I'm Weather

Wenden Sie sich an unser Support-Team, wenn Sie Hilfe benötigen. Wir sind für Sie da!

Anscheinend gab es ein Problem bei der Zahlungsüberprüfung.

Oh nein, da stimmt was nicht

Dies kann einen Moment dauern. Vielen Dank für Ihre Geduld

Bitte warten Sie, während wir Ihre Zahlung aus dem Wetter bearbeiten

Überprüfung der Zahlung

Ihr Pro-Abonnement ist jetzt aktiv! Wenn Sie Fragen haben, können Sie sich gerne an unser Support-Team wenden.

Vielen Dank für Ihren Kauf.

Zahlung verifiziert!

Klima

Es tut uns leid, aber es ist etwas schiefgegangen. Bitte versuchen Sie es später noch einmal.

Oops! Etwas ist schief gelaufen

Die folgenden Vorhersagemodelle sind verfügbar.

Vorhersage

10-Jahres-Klimadurchschnitte, jährlich aktualisiert.

Wettergrade für verschiedene (Sport-)Aktivitäten.

Wettergrade

Kurzfristige Vorhersagen: Radar und Satellit.

Jetztcast

Unternehmen nutzen unsere Tools, um ihr Geschäft zu verbessern

Treffen Sie unsere Partner, die mit unseren Daten Innovationen schaffen

Das Expertentool für den echten Wetterprofi, Zugang zu den folgenden Optionen:

Atmosphären- und Wellenmodelle (GFS, ECMWF-BNL+, ICON, ARPERGE, Harmonie, AROME).

Infoplaza Optimal Model - beste mögliche Wettervorhersage für BNL - sehr hohe Auflösung und stündlich aktualisiert.

Nowcast-Informationen von Radar-, Satelliten- und Blitzsensoren (weltweit).

Klimainformationen pro Standort basierend auf dem ERA-Modell.

Premium-Support, Datenschutz und keine Werbung.

Voller Zugriff für weniger als 2 Euro pro Monat, <b>23,99 Euro</b> pro Jahr.

Optimal

Total cloud cover, Precipitation and Pressure.

Atmosphere

The INFOPLAZA Optimal model is the best possible forecast for NW Europe, mixing weather models, human quality control and observations.

INFOPLAZA

DWD ICON D2

ICON-D2 is a high-resolution numerical weather prediction model developed by the German Weather Service.

ICON-D2

DWD ICON Europe

ICON-EU, developed by the German Weather Service (DWD), is a high-resolution weather model tailored for Europe.

ICON-EU

ECMWF HRES Europe

ECMWF-EU is a numerical weather prediction model developed by the European Centre for Medium-Range Weather Forecasts (ECMWF).

ECMWF-EU

ECMWF HRES Global

ECMWF-GLOBAL is a numerical weather prediction model developed by the European Centre for Medium-Range Weather Forecasts (ECMWF).

ECMWF GLOBAL is the open data distributed and copyrighted by [ECMWF](https://www.ecmwf.int/en/forecasts/datasets/open-data), which is licensed under the [CC BY 4.0 license](https://creativecommons.org/licenses/by/4.0/).

ECMWF-GLOBAL

KNMI Harmonie

KNMI-HARMONIE is a high-resolution weather model developed by the Royal Netherlands Meteorological Institute (KNMI).

HARMONIE

KNMI Harmonie Caribbean

KNMI-HARMONIE-CARIBBEAN is a high-resolution weather model developed by the Royal Netherlands Meteorological Institute (KNMI).

HARMONIE-CARIBBEAN

MeteoFrance Arome

AROME is a high-resolution weather model developed by Météo-France.

AROME

MeteoFrance Arpege

ARPEGE-EU is an EU-based numerical weather model developed by Météo-France.

ARPEGE-EU

ARPEGE is a global numerical weather model developed by Météo-France.

ARPEGE-GLOBAL

The Global Forecast System (GFS) is a numerical weather prediction model run by the National Centers for Environmental Prediction (NCEP).

ECMWF ensemble NL

Ensemble

ECMWF-NL-ENSEMBLE is a probabilistic model run by the European Centre for Medium-Range Weather Forecasts (ECMWF).

ECMWF-NL-ENSEMBLE

Infoplaza wave

Wave

INFOPLAZA-WAVE is an in-house wave model.

INFOPLAZA-WAVE

DMI DKSS

DMI-DKSS

DMI WAM

DMI-WAM

DWD WAM

ICON-EU-WAVE is an ICON-based wave model.

ICON-EU-WAVE

RTOFS

IMW-RTOFS

Mercator

MERCATOR is a global ocean circulation model.

MERCATOR

GFS wave

GFS-WAVE

CAMS Europe

Other

CAMS EU is a Europe focused air quality model.

CAMS-EU

CAMS Global

CAMS Global is a worldwide air quality model.

CAMS-GLOBAL

Aurora 0.25° pretrained

Experimental

Aurora is an AI foundation weather model created by Microsoft. This version of Aurora produces data at 0.25 degrees resolution.

Aurora is created by and copyrighted by [Microsoft](https://github.com/microsoft/aurora) / [Bodnar et al. (2024)](https://arxiv.org/abs/2405.13063), weights licensed under [CC BY-NC-SA 4.0 license](https://creativecommons.org/licenses/by-nc-sa/4.0/) as per [HuggingFace](https://huggingface.co/microsoft/aurora/tree/main).

ECMWF AIFS

AIFS is an attention-based graph neural network based AI weather model trained on ERA5 reanalysis data.

ECMWF-AIFS is created by and copyrighted by [ECMWF](https://www.ecmwf.int/en/forecasts/datasets/open-data), which is licensed under the [CC BY 4.0 license](https://creativecommons.org/licenses/by/4.0/).

ECMWF-AIFS

FengWu

FengWu is a Transformer based AI weather model trained on 39 years of ERA5 reanalysis data.

FengWu is created by and copyrighted by [Shanghai AI Laboratory](https://github.com/OpenEarthLab/FengWu) / [Chen et al. (2023)](https://arxiv.org/abs/2304.02948), weights licensed under [CC BY-NC-SA 4.0 license](https://creativecommons.org/licenses/by-nc-sa/4.0/).

FourCastNet v2

FourCastNet v2 is a Spherical Fourier Neural Operators based AI weather model that is trained on 37 years of ERA 5 reanalysis data.

FourCastNet v2 is created by and copyrighted by [Nvidia](https://developer.nvidia.com/blog/modeling-earths-atmosphere-with-spherical-fourier-neural-operators/) / [Bonev et al. (2023)](https://arxiv.org/abs/2306.03838), weights licensed under [Apache 2.0 license](https://www.apache.org/licenses/LICENSE-2.0).

FuXi

FuXi combines 3 AI weather models to forecast for the short, medium and long term. It is trained on 39 years of ERA5 reanalysis data.

FuXi is created by and copyrighted by [Fudan University](https://github.com/tpys/FuXi) / [Chen et al. (2023)](https://arxiv.org/abs/2306.12873), weights licensed under [CC BY-NC-SA 4.0 license](https://creativecommons.org/licenses/by-nc-sa/4.0/).

Pangu-Weather

Pangu-Weather is a Swin transformer based AI weather model trained on 39 years of global ERA5 reanalysis data.

Pangu-Weather is created by and copyrighted by [Huawei Cloud](https://github.com/198808xc/Pangu-Weather) / [Bi et al. (2023)](https://www.nature.com/articles/s41586-023-06185-3), weights licensed under [CC BY-NC-SA 4.0 license](https://creativecommons.org/licenses/by-nc-sa/4.0/).