We conduct regular verification of our forecast, comparing them to actual observation data. Thereby, we make sure that our services are delivering top quality forecasts, and continuously improving. We are the first commercial service who publishes verification data on their website.

Why do we publish our validations? Because:
1. We are transparent: our customers should know what they get;
2. We deliver quality: our accuracy is so high, that it is worth showing.
3. We are realistic: you should know what to expect from a forecast - and what not.
4. We are competitive: if someone believes we are not good enough - show us how to do better.
What does meteoblue quality mean? Here are some examples:
TEMPERATURE:
meteoblue predicts more than 70% of all temperatures with less than 2°C difference to the reality - 3 days (72 hours) in advance. For 12 hours ahead, more than 80% of all temperature forecasts are less than 2°C different from measurement - on an hourly basis. The RMSE (Root Mean Square Error) of the hourly forecast is less than 2.5°C for up to 3 day forecasts,  and around 2°C for 1 day forecast  (these data are valid for Europe and North America).
What does that mean?
Personally: If you assume the you can distinguish temperature differences of more than 2°C (by feeling),  than 2/3 of all meteoblue hourly temperature forecasts are already correct 3 days in advance! It means that when you look at a meteoblue forecast for the next 72 hours, you will experience during at least 54 hours the same temperature as meteoblue forecasts.
Technically: If you interpolate temperature measurements of a weather station made every 3 hours into hourly data and compare them to the actual hourly measurements, your RMSE will be 1.5-2.0°C. The meteoblue forecast error is on average 2.2°C. This means that the temperature forecast is already almost as good as a measurement.

WIND:
The meteoblue wind forecast for the period of 12-48 hours ahead reaches 70-80% agreement (Correlation r²) with measured values. Knowing that wind can vary substantially within a 200 metre distance, this is a very high correlation. When wind is measured within distances of 200-500 metres, these measurements rarely show a higher agreement between each other than meteoblue forecast do.
What does that mean?
Personally: If you want to know the wind situation for an area of 3-12 kilometers, looking at the meteoblue forecast gives you the same precision as looking at a measurement from a weather station within that area.
Technically: meteoblue models forecast the wind with a precision almost equivalent to mesurements. Adding local correction techniques, the correlation (r²) can be increased by further 5-10%. This means that your can reach a 90% correlation using the meteoblue wind forecast on an hourly basis for 1-5 days ahead.

PRECIPITATION:
meteoblue can forecast more than 75% or 85% of all precipitation events with more than 2 or 5 millimeters (mm) correctly 3 days in advance. This includes forecasting the days on which such events will not occur. Looking at precipitation events of 2 mm, meteoblue can forecast 50% of those 6 days in advance, and more than 60% one day in advance.
What does that mean?
Personally: If meteoblue forecasts rain 1 day ahead, it will arrive in at least 2 of 3 cases; and a meteoblue rain forecast 6 days ahead is still more than 50% likely to occur.
Technically: with meteoblue precipitation forecast models, you have statistics that are so solid that you can calculate economics of intervention for precipitation events based on the meteoblue forecast.

MORE VALIDATIONS:
A comparison of meteoblue NMM-13 weather forecasts with measurements on 2800 weather stations for 2008 can be viewed and downloaded by clicking HERE.
A comparison of the meteoblue NMM weather forecast to other forecast methods can be viewed and downloaded by clicking HERE.
WEATHER STATIONS:
meteoblue forecasts are high-quality approaches to the reality. Are weather stations still needed?
Yes, if…
… the reality is characterised by small-scale differences (e.g. valleys, mountain summits),
… short term changes within a range of minutes are important (e.g. airports),
… long-term developments have to be observed (e.g. disease development in a vineyard) or
… small differences have great economic importance (e.g. frost on the road),
then weather stations are very important for the decision making on weather-dependent measures.
meteoblue forecasts can complement such measurements, where the decisions have to be taken 6-144 hours before arrival of the event.