellite forecast, the additional information and accuracy of the actual wind measurements gives a more accurate forecast.

For more information on using crowdsourced data in the most accurate wind map animations, and generating high-resolution wind maps of your own boating waters, see SailTimer.boats. Or check out the marine weather animations in the SailTimer app.