Time dimensions

Weather occurs in the past, the present and the future. meteoblue therefore presents weather information in four time dimensions. These are:

Climate

Climate shows aggregated weather parameters from the past, covering 5-30 years of past data. This allows to describe the climate for an area or location. Climate data typically shows minima, averages, maxima for specific periods like days, months, years, and includes the most common variables, such as temperature, relative humidity, precipitation, wind, radiation, sunshine and pressure. Climate information is available from measurements for some locations, where measurement data are available over a longer period of time, and from simulations covering the entire world since 2008.

You can find examples of a climate feature with the meteograms Climate or Climate comparison.

History

History shows weather variables from a specific time in the past. Historical data and diagrams are available for hours, days, months and entire years, and can be selected for a specific period. They are used to reproduce weather conditions at a specific location during a specific time, using the most common variables. 

Nowcast

Nowcast shows weather data for the present. These may be measured (by weather stations), observed (by satellites, cameras or users) or simulated (by nowcasting methods) and show the best information available for the current conditions. For time ranges of a few hours, it is also possible to forecast some weather phenomena, such as showers, with a higher accuracy, based on real-time observations.

Nowcast weather information is only available for areas where sufficient real-time data is available. An example of a nowcast feature is the rainNOW

Forecast

Forecast shows weather data for the future. These are always simulated data because measurements and observations can not be available for the future. Forecast weather information is commonly called weather "forecast", "prediction" or "prognosis". 
meteoblue calculates forecast data for nowcasting (0-6 hours), day-ahead forecast (0-36 hours ahead), week ahead (0-7 days), and 2-weeks ahead (0-14 days). These are also defined as "short and medium range" forecasts. meteoblue does currently not offer "long range" forecasts for 1-6 months because these forecasts are still usually only valid for large areas, not for specific locations, frequently associated with lower precision and only possible for a few variables.
To forecast probable weather conditions for future months and years, we offer the "clima" information to give users an overview of the possible conditions at a selected locations during the period of interest.

Forecast information is shown as tables, diagrams, maps and available as data, both through our website and professional interfaces. It is updated regularly, at least twice a day. 

How to determine past weather — differences in temperature forecast for the same area — why?

For locations in a very complex terrain, for example, mountainous area, the simulation can differ from conditions at one particular location. So to characterise the weather (and climate) in a place, we have the following methods:

1. Measurements: There are no measurements for locations without an installed functioning measurement station, in order to measure weather data for a longer period of time.

2. Measurements from neighbouring locations: this works reasonably well, if the measurement station is not so far away and the terrain is fairly homogeneous.

3. High resolution simulations (Local area models) must be available for the location.

4. Global simulations: this is the simulation which we offer for such locations (30 km in hourly intervals), so this option gives you a fair idea about the weather - but is not able to discern local air flows, and phenomena such as local thunderstorms, wind patterns and snow cover effects.

5. Remote sensing (Satellites): these provide information about cloudiness and can be used to check the validity of the other methods by direct comparison of the cloudiness data.  

6. Local observations (collections of anecdotal or other information describing the weather): these give you an idea on how valid any of the other methods are.

For more advanced studies, a combination of these methods can yield more precise information about local conditions. This is warranted if there are decisions of larger economical impact to be taken.