meteoblue compensated for all its CO2 emissions of 2022
As part of our climate protection strategy and as done yearly since 2020, we calculated our carbon footprint and compensated for the emitted CO2.
In the Austrian Alps, it snowed last week. The snowfall creates optimal conditions for skiing.
The variables shown are from direct model output and not scaled to the exact altitude and position of the selected place.
Frequently, forecasts are spot on, sometimes less accurate and a few times they are completely wrong. It would be great to know in advance if the forecast is likely to be correct, but how? All weather forecasts are computed by computer models, and sometimes these differ significantly, which indicates uncertainty and difficulty to make an accurate forecast of the weather. In such cases, the weather forecast is likely to change on a daily basis. Our Multi-Model diagram shows the weather forecast of multiple models from meteoblue and others, mostly national weather agencies. Generally, the uncertainty of the forecast increases with the differences between models.
What to do if the forecast is uncertain?
These weather patterns are very difficult to forecast, vary in place and time or depend on local terrain. While locally forecast precipitation does not occur, it might rain just a few kilometres away. A cold front could arrive a few hours later or thunderstorms might or might not develop. Such conditions are error prone and should be handled carefully. In some cases, even different models may not detect such conditions.
Weather models simulate physical processes. A weather model divides the world or a region into small "grid-cells". Each cell is about 4km to 40km wide and 100m to 2km high. Our models contain 60 atmospheric layers and reach deep into the stratosphere at 10-25 hPa (60km altitude). The weather is simulated by solving complex mathematical equations between all grid cells every few seconds and parameters like temperature, wind speed or clouds are stored for every hour.
meteoblue operates a large number of weather models and integrates open data from various sources. All meteoblue models are computed twice a day on a dedicated High Performance Cluster.
NEMS model family: Improved NMM successors (operational since 2013). NEMS is a multi-scale model (used from global down to local domains) and significantly improves cloud-development and precipication forecast.
|NEMS4||Central Europe||4 km||72 h||10:16 GMT+0330||meteoblue|
|NEMS12||Europe||12 km||180 h||11:11 GMT+0330||meteoblue|
|NEMS2-12||Europe||12 km||168 h||13:55 GMT+0330||meteoblue|
|NEMS-8||Central America||12 km||180 h||14:01 GMT+0330||meteoblue|
|NEMS12||India||12 km||180 h||12:00 GMT+0330||meteoblue|
|NEMS10||South America||10 km||180 h||13:39 GMT+0330||meteoblue|
|NEMS10||South Africa||10 km||180 h||12:55 GMT+0330||meteoblue|
|NEMS8||New Zealand||8 km||180 h||11:14 GMT+0330||meteoblue|
|NEMS8||Japan East Asia||8 km||180 h||10:53 GMT+0330||meteoblue|
|NEMS30||Global||30 km||180 h||09:54 GMT+0330||meteoblue|
|NEMS2-30||Global||30 km||168 h||15:35 GMT+0330||meteoblue|
NMM model family: the first weather model from meteoblue (operational since 2007). NMM is a regional weather model and highly optimised for complex terrain.
|NMM4||Central Europe||4 km||72 h||09:09 GMT+0330||meteoblue|
|NMM12||Europe||12 km||180 h||10:31 GMT+0330||meteoblue|
|NMM18||South America||18 km||180 h||12:37 GMT+0330||meteoblue|
|NMM18||South Africa||18 km||180 h||11:03 GMT+0330||meteoblue|
|NMM18||Southeast Asia||18 km||180 h||11:37 GMT+0330||meteoblue|
Third-party domains: As seen on most other websites
|ECWMF-IFS||Global||30 km||144 h (@ 3 h)||11:23 GMT+0330||European Centre for Medium-Range Weather Forecasts (ECMWF)|
|UKMO-10||Global||10 km||144 h (@ 3 h)||08:53 GMT+0330||UK MET OFFICE|
|UKMO-2||UK||2 km||120 h (@ 3 h)||09:47 GMT+0330||UK MET OFFICE|
|ICON7||Europe||7 km||120 h (@ 3 h)||20:02 GMT+0330||Deutscher Wetterdienst|
|ICON13||Global||13 km||180 h (@ 3 h)||09:30 GMT+0330||Deutscher Wetterdienst|
|ICON2||Germany & Alps||2.2 km||48 h||17:59 GMT+0330||Deutscher Wetterdienst|
|GFS22||Global||22 km||180 h (@ 3 h)||20:02 GMT+0330||NOAA NCEP|
|GFS22||Global||40 km||180 h (@ 3 h)||20:20 GMT+0330||NOAA NCEP|
|GFSENS05||Global||40 km||384 h (@ 3 h)||13:30 GMT+0330||NOAA NCEP|
|NAM3||North America||3 km||60 h||19:30 GMT+0330||NOAA NCEP|
|NAM5||North America||5 km||60 h||20:51 GMT+0330||NOAA NCEP|
|NAM12||North America||12 km||84 h (@ 3 h)||19:06 GMT+0330||NOAA NCEP|
|FV3-5||Alaska||5 km||60 h||15:00 GMT+0330||NOAA NCEP|
|GEM2||North America||2.5 km||48 h||10:16 GMT+0330||Environment Canada|
|GEM15||Global||15 km||168 h (@ 3 h)||09:47 GMT+0330||Environment Canada|
|AROME2||France||2 km||42 h||19:45 GMT+0330||METEO FRANCE|
|ARPEGE11||Europe||11 km||96 h||19:38 GMT+0330||METEO FRANCE|
|ARPEGE40||Global||40 km||96 h (@ 3 h)||19:59 GMT+0330||METEO FRANCE|
|HRMN5||Central Europe||5 km||48 h||20:52 GMT+0330||KNMI|
|MSM5||Japan||5 km||78 h||14:57 GMT+0330||Japan Meteorological Agency|
meteoblue weather models cover most populated areas at high resolution (3-10km) and world wide at moderate resolution (30km). The map on the side displays NMM models as red and NEMS models as black boxes. Other colors show third-party models. Global models are not shown. For a single forecast, multiple weather models, statistical analysis, measurements, radar and satellite telemetry are considered and combined to generate the most probable weather forecast for any given location on Earth.